Assessing the Accuracy of the Substance Abuse Subtle Screening Inventory-3 Using DSM-5 Criteria

John M. Laux, Robin M. DuFresne, Allison K. Arnekrans, Sylvia Lindinger-Sternart, Christopher P. Roseman, Amy Wertenberger, Stephanie Calmes, Darren W. Love, Andrew M. Burck, Jim Schultz

The Substance Abuse Subtle Screening Inventory-3 (SASSI-3; Miller & Lazowski, 1999) is a substance use screen that uses logically derived, or obvious questions, as well as subtle, or empirically derived questions. The SASSI-3 can be completed, scored and interpreted in 15 minutes. Side one consists of 67 true–false items selected for their ability to statistically differentiate between a criterion group of persons with substance dependence and a control group of non-substance dependent persons. The 67 empirically derived items are used in an effort to defeat dissimulation and are similar in nature and purpose to items found on the MacAndrew Alcoholism Scale-Revised (MAC-R; MacAndrew, 1965). As such, these empirically derived items are useful with individuals who are either intentionally or unintentionally denying a substance use disorder (Laux, Piazza, Salyers, & Roseman, 2012). These comprise the Symptoms scale (SYM), which assesses the symptoms and consequences of drug and alcohol use; the Obvious Attributes scale (OAT), a measure of the obvious symptoms of substance dependence; the Subtle Attributes scale (SAT), an indirect measure of substance use that employs items with non-substance-related content; the Defensiveness scale (DEF), which measures denial or minimization; the Supplemental Addiction Measure scale (SAM), which discriminates general defensiveness from defensiveness related to substance use; the Family Versus Control Subjects scale (FAM), which identifies those who are likely to focus on the thoughts and feelings of others to their own neglect; the Correctional scale (COR), used to detect response patterns similar to those produced by persons with a history of criminal behaviors; and the Random Answering Pattern scale (RAP), designed to identify haphazard answering. Side one also includes questions about respondents’ marital status, employment status, education, ethnicity and income.

 

Side Two consists of 12 items specific to alcohol use and 14 items regarding use of other substances. Response options to these 26 items are never, once or twice, several times, and repeatedly. These 26 items comprise the Face Valid Alcohol (FVA) and Face Valid Other Drugs (FVOD) scales and are similar to items found on the Michigan Alcoholism Screening Test (MAST; Selzer, 1971) and the CAGE (Ewing, 1984). The SASSI-3 is interpreted using nine decision rules. The first five decision rules are based solely on the unique contributions of individual scales. The remaining four decision rules involve a combination of two or more scales. A decision rule is coded “yes” if the associated SASSI-3 scale or scales’ raw score is equal to or greater than the decision rule’s cut score. Otherwise, the decision rule is coded as “no.” The respondent is determined to have a “high probability of having a substance dependence disorder” if any of the decision rules are met (Miller & Lazowski, 1999, p. 10).

 

Not only does the SASSI-3 do a better job of identifying alcohol use disorders than the MAST, CAGE and MAC-R (Laux, Perera-Diltz, Smirnoff, & Salyers, 2005; Laux, Salyers, & Kotova, 2005), it provides the added benefit of screening for drug use other than alcohol. The most recent inquiry into substance use screens indicated that the SASSI-3 is the substance use screen most frequently used by Master Addictions Counselors certified by the National Board for Certified Counselors (Juhnke, Vacc, Curtis, Coll, & Paredes, 2003).

 

The SASSI-3 Manual (Miller & Lazowski, 1999) reported a sensitivity (true positive) rate of 94.6% and specificity (true negative) rate of 93.2%. Subsequent field research produced results consistent with the psychometric claims made in the SASSI-3 Manual (Burck, Laux, Harper, & Ritchie, 2010; Burck, Laux, Ritchie, & Baker, 2008; Calmes et al., 2013; Hill, Stone, & Laux, 2013; Laux, Perera-Diltz, Smirnoff, & Salyers, 2005; Laux, Salyers, & Bandfield, 2007; Laux, Salyers, & Kotova, 2005; Wright, Piazza, & Laux, 2008). Further, Laux et al. (2012) demonstrated that the SASSI-3’s empirical items and associated decision rules increased the instrument’s screening accuracy. In addition, persons’ willingness and ability to self-report having a substance use disorder as described in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR; American Psychiatric Association [APA], 2000) did not negatively affect the instrument’s sensitivity. Laux et al. (2012) found that the SASSI-3 produced high sensitivity rates across varying levels of motivation to change among persons who lost parental rights due to substance use.

 

APA published the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in 2013. This most current version of the DSM brought forward major and important changes to the way the substance use disorder (SUD) chapter is conceptualized (Dailey, Gill, Karl, & Barrio Minton, 2014). Notably, the former dichotomous substance abuse and substance dependence categories have been removed and replaced with a continuum under the heading of “Substance Use Disorders” (APA, 2013, p. 483). The criterion formerly associated with the substance abuse and substance dependence disorders have been merged onto one continuum, to which craving has been added. Clients are determined to have a mild SUD if two or three criteria are met, a moderate SUD when four to five symptoms are met, and a severe SUD when six or more symptoms are endorsed.

 

Because previous versions of the DSM criteria were frequently used as the gold standard against which SUD screens were compared (Ashman, Schwartz, Cantor, Hibbard, & Gordon, 2004; Lazowski, Miller, Boye, & Miller, 1998), it is of interest to investigate the degree to which the SASSI-3 accurately predicts the new DSM-5 substance use diagnostic criteria. Our literature review produced two examples of empirical comparison between the SASSI-3, or its predecessors, and DSM criteria. The first (Lazowski et al., 1998) reported on the standardization efforts that produced the instrument’s third version. This research team used the data from persons whose case files had a DSM-III-R (APA, 1987) or a DSM-IV (APA, 1994) substance use diagnosis and an administration of the SASSI-3. How the participants were diagnosed was not specified. The results of this investigation found that the SASSI-3’s overall accuracy rating was 97%, the sensitivity rating was 97% and the specificity rating was 95%. A second study (Ashman et al., 2004) sought to determine the SASSI-3’s ability to screen for substance abuse among persons with traumatic brain injury. Ashman et al. (2004) used the Structured Clinical Interview for DSM-IV (First, Spitzer, Gibbon, & Williams, 1996) as the criterion variable against which the SASSI’s results were compared. These authors concluded that while the SASSI’s overall decision and FVA scale yielded “modest accuracy, sensitivity, and specificity rates” (p. 198), the FVOD scale had high sensitivity (95%) but only moderate accuracy (83%) and specificity (82%) among persons with traumatic brain injury.

 

The purpose of this study was to extend this line of research and examine the SASSI-3’s ability to accurately assess the presence of an SUD using DSM-5 criteria. Specifically, the authors calculated kappa statistics to estimate the degree of agreement between the SASSI-3’s overall decision rules, its individual decision rules and counselors’ DSM-5 SUD diagnoses. This analysis is important because these decision rules directly affect the SASSI-3’s final SUD classification (i.e., high probability of substance dependence disorder/low probability). Further, we examined the SASSI-3’s specificity and sensitivity using receiver operating characteristics (ROC) curves. We hypothesized that we would find good agreement between the overall SASSI-3 score and the DSM-5 SUD diagnosis. We further expected to find good agreement between the SASSI-3 face valid scales and the DSM-5 SUD diagnosis. We expected to find a moderate to low agreement between the SASSI-3 subtle scales and the DSM-5 SUD diagnosis. Additionally, we hypothesized that the ROC analysis would provide optimal cut-off scores for each of the SASSI-3 subscales that would improve those scales’ sensitivity and specificity. Study participants were selected from an inpatient SUD treatment center, an urban university, and a community mental health center that provides court-ordered outpatient treatment for clients with substance use issues. These populations were selected in order to match the populations on which the SASSI-3 was standardized (Miller & Lazowski, 1999).

 

Method

 

Participants

This study included participants (N = 241) recruited between October 2013 and May 2014. There were 114 females (47.3%) and 127 males (52.7%). The participants’ average age was 33.63 (SD = 6.83, range = 19–47). One hundred thirty-one (54.4%) were European American, 52 (21.6%) were African American, 7 (2.9%) were Hispanic, 12 (5.0%) were biracial, and 4 (1.7%) were Asian American. Thirty-five (14.5%) provided no ethnic background information. The average number of years of education completed was 12.48 (SD = 1.79, range = 7–18). Thirty-two (13.3%) were married, 156 (64.7%) were never married, 27 (11.2%) were divorced, 16 (6.6%) were separated, 4 (1.7%) were widowed, and 6 (2.5%) did not indicate a marital status. Thirty-three (13.7%) participants listed their employment as full-time, 22 (9.1%) as part-time, 91 (37.8%) as not employed, 65 (27.0%) as student, 9 (3.7%) as home maker, 13 (5.4%) were disabled, 2 (.8%) listed retired, and 6 (2.5%) listed no employment status. The sample features fewer employed, and more unemployed and student participants than the SASSI-3 normative sample (Miller & Lazowski, 1999).

 

Participants were recruited from three sites in Ohio. A total of 117 (48.5% of the total sample) participants were recruited from an adults-only comprehensive community mental health substance abuse treatment center. Another 61 subjects (25.3% of the total) were recruited from a private, non-profit organization specializing in court-ordered outpatient mental health treatment. Finally, 63 students (26.1% of the sample) enrolled at a large, public, urban university in Ohio were recruited to provide a sample of individuals who were less likely to be substance users. A one-way ANOVA [F(2, 233) = 24.28, p = .000, η2 = .172] showed that the college students’ mean age (M = 23.86, SD = 9.04) was significantly lower than the inpatient substance abuse clients’ (M = 35.80, SD = 11.36) and the outpatient clients’ (M = 32.80, SD = 10.88).

 

Procedure and Materials

The procedures involved here were approved by the sponsoring institution’s Institutional Review Board and the data collection sites, and were consistent with the American Counseling Association’s Code of Ethics (2014). Three licensed counselors who had completed two graduate courses in testing and assessment conducted standardized interviewing and administered SASSI-3s. All three counselors completed training in SUD interviewing and SASSI-3 administration and scoring prior to the study’s beginning. All persons receiving treatment at sites 1 and 2 were asked to participate. A total of 117 of the 118 (99.2%) persons at site 1 and 61 of the 64 (95.3%) persons at site 2 agreed to participate. Sixty-three of 79 students (79.8%) enrolled in one of three separate undergraduate counseling courses agreed to participate.

 

Each participant met individually with a researcher who used the structured SUD questionnaire to conduct an interview and administered the SASSI-3. The SASSI-3s were scored and interpreted by a fourth researcher who had no knowledge of the interviewing researchers’ diagnostic impressions. For quality control purposes, the senior author reviewed the SASSI-3 scoring and questionnaire results.

 

Instruments

     Structured Substance Use Disorder Questionnaire. At present, no structured guide or screen exists that was developed and normed using the current DSM-5 SUD criteria. To ensure that the counselors were uniform in their substance use interviews and that their interviews were consistent with the DSM-5 criteria, we designed a 22-item questionnaire to determine whether participants would meet criteria for a DSM-5 SUD. This questionnaire was based on the 11 criteria for an SUD from the DSM-5 (APA, 2013). These items were yes/no questions corresponding to the criteria for an SUD and were divided into two sections. The first 11 items applied to alcohol use and the second 11 items applied to the use of other drugs. Consistent with the DSM-5’s SUD section, participants who responded “yes” to two or more items in either section met criteria for a DSM-5 substance use disorder.

 

Endorsement of two items in the first section indicated the participant met criteria for an SUD involving alcohol use; endorsement of two items in the second section indicated the participant met criteria for an SUD involving other drugs. Severity of the SUD was based on decision rules provided in the DSM-5: 2–3 symptoms indicated a mild SUD, 4–5 symptoms indicated a moderate SUD, and 6 or more symptoms indicated a severe SUD (APA, 2013). Counselors clarified the meaning of items as needed. No distinction was made between different types of drug use (marijuana, cocaine, etc.) because the SASSI-3 does not do so. The internal consistency estimates for the alcohol and other drug use sections were high ( = .94 and  = .97, respectively).

 

Data Analysis

The authors used two methods of statistical analysis. Cohen’s kappa was used to measure the agreement between the two dichotomous DSM-5 SUD diagnosis variables (i.e., met criteria or not) and the overall score on the SASSI-3 (high probability of substance dependence disorder/low probability). Cohen’s kappa also was used to compare the DSM-5 diagnosis of either an SUD involving alcohol or one involving other drug use to the score on the SASSI-3 subscale 1 (FVA) or subscale 2 (FVOD), respectively. It was then used to measure agreement between the DSM-5 SUD diagnosis and the scores on subscales 3–9 on the SASSI-3. The value of the kappa is between 0 and 1 and is divided into 5 levels of agreement: .01 to .20 signifies slight agreement; .21 to .40 fair; .41 to .60 moderate; .61 to .80 substantial; and .81 to .99 near perfect agreement (Landis & Koch, 1977).

 

Unlike the kappa, ROC curve analysis is used with continuous variables. ROC analysis allows one to measure a trade-off between specificity (true positives) and sensitivity (true negatives; Youngstrom, 2014). ROC allows the investigator to determine how specificity and sensitivity change when the cut-off value of the continuous variable is changed. ROC value is expressed as an area under the ROC curve (AUROC). ROC curves are graphically represented as the relationship between an instrument’s specificity (horizontal axis) and sensitivity (vertical axis). ROC curves are interpreted by finding the point on the graph where a scale’s sensitivity and specificity are balanced. To the naked eye, this optimal point is where the curve begins to flatten out at the top. ROC analyses are performed on individual scales, but not multiple scales. As such, ROC analyses can only be performed on those SASSI-3 decision rules that involve individual scales (decision rules 1–5). Decision rules 6–9 involve input from two or more SASSI-3 scales and are therefore not subject to ROC analysis. The ROC scores are categorized as follows: ≥ .90, excellent; ≥ .80, good; ≥ .70, fair; and < .70, poor (Youngstrom, 2014).

 

Results

 

A review of the participants’ random answering profile (RAP) scores indicated that all profiles were valid. Of the 241 participants, the SASSI-3 classified 153 (63.5%) as having a high probability of having a substance dependence disorder. Raw SASSI-3 scale scores were converted to t scores using the SASSI-3 Manual’s Appendix C (Miller & Lazowski, 1999).

 

 

Table 1

 

SASSI-3 Scale Descriptive Data and Internal Consistency Estimates

 

SASSI-3 Scale

Mean t score

Standard Deviation

Range

Alpha

FVA

55.67

15.86

41-110

0.93

FVOD

70.58

25

5-116

0.97

SYM

63.58

14.68

36-92

0.81

OAT

60.23

12.25

35-85

0.74

SAT

58.35

14.78

24-99

0.52

DEF

45.33

10.81

24-73

0.53

SAM

62.76

12.09

30-94

0.63

FAM

44.1

12.18

4-76

0.24

COR

61.21

13.74

36-88

0.63

 

Note. FVA = Face Valid Alcohol scale; FVOD = Face Valid Other Drugs scale; SYM = Symptoms scale; OAT = Obvious Attributes scale; SAT = Subtle Attributes scale; DEF = Defensiveness scale; SAM = Supplemental Addiction Measure scale; FAM = Family versus Control Subjects scale; COR = Correctional scale.

 

 

Table 1 represents each SASSI-3 scale’s mean, standard deviation, range of scores and Cronbach’s alpha. These internal consistency reliability estimates were comparable with previously reported alphas (Burck, Laux, Harper, & Ritchie, 2010; Burck et al., 2008). The counselor’s interviews indicated that 188 (78.0%) of the participants met SUD criteria as specified in the DSM-5. Of these 188, 25 (13.3%) had a mild SUD, 13 (6.9%) were moderate, and 127 (67.6%) had a severe SUD. Of the 188 participants diagnosed with an SUD, 85 participants (45.2%) had an alcohol use disorder. Of these 85, 33 (38.8%) had a mild alcohol SUD, 13 (15.3%) were moderate, and 39 (45.9%) were severe. One hundred thirty-three participants (55.2%) were positive for an SUD other than alcohol. Of these 133, 10 (7.5%) had a mild disorder, 8 (6.0%) were moderate, and 115 (86.5%) were severe.

 

Cohen’s kappa (κ) statistic was calculated to determine the agreement between the DSM-5 diagnosis (i.e., met criteria or not) and the SASSI-3 overall score and each of the SASSI-3’s decision rules. Table 2 presents the results of these analyses as well as the number of SASSI-3 true positive, true negative, false positive and false negative classifications. The overall SASSI-3’s agreement with the counselors’ diagnostic decisions was fair (κ = .423, p = .060). The SASSI-3 results concurred with counselors’ diagnostic interviews on 182 cases and disagreed on 59 cases. The SASSI-3’s sensitivity (true positives) and specificity (true negatives) rates were .75 and .77, respectively.

 

 

 

 

 

 

 

 

Table 2

 

Agreement Between Counselors’ Diagnoses and SASSI-3 Individual and Total Decision Rules

 

Rule

True Positive

True Negative

False Positive

False Negative

Kappa

11

31 (12.9%)

151 (62.7%)

5 (2.1%)

54 (22.4%)

0.383***

22

105 (43.6%)

105 (43.6%)

3 (1.2%)

28 (11.6%)

0.745*****

3

91 (37.8%)

47 (19.5%)

6 (2.5%)

97 (40.2%)

0.229***

4

32 (13.3%)

53 (22.0%)

0 (0%)

156 (64.7%)

0.083**

5

38 (15.8%)

53 (22.0%)

0 (0%)

150 (62.2%)

0.100**

6

62 (25.7%)

50 (20.7%)

3 (1.2%)

126 (52.3%)

0.149**

7

107 (44.4%)

48 (19.9%)

5 (2.1%)

81 (34.0%)

0.313***

8

4 (1.7%)

52 (21.6%)

1 (0.4%)

184 (76.3%)

0.001*

9

59 (24.5%)

46 (19.1%)

7 (2.9%)

129 (53.5%)

0.100**

SASSI-3

141 (58.5%)

41 (17.0%)

12 (5.0%)

47 (19.5%)

0.423****

 

Note. 1 = Rule 1 kappa tested against positive for alcohol use disorder only. 2 = Rule 2 kappa tested against all substance use disorders but alcohol use. All other kappa values are calculated for each Decision Rule’s agreement a clinical diagnosis of any substance use disorder. * = less than chance agreement, ** = slight agreement, *** = fair agreement, **** = moderate agreement and ***** = substantial agreement (Landis & Koch, 1977).

 

 

A closer examination of the kappa data indicates that the SASSI-3 and its subscales’ areas of weakness were the false negative rates. That is, the SASSI-3 failed to identify persons as likely substance dependent that the counselors judged as substance dependent (i.e., met criteria or not). Based on the kappa data, the SASSI-3 overall score incorrectly categorized 47 (19.5%) of the sample as not in need of further SUD assessment. This suggests that the decision rules’ cut scores may be too high for this sample. To test this hypothesis, the researchers investigated the SASSI-3’s FVA, FVOD, SYM, OAT and SAT scales’ specificity and sensitivity using ROC analyses (Youngstrom, 2014).

 

The ROC analysis of the FVA scale produced an AUROC value of .861, p = .000, standard error = .026, with a 95% confidence interval range of .811 to .912. This indicates that there is a good agreement between the FVA scale and the counselors’ alcohol use disorder diagnoses (Youngstrom, 2014). A review of the coordinates of the curve (Figure 1) demonstrates that an adjusted FVA t score cut-off of 53.5 would provide the optimal balance between sensitivity (.79) and specificity (.80). A t score of 53.5 translates into an FVA raw score of approximately 6 for both sexes. Rule 1 was recalculated using a raw score of 6 for both sexes and a kappa statistic was calculated to determine the agreement rate between this new FVA cut score and the counselors’ alcohol use disorder diagnoses. The new kappa statistic was .551, p = .000. The new Rule 1 sensitivity and specificity rates were, respectively, .81 and .77. Rule 1’s false positive rate was .19 and the false negative rate was .23. Lowering the Rule 1 cut score to 6 improved the kappa statistic by .168.

 

 

Figure 1.

 

ROC Curve for FVA t Score Plotted Against Counselor Alcohol Use Disorder Diagnosis

 

Note. Diagonal segments are produced by ties.

 

 

The ROC analysis of the FVOD scale produced an AUROC value of .965, p = .000, standard error = .013, with a 95% confidence interval range of .940 to .990. This indicates that there is an excellent agreement between the FVOD scale and the counselors’ SUD other than alcohol dependence diagnoses (Youngstrom, 2014). A review of the coordinates of the curve (Figure 2) argued against making any adjustments to the current FVOD score cut-offs for Rule 2.

 

Figure 2.

 

ROC Curve for FVOD t Score Plotted Against Counselor SUD Diagnosis

 

Note. Diagonal segments are produced by ties.

 

 

The ROC analysis of the SYM scale produced an AUROC value of .803, p = .000, standard error = .035, with a 95% confidence interval range of .735 to .871. This indicates that there is a good agreement between the SYM scale and the counselors’ SUD diagnoses (Youngstrom, 2014). A review of the coordinates of the curve (Figure 3) demonstrates that an adjusted SYM t score cut-off of 56.5 would provide the optimal balance between sensitivity (.761) and specificity (.774). A t score of 56.5 translates into an SYM raw score of approximately 5 for males and 4 for females. Rule 3 was recalculated using these new raw scores and a kappa statistic was calculated to determine the agreement rate between this new SYM cut score and the counselors’ overall SUD diagnoses. The kappa statistic was .437, p = .000. The new Rule 3 sensitivity and specificity rates were, respectively, .76 and .77. Rule 3’s false positive rate was .23 and the false negative rate was .24. Lowering the Rule 3 cut score to 6 improved the kappa statistic by .208.

 

Figure 3.

 

ROC Curve for SYM, OAT and SAT t Scores Plotted Against Counselor SUD Diagnosis

 

Note. Diagonal segments are produced by ties.

 

The ROC analysis of the OAT scale produced an AUROC value of .717, p = .000, standard error = .038, with a 95% confidence interval range of .643 to .791 (Figure 3). This indicates that there is fair agreement between the OAT scale and the counselors’ SUD diagnoses (Youngstrom, 2014). It was not possible to adjust the OAT t score to produce an optimal cut-off score such that a balance between sensitivity and specificity could be obtained. For example, to attain a sensitivity rating of .82, the
t score cut-off would have to be lowered to 48.5, which would produce a specificity rating of .634.

 

The ROC analysis of the SAT scale produced an AUROC value of .654, p = .001, standard error = .037, with a 95% confidence interval range of .582 to .727 (Figure 3). This indicates that there is poor agreement between the SAT scale and the counselors’ SUD diagnoses (Youngstrom, 2014). As with the OAT scale, no cut-off score could be determined that would provide an optimal balance between sensitivity and specificity.

 

The SASSI-3’s overall decision was recalculated using the lowered Rule 1 and Rule 3 cut scores. This process resulted in a total of 188 persons being classified as likely dependent on the SASSI-3, or a change in the total number of classifications by 28. A follow-up analysis comparing the SASSI-3 final decision using the adjusted scores for Rules 1 and 3 and the original cut scores for Rules 2 and 4–9 with the counselors’ decisions produced a kappa of .457 (p = .000). This kappa is slightly higher than the kappa produced using unadjusted Rule 1 and 3 cut-offs (κ = .423). The adjusted process identified 161 of the 181 (sensitivity = .89) participants whom the counselors classified as having an SUD. However, this increased sensitivity came at the cost of decreased specificity. The adjusted process identified only 33 (specificity = .55) of those participants whom the counselors determined did not have an SUD. The false positive rate and the false negative rate for this adjusted process were, respectively .45 and .11. In sum, this process increased the number of true positives by 20, decreased the number of true negatives by 8, increased the number of false positives by 8, and decreased the number of false negatives by 20. As one might expect, lowering the cut scores on these two rules increased the instrument’s ability to detect the presence of problems, but did so at the cost of possibly overdiagnosing 8 (3%) additional participants while reducing the false negative classifications by 20 (8.3%).

 

Discussion

 

The DSM-5 section on SUDs includes significant changes. Chief among these changes is the movement away from an abuse/dependence dichotomy to an SUD continuum that includes all of the criteria previously unique to abuse and dependence disorders as well as the addition of a craving criterion. The present study examined the SASSI-3’s utility in predicting counselors’ diagnostic classifications using the new DSM-5 SUD criteria. The results provided a mixed picture. The SASSI-3’s agreement with the counselors’ diagnoses was moderate. This finding prompted us to conduct a similar series of kappa analyses for each of the SASSI-3’s decision rules and ROC analyses for the first five SASSI-3 decision rules. The last four decision rules could not be analyzed with the ROC as they are each composed of more than one scale of the SASSI-3. The decision rules’ agreement with the counselors’ diagnoses varied considerably. The kappa values presented in Table 1 are below what would be expected based on previously published agreement statistics using previous versions of the DSM (Miller & Lazowski, 1999). The SASSI-3 and its decision rules’ false negative values suggested that the instrument’s modest agreement with the counselors may have been a consequence of unnecessarily high raw score cut-off points. Consistent with Clements’ (2002) findings related to adjusting cut scores, the ROC score analyses presented mixed results. The ROC analyses provided evidence that lowered FVA and SYM cut scores improved these scales’ respective sensitivity and specificity estimates. The FVOD scale’s current cut score produced high sensitivity and specificity and did not need to be improved. The OAT and SAT cut scores could not be adjusted without unwanted compromises to either scale’s associated decision rules’ sensitivity and specificity. The SASSI-3’s overall decision was recalculated using the lowered Rule 1 and Rule 3 cut scores. This process resulted in an improvement in sensitivity with a slight decrease in specificity. The net result was an improvement in the SASSI-3’s overall agreement with licensed counselors’ SUD determinations. Our FVOD scale’s sensitivity and specificity findings are consistent with those of First et al. (1997) and Lazowski et al. (1998), and suggest that the FVOD scale is useful in predicting DSM-IV-TR and DSM-5 non-alcohol SUDs. Our FVA scale findings are consistent with those of First et al. (1997) but differ from those of Lazowski et al. (1998). There are no other SASSI-3 ROC analyses available for comparison.

 

These results elicit deliberation about whether SUD counselors would be better served by an SUD screening instrument that over- or under-predicts SUD diagnoses. In the case of a scoring method that produces higher sensitivity but lower specificity, resource allocation might be a concern. A counselor’s diagnostic time might be unnecessarily spent ruling out clients, and clients might be unnecessarily inconvenienced by participating in a full SUD assessment. Alternatively, counselors using a scoring method with lower sensitivity but higher specificity would have fewer clients unnecessarily inconvenienced and spend less time assessing persons who do not need SUD treatment. The unfortunate trade-off is that persons with an SUD who might benefit from assessment and treatment would otherwise be sent home without an appropriate recommendation.

 

The health, social, psychological and legal implications of misdiagnosing clients with SUDs have been documented (Brown, Suppes, Adinoff, & Thomas, 2001; Horrigan, Piazza, & Weinstein, 1996; McMillan et al., 2008). Therefore, SUD counselors would benefit from a screening instrument with high sensitivity and specificity (Tiet, Finney, & Moos, 2008). When that goal cannot be achieved, SUD counselors and agencies may want to consider which of these two is more important.

 

Counselors and their agencies might consider their patient population and setting. Among populations likely to have an SUD, specificity might be less important than sensitivity. Conversely, a counselor working at a community mental health agency or college counseling center may benefit from a highly sensitive instrument to identify clients with dual diagnosis treatment needs. In sum, this study represents the first investigation of the SASSI-3’s agreement with the new DSM-5 SUD criteria. Past research (e.g., Laux et al., 2012) has demonstrated that the SASSI-3’s subtle scales improve the instrument’s diagnostic accuracy over that which is obtained using face valid approaches only. As such, we are cautious about drawing strong conclusions about the SASSI-3’s agreement with the DSM-5 criteria until a larger sample of research is available.

 

Limitations and Suggestions for Future Research

ROC curve analysis allows for the examination of one scale at a time. Consequently, we were unable to use these methods to examine the SASSI-3 decision rules that use more than one scale (Rules 6, 7, 8 and 9). These decision rules include data from the instrument’s subtle and obvious questions and are important contributors to the overall instrument’s sensitivity and specificity. Thus, the inability to examine these decision rules excludes results that may impact the SASSI-3 sensitivity and specificity.

 

This study collected data from three different locations: a university campus, an inpatient SUD treatment center and an outpatient mental health counseling center. The participants from the college sample were significantly younger, by 9 and 11 years respectively, than those from the other collection sites. Because SUDs are progressive in nature, we recommend that subsequent researchers conduct sample-specific SASSI-3 analyses to determine whether or not population-specific, rather than universal, cut-offs would be useful. Additionally, because there were very few persons in this sample whose use of drugs other than alcohol was categorized as mild, it is not clear whether the FVOD’s lower kappa value was due to the instrument itself or the sample’s homogeneity.

 

Finally, the DSM-5’s SUD diagnosis is on a continuum and includes severity specifiers (mild, moderate or severe). It may be more diagnostically useful to expand the SASSI-3 to address these specifiers, rather than rely solely on the current dichotomous likely/not likely dependent conclusion. Future researchers are encouraged to determine what decision rule cut scores would be associated with each of the three levels of SUD severity.

 

 

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.

 

 

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John M. Laux is a Professor at The University of Toledo. Robin M. DuFresne is a practicing clinical counselor at the Zepf Center in Toledo, Ohio. Allison K. Arnekrans is an Assistant Professor at Central Michigan University. Sylvia Lindinger-Sternart is an Assistant Professor at the University of Great Falls. Christopher P. Roseman is an Associate Professor at The University of Toledo. Amy Wertenberger is a doctoral candidate at The University of Toledo. Stephanie Calmes is a professional counselor at Harbor Behavioral Health in Toledo, Ohio. Darren W. Love is the Treatment Program Manager at Court Diagnostic and Treatment Center in Toledo, Ohio. Andrew M. Burck is an Assistant Professor at Marshall University. Jim Schultz is a mental health counselor at Harbor Behavioral Health in Toledo, Ohio. Correspondence may be addressed to John M. Laux, MS 119, 2801 W. Bancroft St., Toledo, Ohio, 43606, John.Laux@utoledo.edu.

 

Excoriation Disorder: Assessment, Diagnosis and Treatment

Nicole A. Stargell, Victoria E. Kress, Matthew J. Paylo, Alison Zins

Excoriation disorder, sometimes colloquially referred to as skin picking disorder, is a newly added disorder in the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association [APA], 2013). Despite being a newly-classified DSM disorder, excoriation disorder is relatively common and affects between 1.4 and 5.4% of the general population (Grant et al., 2012). The purpose of this article is to provide professional counselors with a general understanding of how to assess, diagnose and treat excoriation disorder.

 

The prevalence of excoriation disorder may be underestimated, as it is sometimes overlooked, particularly because of comorbidity with other mental disorders (e.g., depression, anxiety, obsessive-compulsive disorder; Hayes, Storch, & Berlanga, 2009). Previously underestimated numbers of its prevalence also may be due to the covertness often associated with this disorder (Grant & Odlaug, 2009). Many people with excoriation disorder go to great lengths to hide their behavior from others (e.g., significant others, family members, health professionals) due to fear or embarassment.

 

Historically, excoriation disorder has been associated with obsessive-compulsive disorder (OCD), and it is now listed as a unique diagnosis in the obsessive-compulsive and related disorders section in the DSM-5 (Ravindran, da Silva, Ravindran, Richter, & Rector, 2009). According to the APA (2013), excoriation disorder involves the recurrent, excessive and often impulsive scratching, rubbing and picking of skin which leads to tissue damage and lesions. Those who have excoriation disorder frequently initiate attempts to eradicate these destructive behaviors, yet have difficulty doing so. In order for the diagnosis of excoriation disorder to be applied, individuals must experience clinically-significant distress or impairment in social, occupational or other important areas of functioning due to the routine nature of the skin picking behaviors (APA, 2013). Because of its physical manifestation, this phenomenon has frequently been discussed in medical research, but it is now receiving attention in mental health circles.

 

Etiology of Excoriation Disorder

 

Little is known about the etiology of excoriation disorder. Much of the current excoriation disorder research has been based on previous research conducted on trichotillomania. Excoriation disorder and trichotillomania are body-focused repetitive behaviors (BFRB) under the same DSM-5 classification, and the etiologies behind both disorders might be similar (Flessner, Berman, Garcia, Freeman, & Leonard, 2009). Most theorists suggest that excoriation disorder is rooted in both biological and psychological factors (Grant et al., 2012).

 

Biological factors related to excoriation disorder include genetic predispositions and neurological sensitivity to emotional stimuli, which result in emotional impulsivity and a need to self-soothe (Snorrason, Smári, & Ólafsson, 2011). In one study of 40 individuals who had excoriation disorder, 43% had a first-degree relative with the disorder (Neziroglu, Rabinowitz, Breytman, & Jacofsky, 2008). Specific genes (e.g., Hoxb8 and SAPAP3) have been identified as potential predictors of this disorder (Grant et al., 2012). In animal studies, mice with these genes engaged in excessive grooming to the point of skin lesions, behaviors similar to those of people who have excoriation disorder (Grant et al., 2012). Conversely, in another study, humans with the SAPAP3 gene only met criteria for excoriation disorder 20% of the time (Dufour et al., 2010). It is important to note that genetics appear to play a role in the development of excoriation disorder, but other factors contribute to the disorder’s etiology and maintenance as well (Grant et al., 2012; Lang et al., 2010).

 

In terms of psychological factors, skin picking behaviors help regulate uncomfortable emotions and can become a behaviorally-reinforced coping mechanism used to manage negative feelings (Lang et al., 2010). Some researchers suggest that excoriation disorder is rooted in higher levels of emotional impulsivity and that this characteristic supports and encourages the development of the disorder (Grant et al., 2012). Those with excoriation disorder experience obsessive thoughts about skin picking and engage in more impulsive, sensation-seeking behaviors (e.g., picking, rubbing) than those without the disorder (Snorrason et al., 2011). Those with excoriation disorder often have a greater difficulty with response inhibition and an increased difficulty suppressing an already initiated response as compared to control participants (Grant, Odlaug, & Chamberlain, 2011; Odlaug & Grant, 2010). For example, it might be more difficult for those with excoriation disorder to retract their hand if they already started reaching for an object to use to excoriate. This elevated level of impulsivity may be rooted in brain abnormalities; however, further research is necessary to clearly establish this connection (Grant et al., 2012).

 

Another common theory regarding the onset and maintenance of excoriation disorder is that skin picking behaviors can help regulate emotions and can become a behaviorally-reinforced coping mechanism used to manage elevated levels of anxiety, stress and arousal. Individuals who skin pick often display elevated stress responses to normal stimuli (Lang et al., 2010), and skin picking appears to temporarily sooth such stress. Additionally, obsessive thoughts about skin imperfections and anxiety over not picking can be temporarily relieved by completing the behaviors (Capriotti, Ely, Snorrason, & Woods, 2015). As such, there is a behavioral component—in addition to the genetic and biological components of the disorder—that must be considered when understanding the etiology, assessment, diagnosis and treatment of excoriation disorder.

 

Assessment and Diagnosis of Excoriation Disorder

 

     The proposed etiologies (e.g., genetic predispositions, biological markers) and functions (e.g., soothing emotional reactivity, reducing obsessive thoughts) of excoriation disorder inform the diagnostic and assessment process. It is important that counselors have a thorough understanding of the DSM-5 criteria for excoriation disorder and understand that many clients with this disorder might hide physical markers and omit skin picking information unless asked directly (Grant & Odlaug, 2009). As such, counselors might use formal assessments, in addition to clinical judgment, in order to make an accurate diagnosis and best understand the client’s behaviors.

 

Assessment

A number of assessment tools can be used to assist in assessing, diagnosing and treating those who have excoriation disorder. Each measure can be utilized by counselors in developing a holistic conceptualization of the client and for engaging in differential diagnosis. Upon accurate diagnosis of excoriation disorder, assessment measures also can aid counselors in selecting appropriate treatment goals, interventions and modalities for each client, and they can be used to assess client behavior change.

 

Keuthen et al. (2001b) constructed three skin picking scales that can be used to assess excoriation disorder and aid in the assessment and treatment process. The first measure, the Skin Picking Scale (SPS), can be used to measure the client’s self-reported severity of skin picking behaviors. This measure consists of six items that relate to the frequency of picking urges, intensity of picking urges, time spent engaging in skin picking behaviors, interference of the behaviors in functioning, avoidance behaviors and the overall distress associated with the excoriation-related behaviors. Each item is assessed on a 5-point scale of 0 (none) to 4 (extreme), resulting in a range of total scores between 0 and 24. The SPS demonstrated high internal consistency with adequate convergent validity (Keuthen et al., 2001a). Pragmatically, this measure can be used to distinguish self-injurious skin picking from non-self-injurious skin picking. As treatment gains are made, corresponding scores should decrease.

 

The second measure is the Skin Picking Impact Scale (SPIS). The SPIS is a self-report questionnaire designed to assess the impacts or consequences of repetitive skin picking (e.g., negative self-evaluation, social interference; Keuthen et al., 2001a). Each of the scale’s 10 items are rated on a 6-point scale from 0 (none) to 5 (severe), resulting in a total score ranging from 0 to 50. The SPIS has high internal consistency (Keuthen et al., 2001a; Snorrason et al., 2013), and scores appear to correlate with duration of picking, satisfaction of picking and shame associated with picking.

 

The third measure is the Skin Picking Impact Scale-Shorter Version (SPIS-S). The SPIS-S is the shorter version of the SPIS consisting of only a 4-question scale (Snorrason et al., 2013). The SPIS and the SPIS-S have a similar factor structure and both have high internal consistency. These measures assess the impacts of picking behaviors on social life, perceived embarrassment associated with picking behaviors, consequences of picking behaviors and perception of attractiveness (Snorrason et al., 2013). The ultimate difference between the two scales is the brevity of the shorter version measure as compared to 10 items on the other measure. Snorrason and associates (2013) found acceptable discriminant and convergent validity for the SPIS and the SPIS-S; both measures may be considered for clinical use.

 

The Milwaukee Inventory for the Dimensions of Adult Skin Picking (MIDAS) is another skin picking assessment measure (Walther, Flessner, Conelea, & Woods, 2009). The MIDAS consists of 21 items and highlights the degree of focused picking (e.g., body sensations, reaction to negative emotions) and automatic picking behaviors (e.g., unaware of skin picking behaviors, concentrating on another activity, unintentional picking; Walther et al., 2009). Within the measure, each item is rated on a 5-point scale (i.e., 1–5; not true of my skin picking to always true for my skin picking), and a specific score is provided for focused and automatic picking. The MIDAS demonstrates adequate internal consistency and good validity (i.e., construct and discriminant), making it a reliable and valid measure for distinguishing types of skin picking behaviors (Walther et al., 2009). This assessment is especially useful in facilitating an understanding of the client’s motivations for skin picking, as well as potential ways to reduce the problematic behaviors.

 

The Skin Picking Impact Survey (SKIS; Tucker, Woods, Flessner, Franklin, & Franklin, 2011) is a self-report survey measure. The SKIS, which consists of 92 items, is used to explore multiple dimensions of skin picking behaviors. This survey consists of individual items that assess skin picking symptoms (e.g., presentation), levels of severity (e.g., urges, intensity, time spent, distress, avoidance), consequences (i.e., physical and psychosocial), treatment-seeking history, and demographic information. The SKIS demonstrated acceptable internal consistency (Tucker et al., 2011). Additional items are used to assess for comorbid disorders and other associated symptoms (e.g., depression, anxiety, stress).

 

Finally, a unique approach to assessing excoriation disorder is to utilize a functional analysis assessment (LaBrot, Dufrene, Ness, & Mitchell, 2014). Although not created primarily to assess skin picking behaviors, a functional analysis assessment is a behavioral technique used to explore the relationship between any stimuli and response (e.g., being cold and shivering; LaBrot et al., 2014). With regards to excoriation disorder, the functional analysis assessment consists of behavior scales and individual interviews with anyone close to the client (e.g., spouse, family member, classroom teacher). The interviews include a discussion of the client’s behaviors and antecedents to such behaviors (LaBrot et al., 2014). This interview also involves a direct observation of the client in the most problematic setting (e.g., home, work, school), and counselors should take note of the time of day or events that often lead up to skin picking behaviors.

 

A functional analysis assessment also might involve the use of a thought log to help explore thoughts that lead to skin picking behaviors (LaBrot et al., 2014). This connection between thoughts (i.e., obsessions) and behaviors (i.e., compulsions) is characteristic of the obsessive-compulsive DSM-5 classification under which excoriation disorder is housed. Counselors may suggest that clients self-monitor their skin picking behaviors in order to better understand the frequency, triggers, cues, and increases or reductions in thoughts and behaviors. For example, clients may be asked to place a journal or worksheet in places where picking often occurs (e.g., bathroom, bedroom) and then to report and rate the intensity of urges, precipitating events, alternative behaviors, and if picking behaviors actually occurred. When assessing skin picking, clients also should be invited to note any attempts to stop picking, consequences of the skin picking behaviors, and other behaviors that could potentially serve as incompatible replacements (LaBrot et al., 2014). The use of a functional analysis assessment allows the counselor to gain a more complete, contextual picture of the behaviors.

 

To gain a richer understanding of the client’s behaviors, counselors might (if approved by the client) gather assessment and baseline information from the client’s friends and family members (Grant & Stein, 2014). During the assessment process, counselors should explore all aspects of the client’s life, including recent life experiences, past traumas and current life stressors (LaBrot et al., 2014).  An accurate diagnosis and collaborative treatment plan can be developed when this information is integrated to form a contextual understanding of the client’s skin picking experiences.

 

Diagnosis

A thorough assessment helps counselors to identify an accurate diagnosis. Armed with assessment data, counselors can determine the presence of excoriation disorder and any comorbid disorders. In order to accurately diagnose the disorder, counselors must be familiar with the DSM-5 diagnostic criteria and understand diagnostic considerations related to the disorder.

 

The onset of excoriation disorder varies significantly, but it most often begins in early adolescence or between the ages of 30 to 45 years old (Grant et al., 2012). Skin picking causes physical harm, and clients often make repeated attempts to reduce the behavior because of the distress and physical impairment it invites. By definition, excoriation disorder is not caused by a substance or medical condition and not accounted for by another disorder (APA, 2013). The diagnostic features of excoriation disorder remain the same regardless of age or other multicultural factors (Grant et al., 2012). The general features that a counselor should look for when diagnosing excoriation disorder include a preoccupation with picking behaviors, difficulty in controlling the behaviors and distress resulting from the behaviors.

 

Because this is a newer diagnosis, it is often overlooked, misdiagnosed (Grant et al., 2012), or overshadowed by comorbid diagnoses (APA, 2013; Grant & Stein, 2014; Hayes et al., 2009). It is important to distinguish between excoriation disorder and nonsuicidal self-injury, both of which involve self-inflicted damage to the body that provides relief from unwanted thoughts or feelings (APA, 2013). Nonsuicidal self-injury is typically motivated by negative thoughts or feelings about the self in relation to others, and bodily harm provides a feeling of relief or euphoria (APA, 2013; Shapiro, 2008). Conversely, excoriation disorder is an obsessive-compulsive and related disorder and is more ritualistic; unwanted thoughts and feelings are directly related to bumps or certain types of scabs on the body, and clients have a routine related to removal (e.g., examining, picking) and disposal (e.g., playing with or eating) of such bumps or scabs (APA, 2013; Capriotti et al., 2015; Walther et al., 2009).

 

Individuals with excoriation disorder generally have difficulty resisting the urge to pick and often believe their behavior cannot be altered or changed (Kress & Paylo, 2015). Typically, there are two types of picking behaviors: behaviors that are automatic and behaviors that are focused (Christenson & Mackenzie, 1994). Individuals who engage in picking behavior outside of their awareness, such as while watching television or while reading a book, are engaging in what is known as automatic picking. Those who are fully aware of their behavior and pick to regulate or to manage negative emotions due to specific thoughts or stressors are engaging in focused picking. Both types of picking typically cause client embarrassment, impair functioning and are difficult to manage and control (Odlaug, Chamberlain, & Grant, 2010).

 

Although focused skin picking might seem to be more directly tied to conscious obsessions than the automatic type, both types were reclassified under obsessive-compulsive and related disorders in the DSM-5 due to the universal obsessive and compulsive features of the disorder; these obsessions and compulsions also are shared with individuals who have trichotillomania (Snorrason, Belleau, & Woods, 2012) and body dysmorphic disorder (Tucker et al., 2011). In each of these disorders, obsessions lead to an overwhelming urge to act upon unhelpful thoughts, which is often followed by a brief sense of relief once the compulsion has been engaged and completed. However, the urge inevitably arises again (despite bodily damage and some potential shame), and the cycle continues.

 

Ultimately, excoriation disorder is characterized by recurrent and excessive tissue damage that is not better accounted for by nonsuicidal self-injury. Those who have excoriation disorder have difficulty controlling their picking behaviors and experience clinically significant distress or impairment as a result of these behaviors (APA, 2013). Assessment measures can be used in conjunction with the DSM-5 in order to make an accurate diagnosis that can inform clients’ treatment.

 

Treatment of Excoriation Disorder

 

Several evidence-based treatment options are available for use in treating those who have excoriation disorder (Kress & Paylo, 2015). Unfortunately, many providers fail to use evidence-based treatment approaches in their work with this population (Tucker et al., 2011). A relatively small number of randomized controlled treatment studies have been conducted on this population; however, the most evidence-based approaches include cognitive behavioral therapy, habit reversal training and pharmacotherapy (Capriotti et al., 2015; Kress & Paylo, 2015).

 

Cognitive Behavioral Therapy

Cognitive behavioral therapy (CBT) is an effective strategy for working with clients who have excoriation disorder (Grant et al., 2012; Schuck, Keijsers, & Rinck, 2011). Schuck et al. (2011) conducted a randomized study of college-age students who reported pathological skin picking; participants were provided four sessions of CBT and compared to those on a waitlist. These researchers observed a significant decrease in psychosocial impact of skin picking, severity of skin picking and perceived strength of skin picking cognitions in the group randomly assigned to the four sessions of CBT. These treatment effects were maintained at a two-month follow-up, thus suggesting that CBT is effective in reducing the severity of symptoms, effect of symptoms and dysfunctional cognitions associated with excoriation disorder.

 

Practically, CBT for clients with excoriation disorder is focused on using cognitive restructuring to counter dysfunctional thoughts (Schuck et al., 2011). Before engaging in CBT techniques, a counselor should ascertain the nature and location of the picking and provide clients with psychoeducation regarding the etiological and maintenance factors related to their disorder. Socratic questioning is one CBT technique used to help clients recognize their fundamental beliefs and automatic thoughts surrounding skin picking (Kress & Paylo, 2015). When applying this technique, the counselor generates a hypothesis about the client’s thoughts (that lead to skin picking), but leads the client to the information rather than suggesting it. The client is led to insight through a series of questions regarding the topic of interest. For example, the counselor might believe that a client’s skin picking obsessions become stronger when personal and professional obligations become overwhelming. The counselor might ask, “What feelings do you have when picking? What time of day do you typically pick? Are there ever days when you do not pick?” The counselor would use reflections to organize and expand upon the client’s responses until they gain new insight about their thoughts, patterns and beliefs regarding this behavior.

 

When using CBT, irrational thoughts are examined for validity and replaced with more rational thoughts and behaviors (Kress & Paylo, 2015). For example, an individual tempted to engage in skin picking after an argument with a spouse would challenge the need to pick with more rational thoughts, such as, “Even if I become anxious, I can tolerate the anxiety. Instead of picking, I can clean the house or exercise.” This type of change occurs over a period of time, and counselors and clients should celebrate small victories, such as delayed or reduced skin picking, as the more rational thoughts begin to become more salient.

 

CBT not only involves cognitive interventions, but also includes behavioral interventions such as homework, preventative measures, activity replacement and relapse prevention (Capriotti et al., 2015; Kress & Paylo, 2015; Schuck et al., 2011). Counselors may assign homework such as CBT thought logs to help clients track picking behaviors. While reviewing the logs in session, counselors can assist clients in developing preventative measures, such as wearing gloves or bandages to hinder skin picking, and activity replacement such as reading a book, cleaning or watching television instead of skin picking. CBT also places a heavy emphasis on relapse prevention, or the preparation to prevent future urges to pick.

 

Habit Reversal Training

Habit reversal training (HRT) is an effective strategy for working with clients who have excoriation disorder (Capriotti et al., 2015; Grant et al., 2012; Teng, Woods, & Twohig, 2006). HRT is a behavioral approach that involves helping clients gain awareness of their skin picking and then replace the picking with more adaptive behaviors (Grant et al., 2012; Ravindran et al., 2009; Snorrason & Bjorgvinsson, 2012; Teng et al., 2006). The first step of treatment is awareness training, which helps clients who are often unaware of their skin picking to associate factors, such as time of day and specific situations, to skin picking behavior (Teng et al., 2006). To facilitate this awareness, a counselor may point out in-session skin picking behavior. After developing an awareness of antecedent situations (i.e., the situations that precede picking incidents), the counselor and client collaboratively develop a competing response, or another behavior that is inconsistent with skin picking, to substitute for the skin picking behaviors (Teng et al. 2006). An example of an alternative behavior would be clenching one’s fist each time a client notices that he or she is picking. This competing response, which should be one that is easily applicable in a number of situations, diminishes the urge or reduces its intensity.

 

The next step in HRT is the establishment of a contingency management system or token economy involving rewards and punishments. This type of treatment approach allows the clients’ behaviors to be rewarded as they make successive approximations toward the goal. Rewards and punishments must be meaningful to clients, and they also must be specific and timely. At first, rewards are extrinsic, such as verbal praise or toys with children. As target behaviors are reached (e.g., reduced skin picking), clients begin to access more intrinsic reinforcers (e.g., an increased sense of self-esteem, feelings of belonging within the community/society). Finally, clients are coached to consistently implement these operant conditioning strategies outside of session and to eventually apply them to new behaviors (Capriotti et al., 2015; Teng et al., 2006). The client gradually realizes that skin picking is not a necessary coping skill, as other, more adaptive behaviors can be used to effectively reduce stress.

 

Teng et al. (2006) conducted a controlled study in which they compared HRT treatment to a waitlist control group. These researchers demonstrated a significant reduction in skin picking behaviors at the termination of treatment and upon follow-up assessment, as compared to the control group. The research on HRT suggests that it is a promising approach for use with those who have excoriation disorder.

 

Acceptance and Commitment Therapy

Acceptance and commitment therapy (ACT), when used in conjunction with HRT, demonstrates clinical promise in treating those who have excoriation disorder (Capriotti et al., 2015; Flessner, Busch, Heideman, & Woods, 2008). Capriotti et al. (2015), through the use of multiple clinical case studies, demonstrated that Acceptance-Enhanced Behavioral Therapy (i.e., ACT plus HRT) decreased excoriation symptomology in three of four participants in their case study research. These results support the findings of a similar case study done by Flessner et al. (2008), which demonstrated decreased symptomatology of excoriation disorder when ACT was incorporated with HRT.

 

ACT uses mindfulness techniques to teach acceptance of negative thoughts and emotions and then combines behavior-change techniques to address unhealthy behaviors (Flessner et al., 2008). Initially, the counselor helps the client investigate previous attempts to curb skin picking behaviors (such as avoidance or relaxation while picking). Then, the client and counselor work to distinguish between urges to pick (i.e., thoughts, feelings, sensations) and actual skin picking, emphasizing that even if urges are acted upon, they will soon return. As such, the focus is on increased distress tolerance and acceptance of urges (Kress & Paylo, 2015). The difficulty of controlling urges can be illustrated through metaphors in which the client gains control and a position of power over an undesirable, yet steadfast external circumstance (e.g., working is unavoidable, but you can find a job you enjoy).

 

Next, using ACT treatment, the client’s ability to control his or her own thoughts and behaviors is highlighted. This emphasis on controlling behavior stands in contrast to most clients’ natural inclination to focus on controlling or avoiding external situations. Next, the counselor and client work to modify and change the thoughts and feelings associated with urges to pick (Flessner et al., 2008). The client and counselor address six processes that contribute to healthy, flexible living: present-moment awareness; acceptance (as opposed to avoidance); nonjudgmental awareness of one’s thoughts; values clarification; changing, rather than reducing, unhelpful thoughts; and short- and long-term behavioral goals. Lastly, treatment progress is reviewed, and the client and counselor engage in relapse management (Flessner et al., 2008; Twohig, Hayes, & Masuda, 2006). Counselors also can integrate medication management when therapeutically indicated.

 

Pharmacotherapy

If pharmacotherapy is used to treat excoriation disorder, it should be used in conjunction with counseling; medication can control physical symptoms, but contributing mental health factors must be addressed in order to holistically help the client make enduring behavior changes (Grant et al., 2012). Selective serotonin reuptake inhibitors, specifically Fluoxetine (Prozac), have been shown to be effective in treating excoriation disorder and other BFRB (Grant et al., 2012; Simeon et al., 1997). However, this effect has not been consistent across clients (Grant & Odlaug, 2009). Therefore, additional research on the effectiveness of medication is needed. Counselors should provide intentional treatments for clients while taking into account unique client considerations.

 

Special Considerations

 

Although those with excoriation disorder might go to great efforts to conceal their wounds from others (Grant & Odlaug, 2009), they are likely to admit to skin picking behaviors when effectively questioned by a mental health professional (APA, 2013). It is important to ensure the clients with excoriation disorder are physically well (i.e., free from medical complications associated with picking), and a referral to medical professionals to ensure physical safety and appropriate medical care may be necessary (Grant et al., 2012).

 

Excoriation disorder occurs more often in those who also have OCD (APA, 2013). Several additional disorders are often found to be comorbid with excoriation disorder, including trichotillomania, major depressive disorder, anxiety, psychotic disorders, neurodevelopmental disorders and factitious disorder (APA, 2013; Hayes et al., 2009). Picking behaviors also could be due to a general medical condition or substance use (e.g., such as with methamphetamine addictions), and these should be ruled out (APA, 2013).

 

     Those with first-degree family members who have excoriation disorder are more likely to also develop skin picking behaviors (APA, 2013). However, skin picking often begins during puberty, and the onset is often associated with the development of skin irregularities (e.g., acne; APA, 2013, Tucker et al., 2011). It was found that approximately 87% of college-aged students in Turkey who had acne or other skin blemishes displayed some skin picking behaviors, but only about 2% reported clinically-significant symptoms of excoriation disorder (Calikusu, Kucukgoncu, Tecer, & Bestepe, 2012). The aforementioned finding suggests that dermatological factors, such as acne, might explain the onset of excoriation disorder, but not necessarily the maintenance of such behaviors. As such, family history of such behaviors should be considered by counselors when assessing and treating this disorder.

 

Collaborative relationships with other professionals can be helpful when working with a client who has excoriation disorder. If clients are provided with psychopharmaceutical interventions, counselors should take care to communicate with the prescribing physician in order to help the client maintain proper medication schedules and to potentially provide psychoeducational support to the client (Grant et al., 2012). Although consultation with a dermatologist is not always necessary, this valuable resource should be integrated into treatment when possible, and open communication can ensure that clients are receiving the support that they need (Calikusu et al., 2012; Grant et al., 2012).

 

Finally, although excoriation disorder is now an official DSM diagnosis, the research literature on effective treatments is still in its infancy stage (Capriotti et al., 2015). Additional research also is needed to determine the prognosis of excoriation disorder. As previously indicated, researchers have found psychopharmaceutical and cognitive behavioral interventions to be promising (Flessner et al., 2008; Grant et al., 2012; Schuck, et al., 2011; Simeon et al., 1997), but additional outcome research still needs to be conducted on this disorder (Capriotti et al., 2015). Further research on this new DSM-5 disorder will provide more concrete information regarding assessment and treatment options for this population.

 

Summary

 

The etiology of excoriation disorder is still being explored, and several theories are currently supported as viable options. Both biological and psychological factors appear to contribute to the development and maintenance of this disorder (Grant et al., 2012). Skin picking behaviors are often found in those who have higher levels of emotional impulsivity, and these behaviors might serve as a way for individuals to regulate their emotions.

 

There are several formal measures that can be used to aid in the assessment and diagnosis of excoriation disorder. In addition to formal quantitative measures, the functional analysis assessment is a helpful method that can be used to increase both the client’s and the counselor’s understanding of the behaviors (LaBrot et al., 2014). Regardless of the assessment procedures employed, counselors should explore all aspects of the client’s life in order to create a comprehensive treatment approach.

 

Since excoriation disorder is a new diagnosis in the DSM-5, it is often overlooked or misdiagnosed. Counselors should fully assess a client’s presenting concerns in order to determine an accurate and helpful diagnosis. Counselors also should note that this disorder is often comorbid with other mental disorders (APA, 2013; Grant et al., 2011; Hayes et al., 2009).

 

In terms of the treatment of excoriation disorder, CBT is one of the more evidence-based approaches (Grant et al., 2012; Schuck et al., 2011), as is HRT (Grant et al., 2012; Teng et al., 2006). ACT has been used with success with HRT (Capriotti et al., 2015; Flessner et al., 2008). Psychopharmacotherapy also holds promise as an effective adjunct to psychosocial treatments (Grant et al., 2012; Simeon et al., 1997).

 

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.

 

 

 

References

 

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Capriotti, M. R., Ely, L. J., Snorrason, I., & Woods, D. W. (2015). Acceptance-enhanced behavior therapy for excoriation (skin-picking) disorder in adults: A clinical case series. Cognitive and Behavioral Practice, 22(2), 230-239. doi:10.1016/j.cbpra.2014.01.008

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Dufour, B. D., Adeola, O., Cheng, H. W., Donkin, S. S., Klein, J. D., Pajor, E. A., & Garner, J. P. (2010). Nutritional up-regulation of serotonin paradoxically induces compulsive behavior. Nutritional Neuroscience, 13,
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Flessner, C. A., Berman, N. C., Garcia, A. M., Freeman, J. B., & Leonard, H. L. (2009). Symptom profiles on pediatric obsessive compulsive disorder: The effects of comorbid grooming conditions. Journal of Anxiety Disorders, 23, 753–759. doi:10.1016/j.janxdis.2009.02.018

Flessner, C. A., Busch, A. M., Heideman, P. W., & Woods, D. W. (2008). Acceptance-enhanced behavior therapy (AEBT) for trichotillomania and chronic skin picking: Exploring the effects of component sequencing. Behavior Modification, 32, 579–594. doi:10.1177/0145445507313800

Grant, J. E., & Odlaug, B. L. (2009). Update on pathological skin picking. Current Psychiatry Reports, 11, 283–288.

Grant, J. E., Odlaug, B. L., & Chamberlain, S. R. (2011). A cognitive comparison of pathological skin picking and trichotillomania. Journal of Psychiatric Research, 45, 1634–1638. doi:10.1016/j.jpsychires.2011.07.012

Grant, J. E., Odlaug, B. L., Chamberlain, S. R., Keuthen, N. J., Lochner, C., & Stein, D. J. (2012). Skin picking disorder. American Journal of Psychiatry, 169, 1143–1149. doi:10.1176/appi.ajp.2012.12040508

Grant, J. E., & Stein, D. J. (2014). Body-focused repetitive disorders in ICD-11. Revista Brasileira de Psiquiatria, 36, S59–S64. doi:10.1590/1516-4446-2013-1228

Hayes, S. L., Storch, E. A., & Berlanga, L. (2009). Skin picking behaviors: An examination of the prevalence and severity in a community sample. Journal of Anxiety Disorders, 23, 314–319. doi:10.1016/j.janxdis.2009.01.008

Keuthen, N. J., Deckersbach, T., Wilhelm, S., Engelhard, I., Forker, A., O’Sullivan, R. L., . . . & Baer, L. (2001a). The Skin Picking Impact Scale (SPIS): Scale development and psychometric analyses. Psychosomatics, 42, 397–403.

Keuthen, N. J., Sabine, W., Deckersbach, T., Engelhard, I. M., Forker, A. E., Baer, L., & Jenike, M. A. (2001b). The Skin Picking Scale: Scale construction and psychometric analyses. Journal of Psychosomatic Research, 50, 337–341.

Kress, V. E, & Paylo, M. J. (2015). Treating those with mental disorders: A comprehensive approach to case conceptualization and treatment. Upper Saddle River, NJ: Pearson.

LaBrot, L., Dufrene, B. A., Ness, E., & Mitchell, R. (2014). Functional assessment and treatment of trichotillomania and skin-picking: A case study. Journal of Obsessive-Compulsive and Related Disorders, 3, 257–264. doi:10.1016/j.jocrd.2014.06.006

Lang, R., Didden, R., Machalicek, W., Rispoli, M., Sigafoos, J., Lancioni, G., . . . & Kang, S. (2010). Behavioral treatment of chronic skin-picking in individuals with developmental disabilities: A systematic review. Research in Developmental Disabilities, 31, 304–315. doi:10.1016/j.ridd.2009.10.017

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Ravindran, A. V., da Silva, T. L., Ravindran, L. N., Richter, M. A., & Rector, N. A. (2009). Obsessive-compulsive spectrum disorders: A review of the evidence-based treatments. The Canadian Journal of Psychiatry, 54, 331–343.

Schuck, K., Keijsers, G. P., & Rinck, M. (2011). The effects of brief cognitive-behaviour therapy for pathological skin picking: A randomized comparison to wait-list control. Behaviour Research and Therapy, 49, 11–17. doi:10.1016/j.brat.2010.09.005

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Simeon, D., Stein, D. J., Gross, S., Islam, N., Schmeidler, J., & Hollander, E. (1997). A double-blind trial of fluoxetine in pathological skin picking. Journal of Clinical Psychiatry, 58, 341–347.

Snorrason, Í., Belleau, E. L., & Woods, D. W. (2012). How related are hair pulling disorder (trichotillomania) and skin picking disorder? A review of evidence for comorbidity, similarities and shared etiology. Clinical Psychology Review, 32, 618–629. doi:10.1016/j.cpr.2012.05.008

Snorrason, Í., & Bjorgvinsson, T. (2012). Diagnosis and treatment of hair pulling and skin picking disorders. Laeknabladid, 98, 155–162.

Snorrason, Í., Ólafsson, R. P., Flessner, C. A., Keuthen, N. J., Franklin, M. E., & Woods, D. W. (2013). The Skin Picking Impact Scale: Factor structure, validity and development of a short version. Scandinavian Journal of Psychology, 54, 344–348. doi:0.1111/sjop.12057

Snorrason, Í., Smári, J., & Ólafsson, R. P. (2011). Motor inhibition, reflection impulsivity, and trait impulsivity in pathological skin picking. Behavior Therapy, 42, 521–532. doi:10.1016/j.beth.2010.12.002

Teng, E. J., Woods, D. W., & Twohig, M. P. (2006). Habit reversal as a treatment for chronic skin picking: A pilot investigation. Behavior Modification, 30, 411–422.

Tucker, B. T., Woods, D. W., Flessner, C. A., Franklin, S. A., & Franklin, M. E. (2011). The skin picking impact project: Phenomenology, interference, and treatment utilization of pathological skin picking in a population-based sample. Journal of Anxiety Disorders, 25, 88–95. doi:10.1016/j.janxdis.2010.08.007

Twohig, M. P., Hayes, S. C., & Masuda, A. (2006). A preliminary investigation of acceptance and commitment therapy as a treatment for chronic skin picking. Behaviour Research and Therapy, 44, 1513–1522. doi:10.1016/j.brat.2005.10.002

Walther, M. R., Flessner, C. A., Conelea, C. A., & Woods, D. W. (2009). The Milwaukee Inventory for the Dimensions of Adult Skin Picking (MIDAS): Initial development and psychometric properties. Journal of Behavior Therapy and Experimental Psychiatry, 40, 127–135. doi:10.1016/j.jbtep.2008.07.002

 

 

 

Nicole A. Stargell, NCC, is an Assistant Professor at the University of North Carolina at Pembroke. Victoria E. Kress, NCC, is a Professor at Youngstown State University. Matthew J. Paylo is an Associate Professor at Youngstown State University. Alison Zins is a graduate student at Youngstown State University. Correspondence can be addressed to Nicole Stargell, UNC Pembroke, P.O. Box 1510, Department of Educational Leadership and Counseling, 341 Education Building, Pembroke, NC 28372, nicole.stargell@uncp.edu.

 

Back to Basics: Using the DSM-5 to Benefit Clients

Matthew R. Buckley

It is a pleasure to introduce this special DSM-5 edition of The Professional Counselor, which provides a solid primer regarding changes in the DSM-5 diagnosis process and how these changes will likely impact mental health professionals. Changes within the DSM-5 have prompted counselors to revisit the basics of diagnosis and consider the cessation of certain conventions (e.g., the multiaxial system) and what these changes mean to counselors as they perform their vital work for the benefit of clients. The unprecedented inclusion of various mental health professionals in the development of the DSM-5 is an inherent recognition of how this tool is being used across a wide range of professional disciplines that focus on psychopathology. I hope these articles not only inform, but encourage further research into the practical use of the DSM-5, “stimulate new clinical perspectives” in mental illness (American Psychiatric Association [APA], 2013, p. 10), and inspire continued professional dialogue around DSM nosology and the diagnostic processes.

Keywords: DSM-5, diagnosis, psychopathology, mental illness, multiaxial system

The fifth edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) is an update of a major diagnostic tool (APA, 2013). The manual was originally designed to help mental health professionals within a wide variety of disciplines assess and conceptualize cases in which people were suffering from mental distress. This conceptualization is important in that it facilitates an understanding in a common language toward the development of treatment planning to address complex and entrenched symptomology. The DSM has undergone numerous iterations and represents the current knowledge of mental health professionals about mental illness (APA, 2013). One of the primary aims of the DSM-5 workgroups was to align the manual with the current version of the International Classification of Diseases (ICD-9). In addition, political, social, legal and cultural dynamics influenced the development of the DSM-5—and not without controversy (Greenberg, 2013; Locke, 2011; Linde, 2010; Pomeroy & Anderson, 2013). As with any tool, concerns have emerged about the potential of misuse. It is the professional responsibility of skilled and ethical mental health counselors and other professionals to prevent misapplication of the manual (American Counseling Association [ACA], 2014, E.1.b, E.5.a–d). Walsh (2007) succinctly noted that “the primary goal of the DSM is to enhance the care of individuals with psychiatric disorders” (p. S3).

The introduction of the DSM-IV-TR states that the DSM has been used by numerous mental health practitioners (APA, 2000), with no mention of their investment as legitimate stakeholders in the process of DSM development. Well before the final revision of the DSM-5, various mental health professionals, organizations and other relevant collaborators helped formulate the manual in unprecedented capacities. In the introduction to the DSM-5 (APA, 2013) the authors intentionally state that numerous stakeholders were involved in DSM-5 development including counselors and “patients, families, lawyers, consumer organizations, and advocacy groups” (p. 6). Of particular note was the inclusion of national organizations such as the ACA in the form of a DSM-5 task force, which submitted position statements and recommendations to the APA. Various mental health professionals participated directly in the formulation of the DSM-5, primarily in field trials which “supplied valuable information about how proposed revisions performed in everyday clinical settings” (p. 8). Much of the data supports the use of more than 60 cross-cutting and severity symptom measures (see http://www.psychiatry.org/practice/dsm/dsm5/online-assessment-measures).

Clinical Utility

First (2010) reported that utilizing broad and diverse populations of mental health professionals provides rigor for clinical utility. Achieving clinical utility within the DSM diagnostic processes meets the following four objectives:

to help clinicians communicate clinical information to other practitioners, to patients and their families, and to health care systems administrators;

to help clinicians implement effective interventions in order to improve clinical outcomes;

to help clinicians predict the future in terms of clinical management needs and likely outcomes; and

to help clinicians differentiate disorder from non-disorder for the purpose of determining who might benefit from disorder-based treatments. (First, 2010, p. 466)

Any changes to the DSM were framed within the context of how they might be utilized by all mental health professionals, including revisions to definitions of diagnoses and symptoms, proposed diagnostic categories, dimensional assessment (including cross-cutting), and a renewed emphasis on severity specifiers. Ultimately, the consideration was whether the revised manual would be accepted and utilized by the practitioners it proposed to serve (APA, 2013; First, 2010). First (2010) noted that no mandate exists requiring the use of the DSM by any professional, and that other tools used to arrive at an ICD diagnosis exist or are in development (e.g., the NIMH Research Domain Criteria initiative; APA, 2013; Nussbaum, 2013). The DSM-5 workgroups were challenged to revise the manual in order to make it user-friendly and maintain its relevance among mental health professionals. Even though the manual is an imperfect resource, the goal was to enhance clinical utility.

Determining a Differential Diagnosis

In his primer on diagnostic assessment focused on the DSM-5, Nussbaum (2013) offers six considerations in determining a differential diagnosis that serve as an important basis for practice. These considerations or steps include the following:

to what extent signs and symptoms may be intentionally produced;

to what extent signs and symptoms are related to substances;

to what extent signs and symptoms are related to another medical condition;

to what extent signs and symptoms are related to a developmental conflict or stage;

to what extent signs and symptoms are related to a mental disorder; and

whether no mental disorder is present.

Each of these process steps serves as important reminders for getting back to the basics of rendering diagnoses that help inform treatment. When working with clients, these steps function as points of reference to rule out potential factors influencing misdiagnosis. Additionally, client cultural factors are essential at capturing comprehensive context for assessment and diagnosis.

Consider to what extent signs and symptoms may be intentionally produced. Signs and symptoms may be purposely feigned on the part of a client for secondary gain (e.g., financial benefits, drug seeking, disability status, attention from others, reinforcement of an identity of pathology, avoiding incarceration). Counselors must recognize the context in which signs and symptoms occur and pay attention when something does not “fit” with how a client presents for treatment. Assessing prior mental health treatment (including outcomes), cultural factors and potential motives to fake an illness can assist counselors in making an accurate differential diagnosis.

Consider to what extent signs and symptoms are related to substances. A wise and influential professor and mentor during my graduate training said, “Always assess for substance use!” Clients can present with a variety of conditions that are induced by prescription or over-the-counter drugs, illicit substance, or herbal supplements (Nussbaum, 2013). An important emphasis within the DSM-5 is substance-use and substance-induced disorders, which are included in many relevant diagnostic criteria (APA, 2013). Counselors are well-advised to make this determination in the initial assessment and continue to assess throughout the course of treatment.

Consider to what extent signs and symptoms are related to another medical condition. Clients present with signs and symptoms that may be caused by or coincident with another medical condition in a variety of ways. Nussbaum (2013) defined possible manifestations including (a) medical conditions that directly or indirectly alter signs and symptoms, (b) treatments for medical conditions that alter signs or symptoms, (c)  mental disorders and/or treatments that may cause or exacerbate medical conditions, or (d)  both a mental disorder and a medical condition that are not causally related. Counselors should gather medical information from the client and appropriately follow up with medical personnel as needed to ensure proper and accurate diagnosis, which will lead to more targeted and effective treatment.

Consider to what extent signs and symptoms are related to a developmental conflict or stage. A primary strength of counseling professional identity is the focus on human development as a key factor in client distress and resiliency. The counseling practice of “meeting clients where they are” includes where they are developmentally. Counselors must recognize where incongruence exists between what clients present and the expected behaviors or characteristics of their particular developmental stage. Nussbaum (2013) stresses the importance of gathering a comprehensive psychosocial history to determine expected developmental milestones. Being on the lookout for developmental delays,  regressive behaviors of an earlier developmental period, primal defense mechanisms, or signs of “a developmental conflict in a particular relationship” (p. 201) will help ensure that all essential contextual factors are addressed when making a diagnosis.

Consider to what extent signs and symptoms are related to a mental disorder. The definition of mental disorder has not changed significantly from previous versions of the DSM: a mental disorder is “a syndrome characterized by clinically significant disturbance in…cognition, emotion regulation, or behavior that reflects a dysfunction in the psychological, biological, or developmental processes…[and] usually associated with significant distress or disability in social, occupational, or other important activities” (APA, 2013, p. 20). Identifying mental disorders, or the process of diagnosis, involves more than clear-cut observations and often includes the consideration of complex factors involving comorbidity, symptom clusters “that may be part of a more complex and unified syndrome that has been artificially split in the diagnostic system” (Nussbaum, 2013, p. 202), overlap between diagnostic criteria, genetic predisposition, and the mutual influence of two or more conditions. Counselors must be careful to consider the presence of these factors, consult when necessary, and take into account differential diagnosis to determine the most appropriate diagnosis given the verbal and observable data available.

Consider whether no mental disorder is present. Sometimes a client may present with symptoms that do not meet the full diagnostic criteria for a mental disorder, despite significant distress in social, occupational or other areas of functioning. In these cases, utilizing the not otherwise specified or unspecified diagnoses may be warranted in order to provide opportunities for deeper inquiry. For example, the symptoms of a disorder may be a secondary reaction to an identifiable social stressor that may justify a diagnosis of an adjustment disorder. The possibility exists that there may not be a diagnosis present (Nussbaum, 2013), and in these cases, counselors and other mental health professionals are challenged to make that decision in the face of pressures to diagnose.

Cultural Implications

It is imperative that counselors take their clients’ social and cultural influences into account when assessing and diagnosing. Culture impacts all aspects of diagnosis and treatment, including how and when treatment is sought; power differentials between clients and mental health professionals; the age, gender, ethnicity, race, religion, sexual orientation, and socioeconomic status of both clients and mental health professionals; how illness is defined by both; and how problems are conceptualized and addressed within the context of culture (Lewis-Fernández et al., 2014; Tomlinson-Clarke & Georges, 2014).

Two decades of experience using the Outline for Cultural Formulation (OCR), which was introduced in the DSM-IV (APA, 1994), evolved into the Cultural Formulation Interview (CFI) now contained in the DSM-5, comprised of 16 semi-structured questions designed to collect data in a more consistent and efficient manner. Like other dimensional, cross-cutting and severity measures developed specifically for the DSM-5, the CFI was field tested at 12 sites representing several countries to determine feasibility and usefulness (Lewis-Fernández et al., 2014). For the first time, culture in its varied manifestations has been intentionally incorporated into the DSM nosology through a specific assessment instrument. “The CFI follows a person-centered approach to cultural assessment…designed to avoid stereotyping, in that each individual’s cultural knowledge affects how he or she interprets illness experience and guides how he or she seeks help” (APA, 2013, p. 751). Counselors are encouraged to utilize the CFI as a way to understand their clients more meaningfully and to aid in clinical utility.

The TPC Special Issue: Counseling and the DSM-5 

Because the DSM-5 is a tool for mental health professionals to utilize in their conceptualization of client distress, understanding how to use the DSM effectively is at the heart of this special issue published by The Professional Counselor (TPC). Readers will find a variety of articles that will assist mental health professionals by providing important context for most of the salient changes within the DSM-5 (APA, 2013) from the perspective of professional counseling. Inherent in each of these contributions is the theme of getting back to the basics in not only understanding the DSM-5 conceptually, but also providing ideas for putting concepts into practice.

An essential element in understanding and using the DSM-5 effectively is exploring the foundational and historical roots of this complex nosology. Dailey, Gill, Karl, and Barrio Minton (2014); Gintner (2014); and Kress, Barrio Minton, Adamson, Paylo and Pope (2014) offer excellent overviews of salient changes within the DSM-5 that impact clinical practice, including how the DSM has evolved over time. While there is necessary redundancy on key points (e.g., elimination of the multiaxial format, implementation of cross-cutting symptom measures, closer alignment with the ICD coding system), each article provides an important and unique perspective. Dailey et al. (2014) offer important perceptions on changes within the DSM-5 including how changes evolved historically and the philosophical foundations behind those changes, especially those that clash with the philosophical underpinnings of counseling. The authors review the implications of such changes for professional counselors. Gintner (2014) provides an excellent context regarding the harmonization of the DSM-5 with the ICD, the inclusion of cross-cutting symptom measures and dimensional assessment, and how the manual is organized. The article focuses on how counselors might respond to these changes. Kress et al. (2014) offer an important perspective on the removal of the multiaxial convention used by mental health professionals for over three decades and the implications for counselors in the practice of assessment and diagnosis. These authors provide an important context for the decision to terminate the multiaxial system including advantages and disadvantages of DSM-5 changes.

King (2014) describes the practical application of diagnostic criteria and the use of cross-cutting dimensional assessments. This perspective offers a backdrop on which to compare current practice and how it may alter with use of the DSM-5. This article focuses on clinical utility and ensuring that the DSM-5 remains a guide to assessment, diagnosis and treatment. Schmit and Balkin (2014) give a comprehensive review of the cross-cutting, dimensional and severity measures from the perspective of psychometric instrumentation, including the practical application of validity and reliability. These authors underscore DSM-5 assessments as soft measures and provide important cautions to counselors using these instruments in their work with clients, including the importance of developing multiple data points.

Understanding specific diagnostic categories is essential to good clinical practice. Welfare and Cook (2014); Kenny, Ward-Lichterman and Abdelmonem (2014); and Jones and Cureton (2014) provide solid descriptions of specific diagnostic criteria and emphasize areas essential to our understanding of developmental and demographic strata. Welfare and Cook (2014) tackle chronic and persistent mental illness manifested in diagnoses within the following categories: schizophrenia spectrum and other psychotic disorders, bipolar and related disorders, and depressive disorders.  Clinical examples help contextualize the process of assessing and diagnosing these disorders and provide a detailed example of effectively utilizing each step of the diagnostic process. Kenny et al. (2014) provide a cogent overview of the changes made to the “Feeding and Eating Disorders” chapter, including the addition of binge eating and avoidant/restrictive food intake disorders, severity criteria for anorexia nervosa based on body mass indexes, and how the diagnosis of eating disorder not otherwise specified (EDNOS) has changed as a result. Jones and Cureton (2014) offer important perspectives on significant changes to the “Trauma- and Stressor-Related Disorders” chapter and how these changes may impact clinical practice. The authors discuss how diagnostic criteria have been developed for both children and adults and how cross-cutting symptoms (e.g., panic and dissociation) manifest in a range of disorders. Another significant change to this category is the acknowledgement of sexual abuse as a traumatic event; this takes post-traumatic stress disorder (PTSD) out of the often associated realm of combat veterans and into more common and insidious manifestations of trauma.

Counselors should consider the aforementioned changes to the DSM-5 in the context of their counselor identity. Maintaining professional identity and promoting a wellness- and strength-based perspective continues to be an important concern for the counseling profession and the training of counselors. Tomlinson-Clarke and Georges (2014) provide an overview of maintaining professional identity in the process of assessment and diagnosis within a system representing the medical model. A particular strength is the inclusion of how multicultural competency is crucial in using the DSM-5 effectively, which is an essential basic foundation to sound practice. Implications for counselor preparation also are a focus. Finally, Frances (2014) provides a critical commentary of how the DSM has been used by pharmaceutical companies to leverage significant profits at the cost to consumers of mental health services and our economy. As the former chair of the DSM-IV task force, Frances reminds counselors and other mental health professionals of their essential place within treatment and cautions counselors to use the DSM in a balanced manner. His comments are consistent with advocacy inherent in our profession for treatments that promote client resilience, and address psychosocial and environmental factors that impact client functioning.

Conclusions

This special TPC issue on counseling and the DSM-5 provides a compilation of articles covering the history of the DSM, structural and categorical changes, the process of diagnosis, implications for practice, and cautions and criticisms. These articles validate the unique and important perspective counselors bring to their work, and challenge all mental health professionals to use the DSM-5 accurately. The DSM continues to evolve, and its advocates have made significant strides in reaching out to a variety of professionals; one manifestation of this outreach is the development of the DSM-5 website (see http://www.psychiatry.org/practice/dsm/dsm5). Counselors have the opportunity to use the DSM-5, provide feedback directly to the APA, and help shape and influence future editions of this diagnostic tool. This is an important way counselors can advocate for their clients as well as their profession, and shape how the DSM is used to help treat those suffering from mental and emotional distress.

 

Conflict of Interest and Funding Disclosure

The author reported no conflict of interest or funding contributions for the development of this manuscript.

 

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Gintner, G. G. (2014). DSM-5 conceptual changes: Innovations, limitations and clinical implications. The Professional Counselor, 4, 179–190. doi:10.15241/ggg.4.3.179

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Jones, L. K., & Cureton, J. L. (2014). Trauma redefined in the DSM-5: Rationale and implications for counseling practice. The Professional Counselor, 4, 257–271. doi:10.15241/lkj.4.3.257

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Matthew R. Buckley, NCC, is a faculty member in the Mental Health Counseling program at Walden University, Minneapolis, MN. Correspondence can be addressed to Matthew R. Buckley, Walden University, 100 Washington Avenue South, Suite 900, Minneapolis, MN 55401-2511, matthew.buckley@waldenu.edu.

 

DSM-5 Conceptual Changes: Innovations, Limitations and Clinical Implications

Gary G. Gintner

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) includes numerous alterations to specific disorders, as well as fundamental conceptual and organizational changes. The purpose of this article is to review three fundamental conceptual changes in DSM-5: the harmonization of the manual with the International Statistical Classification of Diseases and Related Health Problems, the introduction of spectrum disorders and dimensional ratings, and the new organization of the manual. For each change, potential benefits and shortcomings are discussed in terms of innovation, limitations and clinical implications.

Keywords:  DSM-5, ICD-10, classification, diagnosis, spectrum disorders 

The DSM is probably one of the most widely referenced texts in the mental health field. Considering this scope of influence, the release of its latest edition, DSM-5 (American Psychiatric Association [APA], 2013), has garnered considerable interest among professionals, patient advocacy groups and the public alike (Paris, 2013). Reactions have ranged from enthusiastic support (McCarron, 2013) to concern (Welch, Klassen, Borisova, & Clothier, 2013) and even calls to reject the manual’s use outright (Frances, 2013; Frances & Widiger; 2012). The strength of this reaction—both positive and negative—reflects the scope of change. DSM-5 attempts to integrate almost 20 years of burgeoning research in psychopathology, classification and treatment outcomes that have emerged since the publication of DSM-IV (APA, 1994), the last major revision of the manual’s criteria sets. While DSM-5 has made numerous alterations to specific disorders, fundamental conceptual and organizational changes have had the most substantial impact on reshaping the manual (APA, 2013; Regier, Kuhl, & Kupfer, 2013).

The purpose of this article is to review three of these fundamental conceptual changes: the harmonization of the manual with the ICD, the introduction of spectrum disorders and dimensional ratings, and the new organization of the manual. For each of these innovations, three questions will be addressed. First, what was the basis for introducing the change as an innovation to the manual? Here the rationale and potential contribution of the change will be discussed. Special attention will be paid to issues such as enhanced diagnostic accuracy, coverage and clinical utility. Second, does the innovation have any potential drawbacks or limitations? For example, to what extent could the innovation contribute to over or underdiagnosis, limit access to treatment, or pose some harm like increased stigmatization? Third, what are the practical consequences of the innovation relative to how clinical mental health counselors provide care for their clients? This section considers the impact on day-to-day practice and how the diagnostic process itself may be transformed. The conclusion section ties these three threads of innovations together and discusses implications for mental health practice in the 21st century.

DSM and ICD Harmony 

There are two major classification systems for mental disorders: the DSM, used primarily in North America, and the ICD, used worldwide under the auspices of the World Health Organization (WHO). The ICD is a much broader classification encompassing causes of death, illness, injury and related health issues with one chapter dedicated to mental and behavioral disorders (Stein, Lund, & Nesse, 2013). As part of the United Nations Charter, countries around the world have agreed to use the ICD codes to report mortality, morbidity and other health information so that uniform statistics can be compiled. In the United States, the ICD codes are the official codes approved by the Health Insurance Portability and Accountability Act (HIPAA), which are used by insurance companies, Medicare, Medicaid and other health-related agencies (Goodheart, 2014). The code numbers that the DSM has always used are derived from whatever the official version of ICD is at that time. Currently, the ninth revision of the ICD (ICD-9; WHO, 1979) is the official coding system in the United States. The 10th revision of the ICD (ICD-10; WHO, 1992/2010) is scheduled to go into effect on October 1, 2015. 

The DSM and ICD classifications of mental disorders have a number of similarities, but also have important differences. Both are descriptive classifications that categorize mental disorders based upon a constellation or syndrome of symptoms and signs. Symptoms are the client’s reports of personal experiences such as feeling sad, anxious or worried. Signs, on the other hand, are observable client behaviors such as crying, rapid speech, and flat affect. Structurally, both manuals group related mental disorders into either chapters (DSM) or diagnostic blocks (ICD). The names and diagnostic descriptions for many of the mental disorders in the ICD are similar to those in the DSM, a consequence of collaboration over the years and a shared empirical pool from which both have drawn. 

Despite these similarities, there are significant disparities. First, DSM criteria are very specific and detailed, while the ICD relies more on prototype descriptions with less detailed criteria and minimal background information to guide the diagnostic process (First, 2009; Paris, 2013; Stein et al., 2013; WHO, 1992). Second, since DSM-III (APA, 1980), the DSM has used a multiaxial system that notes not only relevant mental and medical disorders, but also other diagnostic information such as environmental factors (Axis IV) and level of functioning (Axis V). The ICD, on the other hand, has always employed a nonaxial system that simply lists medical disorders, mental disorders, and other health conditions. These differences in complexity reflect the constituencies that each manual is designed to serve: The DSM is primarily used by licensed mental health professionals with advanced degrees, while the ICD needs to be accessible to a range of health care professionals worldwide with a broad range of educational backgrounds (Kupfer, Kuhl, & Wulsin, 2013; WHO, 1992).

A third discrepancy is that the names and descriptions for many disorders differ, which at times reflects marked conceptual differences (First, 2009). For example, in ICD-10 (WHO, 1992) bulimia nervosa has to be characterized by a “morbid dread of fatness” (p. 179), a concept akin to anorexia, while DSM-IV-TR (Text Revision; APA, 2000) requires that self-evaluation be “influenced” (p. 549) by only body shape or weight. As another example, the definition of the type of trauma that qualifies for post-traumatic stress disorder (PTSD) is much broader in ICD-10 (allowing for events that are exceptionally threatening or catastrophic) than in DSM-IV-TR (requiring that the event must be associated with actual or threatened death, serious injury, or threat to the physical integrity). These ICD-DSM disparities have led to difficulties comparing research results, collecting health statistics, communicating diagnostic information and reaching similar diagnostic decisions (APA, 2013; First, 2009; Widiger, 2005). Like conversing in two different languages, the diagnosis has often been lost in translation. 

Innovation

From the outset of the DSM-5 development process there was a concerted effort to address these disparities. Joint meetings of representatives from APA and WHO met regularly throughout the process in an effort to make the manuals more compatible (APA, 2013; Regier et al., 2013). The goal was to find ways of harmonizing structural, conceptual and disorder-specific differences. The results of this process have had immediate effects on the look of DSM-5 and will have long-term effects on the harmonization of DSM-5 with the upcoming ICD-11, expected to be released in 2017 (APA, 2013; Goodheart, 2014). 

The most significant impact of the harmonizing effort is the discontinuation of the multiaxial system in DSM-5. Axes I–III, the diagnostic axes (APA, 2000), are now collapsed into a nonaxial system, consistent with the ICD format. Psychosocial and environmental problems (formerly Axis IV) can be noted using ICD-10’s codes for problems and situations that influence health status or reasons for seeking care. These are usually referred to as Z codes and were formerly termed V codes in DSM-IV-TR. Axis V’s Global Assessment of Functioning (GAF) has been removed and replaced by an ICD measure for disability, the World Health Organization Disability Assessment Schedule (WHODAS) 2.0 (APA, 2013). Unlike the GAF, however, this rating is not required and serves only as an ancillary tool.

The following is an example of how a DSM-5 diagnosis might be listed using ICD-9’s nonaxial system in ICD-9:

296.42 Bipolar I disorder, current episode manic, moderate severity, with mixed features

307.83 Borderline personality disorder

V62.29 Other problem related to employment

The order of diagnoses would indicate that the bipolar disorder was the principal diagnosis and either the focus of treatment or reason for visit. In this example, borderline personality disorder is a secondary diagnosis. The V code is noted because it is an important area to target in the treatment plan.

There were three major reasons for abandoning the multiaxial system. First, health professionals in general medicine found it difficult to use because it was so different from the ICD format (Kupfer et al., 2013). Second, the multiaxial system contributed to the idea that mental disorders were qualitatively different from medical disorders, a dated dualistic distinction between mind and body (APA, 2013; Kupfer et al., 2013; Lilienfeld, Smith, & Watts, 2013). Third, research had shown that distinctions between Axes I and II were artificial and did not reflect that these axes actually overlapped considerably (Lilienfeld et al., 2013). Thus, the multiaxial system seemed to create artificial distinctions that did not seem valid (Lilienfeld et al., 2013). The ICD, on the other hand, offered a more simplified system that allowed a diverse group of health professionals to code disorders using a similar format.

Substantial harmonization of the manuals, however, will happen in the future. Not much could be done with harmonizing ICD-10 (WHO, 1992), a manual of the DSM-IV (APA, 1994) era, the organization and conceptual framework of which were well established (APA, 2013; Goodheart, 2014). The forthcoming ICD-11 will adopt much of DSM-5’s organizational restructuring (discussed below) and include a number of the new DSM-5 disorders (APA, 2013; Goodheart, 2014). 

Limitations

Despite the potential contribution of this harmonization, there are three major drawbacks to consider. First, the loss of the multiaxial system may compromise the richness of the diagnostic assessment. In a sense, the multiaxial system was holistic in that it provided a way of noting prominent psychiatric conditions, maladaptive personality functioning, medical conditions, relevant stressors and environmental problems, and overall functioning. What will prompt clinicians to consider these important domains remains unclear. Noting V codes and assessing disability using the WHODAS 2.0 may be an alternative. However, these tasks are not required in the diagnostic workup and, if history is any guide, will probably be underutilized.

A second consideration is that consilience with the ICD clearly makes the DSM-5 a “medical classification” (APA, 2013, p. 10) and as David Kupfer, the Task Force Chair of DSM-5, has put it, “psychiatric disorders are medical disorders” (Kupfer et al., 2013, p. 388). The DSM espouses that it is atheoretical (APA, 2013; Lilienfeld et al., 2013), but the momentum is clearly swinging toward the central role of biological factors. This risks a reductionistic conceptualization of mind as simply brain. Alternative perspectives that recognize the importance of contextual, psychological, developmental and cultural factors, fundamental to the mental health counseling tradition (Gintner & Mears, 2009), may suffer as a result. The picture is more ominous considering the National Institute of Mental Health’s initiative, Research Domain Criteria (RDoC), designed to develop the next generation of psychiatric classification based upon underlying etiology of “brain disorders” (p. 749) and the identification of biomarkers (e.g., laboratory tests) to direct treatment selection (Insel et al., 2010). The direction in which the diagnostic train is heading is clear. The question is whether the track can be altered to one that is more balanced and biopsychosocial.

A third concern is that efforts to harmonize the manuals do not address many of the disparities between DSM-5 and ICD-9 or ICD-10. This is particularly true of the new disorders that DSM-5 has added, which lack clear ICD-9 or ICD-10 counterparts. The ICD codes that have been selected often do not map well onto these disorders. For example, the code for DSM-5’s hoarding disorder translates to ICD-9’s and ICD-10’s obsessive-compulsive disorder (OCD). Ironically, hoarding disorder was added because research showed that 80% of the time individuals with this condition did not meet criteria for OCD. As another example, binge eating disorder was added to DSM-5 to recognize individuals who had a pattern of maladaptive bingeing episodes, but did not have the compensatory behaviors (e.g., purging) characteristic of bulimia nervosa. The ICD code selected for this disorder was, nevertheless, bulimia nervosa. Because ICD is updated annually, it may be that more appropriate codes will be made available in future years. Thus, while ICD-DSM consilience has occurred, at least to this point, it has been superficial and restricted to the nonaxial formatting of the diagnosis. Clearly, it may enhance the curb appeal of DSM-5 to the medical community, but the real interior renovation is yet to occur, awaiting ICD-11. 

Clinical Implications

The demise of the multiaxial system means that mental health counselors must be more intentionally biopsychosocial in their diagnostic assessments. More meat can be put on the bare-bones nonaxial system by systematically assessing these biological, psychological and sociocultural factors. This can be accomplished by always assessing whether any important contextual factors can be noted using the V codes, which will be termed Z codes when ICD-10 goes into effect. The WHODAS 2.0, the retired GAF, and other functioning measures can be recruited to assess impairment. While these measures are not part of the formal diagnosis, they can be noted in the chart and inform treatment planning. 

Many insurance companies require a multiaxial diagnosis. The GAF score was often used to justify level of care. At the time of this writing, it is not clear what insurance companies will do with these modifications. The decision here will be important. What insurance companies require, for better or worse, often has profound impact on what clinicians do and the kind of clinical care they deliver.

Spectrum Disorders and Dimensionality 

Both the DSM and ICD classify mental disorders into discrete categories. Clinicians make a yes-no decision about whether or not an individual has a disorder, based upon the particular criteria. But it has long been known that this categorical approach is fraught with problems (First & Westen, 2007; Widiger, 2005). First, comorbidity is common and there is some question as to whether comorbid conditions such as depression and anxiety are distinct or are really different expressions of some shared underlying dysfunction (Lilienfeld et al., 2013). Second, clinicians have used the not otherwise specified (NOS) category 30–50% of the time, indicating that a sizable proportion of phenomena have a varied presentation that existing categories do not capture (Widiger, 2005). This is problematic because NOS is not particularly informative in terms of describing the condition or making decisions about treatments. Finally, a categorical system assumes that each disorder is homogenous and that disorder occurs at the particular cut point. There is no recognition of subthreshold symptoms, and there is the assumption that those who do fulfill the criteria are qualitatively similar. This view is at odds with data showing that symptoms vary considerably in terms of severity and accompanying features (First & Tasman, 2004). In this sense, categorical assignment loses potentially useful clinical information about the condition and about what treatment strategies might be indicated. 

Innovation

DSM-5 attempts to address this issue by introducing dimensionality to supplement the categorical approach (APA, 2013). While categories indicate differences in kind, dimensions describe variations in degree (Lilienfeld et al., 2013). From this perspective, mental disorders are considered to lie on a continuum, like blood pressure. Theoretically, the spectrum can run from optimal functioning to significant impairment. Markers of morbidity or adverse outcome determine where on the spectrum the cut point for disorder is drawn. In the case of blood pressure, for example, it is 140/90. This dimensionality allows for more fine-grained determination of not only severity or impairment, but also improvement or deterioration. Over the past 30 years, research has shown that many mental disorders appear to be more dimensional and heterogeneous than suggested by ICD’s or DSM’s purely categorical system (First & Westen, 2007; Helzer, 2011; Paris, 2013). 

Dimensionality is incorporated into DSM-5 in three general ways. First, DSM-5 has added several formal spectrum disorders, which combine highly related disorders. Autism spectrum disorder merges together DSM-IV-TR’s autism disorder, Asperger’s disorder, childhood disintegrative disorder and pervasive developmental disorder NOS. Research has shown that these four conditions share many common symptoms, and the differences are more a matter of degree (APA, 2013; Tsai & Ghaziuddin, 2014). Another spectrum disorder is substance use disorder, which blends the former categories of abuse and dependence. The somatic spectrum is captured by somatic symptoms disorder, which merges what was formerly somatization disorder, pain disorder and undifferentiated somatoform disorder. For each of these spectrum disorders, DSM-5 provides a severity rating as well as other specifiers to note degree of impairment and complicating features. 

A second way that dimensionality is infused into DSM-5 is that severity ratings and an expanded list of specifiers have been placed within the existing categories. In a sense, DSM-5 tries to dimensionalize the category. While this was done to some extent in previous editions, DSM-5 broadens this effort throughout the manual. For example, a number of new specifiers were added to describe mood episodes such as anxious distress (presence of comorbid anxiety), mixed features (presence of symptoms from the opposite mood pole), and peripartum onset (onset of symptoms sometime during pregnancy through one month post-delivery). The addition of these notations can be helpful in making treatment-planning decisions (First & Tasman, 2004). For example, severity ratings are an important consideration in deciding whether to use psychotherapy or medication for the treatment of major depressive disorder (APA, 2010). Feature specifiers like anxious distress and mixed features have been shown to increase suicide risk and portend a more complicated treatment regime (APA, 2013; Vieta & Valentí, 2013).

A third way that dimensionality is being promoted in DSM-5 is through the availability of a variety of online assessment measures (APA, 2014). These are rating scales that fall into three general categories. First, there are disorder-specific measures that correspond closely to the diagnostic criteria. These measures could be used to buttress the more clinical assessment that relies on the diagnostic criteria. They could also provide a means of assessing the client’s baseline and response to treatment over time. Measures are available for a range of disorders including depression, many of the anxiety disorders, PTSD, acute stress disorder and dissociative symptoms. Versions are available for adults as well as children aged 11–17. Most of these are self-completed but some are clinician-rated. A second type of measure is the WHODAS 2.0, discussed earlier, which assesses domains of disability in adults 18 and older. A third type of measure is referred to as cross-cutting symptom measures (CCSM). Similar to a broadband assessment of bodily systems in medicine, these measures assess common psychiatric symptoms that may present across diagnostic boundaries and may be clinically significant to note in the overall treatment plan. Level 1 CCSM is a brief survey of 13 domains of symptoms (e.g., depression, anxiety, psychosis, obsessions, mania). A more in-depth Level 2 assessment measure is available for a domain that indicates a significantly high rating. These measures can be reproduced and used freely by researchers and clinicians and can be downloaded at http://www.psychiatry.org/practice/dsm/dsm5/online-assessment-measures. Use of these types of measure is hoped to add surplus information that can aid diagnosis, case monitoring and treatment planning. 

Limitations

Dimensions are not only intuitively appealing, but also seem to be a better reflection of nature (Lilienfeld et al., 2013). Notwithstanding, serious concerns have been raised. First, determining the appropriate cut point on these dimensions is critical in terms of determining true psychopathology. If the bar is set too low, there is a danger of pathologizing normal behavior. If set too high, those who need treatment may be excluded and denied services. At this point, data suggest that at least for autism spectrum disorder and substance use disorder, the bar might be set too high. For both, DSM-5 criteria tend to miss people on the more benign end of the spectrum. For example, those who formerly might have been diagnosed with mild to moderate Asperger’s, pervasive developmental disorder NOS, or substance abuse may no longer qualify for a diagnosis (Beighley et al., 2013; Mayes, Black, & Tierney, 2013; Peer et al., 2013; Proctor, Kopak, & Hoffmann, 2013). On the other hand, Frances (2013) has suggested that the threshold for somatic symptoms disorder is set too low, pathologizing many with normal worry about their medical illnesses. 

A second concern is that lumping mild and more severe disorders into a unitary spectrum disorder can have unintended social effects, especially for people on the more benign end of the spectrum. For example, those who formerly were diagnosed with Asperger’s disorder will now be labeled with autism spectrum disorder. A college student who was diagnosed with alcohol abuse using DSM-IV-TR criteria will now carry the same diagnosis as someone who is considered an alcoholic and dependent (Frances, 2013). One unanswered question is the impact of these types of name changes on perceived stigma and consequent help seeking. 

A final concern is that the dimensional measures were released prematurely without adequate testing and without sufficient guidelines for their use (Jones, 2012; Paris, 2013). While some of the measures are well established (e.g., Patient Health Questionnaire [PHQ]-9; APA, 2014), others have little to no psychometric support (e.g., Clinician-Rated Severity of Autism Spectrum and Social Communication Disorders). Scoring guidelines are made available, but information about the measure’s psychometric properties and norming are lacking. There also is no information on who is qualified to use these measures and what type of training they should have. Thus, while dimensionality may be an important innovation in the development of the DSM classification system, there are significant challenges ahead in calibrating these dimensions, refining the measures and considering social consequences. 

Clinical Implications

Will dimensionality help or hinder the diagnostic process? On one level, the additional information about the condition may shift counselors’ fundamental way of thinking about treatment from “curing” clients (dichotomous) to helping them move toward more optimal points on the spectrum (dimensional). The availability of dimensional measures has the potential of improving diagnostic accuracy and providing a measure of treatment outcome (Segal & Coolidge, 2007). It may open the door to more measurement-based care, in which these ratings can be used to assess more precisely the need for care and the extent to which clients are profiting from treatment. This process may be more feasible to administer, score and record if these measures can be stored on tablets or mobile applications. 

In terms of using these dimensional measures, however, the unanswered question is—at what cost? Clinicians are already busy, and anything that encumbers that process even more will be resisted (Paris, 2013). Criteria sets are now a bit more complex to navigate because of the added severity rating and feature specifiers. It will take considerable time to learn and master the range of measures that have been posted online, much less research their psychometric appropriateness for the situations in which they will be used. The wild card is whether managed care will require these types of measures as a way of documenting need for treatment and response to provided services. At this point, clinicians would be best served to proceed cautiously, ensuring that the measures they use are reliable and valid for the client population intended.

The New Organization of DSM-5 

How was it decided in previous editions of the DSM which chapters to include and which disorders to place in each of them? While some research guided this process, tradition and clinical consensus were the primary sources that informed the organization of these earlier manuals (First & Tasman, 2004; Regier et al., 2013; Widiger, 2005). DSM-5 took a radically different approach, drawing upon research that examined how disorders actually cluster together. In this section, the new framework is examined and potential benefits and costs discussed. 

Innovation

The DSM-5 manual is divided into three major sections. Section I provides an introduction, a discussion of key concepts such as the definition of a mental disorder, and guidelines for recording a diagnosis. Section II is the meat of the manual and contains all the mental disorders and other conditions that can be coded with their diagnostic criteria and background information. Section III includes tools for enhancing the diagnostic process, such as some of the dimensional measures discussed earlier, the WHODAS 2.0, and a Cultural Formulation Interview designed to assess the impact of culture on the clinical presentation. This section also includes a list of proposed mental disorders that require further study (e.g., Internet gaming disorder) and an alternative system for diagnosing personality disorders. 

Table 1 lists DSM-5’s major categories (chapters) of mental disorders. Two general principles determined the sequence of chapters and the placement of disorders within chapters. First, disorders were grouped into similar clusters based upon shared underlying vulnerabilities, risk factors, symptoms presentation, course and response to treatment (APA, 2013). Groups that are positioned next to each other share more commonalities than those placed further apart. For example, bipolar disorder follows schizophrenia spectrum because they share a number of vulnerability factors (APA, 2013). Next to bipolar disorder is the chapter on depressive disorders. However, the sequence of chapters indicates that depressive disorders are more distantly related to schizophrenia spectrum. Next, internalizing disorders characterized by depression, anxiety and somatic symptoms are listed in adjacent chapters because of common risk factors, treatment response and comorbidity (APA, 2013). Externalizing disorders, noted by their impulsivity, acting out and substance use, are placed in the latter part of the manual.

Table 1

DSM-5 Classification

Sequence of Chapters in Section II

Neurodevelopmental DisordersSchizophrenia Spectrum and Other Psychotic DisordersBipolar and Related DisordersDepressive DisordersAnxiety Disorders

Obsessive-Compulsive and Related Disorders

Trauma- and Stressor-Related Disorders

Dissociative Disorders

Somatic Symptom and Related Disorders

Feeding and Eating Disorders

Elimination Disorders

Sleep-Wake Disorders

Sexual Dysfunctions

Gender Dysphoria

Disruptive, Impulse Control, and Conduct Disorders

Substance-Related and Addictive Disorders

Neurocognitive Disorders

Personality Disorders

Paraphilic Disorders

Other Mental Disorders

Medication-Induced Movement Disorders and Other Adverse Effects of Medication

Other Conditions That May Be a Focus of Clinical Attention

This shared commonality principle is also evident in the placement of disorders within chapters. As a result, a number of disorders have been transferred to different chapters. For example, DSM-IV-TR’s chapter on sexual and gender identity disorders contained sexual dysfunctions (e.g., premature ejaculation), paraphilias (e.g., exhibitionism) and gender identity disorder. Research showed that these three were not highly related, so they have been moved into different chapters, each of which is more proximally located to related disorders (APA, 2013). As another example, DSM-IV-TR’s anxiety disorders chapter has been divided into three separate chapters: anxiety disorders that are more fear-based (e.g. phobias); obsessive-compulsive and related disorders, which are characterized by preoccupations and repetitive behaviors (e.g., body dysmorphic disorder); and trauma- and stressor-related disorders. The latter is akin to a stress-response spectrum that ranges from severe reactions like PTSD to milder reactions characteristic of an adjustment disorder. It is hoped that these organizational changes will help clinicians locate disorders as well as identify related comorbidities (APA, 2013). 

A second organizational principle is that the DSM-5 framework reflects a life-span perspective, both across and within chapters. Neurodevelopmental disorders (e.g., autism spectrum disorder, attention-deficit/ hyperactivity disorder [ADHD]) are listed first because they typically emerge early in life. Schizophrenia spectrum disorders also frequently have antecedents that manifest themselves in childhood (APA, 2013). Next are disorders that usually appear in adolescence and early adulthood, such as bipolar disorders, depressive disorders and anxiety disorders. In the middle and back of the manual are disorders that emerge in adulthood or late adulthood, such as personality disorders and neurocognitive disorders (e.g., dementia related to Alzheimer’s disease). 

A developmental perspective also is infused into the organization of each chapter. DSM-IV-TR’s chapter on disorders of infancy, childhood and adolescence has been eliminated, and these disorders have been redistributed throughout the manual into relevant chapters. Each chapter is developmentally organized with disorders that emerge in childhood listed first, followed by those that appear in adolescence and adulthood. For example, oppositional defiant disorder and conduct disorder have been moved to the beginning of the chapter on disruptive, impulse control and conduct disorders. In addition, the criteria sets now include developmental manifestations of symptoms. For example, the ADHD criteria set includes both child and adult examples of the various symptoms. There also is an expanded section on development and course for each of the disorders, which explains how symptoms typically unfold over the life span. It is hoped that these types of changes will help clinicians recognize age-related manifestations of symptomatology (Kupfer et al., 2013; Pine et al., 2011). 

The intent of the DSM-5 initiative was to develop a more valid organizational structure grounded in research. In the end it also may help to uncover common etiological factors—the holy grail of classification efforts (Insel et al., 2010; Stein et al., 2013). Certainly, these changes will help with differential diagnosis. The organization provides a better map of the relationship between disorders and how the diagnostic landscape may change over the life span. 

Limitations

The new organization of the DSM-5 has been generally well received (Stein et al., 2013). One major concern that has been raised, however, is the decision to dismantle the chapter on child and adolescent disorders (Pine et al., 2011). Now there is not one place where the range of childhood disorders is listed. The neurodevelopment disorders—the remnant of the former child and adolescent chapter—is largely limited to disorders that manifest with early developmental delays and problems with language, learning, motor behavior, thinking or attention. Missing, however, are a broader range of behavior problems and anxiety disorders that the former chapter included. The problem is that many of these disorders can co-occur. For example, about 30–50% of children with conduct disorder have a specific learning disorder (Gintner, 2000). The wide separation of conditions such as these in the manual may interfere with accurate detection, especially among those who are not familiar with child and adolescent disorders. 

Clinical Implications

Mental health counselors have a new organization to master. Anecdotally, probably one of the most common comments I hear about the new manual is, “Where do I find X now?” Understanding the new organization of the manual will require more than simply looking over the new structure. It will be critical to read the manual to understand why disorders were grouped in a particular chapter. Chapters that are either newly introduced in the manual or that were significantly altered will certainly need to be carefully reviewed. These include the chapters on neurodevelopmental disorders, obsessive-compulsive and related disorders, trauma- and stressor-related disorders, substance-related and addictive disorders, and neurocognitive disorders.

Importantly, the new DSM-5 message is that the structure is designed to indicate relationships within chapters and between chapters. This is a different way of thinking diagnostically. For example, in considering possible diagnostic alternatives, the clinician can first ask this broad question: Is this on the internalizing or externalizing spectrum? If the condition seems more internalizing, then the possible chapters have been winnowed down, and progressively more specific questions can be asked to locate the disorder in the particular chapter. The organization also alerts the diagnostician that adjacent chapters may hold comorbid conditions or even unexplained subthreshold symptoms. To take advantage of this diagnostic aid, however, it will be critical for mental health counselors to learn their way around this new framework.

Conclusions 

These conceptual changes define the new look of DSM-5. ICD’s consilience, dimensionality and the organizational restructuring have fundamentally transformed DSM-5 into a 21st-century document that reflects the current state of knowledge in the mental health profession. The good news is that these changes may make the manual a better reflection of nature (i.e., research has shown it to be more valid) compared to previous editions. As a result, the way counselors diagnose and how they think about mental disorders is changing. Hopefully, such change will not only result in better care, but will also help researchers identify the deeper etiological substrates of mental disorders.

In science, progress also can have a dark side. While the DSM-5 incorporates the latest research, the entire development process and critical review highlight the primitive state of knowledge in the profession. While the spectrums and dimensions will no doubt transform the way mental health professionals diagnose, at this point they are crude and may help certain client populations, but hurt others. Harmonization with the ICD will probably take the DSM-5 to a broader audience of health providers. But it also further medicalizes the DSM-5 and will steer it perilously close to a biologically-based classification system. It will be up to mental health counselors and allied mental health professionals to help correct the course and find the middle way exemplified in the biopsychosocial model. Until then, DSM-5’s advances will be tempered by these potential limitations.

Conflict of Interest and Funding Disclosure

The author reported no conflict of interest or funding contributions for the development of this manuscript.

 

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Clinical Application of the DSM-5 in Private Counseling Practice

Jason H. King

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; APA, 2013) continues its 60-year legacy as a standard reference for clinical practice in the mental health field. Six mental health disorders are reviewed with a focus on changes between the DSM-IV-TR and the DSM-5 that represent the new landscape for each of these disorders, respectively. Following the summary of changes, a clinical scenario is presented so that counselors can capture the vision of using the DSM-5 in their counseling practice. Clinical formulation (sample diagnosis) using the DSM-5 is also presented for each disorder classification.

Keywords: DSM-5, DSM-IV-TR, private practice, clinical formulation, mental disorders 

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; APA, 2013) continues its 60-year legacy as a standard reference for clinical practice in the mental health field. This practical, functional and flexible guide is intended for use by trained counselors in a wide diversity of contexts and facilitates a common language to communicate the necessary characteristics of mental disorders present in their clients (APA, 2013). As counselors use the DSM-5, they will notice an expanded discussion of developmental and life span considerations, cultural issues, gender differences, integration of scientific findings from the latest research in genetics and neuroimaging, and enhanced use of course, descriptive and severity specifiers for diagnostic precision (APA, 2013). They will also notice a dimensional approach to diagnosis, consolidation and restructuring of most mental disorders; a new definition of a mental disorder; and emerging assessments and monitoring tools so as to promote enhanced clinical case formulation.

The intent of this article is to assist all counseling specialists by presenting six clinical scenarios from the author’s counseling practice. The article begins by summarizing the clinical utility of the DSM-5 and provides recommendations for counselors on how to sequence their study of the new manual. Discussed next are use of the new emerging assessment measures, autism spectrum disorder, schizophrenia spectrum and other psychotic disorders, sleep-wake disorders, neurocognitive disorders, and comorbid conditions such as excoriation (skin-picking) disorder and post-traumatic stress disorder—with a focus on prominent changes between the DSM-IV-TR and the DSM-5. Clinical formulation and its associated rationale using the DSM-5 are presented for each disorder classification.

Counselors are encouraged to read the full manual and to especially read the Preface; Section I (i.e., Introduction, Use of the Manual, and Cautionary Statement for Forensic Use of DSM-5); Section III: Emerging Measures and Models (i.e., Assessment Measures); and Appendix (i.e., Highlights of Changes From DSM-IV to DSM-5) before they attempt applied clinical use of the manual. To appreciate the rationale for the DSM-5 changes, counselors are encouraged to read the DSM-IV-TR discussion on limitations to the categorical approach (APA, 2000, pp. xxxi–xxxii) and on the nonaxial format (p. 37). This sequencing of study will help counselors use the manual as intended and avoid diagnostic errors, as well as maintain cultural sensitivity and avoid historical and social prejudices in the diagnosis of pathology (ACA, 2014).

Cross-Cutting Symptom Measures and Disorder-Specific Severity Measures

Clinicians are to administer emerging assessment measures at the initial interview and to monitor treatment progress, thus serving to promote the use of initial symptomatic status and reported outcome information (APA, 2013). The DSM-5 cross-cutting symptom measures support comprehensive assessment by drawing attention to clinical symptoms that manifest across diagnoses. Cross-cutting symptom measures have two levels. Level 1 measures offer a brief screening of 13 domains for adults (i.e., depression, anger, mania, anxiety, somatic symptoms, suicidal ideation, psychosis, sleep problems, memory, repetitive thoughts and behaviors, dissociation, personality functioning, and substance use) and 12 domains for children and adolescents (i.e., depression, anger, irritability, mania, anxiety, somatic symptoms, inattention, suicidal ideation/attempt, psychosis, sleep disturbance, repetitive thoughts and behaviors, and substance use). Level 2 measures provide a more in-depth assessment of elevated Level 1 domains to facilitate differential diagnosis and determine severity of symptom manifestation. The DSM-5 disorder-specific severity measures correspond closely to the criteria that constitute the disorder definition and are intended to illuminate additional areas of inquiry that may guide treatment and prognosis (APA, 2013; Jones, 2012). Counselors can access these no-cost assessment measures at http://psychiatry.org/practice/dsm/dsm5/online-assessment-measures. The DSM-5 provides counselors with further information on the background and reasoning for use of these emerging measures in clinical practice (see pp. 733–748).

Autism Spectrum Disorder 

The New Landscape

From as early as 1993, authors and researchers have referred to the various pervasive developmental disorders as autism spectrum disorder (Rutter & Schopler, 1992; Shuster, 2012; Tanguay, Robertson, & Derrick, 1998). They have also called for use of a dimensional rather than a categorical classification as used in DSM-IV and DSM-IV-TR (Kamp-Becker et al., 2010). Unlike the dichotomous approach of the DSM-IV-TR categorical model, the dimensional approach uses three or more rating scales to measure severity, intensity, frequency, duration or other characteristics of given diagnoses (Jones, 2012). Consensus in the research community for a spectrum classification is clearly demonstrated in that 95% of publications in the past 5 years have used the term “autism spectrum disorder.” Hence, the DSM-5 uses the term spectrum and further informs counselors that “autism spectrum disorder encompasses disorders previously referred to as early infantile autism, childhood autism, Kanner’s autism, high-functioning autism, atypical autism, pervasive developmental disorder not otherwise specified, childhood disintegrative disorder, and Asperger’s disorder” (APA, 2013, p. 53). Consolidating use of these dichotomous autism-based titles into a spectrum designation helps to avoid diagnostic confusion and to minimize fragmented treatment planning.

Based on factor structure models, the DSM-5 presents a major reconceptualization and reorganization of the DSM-IV-TR autistic disorder symptomatology (Guthrie, Swineford, Wetherby, & Lord, 2013). This new spectrum, or dimensional classification, helps counselors to properly assess deficits in social-emotional reciprocity (i.e., the inability to engage with others and share thoughts and feelings); nonverbal communicative behaviors used for social interaction (i.e., absent, reduced or atypical use of eye contact [relative to cultural norms], gestures, facial expressions, body orientation or speech intonation); ability to develop, maintain and understand relationships (i.e., absent, reduced or atypical social interest, manifested by rejection of others, passivity or inappropriate approaches that seem aggressive or disruptive); and marked presentations of restricted, repetitive patterns of behavior, interests or activities. This reconceptualization of autism in the DSM-5 provides counselors with a denser diagnostic cluster to reduce excessive application of the DSM-IV-TR pervasive developmental disorder not otherwise specified classification that resulted in overdiagnosis and concerning prevalence rates (Maenner et al., 2014). 

The DSM-5 further recognizes autism due to Rett syndrome, Fragile X syndrome, Down syndrome, epilepsy, valproate, fetal alcohol syndrome or very low birth weight through use of the specifier associated with a known medical or genetic condition or environmental factor. Counselors also may use the specifiers with or without accompanying intellectual impairment and with or without accompanying language impairment. Examples of descriptive specifier usage include with accompanying language impairment—no intelligible speech or with accompanying language impairment—phrase speech. If catatonia is present, counselors record that separately as catatonia associated with autism spectrum disorder. Severity, or intensity of symptoms, for autism spectrum disorder are now communicated on three levels: Level 1 mild requiring support, level 2 moderate requiring substantial support, and level 3 severe requiring very substantial support (APA, 2013). 

The level of interference in functioning and support required is communicated by using the DSM-5 Clinician-Rated Severity of Autism Spectrum and Social Communication Disorders scale (APA, 2013, p. 52). Examples of mild rating in the social communication psychopathological domain may include the following: without supports in place, deficits in social communication cause noticeable impairments; has difficulty initiating social interactions and demonstrates clear examples of atypical or unsuccessful responses to social overtures of others; and may appear to have decreased interest in social interactions. Examples of mild rating in the restricted interests and repetitive behaviors psychopathological domain may include rituals and repetitive behaviors (RRBs) that cause significant interference with functioning in one or more contexts, or resists attempts by others to interrupt RRBs or to be redirected from fixated interest (APA, 2013).

Examples of moderate rating in the social communication psychopathological domain may include marked deficits in verbal and nonverbal social communication skills, social impairments apparent even with supports in place, limited initiation of social interactions, and reduced or abnormal response to social overtures from others. Examples of moderate rating in the restricted interests and repetitive behaviors psychopathological domain may include RRBs and/or preoccupations and/or fixated interests that appear frequently enough to be obvious to the casual observer and inhibit functioning in a variety of contexts. Frustration or distress is apparent when RRBs are interrupted; it is difficult to redirect attention from fixated interest (APA, 2013).

Examples of severe rating in the social communication psychopathological domain may include severe deficits in verbal and nonverbal social communication skills that cause significant impairments in functioning, very limited initiation of social interactions, and minimal response to social advances from others. Examples of severe rating in the restricted interests and repetitive behaviors psychopathological domain may include preoccupations, fixed rituals and/or repetitive behaviors that significantly interfere with functioning in all domains; distinct distress when rituals or routines are interrupted; difficulty redirecting from fixated interest or returns to it quickly. Counselors are advised to review Table 2 Severity Levels for Autism Spectrum Disorder displayed in the DSM-5 (APA, 2013, p. 52).

Clinical Scenario

Walter, a 22-year-old male, was referred to counseling by the State Office of Rehabilitation for career and vocational assistance, with a special focus on his mental health needs and confirming the presence of his previous diagnosis of Asperger’s disorder given in 2004. Counselors working with adults presenting with autism spectrum symptoms will appreciate the DSM-5’s new adult textual narrative. Some of these additions help to understand adults like Walter, who:

  • Must show persistent symptoms from early childhood across multiple contexts.
  • Display difficulties processing and responding to complex social cues;
  • Suffer from anxiety because of purposefully calculating what is socially intuitive for other adults;
  • Express difficulty in coordinating nonverbal communication with speech;
  • Struggle to comprehend what behavior is considered appropriate in one situation but not another; and
  • Learn to suppress repetitive behavior in public.

Following assessment procedures outlined in the DSM-5 to use “standardized behavioral diagnostic instruments with good psychometric properties, including caregiver interview, questionnaires and clinician observation measures” (APA, 2013, p. 55) and by Jones (2010), clinical assessment of Walter included the following:

  • Biopsychosocial clinical interview of Walter with his mother as an additional informant
  • Level 1 Cross-Cutting Symptom Measure (see APA, 2013, pp. 733–744 or www.psychiatry.org/dsm5)
  • The Clinician-Rated Severity of Autism Spectrum and Social Communication Disorders (see APA, 2013, p. 52 or www.psychiatry.org/dsm5)
  • Historical evaluations (prior psychological testing results)
  • Collateral reports from the referring vocational rehabilitation counselor
  • Simon Baron-Cohen’s Autism Spectrum Quotient (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001; Ketelaars et al., 2008)

Adhering to DSM-5 dimensional rather than DSM-IV-TR multiaxial classification (Jones 2012), Walter was diagnosed using this format:

299.00 Autism spectrum disorder; requiring substantial support for social communication and social interaction (level 2 moderate); requiring support for restricted repetitive behaviors, interests and activities (level 1 mild); without accompanying intellectual impairment; without accompanying language impairment; without catatonia.

Notice the diagnostic precision offered by the DSM-5 in comparison with Walter’s non-descriptive diagnosis using the DSM-IV-TR formulation: Asperger’s Disorder (APA, 2000). In contrast, the severity ratings for autism spectrum disorder are listed independently for social communication and restricted repetitive behaviors, rather than providing a global rating for both psychopathological domains (per the DSM-5 they are listed from most severe to least severe). For Walter, his moderate severity rating of requiring substantial support for social communication means: “Marked deficits in verbal and nonverbal social communication skills; social impairments apparent even with supports in place; limited initiation of social interactions; and reduced or abnormal responses to social overtures from others” (APA, 2013, p. 52). His mild severity rating of requiring support for restricted repetitive behaviors (RRBs) means: “Inflexibility of behavior causes significant interference with functioning in one or more contexts. Difficulty switching between activities. Problems of organization and planning hamper independence” (APA, 2013, p. 52). The diagnostic formulation offered to counselors in the DSM-5 provides a richer contextual description of the client to support more personalized treatment planning. This attention to dimensional ratings and individualized treatment strategies is also captured in the newly conceptualized schizophrenia spectrum disorders.

Schizophrenia Spectrum and Other Psychotic Disorders 

The New Landscape

Counseling clients presenting with psychotic and schizophrenia spectrum disorders is challenging and diagnostically complex. To assist with these difficulties, the DSM-5 presents a new conceptualization to facilitate clinical utility and to streamline diagnostic formulations (Bruijnzeel & Tandon, 2011). Similar to autism, schizophrenia has been referenced as a spectrum disorder since 1995 (Kendler, Neale, & Walsh, 1995) and the DSM-5 marks the official recognition of this spectrum conceptualization by embedding the word in the diagnostic title. Essential to competent practice in this area is reading the section on key features that define the psychotic disorders on pages 87–88 of the DSM-5 (APA, 2013; e.g., delusions, hallucinations, disorganized thinking, grossly disorganized or abnormal motor behavior, and negative symptoms). Further critical reading is the new Clinician-Rated Assessment of Symptoms and Related Clinical Phenomena in Psychosis on the DSM-5 pages 89–90 (APA, 2013). These pages describe the heterogeneity of psychotic disorders and the dimensional framework for the assessment of primary symptom severity within the psychotic disorders. This spectrum conceptualization differs from the DSM-IV-TR categorical and mutually exclusive diagnostic system that assumed “mental disorders are discrete entities, with relatively homogeneous populations that display similar symptoms and attributes of a disorder” (Jones, 2012, p. 481). 

The new Clinician-Rated Dimensions of Psychosis Symptom Severity (CRDPSS) is used to understand the personal experience of the client, to promote individualized treatment planning, and to facilitate prognostic decision making (Flanagan et al., 2012; Heckers et al. 2013). Counselors can obtain the CRDPSS in the DSM-5 pages 742–744 (APA, 2013) or www.psychiatry.org/dsm5. The CRDPSS is an eight-item measure used to assess the severity of mental health symptoms that are important across psychotic disorders. These symptoms include delusions, hallucinations, disorganized speech, abnormal psychomotor behavior, negative symptoms (i.e., restricted emotional expression or avolition), impaired cognition, depression and mania. Psychosis symptoms are rated on a five-point scale: not present, equivocal (severity or duration not sufficient to be considered psychosis), mild (little pressure to act, not very bothered by symptoms), moderate (some pressure to respond or somewhat bothered by symptoms) and severe (severe pressure to respond to voices or very bothered by voices). 

According to the DSM-5, proper use of the CRDPSS may include clinical neuropsychological assessment (especially of client cognitive functioning) to help guide diagnosis and treatment. Counselor “assessment of [client] cognition, depression, and mania symptom domains is vital for making critically important distinctions between the various schizophrenia spectrum and other psychotic disorders” (APA, 2013, p. 98). Depending on the stability of client symptoms and treatment status, the CRDPSS may be completed at regular intervals as clinically indicated to track changes in client symptom severity over time. Consistently high scores on a specific domain may indicate significant and problematic areas for the client that may warrant further assessment (mental status examination), treatment (counseling and pharmacological), and follow-up (case management). 

In the DSM-5, delusional disorder is retained as listed in DSM-IV-TR, including its classic subtypes of erotomanic, grandiose, jealous, persecutory and somatic. Some textual updates occur in the DSM-5 for brief psychotic disorder that place emphasis on disorganized or catatonic behavior. Schizophreniform disorder in the DSM-5 parallels the description in the DSM-IV-TR. Diagnostic precision for schizophrenia in the DSM-5 is communicated with new course specifiers that can “be used after a 1-year duration of the disorder and if they are not in contradiction to the diagnostic course criteria” (APA, 2013, p. 99). These new course specifiers communicate a time period in which the symptom criteria are fulfilled (acute), a period of time during which improvement after a previous episode is maintained and in which the defining criteria of the disorder are only somewhat fulfilled (partial remission), or a period of time after a prior episode during which no disorder-specific symptoms are present (full remission). Counselors also can communicate these specifiers based on first episode, multiple episodes, continuous episodes or unspecified. Use of these specifiers assists counselors in determining the intensity, frequency and duration of clinical intervention services that are more person-centered.

To align with a dimensional, or spectrum paradigm, the categorical DSM-IV-TR schizophrenia subtypes (i.e., paranoid type, disorganized type, catatonic type, undifferentiated type and residual type) are not used in the DSM-5 because they are included in the previously described CRDPSS. Research also does not support the use of the subtypes and does not indicate any qualitative differences between the subtypes that impact treatment planning or symptom presentation (Tandon et. al., 2013). Catatonia, a syndrome of disturbed motor, mood and systemic signs, becomes a specifier in the DSM-5, applicable for neurodevelopmental, depressive, bipolar and all psychotic disorders (APA, 2013). Unlike the DSM-IV-TR, the DSM-5 does not contain the following exception clause to diagnose schizophrenia: “Only one Criterion A symptom is required if delusions are bizarre or hallucinations consist of a voice keeping up a running commentary on the persons’ behavior or thoughts, or two or more voices conversing with each other” (APA, 2000, p. 312). Removal of this language restricts classification to avoid excessive classification in nonclinical profiles, thus promoting ethical practice (ACA, 2014).

Although the DSM-5 acknowledges that “there is growing evidence that schizoaffective disorder is not a distinct nosological category” (APA, 2013, pp. 89–90; see also Malaspina et al., 2013), this disorder is retained, with some textual refinements to more stringently define the clinical syndrome. These changes include the following: criterion B: “lifetime duration of the illness” (APA, 2013, p. 105); and criterion C: major mood episode must be “present for the majority of the total duration for the active and residual portion of the illness” (APA, 2013, p. 105) instead of the DSM-IV-TR’s focus on substantial portion for the active and residual portion of the illness.

Clinical Scenario

Ryan, a 22-year-old Caucasian male, presented with an extensive history of auditory hallucinations and erotomanic and paranoid delusions. In the spirit of the DSM-5, he was administered the CRDPSS six times, beginning with the onset of counseling and then at various counseling sessions during his treatment. Use of the CRDPSS promotes clinical utility. For example, Ryan is able to identity trends and patterns related to life stressors and symptom elevations and reductions. This level of clinical assessment provides a framework for targeted treatment planning and clinical intervention. Ryan also feels empowered over his mental illness and obtains a more positive perspective regarding his self-efficacy with coping skills to manage his psychotic symptoms. Most importantly, the CRDPSS encourages measurement-based care in the burgeoning era of practice-based evidence requirements (Tandon et al., 2013). Adhering to the DSM-5 dimensional classification, I diagnosed Ryan using this format:

295.70 Schizoaffective disorder, bipolar type, severe hallucinations, moderate delusions (erotomanic and persecutory), moderate abnormal psychomotor behavior, moderate negative symptoms, equivocal disorganized speech, continuous episode, currently in partial remission, without catatonia.

Compare the DSM-5 clinical formulation to the DSM-IV-TR diagnostic formulation:

295.70 Schizoaffective disorder, bipolar type.

The DSM-5 diagnostic conceptualization offers a contextualized framework in “developing a comprehensive treatment plan that is informed by the individual’s cultural and social context” (APA, 2013, p. 19) by rating primary symptoms of psychosis in order of severity so as to promote prognostic decision-making. This level of diagnostic specificity also is found in the DSM-5 sleep-wake disorders.

Sleep-Wake Disorders 

The New Landscape

Sleep-wake disorders in the DSM-5 represent a radical revamping of diagnostic syndromes, clinical conceptualization and specifier annotations. This is because the “DSM-IV was prepared for use by mental health and general medical clinicians who are not experts in sleep medicine” (APA, 2013, p. 362). Grounded in the current International Classification of Sleep Disorders, 2nd edition (ICSD-2), the DSM-5 sleep-wake disorders work group used this classification system as a benchmark for diagnostic revision. When counselors read each sleep-wake disorder in the DSM-5, they will discover that a note about relationship to the ICSD is presented. Because of the new sleep-wake disorder conceptualization and the dimensional (instead of categorical) formulation of mental disorders in the DSM-5, counselors are to use the emerging measures for sleep-wake disorders for children and adults located at www.psychiatry.org/dsm5. 

As counselors read the sleep-wake disorders chapter in the DSM-5, they will notice an increased emphasis on a multidimensional approach to assessment that includes medical examination, such as the use of polysomnography, quantitative electroencephalographic analysis and testing for hypocretin (orexin) deficiency (APA, 2013). They will also notice a greater emphasis on the dynamic relationship between sleep-wake disorders and certain mental or medical conditions, and that pediatric and developmental criteria and the general text are integrated based on existing neurobiological and genetic evidence and biological validators (Kaplan, 2013). The DSM-5 sleep-wake disorders textual descriptors use the terminology “coexisting with” or “comorbidity” instead of the DSM-IV-TR “related to” or “due to.” Sleep-wake disorders in the DSM-5 further provide diagnostic precision by offering use of course specifiers (i.e., episodic, persistent, recurrent, acute, subacute), descriptive specifiers (i.e., with mental disorder, with medical condition, with another sleep disorder), and severity specifiers (i.e., mild, moderate, severe). 

The insomnia-based sleep-wake disorders focus on problems with initiating or maintaining quality sleep. Some of these disorders preclude assessment by a counselor, as they require examination by a sleep medicine expert. The DSM-IV-TR primary insomnia and insomnia related to another mental disorder are merged in the DSM-5 to become insomnia disorder. The DSM-IV-TR primary hypersomnia and hypersomnia related to another mental disorder are merged to become the DSM-5 hypersomnolence disorder. Narcolepsy is retained in the DSM-5 with substantial symptom description changes, five new specifiers and requirements for sleep medicine examination to confirm a diagnosis. Narcolepsy now requires either the presence of cataplexy (sudden loss of muscle tone), hypocretin deficiency as measured using cerebrospinal fluid, or REM sleep latency deficiency as measured using polysomnography (APA, 2013). Breathing-related sleep disorders in the DSM-5 include obstructive sleep apnea hypopnea, central sleep apnea (new for the manual) and sleep-related hypoventilation (new for the manual). Circadian rhythm sleep-wake disorders in the DSM-5 no longer recognize jet lag, resulting in five types (i.e., delayed sleep phase, advanced sleep phase, irregular sleep-wake, non-24-hour sleep-wake and shift work) for counselors to select when diagnosing this syndrome. Parasomnias, defined as abnormal behavior or physiological events during sleep, also are reconceptualized in the DSM-5. The DSM-IV-TR sleepwalking disorder and sleep terror disorder are merged to become the DSM-5 non–rapid eye movement sleep arousal disorder, with sleepwalking type, sleep-related eating, sleep-related sexual behavior, and sleep terror type specifiers (APA, 2013). Nightmare disorder is retained with no substantial changes from the DSM-IV-TR. The DSM-IV-TR parasomnia not otherwise specified is renamed in the DSM-5 to rapid eye movement sleep behavior disorder for disruptive dream enacting behaviors, and DSM-IV-TR dyssomnia not otherwise specified is renamed in the DSM-5 to restless legs syndrome.

Clinical Scenario

Jasmine, a 36-year-old Caucasian female, is married and has four children. She reported a history of major depression (with two to three episodes of intense suicidal ideation) and generalized anxiety disorder. Results from the World Health Organization’s Adult ADHD Self-Report Scales (Kessler et al., 2004) indicated possible attention-deficit/hyperactivity disorder combined presentation. Results from the psychometric Conners’ Continuous Performance Test II confirmed the presence of a mild to moderate ADHD combined presentation profile. Despite pharmacological (both prescription and over the counter) and psychological (sleep hygiene and behavioral-focused) interventions, Jasmine continued to report daytime sleepiness, fatigue and unrefreshing sleep throughout the week, lasting for many months. This produced functional impairment with employment obligations and interpersonal relationships.

In the spirit of the DSM-5 and in collaboration with her general practitioner, Jasmine was referred to a local sleep medicine clinic to receive formal sleep-wake disorder testing (polysomnography). This was done to confirm the presence of an independent sleep-wake disorder not better accounted for by her depression and anxiety disorders. The resulting sleep-wake study report included the following excerpts:

This is 36-year-old female patient with a past medical history that is remarkable for gastric reflux, allergies and asthma. Patient is overweight with a BMI (body mass index) of 26.31. There is a longstanding history of: frequent awakenings, use of sleeping pills, frequent difficulty waking up, nonrestorative sleep, excessive daytime sleepiness, nasal congestion, frequent loud snoring, palpitations, night sweats and waking up with muscle paralysis. Patient complains of excessive daytime sleepiness with an Epworth Sleepiness score that is abnormal at 14 out of 24. Total sleep time is adequate at 8 hours per night. Patient denies smoking and drinking alcohol. Current medications include: Pantoprazole, Simvastatin, Amitriptyline, Loratadine and Fluticasone. As such, an overnight sleep study was ordered for evaluation of an underlying sleep-related breathing disorder.

Interpretation:

  • Obstructive apneas (suspension of external breathing) of 17.1/hour associated with oxygen desaturation to as low as 72%. This is consistent with the diagnosis of moderate Obstructive Sleep Apnea.
  • Sleep-related hypoventilation/hypoxemia due to sleep apnea is present.
  • Severe initial insomnia.

Recommendations:

  • Continuous positive airway pressure (CPAP) therapy should be offered to this patient given the risk of stroke and the significant daytime sleepiness. As such, a second overnight sleep study for CPAP titration is strongly recommended. If daytime sleepiness persists despite adequate CPAP therapy, then further evaluation for hypersomnolence should be considered.

Recall that hypersomnolence, excessive sleepiness, is a new disorder for the DSM-5. Addition of this diagnosis conforms to the sleep medicine expert’s recommendation for potential comorbid existence.

Adhering to the DSM-5 dimensional rather than the DSM-IV-TR multiaxial classification (Jones, 2012), Jasmine received the following diagnostic formulation:

  • 327.23 Moderate obstructive sleep apnea hypopnea (see APA, 2013, pp. 378–383);
  • V61.10 Relationship distress with spouse (see APA, 2013, p. 716);
  • 296.32 Moderate major depressive disorder, recurrent (the Level 2 — Depression—Adult [PROMIS Emotional Distress—Depression—Short Form] and the Severity Measure for Depression—Adult [Patient Health Questionnaire–9] were administered to determine severity rating (see also Jones, 2012; APA, 2014);
  • 327.24 Mild idiopathic sleep-related hypoventilation (see APA, 2013, pp. 387–390);
  • 314.01 Mild attention-deficit/hyperactivity disorder, combined presentation, in partial remission (see APA, 2013, pp. 60–61 for discussion on new severity and remission specifier options); and
  • 300.02 Mild generalized anxiety disorder (the Severity Measure for Generalized Anxiety Disorder—Adult [APA, 2014] was administered to determine severity rating).

Counselors are reminded that depression, anxiety and cognitive changes often accompany sleep-wake disorders and must be addressed in treatment planning and management (APA, 2013). To assist with targeted treatment interventions for sleep-wake disorders, counselors are encouraged to use Milner and Belicki’s (2010) sleep hygiene recommendations.

Neurocognitive Disorders 

The DSM-IV-TR chapter “Dementia, Delirium, Amnestic, and Other Cognitive Disorders” is renamed to “Neurocognitive Disorders” (NCDs) in the DSM-5. Cognitive impairments occur in most mental disorders, including schizophrenia, bipolar disorder, depression, attention-deficit/hyperactivity disorder and autism (APA, 2013). However, the DSM-5 NCDs work group focused on those disorders for which the cognitive deficit is the primary one and is attributable to known physical or metabolic brain disease­­—hence the designation neurocognitive (Campbell, 2013).

To delineate between normative aging declines and lifelong patterns, the DSM-5 requires neuropsychological testing as part of the clinical evaluation process (except for delirium). Compared to the DSM-IV-TR, the NCDs in the DSM-5 represent a significant reorganization and reconceptualization (Ganguli, 2011) reflected in two new diagnostic categories: major and mild NCDs (Geda & Nedelska, 2012). Major NCD is characterized by significant cognitive decline, interference with activities of daily living, and symptom manifestation two or more standard deviations from the mean on neurocognitive domains (see Table 1, APA, 2013, pp. 593–595). Specifiers for the major NCD designation include mild (difficulties with instrumental activities of daily living, such as housework or managing money), moderate (difficulties with basic activities of daily living, such as feeding and dressing), and severe (fully dependent).

In contrast to major NCD, mild NCD is characterized in the DSM-5 as modest cognitive decline, intact activities of daily living, and symptom manifestation one standard deviation from the mean on neurocognitive domains. Mild NCD is a former diagnostic consideration from the DSM-IV-TR (2000) Appendix B: Criteria Sets and Axes Provided for Further Study (p. 764). Mild NCD is considered an up-streaming diagnostic conceptualization to assist with early diagnostic detection because the neuropathology underlying mild NCD emerges well before the onset of clinical symptoms (APA, 2013).

The DSM-5 offers two new NCD designations: probable and possible. Probable is added to the diagnostic title if there is evidence of a causative disease genetic mutation from either genetic testing, evidence of family history, evidence from laboratory blood testing, or evidence from neuroimaging. Possible is used if there is no evidence resulting from the previously mentioned probable objective factors (APA, 2013). Counselors also may use the retained DSM-IV-TR descriptive specifier, without or with behavioral disturbance to indicate the presence of psychotic symptoms, mood disturbance, agitation, apathy or other behavioral symptoms.

The DSM-5 contains 10 etiological specifiers (formally referred to as subtypes in the DSM-IV-TR). The DSM-5 changed the title of the DSM-IV-TR Pick’s disease to frontotemporal lobar degeneration and changed the DSM-IV-TR’s Creutzfeldt–Jakob disease to Prion disease so as to more objectively communicate the active pathophysiological mechanisms responsible for the neuronal degeneration and resulting cognitive disturbances (APA, 2013). The DSM-5 added Lewy body disease and multiple etiologies as etiological specifiers and merged the DSM-IV-TR dementia due to head trauma and postconcussional disorder (found in Appendix B: Criteria Sets and Axes Provided for Further Study) to become traumatic brain injury (TBI). Counselors will appreciate the table listed on page 626 (APA, 2013) that presents severity ratings for TBI, and will find that Jones, Young, and Leppma’s (2010) article complements the DSM-5 conceptualization of TBI and offers additional assessment and diagnostic assistance.

Clinical Scenario

Jaxson, a male client in his mid-40s who suffered three TBIs, each resulting from independent automobile accidents, presented for counseling. He presented with post-concussion syndromes reflected in physical symptoms (headaches, dizziness, fatigue, noise/light intolerance, insomnia, nausea, physical weakness), cognitive symptoms (memory complaints, poor concentration), and emotional symptoms (depression, anxiety, irritability, increased aggression, mood lability). Textual additions to the DSM-5 further explained the causal relationship between TBIs and major depressive episodes, facilitating a more accurate clinical formulation. The most salient DSM-5 (APA, 2013) diagnostic guidelines included the following:

  • With moderate and severe TBI, in addition to persistence of neurocognitive deficits, there may be associated neurophysiological, emotional, and behavioral complications. These may include . . . depression, sleep disturbance, fatigue, apathy, inability to resume occupational and social functioning at pre-injury level, and deterioration in interpersonal relationships.
  • Moderate and severe TBI have been associated with increased risk of depression. (p. 626)
  • Individuals with TBI histories report more depressive symptoms, and these can amplify cognitive complaints and worsen functional outcome. (p. 627)
  • There are clear associations, as well as some neuroanatomical correlates, of depression with . . . traumatic brain injury. (p. 181)

Using the DSM-5’s Severity Ratings for TBI, three previously administered clinical neuropsychological tests and the DSM-5’s Table 1 Neurocognitive Domains, Jaxson received the following dimensional diagnostic formulation per the DSM-5 (APA, 2013):

  • 293.83 Moderate-severe depressive disorder due to TBI, with major depressive-like episode (p. 181; coding rules require that a mental disorder due to another medical condition be listed first; pp. 22–23);
  • Moderate-mild disability (87 per self-administered World Health Organization Disability Assessment Schedule [WHODAS] 2.0; pp. 745–748);
  • 331.83 Probable mild neurocognitive disorder (NCD) due to TBI (pp. 624–627);
  • V62.29 Other problem related to employment (recent change of job, underemployment and psychosocial stressors related to work due to TBI; p. 723); and
  • V61.29 Relationship distress with spouse (due to TBI; p. 716).

This approach to clinical case formulation also is demonstrated in the assessment and diagnosis of post-traumatic stress disorder and excoriation (skin-picking) disorder.

Comorbid Diagnostic Formulation 

Comorbidity refers to the presence of multiple diagnoses or pathologies within the same individual (Jones, 2012). This final section presents a discussion on the DSM-5’s new obsessive-compulsive and related disorder, excoriation (skin-picking) disorder and the revised conceptualization of post-traumatic stress disorder.

Excoriation (Skin-Picking) Disorder

Excoriation, also referred to as dermatillomania (Grant et al., 2012), is characterized by the repetitive and compulsive picking of skin, leading to tissue damage, and is a new diagnosis to the DSM-5. This addition reflects the growing prevalence of this psychiatric condition (Grant et. al., 2012). Excoriation is characterized by compulsive picking, rubbing, squeezing, lancing or biting of the skin. Not included in this disorder are individual behaviors that involve nail biting, lip biting or cheek biting. If individuals manifest these conditions they are coded as other specified obsessive-compulsive related disorder (APA, 2013, p. 263). Cutting, or nonsuicidal self-injury, is not a codable mental disorder in the DSM-5 (see APA, 2013, pp. 803–806) and is not conceptualized in the symptomology of excoriation. Counselors are encouraged to consider cutting behavior in their clients as manifestations of symptoms related to depressive disorders, bipolar disorders, anxiety disorders, trauma disorders—and most particularly dissociative identity disorder and borderline personality disorder, in which self-injurious behavior is frequent. Individuals engaged in excoriation may target their face, arms, hand, skin irregularities, pimples, calluses or scabs. They may use objects such as tweezers, pins, scissors and fingernails and be triggered by anxiety, boredom, distress or tension (Grant et al., 2012). Some individuals with excoriation display rituals (e.g., biting off, chewing and swallowing skin), permanent skin damage, scarring, lesions, infection or disfigurement. Individuals with excoriation spend several hours per day for months and years picking at their skin, thinking about picking, and resisting urges to pick. Because the skin-picking is so frequent, pain is not routinely reported. Marked functional impairment from excoriation may include work interference, missed school, difficulty managing school tasks and studying, and avoidance of social or entertainment events. Excoriation cannot be due to physiological effects of a substance (e.g., methamphetamine or cocaine), to another medical condition (e.g., scabies), or better explained by symptoms of another disorder (APA, 2013).

Post-Traumatic Stress Disorder

Some important modifications to post-traumatic stress disorder occur in the DSM-5. First, the DSM-IV-TR language has shifted from “threat to the physical integrity of self or others” (APA, 2000, p. 467) to “sexual violence” (APA, 2013, p. 271). Second, the DSM-5 removed the DSM-IV-TR criterion A2 “subjective fear-based distress” because not all traumatized individuals experience fear, terror or horror when exposed to a trauma stressor. Some traumatized individuals may become anhedonic, dysphoric, aggressive or phobic; experience arousal and reactive-externalizing behaviors; or experience dissociation. Third, a new trauma exposure source is added to the traditional DSM-IV-TR trauma sources (i.e., directly experiencing, witnessing, and learning that a traumatic event occurred to a close family member or friend): “experiencing repeated or extreme exposure to aversive details of the traumatic event(s)” (APA, 2013, p. 271). An important note regarding this new exposure source in the DSM-5 indicates that “criterion A4 does not apply to exposure through electronic media, television, movies, or pictures, unless exposure is work related” (APA, 2013, p. 271). Examples of work-related electronic media exposure may include an individual who edits graphic news video or pictures, an individual who performs frequent digital-based forensic science investigations of graphic crime scenes, or an individual who views military-oriented electronic images displaying graphic human remains captured from unmanned aerial vehicles. Fourth, the DSM-5 requires that an individual manifest at least one symptom from each of the following pathological clusters:

  • Intrusion symptoms;
  • Persistent avoidance of stimuli;
  • Negative alterations in cognitions and mood (new to the DSM-5); and
  • Marked alterations in arousal and reactivity.

Fifth, the DSM-IV-TR specifier “delayed onset” is renamed to “delayed expression” in the DSM-5 so as to communicate whether the full diagnostic criteria are not met until at least 6 months after the trauma-causing event (APA, 2013, p. 272). Sixth, “with dissociative symptoms” (Dalenberg & Carlson, 2012) is a new descriptive specifier that can include either depersonalization (e.g., feeling as though one were in a dream; feeling a sense of unreality of self or body or of time moving slowly) or derealization (e.g., the world around the individual is experienced as unreal, dreamlike, distant or distorted; APA, 2013). Seventh, separate diagnostic criterion exist for children ages 6 years and younger. Counselors are encouraged to read van den Heuvel and Seedat (2013) for a detailed review of screening measures and diagnostic instruments for post-traumatic stress disorder in preschool populations.

Clinical Scenario

Mary, a female in her mid-50s, presented with an extensive history of sexual trauma resulting in post-traumatic stress disorder and excoriation. To verify the presence and severity of her trauma and excoriation, Mary was administered the DSM-5 Level 1 cross-cutting symptom measure. Elevated responses (i.e., feeling nervous, anxious, frightened, worried, or on edge and feeling driven to perform certain behaviors or mental acts over and over again) triggered administration of the DSM-5 Level 2 cross-cutting symptom measures (i.e., the Repetitive Thoughts and Behaviors Scale, the National Stressful Events Survey PTSD Short Scale, and the Modified Brief Dissociative Experiences Scale). Adhering to the DSM-5 dimensional classification, Mary’s diagnostic formulation was conceptualized in the following format: 

  • 309.81 Moderate post-traumatic stress disorder, with mild depersonalization
  • 698.4 Excoriation (skin-picking) disorder.

This diagnostic formulation contains a layered intensity description as both the disorder and the descriptive specifier have a severity rating; hence promoting clinical utility by informing Mary’s treatment plan and assisting with prognostic and outcome factors (APA, 2013). For example, this level of diagnostic precision targeted Mary’s cognitive, affective and behavioral post-traumatic and depersonalization symptoms individually, rather than globally.

Conclusion 

The DSM-5 represents 12 years of culminating work among hundreds of medical and mental health professionals. The manual was revised in a manner so as to stimulate new clinical perspectives, to promote a new generation of research into the biological markers of mental health disorders and to facilitate more reliable diagnoses of the disorders (APA, 2013). This article presented clinical scenarios from actual clients the author worked with in an outpatient counseling private practice. The intent is that counselors feel more comfortable and confident in their use of the DSM-5 to develop a counseling professional identity that stimulates client growth and development (Erikson & Kress, 2006; King, 2012).

 

Conflict of Interest and Funding Disclosure

The author reported no conflict of interest or funding contributions for the development of this manuscript.

 

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Jason H. King is Student Development Coordinator in the School of Counseling at Walden University. Correspondence can be addressed to Jason H. King, 100 Washington Avenue South, Suite 900, Minneapolis, MN 55401-2511, jason.king6@waldenu.edu.