Dec 2, 2014 | Article, Volume 4 - Issue 5
Qi Shi, Xi Liu, Wade Leuwerke
This study sought to examine students’ perceptions of their school counselors in two high schools in Beijing, China. Independent t tests found that female students rated school counselors’ availability significantly higher than male students did. Also, students who had received prior counseling services rated counselors significantly higher in the following areas than did students who had never received counseling services: knowledge of achievement tests, friendliness and approachability, understanding students’ point of view, advocating for students, promptness in responding to requests, ability to explain things clearly, reliability to keep promises, availability, and overall effectiveness. A 2 × 2 between-subjects ANOVA found an interaction effect between gender and use or nonuse of counseling services. In general, students gave positive evaluations of school counselors and were satisfied with counseling services.
Keywords: school counselors; counseling services; students’ perceptions; high schools; Beijing, China
China has been experiencing dramatic economic and social changes in the past 3 decades (Guthrie, 2012). During this time there has been increased attention to both mental health problems and student development (Cyranoski, 2010; Lim, Lim, Michael, Cai, & Schock, 2010; Xin & Zhang, 2009). It has been estimated that at least 17.5% of the Chinese population has some form of mental illness, one of the highest rates in the world (Phillips et al., 2009), accounting for about 20% of hospitalizations in the country (Fei, 2006). Facing significant mental health challenges, several authors have noted the need for more counseling professionals and mental health service providers (Cook, Lei, & Chiang, 2010; Davey & Zhao, 2012). In rural areas with fewer resources, the demand for mental health care is even greater (Ji, 2000).
Given such great needs for mental health services, China has been making tremendous efforts in reforming its mental health service system (Tse, Ran, Huang, & Zhu, 2013). In 2004, China launched the 686 Project, a mental health reform initiative modeled on the World Health Organization’s recommended framework for integrating hospital-based services with a community mental health service system (Ma, 2012). By the end of 2011, 1.83 million Chinese people with severe mental illness had been treated as a result of the project.
While China has witnessed growth in the counseling profession, at the same time it has struggled to build national certification and licensing standards, and create comprehensive counselor training (Chang & Kleinman, 2002; Cook et al., 2010; Davey & Zhao, 2012; Ding, Kuo, & Van Dyke, 2008; Hou & Zhang, 2007). In 2002, China’s National Counseling Licensing Board was formed, and there is currently a three-tier national licensing program. More than 30 locations throughout China offer the qualification exams for counselors, and recently a national exam to license school counselors was instituted (Lim et al., 2010). Results from a nationwide survey of professional training of mental health practitioners in China showed that quality of training and supervision were among common concerns (Gao et al., 2010). Also, more accredited professional training programs at the university or college level must be designed and established. Beijing Normal University, in collaboration with Rowan University in the United States, was reported to be the first university in China to offer a school counseling training program (Lim et al., 2010).
Mental Health of Students in China
Increased attention to student well-being has shown high prevalence of mental health problems among Chinese students (Cook et al., 2010; Wang & Miao, 2001). Common psychological problems among students included test anxiety, academic pressure, loneliness, social discomfort, video game addiction (Thomason & Qiong, 2008), Internet addiction, child obesity, self-centeredness and reclusion (Worrell, 2008). A study from a metropolitan area in southeastern China showed that 10.8% of high school students had mental health concerns including hostility, compulsions, depression and interpersonal relationship sensitivity (Hu, 1994). A more recent survey conducted by Wu et al. (2012) among 1,891 high school students in a southern city in China showed that 25% of the adolescents reported a perceived need for mental health services, while only 5% of the sample had used school-based mental health services, and 4% had used non-school-based services.
Researchers are starting to identify factors that contribute to Chinese students’ mental health problems, including the pressure to achieve academic success (Corbin Dwyer & McNaughton, 2004; Thomason & Qiong, 2008; Worrell, 2008), being an only child (Liu, Munakata, & Onuoha, 2005; Thomason & Qiong, 2008; Worrell, 2008), prevalence of physical abuse (Wong, Chen, Goggins, Tang, & Leung, 2009), inability to cope with multiple expectations and requirements (Tang, 2006), increased attention to personal and social development (Corbin Dwyer & McNaughton, 2004), and the generation gap between children and their parents (Thomason & Qiong, 2008). Zheng, Zhang, Li, and Zhang (1997) suggested that parents and teachers who did not attend to students’ psychological problems contributed to the high rates of mental health problems among students. Because they have the most direct interaction with students, homeroom teachers and subject teachers in China are well-positioned to help students address their mental health concerns. In fact, Chinese homeroom teachers perform a wide variety of counseling tasks (Shi & Leuwerke, 2010). However, teachers do not receive sufficient training in providing counseling services.
School Counseling in China
School counselors are uniquely positioned to impact the mental health and academic success of students in China. As would be expected with developing professions, there are numerous challenges to school counseling in China: (a) a tremendous shortage of qualified school counselors (Cook et al., 2010; Shi & Leuwerke, 2010; Thomason & Qiong, 2008; Yan, 2003; Zheng et al., 1997), (b) an urgent need for more accredited training programs (Gao et al., 2010; Leuwerke & Shi, 2010; Lim et al., 2010) and (c) a lack of support and respect from teachers and other school staff (Jiang, 2005; Leuwerke & Shi, 2010). Although many schools in China, especially in urban areas, have begun to establish counseling offices and hire school counselors, this profession is still in its primitive developmental stage (Leuwerke & Shi, 2010). Moreover, school counselors themselves have expressed great need for more training and standard education to better serve their students (Leuwerke & Shi, 2010). A standardized training system is imperative to provide training, assessment, issuance of licenses and continued education (Cook et al., 2010; Davey & Zhao, 2012; Yan, 2003; Zheng et al., 1997).
Facing the serious situation of Chinese students’ mental health concerns and school counseling challenges, the Chinese government has turned greater attention to advanced mental health education in K–12 schools. Government policies on education reform have put more emphasis on students’ mental health and the availability of psychological services (Ding et al., 2008). The Ministry of Education in China has published two important government guidelines in the past 2 decades. “Several Suggestions on Improving Mental Health Education in Elementary & Secondary Schools” (Zhong guo jiao yu bu, 1999) identified moral and politics teachers, homeroom teachers, Communist Youth League cadres, and school counselors as the personnel in schools responsible for the mental health needs of students. K–12 schools with available resources and funding were required to establish counseling offices, and school counselors were identified as the leaders of this system (Ministry of Education of the People’s Republic of China, 1999). In 2012, the Ministry of Education released the updated version of “Guideline of Mental Health Education in Elementary & Secondary Schools.” This guideline described the goals, content and methods of mental health education as well as the personnel responsible for delivery. The report specifically called for educating students about basic knowledge and skills regarding interpersonal relationships, career development, and living and socialization (Zhong guo jiao yu bu, 2012).
As required by the Chinese government, schools in large cities have begun to hire school counselors to provide counseling for their students (Jiang, 2005). In K–12 schools in China, school counseling is called school guidance or mental health education, which is actually a part of political and moral education (Jiang, 2005). School guidance in K–12 school settings has been taught as a subject course like math or science (Hou & Zhang, 2007). In addition to school counselors, homeroom teachers also play an important role in mental health services for students by performing a large range of counseling tasks (Shi & Leuwerke, 2010; Wang, 1997). Chinese students access psychological services in schools through a variety of channels: individual counseling, group activities, lectures on common psychological concerns, parent and teacher consultation, and classroom guidance (Leuwerke & Shi, 2010).
The expansion of services in the Chinese school system has made counseling more accessible than ever to students (Thomason & Qiong, 2008). However, empirically based literature examining the role, function and scope of school counseling in China is virtually nonexistent (Jiang, 2005; Leuwerke & Shi, 2010; Shi & Leuwerke, 2010; Thomason & Qiong, 2008). Very little is known about the amount of counseling that students actually receive at school, let alone how students perceive school counselors and the school counseling services they receive (Leuwerke & Shi, 2010). The present study sought to examine some of these questions. Through surveys of students at two high schools in Beijing, the authors explored students’ use of counseling in school as well as their perceptions of the school counselors. The authors also examined possible differences among students who sought services or not, as well as any differences across gender. Correspondingly, the research questions in this study were as follows: (a) How many students seek counseling services and how often do they meet their school counselors in these two high schools in Beijing? (b) Do students’ perceptions of the school counselors differ across gender? (c) Do students’ perceptions of the school counselors differ depending on whether or not they seek counseling services? (d) Do male and female students’ perceptions differ depending on whether or not they seek counseling services?
Methods
Participants
A total of 137 (47 male, 90 female) students from two high schools in Beijing completed questionnaires; 293 surveys were distributed, resulting in a return rate of 46.76%. The sample was recruited through the first author’s contacts in Beijing. Among the students who completed the survey, 126 were from a high school affiliated with Beijing Normal University and 11 were from a high school affiliated with Beijing Renmin University. The sample consisted of 12.4% (n = 17) senior 1 students (equivalent to 10thgraders in the United States), 78.8% (n = 108) senior 2 students (equivalent to 11th graders in the United States) and 8.8% (n = 12) senior 3 students (equivalent to 12th graders in the United States). The two high schools recruited for the study are among the top ranked high schools in Beijing. The school counselors being evaluated in these two high schools had an average of 8 years of experience working as professional school counselors. Students from these schools typically perform very well in academics and gain admission to universities after high school. As for plans after high school, 97.8% (n = 134) of the students surveyed stated that the plan was a 4-year college, with only three students indicating “other plans.” No student indicated planning to attend a 2-year college or vocational training school or get a job right after graduating from high school.
Instrument
Participants completed a brief demographic questionnaire as well as the Chinese High School Students’ Perceptions of School Counselors Survey. All information students provided in the survey was anonymous. The demographic questionnaire included items such as students’ grade level, gender and postsecondary plans. The Chinese High School Students’ Perceptions of School Counselors Survey used in this study was adapted from McCullough’s (1973) survey that was originally designed to determine high school students’ perceptions of school counselors’ services in the United States. Some changes were made to adapt to Chinese students’ cultural background, including adding two questions about the number of times that students had tried to see the school counselor and the actual number of times that they had met with the school counselor. After indicating the number of times they had tried and actually met with a school counselor, participants rated their counselor’s ability and effectiveness on a four-point Likert scale (4 = excellent, 3 = good, 2 = fair, 1 = poor) in the following 11 areas: knowledge of college admission, knowledge of vocational information, knowledge of achievement tests, friendliness and approachability, understanding students’ point of view, advocate for students, promptness in responding to requests, ability to explain things clearly, reliability to keep promises, availability to students, and overall effectiveness.
Translation
The authors created all materials utilized in this study in English, and the first author then translated the documents into Mandarin Chinese. To examine translation quality, a bilingual, native Chinese speaker who was not part of the research team subsequently translated all documents back into English. The authors evaluated and considered these translated documents equivalent. This approach is consistent with common practice in research requiring translation of documents (Larkin, de Casterlé, & Schotsmans, 2007; Liu et al., 2005).
Design
Data analyses were conducted based on the four research questions in this study. First, descriptive statistical analysis was conducted to learn the number of students who had sought counseling services and the frequency of their meetings with a counselor. Second, an independent t test was conducted to determine the differences between male and female students’ perceptions of their school counselors’ services. Third, another independent t test was performed to examine the differences between students’ perceptions of their school counselors’ services depending on whether or not the students had sought prior counseling services. Finally, a 2 × 2 between-subjects ANOVA was done to determine whether there was a statistically significant interaction effect between gender and whether or not students sought prior counseling services.
The data from students who had never had individual meetings with counselors were included in these analyses. These data were included because these students had had contact with school counselors in other circumstances (e.g., lectures, classroom guidance, school-wide gathering), even though they had not met with school counselors individually (Leuwerke & Shi, 2010).
Procedure
Five teachers at the two high schools assisted with data collection. Since research participation and the protocol were new to most of the teachers, explanation of the confidential and voluntary nature of the project was provided through teleconference. Questions from the teachers were answered via e-mail. One of the teachers in Beijing was in charge of the informed consent forms and data storage. Parents of the students in the classrooms of all five teachers received one copy of the informed consent and all granted consent for their child to participate in the research. Students then received e-mails. An online survey tool (http://www.surveymonkey.com) was used to administer the questionnaire.
Results
The first goal of this study was to examine how many students had sought services from school counselors and the number of meetings they had had with their school counselors since they entered high school. Descriptive statistics were obtained in order to achieve this goal. Nearly half of the participants (48.9%, n = 67) reported having seen counselors at least once. Among these 67 students, the majority (n = 41) had met once individually with a school counselor, 22 had seen a school counselor individually two to three times, and four students had talked with school counselors four to five times. No student reported having met with a school counselor more than five times. Information on the length of these individual counseling sessions was not obtained in the survey.
The second goal of this study was to examine the students’ perceptions of their school counselors. Fifty-three students provided a complete evaluation of their school counselors in the survey. Among these 53 students, 36 had used counseling services before, whereas 17 reported no individual meetings with a counselor. As shown in Table 1, students’ most positive ratings of their school counselors were for friendliness and approachability (M = 3.20, SD = 1.25) and ability to explain things clearly (M = 2.99, SD = 1.33). The lowest rated attributes were knowledge of college admission (M = 1.30, SD = 1.42) and knowledge of vocational information (M = 1.10, SD = 1.30).
Table 1
Descriptive Statistics on Students’ Evaluations of School Counseling Services
School counseling services evaluated
|
N
|
Min
|
Max
|
M
|
SD
|
Friendliness and approachability |
137
|
0
|
4
|
3.20
|
1.25
|
Ability to explain things clearly |
137
|
0
|
4
|
2.99
|
1.33
|
Availability to students |
137
|
0
|
4
|
2.77
|
1.38
|
Understanding students’ points of view |
138
|
0
|
4
|
2.73
|
1.32
|
Promptness in responding to requests |
137
|
0
|
4
|
2.68
|
1.47
|
Reliability to keep promises |
137
|
0
|
4
|
2.37
|
1.62
|
Advocate for students |
137
|
0
|
4
|
2.31
|
1.51
|
Knowledge of achievement tests |
137
|
0
|
4
|
1.82
|
1.44
|
Knowledge of college admission |
141
|
0
|
4
|
1.30
|
1.42
|
Knowledge of vocational information |
138
|
0
|
4
|
1.10
|
1.30
|
Overall effectiveness |
137
|
0
|
4
|
2.51
|
1.40
|
Valid N (listwise) |
137
|
|
|
|
|
Furthermore, independent t tests were conducted to determine whether students’ ratings of counseling services differed significantly between genders and between students who had or had not sought counseling services. A statistically significant result was found in students’ ratings of school counselors’ availability in the independent t test based on gender. Female students rated school counselors’ availability significantly higher than male students did (F = 4.196, p < .05). Statistically significant results also were found based on whether or not the students had sought counseling services. As shown in Table 2, students who had received prior counseling services rated counselors significantly higher in the following areas than did students who had never received counseling services: knowledge of achievement tests, friendliness and approachability, understanding students’ point of view, advocate for students, promptness in responding to requests, ability to explain things clearly, reliability to keep promises, availability, and overall effectiveness.
Table 2
Students’ Evaluations of School Counselors Depending on Whether or Not They Seek Services
School counseling services evaluated
|
Levene’s testa
|
|
t testb
|
F
|
p
|
|
t
|
df
|
p
|
M
difference
|
SE
difference
|
|
|
|
|
|
|
|
|
|
Knowledge of college admission |
.59
|
.443
|
|
1.84
|
139
|
.068
|
.46
|
.25
|
Knowledge of vocational information |
.55
|
.460
|
|
2.22
|
135
|
.028
|
.51
|
.23
|
Knowledge of achievement tests |
7.61
|
.007
|
|
1.53
|
134
|
.128
|
.40
|
.26
|
Friendliness and approachability |
7.34
|
.008
|
|
2.10
|
135
|
.038
|
.47
|
.22
|
Understanding students’ points of view |
8.26
|
.005
|
|
2.46
|
136
|
.015
|
.57
|
.23
|
Advocate for students’ |
2.89
|
.092
|
|
2.50
|
135
|
.014
|
.67
|
.27
|
Promptness in responding to requests |
18.23
|
.000
|
|
2.12
|
135
|
.036
|
.55
|
.26
|
Ability to explain things clearly |
17.92
|
.000
|
|
2.24
|
135
|
.027
|
.53
|
.24
|
Reliability to keep promises |
9.28
|
.003
|
|
2.44
|
135
|
.016
|
.70
|
.29
|
Availability to students |
9.59
|
.002
|
|
2.24
|
135
|
.027
|
.55
|
.25
|
Overall effectiveness |
39.95
|
.000
|
|
3.03
|
135
|
.003
|
.74
|
.25
|
aLevene’s test for equality of variances. bt test for equality of means.
A 2 × 2 between-subjects ANOVA was conducted to evaluate the effects that gender and students’ experiences with counseling services had on students’ perceptions of counseling services. Levene’s test and Fmax indicated that the homogeneity of variances assumption was met. A statistically significant interaction effect was found between gender and whether or not the students had received counseling services, F(1, 133) = 5.923, p = .016. As shown in Figure 1, the relationship between whether or not students had received counseling services and their perceptions of school counselors differed depending on gender. Among students who had had individual meetings with their counselors, males rated the counselors higher than females did, while females rated the counselors higher than males did if they had never received counseling services.

Figure 1. Mean differences on gender and whether or not students received counseling services.
Discussion
In this study, almost half of the participants reported seeking help from a school counselor at least once. Interestingly, over 60% of the students who had met with a counselor had not returned for a subsequent meeting. Although China has seen the presence of school counselors increase in urban schools, it is still not common for students to seek counseling services (Thomason & Qiong, 2008). While the specific reasons why the students discontinued meeting with school counselors in this study are not clear, the following factors might help explain this phenomenon: (a) students have been found to be most concerned with physical health and to have failed to consider other aspects of health such as mental/psychological, behavioral and social (Wang, Zou, Gifford, & Dalal, 2014); (b) stigma toward mental illness exists among Chinese students (Thomason & Qiong, 2008; Wang, Huang, Jackson, Chen, & Laks, 2012); (3) Chinese cultural beliefs promote solving family-related issues inside one’s own family (Cook et al., 2010); and (4) students spend the majority of their time preparing for the National College Entrance Exam (NCEE), which Chinese school counselors perceived as an impediment to students’ utilization of school counseling services and future school counseling development in China (Leuwerke & Shi, 2010).
As for the modal number of counseling sessions that school counselors hold in secondary schools in China and the United States, little is presented in the current literature. More research has been conducted on college students’ attendance of counseling sessions offered by university counseling centers. For example, Draper, Jennings, Baron, Erdur, and Shankar (2002) found that, on average, college students met with counselors only three times. A number of studies have confirmed that most college students attend only a few sessions and that 50% terminate counseling prematurely (Ledsky et al., 2000; Renk, Dinger, & Bjugstad, 2000; Whipple et al., 2003). The number of counseling sessions that school counselors have with high school students could be likewise related. Students who visit school counselors by referral normally do not return for a second session, even though more sessions are indicated (E. Zhang, personal communication, June 5, 2007).
In China’s current school system, homeroom teachers have close, day-to-day interaction with students in their own homerooms; these teachers are responsible for students’ behavior, academic performance, mental health and all-around development (Lim et al., 2010; Shi & Leuwerke, 2010). Homeroom teachers may refer students to school counselors if they feel that students’ problems are beyond the teachers’ ability to solve (E. Zhang, personal communication, June 5, 2007). Future research could help explain why students tend to meet with their counselor only one time, and could explore the factors associated with students’ premature termination. It might be that Chinese counselors are giving an intentional or unintentional message that only one session is appropriate. Additional research is necessary to explore how school counselors could reach out to more students and reduce the stigma attached to mental problems, which might encourage more students to utilize individual counseling in school settings.
The descriptive results of this study provide some preliminary information about the level of students’ satisfaction with particular areas. Based on the students’ perceptions in two high schools in Beijing, it appears that school counselors are doing quite well in many different areas, such as friendliness and approachability to students, ability to explain things clearly, and availability. However, there are some areas in which school counselors must improve their knowledge and skills (e.g., college admission, vocational information and opportunities, achievement tests). When interpreting the results of this study, it is important to keep in mind that participants in this study are all from top-ranking high schools in Beijing, where students have a general college-going mindset and therefore place significant emphasis on academic achievement; in addition, these students have a higher expectation and interest in seeking counseling services related to applying for college. Also, in the current school systems in China, homeroom teachers are normally in charge of handling students’ academic testing, disseminating college-related information and helping students prepare for college (Shi & Leuwerke, 2010). Therefore, school counselors might not be as prepared as homeroom teachers to provide information regarding college admission and achievement tests.
As for the low ratings in the area of vocational information and opportunities, it is critical to consider the fact that the practice and profession of career counseling is still in the developmental stage in China (Leuwerke & Shi, 2010; Zhang, Hu, & Pope, 2002). Unfortunately, a thorough literature search revealed no information on the current conditions of school counselors’ training in China. However, a few studies have briefly mentioned the training or education that school counselors receive. For example, Gao et al. (2010) conducted a national survey on professional training experience among mental health practitioners in China, with only half of their sample working in educational settings such as high schools and universities. The researchers found that mental health practitioners reported receiving only short-term training and continuing education that focused on theories; a majority reported receiving no supervision or case consultation (Gao et al., 2010). Although there is a lack of literature on school counselors’ training in particular, several authors have indicated an urgent need for a more regulated, comprehensive and standardized training and qualification system for school counselors in China (Cook et al., 2010; Leuwerke & Shi, 2010; Lim et al., 2010; Thomason & Qiong, 2008).
It was expected that students who had had individual meetings with school counselors would rate counseling services differently than the students who had never seen school counselors individually. Students who had received counseling services before rated school counselors at a significantly higher level than students who had never had counseling services in many different areas, including the school counselors’ test skills, approachability, understanding, advocacy, promptness, ability, reliability, availability and overall effectiveness in providing counseling services. This finding is not surprising, considering that students who have had personal contact with the school counselors might have a better understanding of the role of school counselors and the services they provide, and therefore are more likely to give a higher rating of school counseling services. In a study conducted in Turkey, Yüksel-Şahin (2008) also found that the factor of whether students had met with school counselors was a significant predictor of students’ evaluations of counseling guidance service.
Similarly, gender differences were expected in students’ rating of school counselors. The results show significantly higher ratings from female students than male students of school counselors’ availability. From the descriptive results of this study, one can see that female students reported more contact with school counselors than male students did; this finding might help explain female students’ higher rating of school counselors’ availability.
Finally, an interaction effect was found in students’ ratings of the effectiveness of their counselors in the 2 × 2 between-subjects ANOVA based on gender and whether or not students seek counseling services. In a 2009 study, Hou, Zhou, and Ma examined high school and university students’ expectations of counseling in China. Results of their study showed that female students had significantly higher scores than males in terms of their own openness and counselors’ acceptance. Meanwhile, the researchers also found that students who did not have counseling experience had significantly lower scores on their motivation compared to their counterparts. These trends continued in the current study, which further supports the idea that students’ previous counseling experiences and gender relate closely to their expectations and perceptions of counselors and counseling services in general.
As a developing profession facing a huge student population, school counselors in China are doing a more than adequate job with limited resources. In the current study, most high school students reported seeking counseling services from their school counselors more than once, and they reported having generally positive experiences in counseling. Meanwhile, these students also had positive perceptions of their school counselors’ services; however, they reported the need for more vocational guidance or more knowledge of achievement tests from their counselors. An interaction effect was found in students’ perceptions of school counseling services based on students’ gender and whether they had met with school counselors before.
Implications
This study contributes to the literature by filling a research gap in Chinese students’ utilization and perceptions of school counseling. This line of inquiry is very important for the future development of the school counseling profession in China in that it provides implications for researchers and school counseling practitioners, as well as counselor educators. Future researchers could further investigate factors that might predict students’ utilization of school counseling services and what students need the most from counseling. More efforts need to be made in both conducting empirical research in the school counseling field and in exploring ways to improve the profession that will suit China’s cultural and social situations (Jiang, 2005; Thomason & Qiong, 2008). Moreover, the findings from this research are informative for school counseling practitioners in China. Chinese school counselors may want to self-evaluate their services and seek further training and education to improve their services in the areas that students rated lower. School counselors also could explore ways to make their services more accessible for students. Finally, the results of this research can be beneficial for counselor educators, who could contribute to improving the quality of school counselors’ training and education by providing opportunities for supervision, practice and professional development courses targeting the knowledge and skills that school counselors need most.
Limitations
There were a number of limitations in this study that limit generalization and call for additional research. First, the sample in this study was a convenience sample; the majority of the participants were from one high school, also limiting the generalizability of the results. Second, the two high schools are similar to each other in that they are top-ranking high schools in Beijing, and their students have similar future plans. Therefore, the results of this study may not apply to other geographic areas in China, especially rural areas, because a difference exists in educational conditions between economically developed areas (e.g., Beijing, Shanghai, Guangzhou) and underdeveloped areas (e.g., rural areas in West China). Students from different geographical areas in China may encounter different mental health problems, and the development of school counseling in urban and rural China may be different (Yan, 2003). The position of school counselor may not even exist in some areas in China. Third, the sample lacks diversity in terms of gender and grade level. Most of the participants in this study were female students and senior 2 students. Gender may be a variable that influences how students perceive counseling and school counselors. Future research utilizing more diverse and larger samples from across the country will be able to provide a more detailed and general picture of school counseling in high schools across China. Lastly, the instrument used in this study was adapted from an instrument that was developed several decades ago. Although some modifications were made, the validity and reliability of the scale used for Chinese students are not clear at this time. Future studies may investigate the validity and reliability of this instrument and also develop new instruments that are specially designed to measure students’ perceptions of Chinese school counselors’ effectiveness, competence, expertise and contributions.
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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Qi Shi is an assistant professor at Loyola University Maryland. Xi Liu is a doctoral student at George Washington University. Wade Leuwerke is an associate professor at Drake University. Correspondence can be addressed to Qi Shi, 2034 Greenspring Drive, Timonium, Maryland 21093, qshi@loyola.edu.
Dec 2, 2014 | Article, Volume 4 - Issue 5
Isaac Burt
This pilot study explored differences between the levels of anger expression and anger control by adolescent males and females. Eighteen participants (9 males and 9 females) completed a strength-based anger management group promoting wellness. Anger management group counseling consisted of a 10-week continuous intervention emphasizing anger reduction, anger control and appropriate anger expression. Results indicated gender differences in that females exhibited more anger expression, as well as less anger control. However, females had higher levels of overall improvement. The article concludes with limitations and implications for mental health counseling with adolescent populations.
Keywords: mental health counseling, group counseling, anger management, adolescent, gender differences
The profession of mental health counseling serves a diverse population with a variety of needs, including substance abuse and anger management issues (Gutierrez & Hagedorn, 2013). In order to provide services to clients, mental health counselors use a number of modalities, such as individual and group counseling. Research indicates that group counseling in particular can be useful with certain populations, such as excessively angry clients (Burt, Patel, Butler, & Gonzalez, 2013; Fleckenstein & Horne, 2004). Traditionally, anger management groups have focused on dealing with anger after it occurs. Recent developments in the field of counseling, however, suggest that a number of new trends are developing with mental health and anger management groups (Burt & Butler, 2011).
One of these trends focuses on early prevention with mental health counselors either providing facilitation or training others to facilitate anger management groups in schools (Curtis, Van Horne, Robertson, & Karvonen, 2010). The targeted clients of most of the early prevention interventions are middle and high school populations (Parker & Bickmore, 2012). Burt and Butler (2011) contended, however, that many early prevention and anger management groups are gender biased and focus excessively on adolescent males. The researchers suggested that while adolescent females experience anger as well, they often do not receive counseling services (Burt & Butler, 2011). As a result, a growing population with similar needs is potentially neglected. While numerous differences do exist between genders, anger is a common emotion experienced by both (Karreman & Bekker, 2012).
Research indicates that differences exist between adolescent males and females with regard to behavioral decision-making processes and expression of emotions (Brandts & Garofalo, 2012). Although research depicts females as more emotionally expressive, males have a reputation of being more predisposed to anger. According to Sadeh, Javdani, Finy, and Verona (2011), females experience anger, but may express it differently than males. For example, instead of expressing anger by striking objects, adolescent females may talk to friends or peers (Fischer & Evers, 2011). Conversely, other studies purport that females express anger similarly to males, but experience difficulty recognizing and admitting the emotion due to social expectations and constraints (Karreman & Bekker, 2012). Males, on the other hand, tend to display anger more commonly and comfortably (Fischer & Evers, 2011). One of the many reasons that adolescent males may feel comfortable expressing anger is because it is socially acceptable (Burt et al., 2013).
An extensive number of studies have investigated anger; however, there appears to be a lack of studies exploring anger differences between genders. Karreman and Bekker (2012) conducted a study on gender differences, investigating autonomy-connectedness between genders. Their study indicated differences related to anger and sensitivity between genders. However, the study did not attempt to determine whether males and females were equal in anger at the beginning or end of the study. Similarly, Burt, Patel, and Lewis (2012) reported that incorporating social and relational competencies into anger management groups reduced anger, but there was no discussion of anger differences between genders. Sadeh et al. (2011) indicated that women expressed more self-anger (i.e., anger directed internally toward themselves) than males, but did not investigate whether differences existed between genders before the study.
Although limited, a small number of studies have attempted to examine anger differences between genders. Similar to Sadeh et al. (2011), Fischer & Evers (2011) found that females expressed subjective anger, or self-anger, more often than males. Buntaine and Costenbader (1997) found that both genders’ self-reports (assessments) indicated no significant differences. Upon further examination of their data, however, they concluded that although self-reports specified no differences, males verbally reported higher responses of anger. In contrast, Zimprich and Mascherek (2012) determined that no anger differences existed between males and females. They declared that although genders may express anger and respond to situations differently, they generally experience similar levels of anger. As can be seen from the preceding studies, inconsistences exist in the literature. Contradicting studies indicate that researchers are unclear as to whether differences in anger exist between genders. As such, a research gap has emerged that needs to be filled (Zimprich & Mascherek, 2012). In order to understand how this research gap developed, it is necessary to examine cultural influences.
Cultural Influences and Misconceptions in Society
According to Carney, Buttell, and Dutton (2007), a misconception exists in Western society that women are less aggressive than men and do not express excessive anger. This fallacy persisted in Western culture until a report from the U.S. National Family Violence Survey of 1975 (as cited in Carney et al., 2007) found a disturbing trend: Females were just as angry as males and expressed excessive anger the same amount that men did. At the time, feminist theory and the feminist movement were developing and stood in stark contrast to these findings. Carney et al. (2007) stated that as such, the National Family Violence Survey findings were largely unreported, and in extreme situations, people reinterpreted or repudiated the survey’s findings. In either case, more misconceptions began to develop in Western culture (Carney et al., 2007), such as the idea that when females experience anger, it is always appropriate to the situation (i.e., anger is permissible). A second mistaken belief is that anger from females is less serious and not as negative. For example, the expression “you look so cute when you’re angry” portrays this biased and potentially chauvinistic thought. A third misconception is that females are more credible in reporting their emotions and, as such, females are more reliable when they state that they are not angry.
Western society has acted upon these cultural misconceptions. For example, certain myths in society (and mental health counseling) persist, declaring the following: (a) only males have angry feelings, (b) all male-comprised counseling groups are anger management groups, (c) males have a limited repertoire of emotions to express, (d) males are too angry and competitive to support one another in groups, and (e) males are not interested in meeting with other males (Andronico & Horne, 2004). Myths about female groups are that they are high functioning, conflicts are resolved faster, and a fair amount of reflection and processing exists (Gladding, 2012). According to researchers, these misconceptions can bias the truth regarding people’s beliefs. For example, Winstok (2011) stated that rates of excessive anger and intimate partner physical abuse among females equal or surpass those of males.
Clearly, cultural misconceptions of gender differences in excessive anger can lead mental health counselors to do a disservice to males and females alike. For example, culture can influence mental health and group counseling by causing a type to develop. This type is defined as best suited to be in anger management groups. As a result, mental health counselors may unconsciously choose more males than females to be members of anger management groups. Thus, a population that desperately needs services can go without an intervention (Carney et al., 2007). Mental health counselors need to reevaluate their thinking in order to avoid overlooking a population needing services due to implicit social misconceptions.
Bandura (2008a) believed that excessive anger was not sudden, but gradually manifested over time. His studies with youth corroborated this idea, as he observed modeling and negative behavioral patterns leads to excessive anger (Bandura, Ross, & Ross, 1963). Supporting Bandura’s work, Burt and Butler (2011) asserted that excessive anger begins in childhood and adolescence. They reinforced the notion that mental health counselors must be aware that both genders have common needs and issues. For females, not receiving services or having services denied, and being told that the emotion they feel is inappropriate, could cause personal damage (Gottfredson, 2002). For instance, society and mental health counselors often depict males as more in need of anger management (Burt & Butler, 2011). Conversely, mental health counselors sometimes neglect and ignore what females need (West-Olatunji et al., 2010). Stated succinctly, a gap exists between what clients need and the options mental health counseling interventions offer to both genders. It is the author’s contention that this gap is an unfair practice, as both genders have similar needs. Research has shown that males and females experience anger equally; as a result, both need anger management groups.
To determine whether both genders expressed anger similarly, the author implemented a pilot study with adolescents to explore the topic before proceeding with a full investigation. As Bandura (2008b) pointed out, anger begins early in life and timely prevention is critical. Provision of early services for children and adolescents can help to prevent issues later in life.
Method
Participants
Participants in this study were male and female middle school students in the sixth, seventh and eighth grades. Thirty potential participants (15 males and 15 females) received invitations for participation, and 20 returned signed parental informed consent forms (10 males and 10 females). Ages of participants ranged from 11–14 years and consisted of 75% Latino/Hispanic (15), 15% Black (3), and 10% White (2). Two participants did not complete the study.
Instrumentation
This pilot study used the State-Trait Anger Expression Inventory-2 Child and Adolescent (STAXI-2 C/A). A well-known and highly used instrument, the STAXI-2 C/A is a self-report assessment that indicates youths’ (ages 9–18) control and expression of their anger (Spielberger, 1999). The STAXI-2 C/A has provided reliable and consistent results across diverse cultures and settings (Chirichella-Besemer & Motta, 2008). The STAXI-2 C/A contains four scales assessing excessive anger in youths. The four scales are as follows: Anger State (S-Ang), Anger Trait (T-Ang), Anger Control (AC) and Anger Expression (AX). Each of the four scales measures a different indicator of anger, in order to provide counselors with a multifaceted perspective of the client’s anger behavior.
Past studies that utilized the STAXI-2 C/A focused on AC and AX because of the strong validity these scales have with other anger assessments (Freeman, 2004); thus, the AC and AX scales were used in this pilot study. Cronbach’s alphas were .92 and .67 for AC and AX respectively (Freeman, 2004). Barrio, Aluja, and Spielberger (2004) stated that Cronbach’s alphas demonstrated by the STAXI-2 C/A indicated a high degree of reliability. Additionally, Barrio et al. (2004) also exhibited high construct validity by correlating the STAXI-2 C/A with the Verbal and Physical Aggressiveness Scale (AFV; Caprara & Pastorelli, 1993). A significant correlation of .43 existed between the two assessments. According to Gladding (2012), numerous counselors fail to measure the successfulness of their groups accurately because of errors in measurement and evaluation. In groups, a large number of therapeutic factors are occurring, which affect members in varying ways (Corey, 2011). Focusing on too many factors can overwhelm counselors and undermine evaluation, which is critically important (Gladding, 2012). In order to avoid this potential problem, this pilot study focused on a limited number of factors.
Procedures
A large, urban public middle school in a metropolitan area provided the setting and participants for this pilot study. Serving 2,000 students in grades 6–8, the school has a standardized documentation system that keeps track of behavioral disruptions. The documentation system records in-school suspensions (ISS), out-of-school suspensions (OSS) and behavioral infractions for students (Burt, 2010). Each student has a personal identification number; the administration connects student infractions to these numbers in order to identify any student. The documentation system also contains a small description of what caused the issue. For instance, some students have behavioral outbursts of anger, while others have infractions for tardiness. Since the focus of this pilot was to determine anger differences between genders, it was imperative for the study to have participants who displayed excessive anger. To increase validity and correctly identify participants, the author used school administration recommendations.
The author conducted interviews with school staff to gather information as suggested by Bryan, Day-Vines, Griffin, and Moore-Thomas (2012). For example, the author asked school deans, teachers and professional school counselors (PSC) for recommendations about students. Many students had a high overall number of OSS and ISS, including a large number of behavioral infractions. However, some infractions were due to nonexcessive anger problems (e.g., tardiness). School staff could provide a safeguard against the author inappropriately recruiting a student who did not truly require services. The author asked school staff if a student’s number of OSS, ISS and infractions corresponded with actual behavior (i.e., excessive anger). Thus, the goal was to eliminate as much bias as possible to ensure the most appropriate candidates.
After interviewing school staff, a pool of candidates emerged, consisting of individuals with documentation of excessive anger, fights and legal procedures in the court system (Burt, 2010). School staff considered these candidates to be at high risk for excessive anger, and candidates’ records of OSS, ISS and behavioral infractions corroborated this belief. According to Burt et al. (2013), more than eight occurrences in a 12-week period constitute a high number of anger issues; thus, this study held the same parameters advocated by Burt et al. (2013). Once a list of eligible candidates emerged, the author interviewed school staff a second time. This second short interview was a safeguard measure before actually contacting candidates. The author wanted to meet with school staff again to reduce potential staff bias and ensure that candidates were still having anger issues. After the last interview, school staff explained the study to candidates in detail.
In order to increase client buy-in, school staff introduced the author of this article (who was also the group facilitator) to candidates. The author met with candidates and explained the study in more detail, in addition to answering any questions. If the candidates were interested in participating, the author gave them informed consent forms to have their parents sign. To increase the likelihood of the candidates returning the informed consent forms, candidates received tokens from the school, which allowed them to buy goods in the school store. If candidates returned signed informed consent forms, they received five tokens, comparable to five U.S. dollars. Out of 30 candidates, 20 returned signed informed consent forms. Although this is a small number, this quantity is permissible for pilot studies (Heppner, Wampold, & Kivlighan, 2008). The author split the participants in half based on gender (10 males and 10 females). One participant dropped out of each group, leaving 18 who completed the study. Each group met at a different time and was not aware of the existence of the other group (Burt, 2010). This pilot study assessed participants’ behavior via the STAXI-2 C/A, given pre- and post-intervention.
Structure of the intervention/anger management group used in the pilot study. The anger management group consisted of eight counseling sessions and two assessment sessions (pretest and posttest assessment; Burt, 2010). Program duration was 10 weeks, and the author of this article conducted each session weekly. Corresponding with Blanton, Christensen, and Shakir (2006), each counseling session contained the following four essential components: an opening question (such as an icebreaker or introductory segment), a behavioral lesson (information gathering and learning), a behavioral activity (an experiential segment in which learned information is applied), and an appreciations and closings segment ending the group (a bonding piece for group members). Counseling sessions concluded after 60 minutes, with opening questions lasting approximately 5–10 minutes. Behavioral lessons took between 10 and 25 minutes and behavioral activities lasted 15–30 minutes. Appreciations and closing concluded after 5–10 minutes. Pre- and post-group paperwork sessions took approximately 15–30 minutes (Burt, 2010). As Burt et al. (2012) suggested, groups must be strength-based (i.e., accentuating members’ strong points), and incorporate collaboration and teamwork. The group was prosocial in nature, emphasized clients’ strengths and developed social bonding. Topics for the eight sessions included the following: improving communication skills, recognizing personal emotions, identifying emotions within others, improving observational skills, advanced detection of emotions in others, noticing anger cues in others, understanding personal anger cues, strategies for calming down, and problem-solving.
Mental health counselor for the intervention. The mental health counselor for both groups was this author, who has experience as a group facilitator and counselor educator. Additionally, the author worked as a training liaison for anger management groups in the school system, teaching conflict resolution and peer mediation. He also has experience working with groups for adults and children with oppositional defiance disorder and anger management issues. The group facilitator used an integrative orientation, utilizing social cognitive theory (SCT) and cognitive-behavioral therapy (CBT; Burt, 2010).
Results
The focus of the study was to determine whether differences existed between male and female levels of excessive aggression. Table 1 displays descriptive statistics and indicates results from the one-way repeated measures ANOVA for AC and AX. Results for youths’ overall AC levels pre- and post-intervention indicated the following, F1, 8 = 6.36, p = .003, ES = .44. Thus, the pilot study showed preliminary findings that a significant difference existed between genders on AC. For the scale of AX, results indicated a statistically significant difference between genders pre- and post-intervention (F1, 8 = 4.06, p = .018, ES = .34). Although repeated measures indicated a statistically significant difference between genders, pair-wise comparisons allowed examination of exactly where differences lay between genders on AC and AX. Thus, a significant difference existed between gender on AC (p = .04), and on AX (.03; Table 1). At the beginning of the pilot study, males had less AC, but females had more AX. However, females had the larger increase in AC post-intervention, as well as the greatest reduction in AX between genders. Hence, females had the greater overall gains and improvement pre- and post-intervention as opposed to males.
Table 1
Outcome results for Anger Control and Anger Expression
|
Pretest
|
|
Posttest
|
|
Males
|
|
Females
|
|
|
|
|
|
Males
|
|
Females
|
|
|
M (SD)
|
|
M (SD)
|
df
|
P
|
F
|
ES
|
|
M (SD)
|
|
M (SD)
|
df
|
P
|
Repeated Measures ANOVA a |
|
|
|
|
|
|
|
|
|
|
|
|
|
Anger Control |
44.22
(12.76)
|
|
51.56
(4.33)
|
8
|
.003
|
6.36
|
.44
|
|
50.00
(14.00)
|
|
63.33 (7.85)
|
8
|
|
Anger Expression |
18.78
(5.58)
|
|
24.67
(3.87)
|
8
|
.018
|
4.06
|
.34
|
|
17.44
(5.50)
|
|
20.67
(2.74)
|
8
|
|
Pair-Wise Comparisons b |
|
|
|
|
.04
|
|
|
|
|
|
|
|
.03
|
Note. a N = 9 b N = 18
Discussion
Females had more AX than males, a finding which corresponds with Cross and Campbell (2011). Males appeared to have less AC and were somewhat less angry than females. A number of studies support the preceding findings, most notably Winstok (2011) and Carney et al. (2007). Further, this pilot’s findings corroborate the idea that both genders have equal problems with excessive anger (Carney et al., 2007). The results from this study also suggest that both genders can improve with interventions designed to address anger. According to Winstok (2011), a common misconception is that males have greater need for excessive anger interventions than females. However, in this pilot study, females responded better to the treatment than males did. This responsiveness to treatment is interesting in that few studies have directly compared sensitivity to interventions by gender. While sensitivity to treatment was not a focal point of this pilot, it is interesting to note and direct attention to this unexpected outcome.
The author believes that the primary underlying reason females responded better to the treatment is that they are an underserved population (West-Olatunji et al., 2010). This is not to say that other explanations are not contributing factors, but because the females in this study possibly represent an underserved population, the aforementioned factor likely has more influence. According to West-Olatunji (2010), an underserved population is one that needs services, but does not have access to help. In addition, a number of the females in this pilot qualify as an underserved population as defined by Burt and Butler (2011). For instance, background information provided by the school indicated that approximately 85% of males in this pilot study received prior services (e.g., counseling) before participating. Conversely, 40% of females in this pilot study received prior services. Although the purpose of this study was not to detail what causes an underserved population to develop, research indicates that it can be due to institutional, social or cultural constraints (West-Olatunji et al., 2010).
While this study did not use qualitative measures as advocated by McCarthy (2012), females verbally disclosed that the school rarely offers them anger management services. Female participants further stated that if those services were more readily available, they would use them. Conversely, males indicated being overwhelmed with staff attempting to persuade them to participate in anger management services. This dichotomy in access to treatment clearly marks the identification of an underserved population. Thus, the females’ higher responsiveness to the intervention is potentially due to the following: Perhaps this study was a first intervention for many of the female participants. For females who did receive prior services, it may have been the first intervention directly dealing with anger.
Day (2008) indicated three characteristics that clients need to increase the likelihood of a successful outcome: the client must be in distress, must actively seek help and must have high expectations for counseling. The female participants (as opposed to the majority of the males) in this study met the preceding three criteria. Members of both genders were in a state of distress (as evidenced by the school’s documentation system). However, females verbally admitted to wanting help and had higher expectations. Consequently, females in the pilot had larger, more consistent gains. As evidenced by West-Olatunji et al. (2010), when underserved populations receive desired treatments, the change is normally larger than average. Thus, the findings in this pilot study connect to previous research and provide a plausible reason for the differences between genders.
Limitations
This pilot study had limitations stemming from research methods. First, the groups were limited to one school, as well as to selection from a standardized school documentation system (Burt, 2010). The documentation system compiled an objective list of behavior issues in school, but did not differentiate between excessively angry and nonexcessively angry behaviors. For example, documented behaviors could range from threatening school staff to not returning school forms promptly. To account for this issue, this study included school staff and administration’s professional suggestions for possible candidates. However, school staff may have had subtle biases for or against certain students. There are limitations to each method of selection, including both the standardized documentation system and the school staff. An additional limitation is that the same mental health counselor (the author of this article) conducted the groups. Due to this limitation, some participants’ changes may be due to the facilitator’s style or personality. More importantly, this study lacked a control group and had a small number of participants. The lack of a control group makes generalizations difficult in that it is uncertain whether other extraneous variables influenced the results. Having a small number of participants decreases the power of the pilot study and makes it difficult to generalize results. However, the fact that a significant finding occurred with a small sample size indicates the strong influence of the intervention (Gay & Airasian, 2003). In schools, it is difficult to conduct full-scale studies due to a number of preexisting conditions, such as high-stakes testing (Burt et al., 2013). Therefore, having a study without a control group and with a small number of participants may be the most appropriate method if investigators are to conduct research in schools (Heppner et al., 2008).
Implications and Future Directions for Research
Implications for mental health counselors stemming from this pilot study are numerous. First, mental health counselors must be aware that both genders need services for excessive anger. Mental health counselors should not allow personal biases and media influences to sway professional opinion (Gladding, 2012). In addition, mental health counselors must advocate for fairness and oppose stereotyped biases and ideologies pushed by society (Burt et al., 2012). According to Gray and Rose (2012), discrimination and internalized oppression begin by ignoring discriminatory societal practices. Only by remaining reflective and cognizant of personal biases can mental health counselors reduce problematic issues and model appropriate behaviors (Young, 2012).
A second implication for mental health counselors is to understand that a strength-based model promoting wellness is critically important for clients (Hagedorn & Hirshhorn, 2009). Specific populations, such as youth, respond better to models incorporating empowerment, which can lead to increased behavioral self-efficacy (Bandura, 2008a). Furthermore, positive modeling by mental health counselors also increases growth and behavioral self-efficacy (Bandura, 2008a). A combination of strength-based approaches, empowerment and modeling improve groups’ interpersonal, intrapersonal and extrapersonal functioning (Gladding, 2012). Third, mental health counselors should seek to improve delivery of services and outcomes by evaluating the group process (Steen, 2011). For instance, Gladding (2012) and McCarthy (2012) reinforced the notion of improving counseling services through research and evaluation. This study provided a formal assessment of a group that could have otherwise gone unreported.
Future researchers may want to improve the overall research design. For example, researchers could include a larger number of participants, groups and multiple facilitators. Moreover, future studies must have a true experimental design, such as a control group with random assignment. Including participants’ personal perspectives and phenomenological views not only increases the validity of research, it improves mental health counselors’ skill levels as well (Gladding, 2012). Qualitative measures improve skill level by giving mental health counselors a clear idea of what actually worked and what did not (Burt & Butler, 2011). Lastly, future researchers may want to pay more attention to gender responsiveness (sensitivity) to treatments, to determine if males or females respond better to specific treatments.
Conclusion
The purpose of this pilot study was to determine whether gender differences existed among adolescents for excessive anger. Preliminary results indicate that differences existed, but that there also were distinctions between genders regarding the intervention itself. Females had better AC, but also had more AX compared to their male counterparts. However, females seemed to respond better to the intervention, as shown by their larger gains and improvement. Males improved as well, but did not have the substantial progress observed in females. While past research may not have lent strong support for gender differences, this author hoped to reinvigorate interest in gender discrepancies. Females are an underserved population with regard to anger management; research has indicated that they experience anger sometimes at a rate paralleling or surpassing males (Cross & Campbell, 2011). However, due to societal stigma and cultural biases, many females do not receive anger management services. Therefore, only rigorous research can determine whether these problems truly exist by improving group research and outcomes (McCarthy, 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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Dec 2, 2014 | Article, Volume 4 - Issue 5
Elizabeth Villares, Kimberly Colvin, John Carey, Linda Webb, Greg Brigman, Karen Harrington
This study examines the convergent validity and divergent validity of the Student Engagement in School Success Skills (SESSS) survey. The SESSS is easy to administer (it takes fewer than 15 minutes to complete) and is used in schools to provide educators with useful information about students’ use of skills and strategies related to school success. A total of 4,342 fifth graders completed the SESSS; the Motivated Strategies for Learning Questionnaire (MSLQ) Cognitive Strategy Use, Self-Regulation, Self-Efficacy and Test Anxiety subscales; and the Self-Efficacy for Self-Regulated Learning (SESRL). The three subscales of the SESSS (Self-Direction of Learning, Support of Classmates’ Learning and Self-Regulation of Arousal) correlated highly with the MSLQ Cognitive Strategy Use and Self-Regulation subscales, moderately correlated with the Self-Efficacy subscale and the SESRL, and did not correlate with the MSLQ Test Anxiety subscale. Future research is needed to use the SESSS subscales as discriminable dimensions.
Keywords: school success, convergent validity, divergent validity, Student Engagement in School Success Skills survey, educators
For more than a decade, researchers have placed increased emphasis on evidence-based practice and a programmatic approach to school counseling (Carey, 2004; Green & Keys, 2001; Gysbers, 2004; Lapan, 2005; Myrick, 2003; Paisley & Hayes, 2003; Whiston, 2002, 2011). This emphasis from the school counseling profession reflects national initiatives. In 2001, the Institute of Education Sciences, the research arm of the U.S. Department of Education, was established to determine, through rigorous and relevant research, what interventions are effective and ineffective for improving student achievement and education outcomes. The What Works Clearinghouse (WWC), an initiative of the Institute of Education Sciences, was created in 2002 to identify studies that provide credible and reliable evidence of the effectiveness of education interventions. The purpose of WWC is to inform researchers, educators and policymakers of interventions designed to improve student outcomes.
The American School Counselor Association’s (ASCA, 2005) response to emerging national policy and initiatives included a call for school counselor-led interventions that contribute to increased student achievement as part of a comprehensive school counseling program. The need for more research to identify evidence-based interventions tying school counselors to improved student academic performance also surfaced in a school counseling Delphi study, which identified the most pressing research questions in the profession (Dimmitt, Carey, McGannon, & Henningson, 2005). The top priority cited by this Delphi study was the need to determine which school counseling interventions resulted in the greatest student achievement gains. In addition, five major reviews of school counseling research all discussed the need for more research to strengthen the link between school counselor interventions and student achievement (Brown & Trusty, 2005; Dimmitt, Carey, & Hatch, 2007; Whiston & Quinby, 2009; Whiston & Sexton, 1998; Whiston, Tai, Rahardja, & Eder, 2011). However, researchers continue to report limitations in the school counseling outcome research. Among the limitations are conclusions drawn from studies based on nonstandardized outcome assessments. For instance, in a review of school counseling studies, Brown and Trusty (2005) concluded that school counseling research has been limited by the lack of valid and reliable instruments that measure the skills, strategies and personal attributes associated with academic and social/relationship success. More recently, Whiston et al. (2011) completed a meta-analytic examination of school counseling interventions and also determined the dominance of nonstandardized outcome assessments in school counseling research as a significant limitation. These limitations continue to be a hindrance for the school counseling profession, given the goal of establishing evidence-based practices that link school counselor interventions to improved student outcomes. The current WWC’s Procedures and Standards Handbook (WWC, 2011) includes review procedures for evaluating studies that determine a particular intervention to be effective in improving student outcomes. The handbook provides nine reasons why a study under review would fail to meet WWC standards for rigorous research. Among the reasons is a failure to use reliable and valid outcome measures.
While a few valid instruments have recently been developed to measure school counseling outcomes (Scarborough, 2005; Sink & Spencer, 2007; Whiston & Aricak, 2008), they do not measure student changes in knowledge and skills related to academic achievement. The Student Engagement in School Success Skills survey (SESSS; Carey, Brigman, Webb, Villares, & Harrington, 2013) was developed to measure student use of the skills and strategies that were (a) identified as most critical for long-term school success and (b) could be taught by school counselors within the scope of the ASCA National Model, through classroom guidance. The importance of continuing to evaluate the psychometric properties of the SESSS lies in the fact that, for school counselors, there has typically been no standardized way to measure these types of outcomes and tie them directly to school counselor interventions. Previous studies on self-report measures of student metacognition indicate that it is feasible to develop such a measure for elementary-level students (Sperling, Howard, Miller, & Murphy, 2002; Yildiz, Akpinar, Tatar, & Ergin, 2009). The foundational concepts, skills and strategies of metacognition as well as the social skills and self-management skills taught in the Student Success Skills (SSS) program are developmentally appropriate for grades 4–10. The questions for the SESSS were developed to parallel these key strategies and skills taught in the SSS program. The instrument was tested for readability and is appropriate for grade 4 and above.
The SESSS is a self-report measure of students’ use of key skills and strategies that have been identified consistently over several decades as critically important to student success in school, as noted in large reviews of educational research literature (Hattie, Biggs, & Purdie, 1996; Masten & Coatsworth, 1998; Wang, Haertel, & Walberg, 1994a). Three skill sets have emerged from this research literature as common threads in contributing to student academic success and social competence: (a) cognitive and metacognitive skills such as goal setting, progress monitoring and memory skills; (b) social skills such as interpersonal skills, social problem solving, listening and teamwork skills; and (c) self-management skills such as managing attention, motivation and anger (Villares, Frain, Brigman, Webb, & Peluso, 2012). Additional research in support of these skills and strategies continues to weave a coherent research tapestry that is useful in separating successful students from students at risk of academic failure (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011; Greenberg et al., 2003; Marzano, Pickering, & Pollock, 2001; Zins, Weissberg, Wang, & Walberg, 2004).
Linking school counseling programs and interventions to improved student outcomes has become increasingly important (Carey et al., 2013). One way for school counselors to demonstrate the impact of classroom guidance and small group counseling on achievement is by measuring the impact of their interventions on intermediate variables associated with achievement. These intermediate variables include the previously mentioned skills and strategies involving cognitive, social and self-management. Instruments that measure these critically important fundamental learning skills and strategies are limited.
The present article explores the convergent and divergent validity of the SESSS (Carey et al., 2013). The article builds upon previous research describing the item development of the SESSS and exploratory factor analysis (Carey et al., 2013) and a recently completed confirmatory factor analysis (Brigman et al., 2014). The current findings contribute to the establishment of the SESSS as a valid instrument for measuring the impact of school counselor-led interventions on intermediate variables associated with improved student achievement.
Method
The data collected on the SESSS occurred within the context of a multiyear, large-scale, randomized control trial funded through the U.S. Department of Education’s Institute of Education Sciences. The purpose of the grant was to investigate the effectiveness of the SSS program (Brigman & Webb, 2010) with fifth graders from two large school districts (Webb, Brigman, Carey, & Villares, 2011). In order to guard against researcher bias, the authors hired data collectors to administer the SESSS, Motivated Strategies for Learning Questionnaire (MSLQ) and Self-Efficacy for Self-Regulated Learning (SESRL), and standardized the training and data collection process. The authors selected these particular surveys because they reflected factors known to be related to effective learning in different ways and because they provided a range of measures, some of which were theoretically related to the SESSS and some of which were not.
Procedures
During the 2011–2012 academic year, graduate students who were enrolled in master’s-level Counselor Education programs at two universities were hired and trained in a one-day workshop to administer the SESSS, MSLQ and SESRL and handle data collection materials. At the training, each data collector was assigned to five of the 60 schools across two school districts. After obtaining approvals from the university institutional review board and school district, the research team members notified parents of fifth-grade students of the study via district call-home systems and sent a letter home explaining the study, risks, benefits, voluntary nature of the study and directions on how to decline participation. One month later, data collectors entered their assigned schools and participating classrooms to administer the study instruments. Prior to administering the instruments, each data collector read aloud the student assent. Students who gave their assent were instructed to place a precoded generic label at the top of their instrument, and then each data collector read aloud the directions, along with each item and possible response choice on the SESSS, MSLQ and SESRL. Each assigned data collector was responsible for distributing, collecting and returning all the completed instruments to a district project coordinator once the data collector left the school building according to the Survey Data Collection Manual. In addition, the data collector noted any student absences and/or irregularities, and confirmed that all procedures were followed.
The district project coordinators were responsible for verifying that all materials were returned and secured in a locked cabinet until they were ready to be shipped to a partner university for data analysis. The coordinators gathered demographic information from the district databases and matched it to the participating fifth-grade students and the precoded instrument labels through a generic coding system (district #1–2, school #1–30, classroom #1–6, student #1–25). The coordinators then saved the demographic information in a password-protected and encrypted Excel spreadsheet on an external device and shipped it to a partner university for data analysis.
Participants
A total of 4,342 fifth-grade students in two large school districts completed the SESSS. The following is the demographic profile of the total participants: (a) gender = 2,150 (49.52%) female and 2,192 (50.48%) male; (b) ethnicity = 149 (3.43%) Asian, 1,502 (34.59%) Black, 865 (19.92%) Hispanic, 18 (.42%) Native American, 125 (2.88%) Multiracial, 1,682 (38.74%) White, and 1 (.02%) no response; (c) socioeconomic status = 1,999 (46.04%) noneconomically disadvantaged and 2,343 (53.96%) economically disadvantaged; (d) disability = 3,677 (84.68%) nondisabled and 665 (15.32%) disabled; (e) 504 status = 4,155 (95.70%) non-504 and 187 504 (4.3%); and (f) English language learners (ELL) = 3,999 (92.1%) non-ELL and 343 (7.9%) ELL students. Demographic information for fifth-grade students in each school district is reported in Table 1.
Table 1
Fifth-Grade Student Participant Demographics by School District
Demographic Characteristics
|
District 1
(n = 2,162)
|
District 2
(n = 2,180)
|
|
|
|
Gender |
FemaleMale |
1,080 (49.90%)
1,082 (50.10%)
|
1,070 (49.10%)
1,110 (50.90%)
|
Ethnicity |
AsianBlack
Hispanic
Native American
Multiracial
White
No response |
89 (04.12%)
899 (41.58%)
165 (07.63%)
7 (00.32%)
64 (02.95%)
938 (43.40%)
—-
|
60 (02.75%)
603 (27.66%)
700 (32.11%)
11 (00.50%)
61 (02.80%)
744 (34.13%)
1 (00.05%)
|
SES |
Non-economically disadvantagedEconomically disadvantaged |
1,118 (51.71%)
1,044 (48.29%)
|
881 (40.41%)
1,299 (59.59%)
|
Disability |
NondisabledDisabled |
1,847 (85.43%)
315 (14.57%)
|
1,830 (83.94%)
350 (16.06%)
|
504 Status |
Non-504504 |
2,108 (97.50%)
54 (02.50%)
|
2,047 (93.90%)
133 (06.10%)
|
English language learners |
Non-ELLELL |
1,968 (91.03%)
194 (08.97%)
|
2,031 (93.17%)
149 (06.83%)
|
Note. n = number of students enrolled in the district; SES = socioeconomic status; ELL = English language learners.
Instruments
Student Engagement in School Success Skills. The SESSS (Carey et al., 2013) was developed to measure the extent to which students use the specific strategies that researchers have shown relate to enhanced academic achievement (Hattie et al., 1996; Masten & Coatsworth, 1998; Wang et al., 1994b). Survey items were written to assess students’ cognitive and metacognitive skills (e.g., goal setting, progress monitoring, memory skills), social skills (e.g., communication skills, social problem solving, listening, teamwork skills) and self-management skills (e.g., managing attention, motivation, anger). After the initial pool of items was developed, items were reviewed by an expert panel of elementary educators and school counselors and subjected to a readability analysis using the Lexile Framework for Reading system (MetaMetrics, 2012). At each stage of review, minor changes were made to improve clarity on several items.
Twenty-seven self-report items (plus six additional items used to control for response set) were assembled into a scale with the following directions: “Below is a list of things that some students do to help themselves do better in school. No one does all these things. No one does any of these things all the time. Please think back over the last two weeks and indicate how often you did each of these things in the last two weeks. Please follow along as each statement is read and circle the answer that indicates what you really did. Please do your best to be as accurate as possible. There are no right or wrong answers. We will not share your answers with your parents or teachers. We will not grade your answers.”
The response format included four options that reflected frequency of strategy use in the last two weeks: “I didn’t do this at all,” “I did this once,” “I did this two times” and “I did this three or more times.” This response format was not conducive to writing clear negatively worded items; therefore, six additional items were developed to help control for response set. Three of these additional items reflected strategies that elementary students were unlikely to use (e.g., searching the Internet for additional math problems to complete). Three items reflected strategies that elementary students were likely to use (e.g., asking a friend when homework was due), but they were not covered in the SSS program.
Based on a previous administration of the SESSS to 262 elementary students in the fourth through eighth grades, Carey et al. (2013) reported an overall alpha coefficient for reliability for the 27-item scale to be .91, and coefficient alphas for each grade ranged between .87 (for fifth grade) and .95 (for seventh grade). All items correlated well with the total scale (ranging between .34 and .63). Scores on the total scale were distributed approximately normally: M =65.83, SD = 15.44.
In addition, Carey et al., (2013) found in an exploratory factor analysis of the SESSS scores of 402 fourth through sixth graders that a four-factor solution provided the best model of scale dimensionality, considering both the solution’s clean factor structure and the interpretability of these factors. These four factors reflected students’ Self-Management of Learning, Application of Learning Strategies, Support of Classmates’ Learning and Self-Regulation of Arousal. Regarding the SESSS factors, Self-Management of Learning and Application of Learning Strategies related closely to the categories of cognitive skills, metacognitive skills and the intentional self-regulation of cognitive processes. Support of Classmates’ Learning related closely to social skills that support classroom learning. Self-Regulation of Arousal related to the self-management of arousal and emotion that can interfere with effective learning. While determining the actual associations of SESSS factors with specific, previously established constructs requires empirical study, it is encouraging that the factor structure determined in this research corresponded with previous research.
In a confirmatory factor analysis study (Brigman et al., 2014), using SESSS scores from a diverse sample of almost 4,000 fifth-grade students, who found that while a four-factor model fit the data well, the scales associated with Self-Management of Learning and Application of Learning Strategies correlated so highly (r = .90) as to be indiscriminate. These items associated with the two factors were combined, and the subsequent three-factor model also proved to better fit the data. Brigman et al. (2014) suggested that the SESSS is best thought of as having three underlying factors corresponding to Self-Direction of Learning (which represents the combination of the original Management of Learning and Application of Learning Strategies factors), Support of Classmates’ Learning and Self-Regulation of Arousal.
Based on factor loadings, Brigman et al. (2014) created three SESSS subscales. The Self-Direction of Learning subscale (19 items) reflects the students’ intentional use of cognitive and metacognitive strategies to promote their own learning. Typical items include the following: “After I failed to reach a goal, I told myself to try a new strategy and not to doubt my ability,” and “I tried to keep myself motivated by imagining what it would be like to achieve an important goal.” The Support of Classmates’ Learning subscale (six items) reflects the students’ intentional use of strategies to help classmates learn effectively. Typical items include the following: “I tried to help a classmate learn how to do something that was difficult for them to do,” and “I tried to encourage a classmate who was having a hard time doing something.” Finally, the Self-Regulation of Arousal subscale (three items) reflects students’ intentional use of strategies to control disabling anxiety and cope with stress. Typical items include the following: “I focused on slowing my breathing so I would feel less stressed,” and “I imagined being in a calm place in order to feel less stressed.”
Motivated Strategies for Learning Questionnaire. The MSLQ is a 55-item, student self-report instrument with five subscales that measure different aspects of students’ motivation, emotion, effort and strategy use (Pintrich & DeGroot, 1990). The different subscales of the MSLQ are designed to be used singly or in combination to fit the needs of a researcher (Duncan & McKeachie, 2005). Items were adapted from various instruments used to assess student motivation, cognitive strategy use and metacognition (e.g., Eccles, 1983; Harter, 1981; Weinstein, Schulte, & Palmer, 1987). The present study used the following four subscales of the MSLQ: Cognitive Strategy Use, Self-Regulation, Self-Efficacy and Test Anxiety.
The Cognitive Strategy Use subscale is composed of 13 items that reflect the use of different types of cognitive strategies (e.g., rehearsal, elaboration, organizational strategies) to support learning. Typical items include the following: “When I read material for class, I say the words over and over to myself to help me remember,” “When I study, I put important ideas into my own words” and “I outline the chapters in my book to help me study.” Pintrich and DeGroot (1990) reported that the Cognitive Strategy Use subscale is reliable (Cronbach’s alpha = .83).
The Self-Regulation subscale includes nine items that reflect metacognitive and effort management strategies that support learning. Typical items include the following: “I ask myself questions to make sure I know the material I have been studying” and “Even when study materials are boring I keep working until I finish.” Pintrich and DeGroot (1990) reported that the Self-Regulation subscale is reliable (Cronbach’s alpha = .74).
The Self-Efficacy subscale is composed of nine items that reflect students’ ratings of their level of confidence in their ability to do well in classroom work. Typical items include the following: “Compared with others in this class, I think I’m a good student” and “I know that I will be able to learn the material for this class.” Pintrich and DeGroot (1990) reported that the Self-Efficacy subscale is reliable (Cronbach’s alpha = .89).
The Test Anxiety subscale includes four items that reflect students’ ratings of their experience of disabling levels of anxiety associated with classroom tests and examinations. Typical items include the following: “I am so nervous during a test that I cannot remember facts I have learned” and “I worry a great deal about tests.” Pintrich and DeGroot (1990) reported that the Self-Efficacy subscale is reliable (Cronbach’s alpha = .75).
Factor analyses indicated that these MSLQ subscales are related to different latent factors. Scores on the Cognitive Strategy Use subscale have been demonstrated to be related to grades on quizzes and examinations, grades on essays and reports, and overall class grades. Scores on the Self-Regulation subscale have been shown to be related to the above measures plus student performance on classroom seatwork assignments. Scores on the Self-Efficacy subscale have been demonstrated to be related to students’ grades on quizzes and examinations, grades for classroom seatwork assignments, grades on essays and reports, and overall class grades. Scores on the Test Anxiety subscale proved to be associated with lower levels of performance on classroom examinations and quizzes, as well as course grades (Pintrich & DeGroot, 1990).
Duncan and McKeachie (2005) reviewed the extensive research on the psychometric properties and research uses of the MSLQ. They concluded that the subscales are reliable, measure their target constructs and have been successfully used in numerous studies to measure student change after educational interventions targeting these constructs.
Self-Efficacy for Self-Regulated Learning scale. The SESRL was designed to measure students’ confidence in their abilities to perform self-regulatory strategies. It is a seven-item self-report instrument based on the Children’s Self-Efficacy Scale (Bandura, 2006; Usher & Pajares, 2008). Items (e.g., “How well can you motivate yourself to do schoolwork?”) reflect students’ judgments about their abilities to perform self-regulation strategies identified by teachers as being frequently used by students (Pajares & Valiante, 1999). The scale has been used successfully with older elementary students in a self-read format and with fourth graders in a read aloud administration format (Usher & Pajares, 2006). Cronbach’s alpha estimates of reliability have ranged between .78 and .84 (Britner & Pajares, 2006; Pajares & Valiante, 2002; Usher & Pajares, 2008). Factor analysis has suggested that the scale is unidimensional. Concurrent validity studies have indicated that the scale is related to measures of self-efficacy, task orientation and achievement (Usher & Pajares, 2006).
Data Analysis
In the initial analysis of the three SESSS subscales, the present authors used mean imputation to replace missing survey responses, by replacing a missing response with the overall mean for that survey item. For each of the 33 SESSS items, only 8.3%–9.1% of the responses were missing. Mean imputation is appropriate when the percentage of missing data is less than 10% and can be considered to be missing at random (Longford, 2005). In the current study, the students with missing survey data had an average SESSS score equal to that of the students with a complete response set, thus supporting the notion that the data were missing at random. Coefficient alpha, used as a measure of reliability, was calculated for each of the subscales before missing values were replaced.
Both convergent and discriminant evidence is needed in the validation process (Campbell & Fiske, 1959; Messick, 1993). Messick (1993) argued that while convergent evidence is important, it can mask certain problems. For example, if all tests of a construct do not measure a particular facet of that construct, the tests could all correlate highly. Likewise, if all tests of a construct include some particular form of construct-irrelevant variance, then the tests may correlate even more strongly because of that fact. Due to these possible shortcomings of convergent evidence, discriminant evidence is needed to ensure that the test is not correlated with another construct that could account for the misleading convergent evidence.
To determine the validity of the three SESSS subscales, the authors examined the correlations between each of the subscales with five other measures: four subscales of the MSLQ (Self-Efficacy, Cognitive Strategy Use, Self-Regulation and Test Anxiety), and the SESRL. Specifically, the authors considered the strength and direction of the SESSS subscales’ correlations with these other measures.
Results
Descriptive statistics and reliability estimates for the instruments used in this study are contained in Table 2. Coefficient alphas for the three SESSS subscales (Self-Direction of Learning, Support of Classmates’ Learning and Self-Regulation of Arousal), were 0.89, 0.79 and 0.68, respectively, and 0.90 for the SESSS as a whole. These results indicate good internal consistency (i.e., that the items within each instrument measure the same construct).
All correlations between pairs of subscales appear in Table 3. Because of the large sample size in this study, statistical significance by itself could be misleading, so the authors used the magnitude and direction of the correlations for their interpretations. Correlation is an effect size reflecting the degree of association of two variables (Ellis, 2010). The correlations among the three SESSS subscales ranged between .47 and .70, which suggests that the subscales measured related but discriminable dimensions of students’ success skill use. In assessing the concurrent validity of these three subscales, it was helpful to first focus on the scales that correlated most highly with the three SESSS subscales. The three SESSS subscales followed the same pattern with respect to strength of correlation. All three correlated most highly with both the Cognitive Strategy Use and Self-Regulation subscales of the MSLQ. These two subscales measure the students’ reported use of cognitive and metacognitive strategies associated with effort management and effective learning.
Table 2
Descriptive Statistics and Reliability Estimates for the Study Scales
Scales |
Scales |
M
|
SD
|
Alpha
|
|
|
|
|
|
|
|
|
|
|
SESSS |
Self-Direction of Learning |
48.6
|
10.88
|
0.89
|
|
Support of Classmates’ Learning |
16.6
|
4.28
|
0.79
|
|
Self-Regulation of Arousal |
7.9
|
2.60
|
0.68
|
|
|
|
|
|
MSLQ |
Self-Efficacy |
28.3
|
4.41
|
0.83
|
|
Cognitive Strategy Use |
48.6
|
8.31
|
0.82
|
|
Self-Regulation |
31.2
|
5.08
|
0.75
|
|
Test Anxiety |
8.8
|
4.03
|
0.79
|
|
|
|
|
|
SESRL |
Self-Eff. for Self-Reg. Learning |
31.2
|
6.10
|
0.83
|
|
|
|
|
|
|
|
Note. SESSS = Student Engagement in School Success Skills; MSLQ = Motivated Strategies for Learning Questionnaire; SESRL = Self-Efficacy for Self-Regulated Learning.
Table 3
Correlations Between Scales
|
SESSS
|
|
MSLQ
|
|
|
SDL
|
SCL
|
SRA
|
|
SE
|
CSU
|
SR
|
TA
|
SESRL
|
SESSS |
|
|
|
|
|
|
|
|
|
SDL
|
—–
|
0.70*
|
0.58*
|
|
0.28*
|
0.54*
|
0.53*
|
-0.02
|
0.44*
|
SCL
|
|
—–
|
0.47*
|
|
0.25*
|
0.39*
|
0.39*
|
-0.02
|
0.35*
|
SRA
|
|
|
—–
|
|
0.12*
|
0.32*
|
0.30*
|
0.08*
|
0.24*
|
MSLQ |
|
|
|
|
|
|
|
|
|
SE
|
|
|
|
|
—–
|
0.61*
|
0.54*
|
-0.38*
|
0.67*
|
CSU
|
|
|
|
|
|
—–
|
0.70*
|
-0.20*
|
0.68*
|
SR
|
|
|
|
|
|
|
—–
|
-0.25*
|
0.70*
|
TA
|
|
|
|
|
|
|
|
—–
|
-0.35*
|
|
|
|
|
|
|
|
|
|
|
SESRL |
|
|
|
|
|
|
|
|
—–
|
Note. SESSS = Student Engagement in School Success Skills survey; MSLQ = Motivated Strategies for Learning Questionnaire; SESRL = Self-Efficacy for Self-Regulated Learning scale; SDL = Self-Direction of Learning; SCL = Support of Classmates’ Learning; SRA = Self-Regulation of Arousal; SE = Self-Efficacy; CSU = Cognitive Strategy Use; SR = Self-Regulation; TA = Test Anxiety;
*p < .01
Next, the three SESSS subscales correlated with the SESRL, which measures students’ beliefs in their capability to engage in common effective self-regulation learning strategies. Again, all three SESSS subscales followed the same pattern, and had a considerable drop in magnitude of correlation with the MSLQ Self-Efficacy subscale, which measures students’ reports of general academic self-efficacy. While smaller, the correlations with the Self-Efficacy subscale (which ranged between .12 and .28) were practically different than 0. The Self-Direction of Learning subscale had the strongest correlations with the other measures, followed by the Support of Classmates’ Learning subscale and finally by the Self-Regulation of Arousal subscale. There is evidence that the three SESSS subscales, the Cognitive Strategy Use subscale and the Self-Regulation subscale of the MSLQ, and the SESRL all measure some common dimension of an underlying construct, probably relating to students’ intentional use of strategies to promote effective learning.
The Self-Regulation of Arousal subscale was the only one of the three SESSS subscales to be significantly correlated with the MSLQ Test Anxiety subscale. Conceptually, students’ abilities to self-regulate arousal should be related to their reported levels of test anxiety. However, given the weak relationship (r = 0.08) and the fact that this observed correlation was actually opposite in direction to the relationship that would be expected, this finding should not be given undue weight. The results of this study offer little to no evidence that the three SESSS subscales measure the same construct as the MSLQ Test Anxiety subscale. This weak or nonexistent relationship is discriminant evidence in that the other SESSS subscales did not correlate strongly or at all with the MSLQ Test Anxiety subscale. However, the three other MSLQ subscales and the SESRL all showed moderate, negative correlations with the MSLQ Test Anxiety subscale. These differing patterns of correlation with MSLQ Test Anxiety suggest that the SESSS subscales capture a different dimension than the common dimension of the underlying construct measured by the MSLQ subscales (including the Test Anxiety subscale) and the SESRL.
Discussion
The observed pattern of results is very useful in determining the validity of inferences that currently can be made from SESSS scores. Based on prior factor analytic studies (Brigman et al., 2014; Carey et al., 2013), the present authors made an attempt to create three SESSS subscales based on the items that load most strongly on each of three underlying factors. These three SESSS subscales showed good internal consistency and moderate intercorrelations suggesting that the three subscales most probably measure related but discriminable dimensions of students’ success skill use. However, the three SESSS subscales showed essentially the same pattern of correlation with comparison scales. Similarly, the pattern of results suggests that there is little or no overlap between the construct measured by the three SESSS subscales and the construct measured by the Test Anxiety subscale of the MSLQ.
Unfortunately, these results do not shed much light on any differences among the SESSS subscales. Each subscale showed essentially the same pattern of correlations with the comparison scales even where differences would have been expected. For example, the authors would have expected the SESSS Self-Regulation of Arousal subscale to correlate significantly with the MSLQ Test Anxiety subscale, since individuals who are better able to regulate their levels of emotional arousal would be expected to experience less specific anxiety.
These results suggest that the SESSS as a whole represents a valid measure of students’ intentional use of strategies to promote academic success. While prior factor analytic studies (Brigman et al., 2014; Carey et al., 2013) have suggested that the SESSS has three related dimensions, making inferences based upon the three SESSS subscales related to these dimensions is not warranted. Instead, until evidence can be found that these three subscales measure discriminable dimensions of success skill use, the SESSS should be used as a unitary measure in research and practice. Future research in this area is necessary.
Conclusion
Researchers have thoroughly documented the need for school counselors to demonstrate their impact on student achievement (Brown & Trusty, 2005; Dimmitt et al., 2007; Whiston & Quinby, 2009; Whiston & Sexton, 1998; Whiston et al., 2011). School counselor-led interventions that provide evidence of improving student performance remain at the top of national initiatives and research agendas (ASCA, 2005; Dimmitt et al., 2005). However, there is a limited amount of standardized outcome assessments specifically tied to school counselor interventions available to evaluate changes in student knowledge, skills and attitudes related to academic achievement.
The SESSS is easy to administer (it takes fewer than 15 minutes to complete) and educators use it in schools to gain valuable information about students’ use of skills and strategies related to school success. Results on the SESSS may be used to improve the implementation of school counselor-led interventions and reinforcement of specific skills in school and home settings. Current findings indicate that SESSS results should be interpreted as a whole rather than by subscale. SESSS results can be used to monitor student progress, and identify gaps in learning as well as factors affecting student behavior.
The SESSS may be used as a screening tool to identify students in need of school counseling interventions and to evaluate student growth in the academic and behavioral domains. A review of SESSS student data may reveal gaps between student groups and identify the need for additional education opportunities, as well as lead to decisions about future goals of the school counseling program and discussions with administration and staff about program improvement (Carey et al., 2013). Finally, SESSS student data can be used to demonstrate how school counselors can impact student academic and personal/social development related to classroom learning and achievement. SESSS results can be shared with various stakeholders through a variety of report formats (e.g., Web sites, handouts, newsletters), publications, or presentations at the local, regional or national level to document the school counselor’s ability to affect student outcomes most related to parents, administrators and other staff (Carey et al., 2013).
There is one limitation in the study worth noting. While the sample size for the current analysis is considered large and diverse, all participates represented a single grade level, fifth grade, and two public school districts. Future analyses should include students from various elementary and secondary settings and grade levels.
Future research on the psychometric properties of the SESSS should include studies that address (a) the reliability and intercorrelations of the assessments corresponding to the three SESSS subscales and (b) the predictive validity that establishes the relationships between SESSS subscales and measures of academic success (e.g., achievement test scores, grades, teacher ratings). These additional studies are necessary to firmly establish the utility of the SESSS as a reliable and valid measure of student success skills.
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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Elizabeth Villares is an associate professor at Florida Atlantic University. Kimberly Colvin is an assistant professor at the University at Albany, SUNY. John Carey is a professor at the University of Massachusetts-Amherst. Linda Webb is a senior research associate at Florida State University. Greg Brigman, NCC, is a professor at Florida Atlantic University. Karen Harrington is assistant director at the Ronald H. Fredrickson Center for School Counseling Research and Evaluation at the University of Massachusetts-Amherst. Correspondence can be addressed to Elizabeth Villares, 5353 Parkside Drive, EC 202H, Jupiter, FL 33458, evillare@fau.edu.
Dec 2, 2014 | Book Reviews
In Loving Someone with Anxiety: Understanding & Helping Your Partner, counselor Kate N. Thieda provides a wealth of accessible insights and practical strategies intended for the audience of a layperson with an anxious partner. However, a reader with an anxious friend, family member or roommate also can benefit from the book’s material. And while Thieda offers information about various anxiety disorders, she emphasizes that one’s anxiety need not qualify as a diagnosable disorder for it to cause distress and strain a relationship.
The book contains topics including the difference between “everyday” anxiety and anxiety disorders, characteristics of specific anxiety disorders and the risk of comorbid conditions, the ways anxiety affects romantic relationships, practical techniques for communication and relaxation, suggestions for responding to specific types of anxiety, ideas for positive lifestyle changes to reduce anxiety, and self-care strategies for caregivers. Throughout the chapters, Thieda offers frequent vignettes of partners facing challenges and implementing solutions. As accessible as her writing already is, these examples further illuminate the points she makes.
Thieda carries out a number of important tasks in this book. Although she suggests that the reader encourage his or her partner to seek professional help if needed, she also offers clear directions and examples for therapeutic strategies at home, such as helping one’s partner create an anxiety hierarchy and move through it. In doing so, she encourages the reader to hope and empowers him or her to better support a partner. Thieda also explains why accommodating one’s partner’s anxieties (e.g., by carrying out a partner’s OCD rituals, making excuses for him or her, offering constant reassurance) is ultimately more destructive than helpful because it communicates that the anxiety is more powerful than the person who experiences it. In addition to providing information about how to help one’s partner, Thieda prioritizes the mental and emotional state of her reader. She normalizes anxious feelings and discusses the high prevalence of anxiety in our culture; she also validates the unpleasant emotions that often accompany caregiving, such as frustration and guilt. Thieda processes the question of whether and how to tell others about one’s partner’s anxiety, emphasizing a balance of respect for one’s partner with the importance of one’s own self-care and support from others.
Although the book is not specifically meant for mental health professionals, it contains a great deal of information that a counselor can use to communicate more effectively with clients. A counselor might recommend that clients read this book and bring questions back to counseling, or implement some of the strategies Thieda offers, which include empathic listening, mindfulness techniques, body scans and abdominal breathing.
A possible limitation of Loving Someone with Anxiety is that it uses DSM-IV-TR diagnostic criteria for anxiety disorders rather than the new criteria of the DSM-5. For example, one important distinction between editions of the manual is that whereas the DSM-IV-TR characterizes PTSD as an anxiety disorder, the DSM-5 identifies it as a trauma- and stressor-related disorder, a change probably at least partly intended to alleviate the stigma of the term anxiety disorder. A reader of Thieda’s book might miss out on this and similar changes in the diagnostic nomenclature. However, because this book is intended for laypeople and Thieda specifically cautions against a reader using the information she provides to diagnose his or her partner, the use of DSM-IV-TR criteria should not have an impact on the reader.
Loving Someone with Anxiety is a valuable resource for those hoping to support an anxious partner, to gain freedom from anxiety’s restrictions and to engage in healthy self-care, as well as for counselors working with such supportive partners.
Reviewed by: Carie McElveen, the National Board for Certified Counselors, Greensboro, NC.
Thieda, K. N. (2013). Loving someone with anxiety: Understanding & helping your partner. Oakland, CA: New Harbinger.
Dec 2, 2014 | Book Reviews
Acceptance and commitment therapy (ACT) has received significant research attention over the past decade and also been used frequently to treat individuals presenting with a variety of clinical concerns ranging from chronic pain and diabetes management to severe depression and substance abuse. In The Big Book of ACT Metaphors: A Practitioner’s Guide to Experiential Exercises and Metaphors in Acceptance and Commitment Therapy, Jill A. Stoddard and Niloofar Afari provide a comprehensive A–Z resource guide for practitioners, trainees and others in the counseling profession to use when working with clients. Additionally, novel metaphors, new experiential exercises and detailed scripts were collected from the entire ACT community to make this a collaborative endeavor and to provide a “one-stop” shop for all.
The book includes nine chapters and 202 pages of material, as well as 10 appendices, additional resources and a complete list of references. The first two chapters provide a brief introduction to Relational Frame Theory (RFT) and specifically explain how ACT is rooted and theoretically grounded in this model. The reader learns about the six core therapeutic processes and the ACT hexaflex. The authors also adequately discuss the function of metaphors, how to create therapeutic metaphors and how to effectively deliver tailored metaphors in treatment. Chapters 3 through 8 provide a more in-depth description of each of the six core ACT processes. Chapter 3 covers acceptance and willingness while chapter 8 focuses on committed action. The other core processes include cognitive defusion, present-moment awareness, self-as-context and values. In each of these chapters, the authors summarize the core process and provide brilliant exercises, metaphors and scripts for the reader, specifically showing how this theory and approach can be translated into practice. The final chapter ties it all together by summarizing and reviewing material from the first eight chapters and also by using a sailing boat metaphor to demonstrate how multiple core processes can occur in counseling. The authors address general guidelines for tailoring metaphors and common stumbling blocks.
While numerous ACT textbooks and workbooks are available, this book is essential for any current or future ACT practitioner. In addition to including over 100 metaphors and exercises, Stoddard and Afari have beautifully organized the content in this book and matched each exercise or metaphor with its respective core process (e.g., values, committed action). The authors go above and beyond to cite the source from which the material was collected and even provide specific page numbers in order to assist the reader in obtaining previously published material. The inclusion of material that can be used for both group counseling and individual sessions represents a strength of the book. Each chapter is concise, easy to read and detailed enough for even the most novice counselor to replicate in session. In addition to the book’s numerous strengths, the authors may consider adding a chapter in future editions on the role of culture and incorporating additional multicultural metaphors and exercises to utilize in practice, ultimately fostering more cultural dialogue and a stronger therapeutic alliance with clients engaging in treatment.
In summary, this practical, useful and relevant book provides an excellent foundation and guide for new clinicians and also a one-stop shop for well-seasoned ACT counselors. Whether as a trainee, clinician, researcher, supervisor or professor, there is something in this book that you can benefit from and can add to your current toolbox.
Reviewed by: Mary-Catherine McClain, The University of Georgia, Athens, GA.
Stoddard, J., & Afari, N. (2014). The big book of ACT metaphors: A practitioner’s guide to experiential exercises & metaphors in acceptance & commitment therapy. Oakland, CA: New Harbinger.
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