TPC-Journal-V5-Issue4

The Professional Counselor /Volume 5, Issue 4 448 had completed suicide. Following this analysis, a multiple regression was used to describe the relationships of the independent or predictor variables to the dependent or criterion variable (Lussier & Sonfield, 2004). Because LCMS states that it is possible to discern the order in which a person experiences each variable with regard to a particular event, the variables were entered into the regression using the following equation: Bereavement = {time since death} + {primary appraisal} + {secondary appraisal} + {coping skills} + {perceived social support} + {perceived stigma}. Results Descriptive Statistics Descriptive statistics provided simple summaries of the demographic characteristics of the sample, as well as descriptors such as means and standard deviations for these characteristics. The sample was a well-educated, racially diverse group of women who had lost their military spouses to suicide. The majority of participants were non-Hispanic White females who had attended at least some college. Most were affiliated with the Army and had been married to the military member who had completed suicide. The majority of the partners had committed suicide while on active duty. The mean age of respondents was 33.48 years ( SD = 5.20; SE = .373); their ages ranged from 23–50 years. The mean number of children aged 17 or under that were a product of the relationship with the service member was 1.12 ( SD = .79; SE = .064); the range was 0–4 children. The mean number of prior suicide attempts by the service member (known/confirmed by the surviving female spouse) was 1.31 ( SD = 1.06; SE = .096); the range was 0–4 prior suicide attempts. Correlation Results Using SPSS Student Version 22.0 software, a Pearson correlation coefficient was used to measure the relationship of bereavement, primary appraisals, secondary appraisals, coping skills, social support, and stigma among women whose military spouses had completed suicide. The correlation coefficient measures the strength and direction of the relationship among variables. When conducting a correlational analysis of two co-occurring variables, the researcher can indicate whether change in one is accompanied by systematic change in the other. Examination of intercorrelations among study variables indicated statistically significant correlations between bereavement and each of four independent variables: primary appraisal, secondary appraisal, coping skill, and stigma. The results for each correlation are presented separately and summarized below as well as in Table 1. Table 1 Correlations for Independent, Dependent and Control Variables CBI TSD PSAM SSAM MSPSS CSES 1. TSD .277* 2. PSAM -.309* -.167 3. SSAM -.309* -.151 .602* 4. MSPSS -.039 .032 .379* .172* 5. CSES -.174* -.167* .494* .473* .585* 6. STOSASS .252* .095 -.196* -.221* .022 -.253 Note: N = 194; CBI = Core Bereavement Items; TSD = Time Since Death (in months); PSAM = Primary Stress Appraisal Measure; SSAM = Secondary Stress Appraisal Measure; CSES = Coping Self-Efficacy Scale; MSPSS = Multidimensional Scale of Perceived Social Support; STOSASS = Stigma of Suicide and Suicide Survivor Scale. * p < .05.