The Distress Thermometer (DT) is a subjective measure developed by the NCCN.2 The DT provides a visual representation of a thermometer and asks patients to rate their level of distress over the past week with 0 indicating no distress and 10 indicating extreme distress. A distress rating of 4 or higher is clinically significant.4,6 Distress may be categorized into 3 levels of severity: mild distress (< 4), moderate distress (4-7), or severe distress (8-10). The DT has been found to have good face validity, sensitivity and specificity, and is user-friendly.2,6,7,13
The measurement additionally lists 39 problems nested within 5 domains: practical, family, emotional, spiritual/religious, and physical. Patients may endorse listed items under each problem domain by indicating yes or no. Endorsement of various items are intended to provide more detailed information about sources of distress. Due to the predominantly male and mostly older population included in this study the ability to have children measure was removed from the family problem domain.
SI was assessed in 2 ways. First, by patients’ self-report through item-9 of the Patient Health Questionnaire-9 (PHQ-9).14 Item-9 asks “over the last 2 weeks, how often have you been bothered by thoughts that you would be better off dead or of hurting yourself in some way?” Responses range from 0 (not at all) to 3 (nearly every day).14 Responses > 0 were considered a positive screen for SI. The process of administering the PHQ-9 item-9 is part of a national VA directive for standardizing assessment of suicide risk (Steve Young, personal communication, May 23, 2018). The PHQ-9 has been found to have good construct validity when used with both medical samples and the general population along with good internal and test-retest reliability.14,15 Second, all veterans also were asked directly about SI during clinical interview, the results of which were documented in health records using a standardized format for risk assessment.
Procedure
Participants were a sample of veterans who were referred for psychology-oncology services. The NCCN DT and Problems List were administered prior to the start of clinical interviews, which followed a checklist and included standardized assessments of SI and history of a suicide attempt(s). A licensed clinical psychologist or a postdoctoral resident conducted these assessments under the supervision of a licensed psychologist. Data gathered during the clinical interview and from the DT and problems list were documented in health records, which were retrospectively reviewed for relevant information (eg, cancer diagnosis, SI). Therefore, informed consent was waived. This study was approved by the JAHVH Institutional Review Board.
Analysis
Data were analyzed using SPSS Version 25. Data analysis proceeded in 3 steps. First, descriptive statistics included the demographic and clinical factors present in the current sample. Difference between those with and without suicidal ideation were compared using F-statistic for continuous variables and χ2 analyses for categorical variables. Second, to examine relationships between each DT problem domain and SI, χ2 analyses were conducted. Third, DT problem domains that had a significant relationship with SI were entered in a logistic regression. This analysis determined which items, if any, from a DT problem domain predicted SI. In the logistic regression model, history of suicide attempts was entered into the first block, as history of suicide attempts is a well-established risk factor for subsequent suicidal ideation. In the second block, other variables that were significantly related to suicidal ideation in the second step of analyses were included. Before interpreting the results of the logistic regression, model fit was tested using the Hosmer-Lemeshow test. Significance of each individual predictor variable in the model is reported using the Wald χ2 statistic; each Wald statistic is compared with a χ2 distribution with 1 degree of freedom (df). Results of logistic regression models also provide information about the effect of each predictor variable in the regression equation (beta weight), odds a veteran who endorsed each predictor variable in the model would also endorse SI (as indicated by the odds ratio), and an estimate of the amount of variance accounted for by each predictor variable (using Nagelkerke’s pseudo R2, which ranges in value from 0 to 1 with higher values indicating more variance explained). For all analyses, P value of .05 (2-tailed) was used for statistical significance.
