Health Psychology and Behavioral Medicine最新文献

Background: No study has investigated the cancer-related fatigue (CRF) among Palestinian breast cancer survivors. Our purpose is to assess, compare, and correlate CRF in breast cancer survivors undergoing radiotherapy (RT) with study variables.

Methods: CRF in breast cancer survivors was assessed using Functional Assessment of Chronic Illness Therapy - Fatigue Scale (FACIT-F) (version 4). The sample consisted of 148 breast cancer survivors undergoing RT. Data was collected between 1 May 2021 and 1 September 2021. The means and standard deviations of the questionnaire using one-way ANOVA, and Pearson correlation coefficient were reported.

Results: Respondents ages ranged from 20 to >65 years old and was divided into four groups: (20-35, 36-50, 51-65, and >65 years, respectively). The total fatigue mean was 2.88 and the SD was 0.84, indicating an intermediate fatigue level among breast cancer survivors. Study survivors with higher education were more likely to be fatigued (F =7.68, P-value =0.001). Divorced survivors were more prone to fatigue compared to married survivors (F =5.83, P-value= 0.001). Finally, survivors who do not have children were more vulnerable to exhaustion compared to those with children (F =7.35, P-value =0.001). Also, younger survivors were more prone to fatigue, compared to older survivors (F =5.29, P-value = 0.002). Results also showed a positive relationship between each of the variables; the number of children (R =0.221, P-value =0.007), age (R =0.311, P-value =0.000), and duration of treatment (R =0.290, P-value =0.000), which means that the greater the number of children, the younger the age, or the longer the duration of treatment, the more fatigue is reported in breast cancer survivors.

Conclusions: Fatigue is frequently observed in breast cancer survivors undergoing RT. It can limit RT treatment continuity. Therefore, early detection of fatigue can help survivors adhere to RT treatment and achieve better clinical results.

Background: Many adults with type 1 (T1D) and type 2 diabetes (T2D) have inadequate sleep increasing their risk of hyperglycemia and developing complications. The objective was to identify psychosocial determinants of healthy sleep habits (HSH) among adults with T1D and T2D.

Methods: The two HSH were: avoiding screen use in bed and having sleep regularity. Adults (≥18 years) with T1D and T2D were invited to complete an anonymous online survey. The questionnaires were based on the Reasoned Action Approach and formative qualitative research previously conducted in 56 adults with T1D and T2D. Habit was included as an additional variable for screen use in bed.

Results: In total, 320 adults with diabetes (T1D: 39%; T2D: 61%) completed the questionnaires (screen use in bed: 174; sleep timing: 146). Close to 75% of participants reported screen use in bed and close to 90% reported sleep timing variability in the last month. Perceived behavioral control (PBC) to avoid screen use in bed (β = -0.4486, p < 0.0001), habit of using screens in bed (β = 0.4002; p < 0.0001), and age (β = -0.0202; p = 0.0086) were determinants of screen use in bed, and this model explained 71% of the variance. PBC for sleep regularity (β = -0.2909; p = 0.0004) and being female (β = 0.5057; p = 0.0069) were determinants of sleep timing variability, and this model explained 28% of the variance. The most important beliefs associated with each HSH were identified to obtain information to design targeted interventions.

Conclusions: Few adults with diabetes have HSH. Screen use in bed was strongly influenced by habit and the results suggest that both HSH are not easy to adopt among adults with diabetes. Younger adults with diabetes should be prioritized for screen use in bed, while females with diabetes should be prioritized for sleep timing variability. Adults with diabetes should have access to behavior change interventions to encourage them to adopt HSH.

Objective: The aim of this study was to determine the unique and shared contributions of various positive psychology constructs (gratitude, optimism, hope, self-compassion, self-efficacy, and emotion regulation) to wellbeing and distress outcomes in young people living with a diverse range of chronic health conditions.

Methods and measures: 169 Australians (84.0% female, mean age = 21.2) who reported living with a chronic physical condition completed a cross-sectional survey assessing wellbeing, distress, and each positive psychology variable. Two multiple regressions were used to determine the unique and shared contributions of the positive psychology variables to wellbeing and distress outcomes.

Results: When considered alongside symptom severity, the variables explained 53.4% and 38.1% of variance in distress and wellbeing, respectively. Only optimism and self-efficacy accounted for unique and significant variance in the model predicting wellbeing, accounting for 6.1% and 4.6% of unique variance, respectively. For the distress model, optimism, self-compassion, and emotion regulation each accounted for significant variance. When considered alongside other variables, hope and gratitude did not contribute to either model.

Conclusion: Findings suggest that individual positive psychology variables differentially contribute to wellbeing and distress outcomes in young people with chronic conditions. Optimism appears to account for unique variance in both outcomes, suggesting it may be a parsimonious target to promote complete mental health in this population.