• 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2020-03
  • 2020-07
  • 2020-08
  • br The Demoralization Scale DS is a


    The Demoralization Scale (DS) is a 24-item self-report measure based on the conceptual framework developed by Kissane, Clarke and col-leagues [11,19]. The scale assesses feelings of disheartenment and being trapped, a sense of failure and reduced self-worth, regret, dys-phoria, and the loss of meaning and purpose over the past two weeks. Total scores may range from to 96. Moderate to high demoralization was defined by a cut-off ≥30 [14].
    We assessed depression using the Patient Health Questionnaire-9 (PHQ-9). The PHQ-9 is a self-report measure of depression according to DSM-IV/V criteria [20]. Total scores may range from to 27. Scores ≥10 indicate at least moderate depression.
    We assessed physical symptom burden with the self-report Memorial Symptom Assessment Scale – Short Form (MSAS-SF [21];). The scale as-sesses the occurrence of 28 common physical symptoms in patients with cancer over the past week. The symptom count refers to the total number of symptoms reported and may range from to 28.
    2.3. Statistical analysis
    We used SPSS (Statistical Package for the Social Sciences) version 19 (IBM SPSS for Windows, IBM Corp., 2010) for all analyses. We calculated descriptive statistics including means, standard deviations, and frequencies for demographic and disease-related characteristics, physical symptom count, attachment security, demoralization, and depression. We calculated Pearson correlations between predictor and dependent variables to study bivariate Compound48 / 80 correlations. Point-biserial cor-relation was used to analyze the association between dichotomous and
    S. Vehling et al.
    metric variables. To analyze the contribution of attachment security to demoralization, we conducted a multiple linear regression analysis that controlled for age, gender, and physical symptom count (model 1a). All variables in the regression analyses were standardized in order to compare the relative importance of predictors.
    To test whether attachment security moderated the association of physical symptom count and demoralization, we added an interaction term as a predictor to the regression model in a subsequent step (model 1b). The interaction term was calculated by multiplying the standar-dized values of physical symptom count and attachment security. We visualized the interaction in a simple slope plot showing the predicted association of symptom count and demoralization at low and high le-vels of attachment security, respectively (a low level referred to one standard deviation below the mean, a high level referred to one stan-dard deviation above the mean [22]).
    We repeated this Compound48 / 80 analysis for attachment anxiety (models 3a and 3b) and attachment avoidance (models 4a and 4b). Finally, to explore dif-ferences in the contribution of attachment security to demoralization and depression, we repeated the analysis process with depression as the dependent variable.
    3. Results
    3.1. Patient characteristics and frequency of demoralization and depression
    Out of 2601 eligible and approached patients, 382 (15%) completed baseline questionnaires relevant to the analyses in the present study (see [16] for flow diagram). Table 1 presents demographic and disease-related characteristics of the sample as well as means and standard deviations for physical symptom count, attachment security, demor-alization and depression. The mean total demoralization score was 25.9 (SD = 14.2). Clinically relevant demoralization was present in 35% of the patients and clinically relevant depression was present in 26% of the patients. Nineteen percent of all patients were demoralized but not depressed and 16% had high levels of demoralization (scores ≥30) and
    Table 1
    Demographic and disease related sample characteristics and descriptive statis-tics for study variables (N = 382).
    Variable N %
    depression (scores ≥10, online supplement Table 5).
    3.2. Bivariate correlations among predictors and dependent variables
    Table 2 presents associations among the predictor variables age, gender, physical symptom count, and attachment security and with dependent variables demoralization and depression. There was a moderate negative association between attachment security and de-moralization (r = −0.57, p < .001) and greater than that with de-pression (r = −0.18, p < .05). Correlations among predictors were weak, indicating collinearity was likely not an issue for model specifi-cation.
    3.3. Contribution of attachment security to demoralization and depression
    Table 3 shows the results of the multiple linear regression models used to analyze the relationships between attachment security, de-moralization, and depression. Model 1a indicated that attachment se-curity was negatively associated with demoralization when age, gender and physical symptoms were controlled (β = −0.54, 95% CI: −0.62 to −0.46). Female gender was negatively associated with demoralization, while the number of physical symptoms was positively associated with demoralization. Testing for the hypothesized interaction of attachment security and physical symptoms (model 1b) revealed that attachment security was a significant moderator of the association between phy-sical symptoms and demoralization (β = −0.10, 95% CI: −0.18 to −0.03). The main effects of gender, symptom burden, and attachment security remained in RNA replicase model, showing a significant contribution under control of the interaction term. Fig. 1 illustrates the moderator effect by showing the association of physical symptoms and demor-alization for high and low levels of attachment security.