Clinical Psychology in Europe最新文献

Purpose: Adverse life events and neuroticism have been shown to be associated with health anxiety (HA), but their interaction has not been studied. This study aimed to examine the separate associations as well as the possible interaction effect of neuroticism and adverse life events with HA.

Method: Cross-sectional self-report data originated from a representative Danish population cohort (DanFunD) (N = 7,493, 18-72 years, 53% females). Primary measures were HA (Whiteley Index 6 revised), neuroticism (NEO personality Inventory Revised short form), and adverse life events (Cumulative Lifetime Adversity Measure, CLAM). The CLAM was split into illness/death related life events (IDE) and other adverse life events (OAE) to test the specificity of IDEs.

Results: Adjusted ordinal logistic regression models showed positive associations with HA for IDEs (OR = 1.05, CI [1.03, 1.08]), OAEs (OR = 1.05, CI [1.03, 1.07]) and neuroticism (OR = 1.08, CI [1.07, 1.09]). A Wald's test revealed no difference in association with HA for IDEs and OAEs (p = .82). Adjusted models showed an interaction effect for neuroticism*IDEs (OR = 1.002, CI [1.000, 1.004]), but not for neuroticism*OAEs (OR = 0.999, CI [0.996, 1.002]).

Conclusion: Associations with HA were found for both adverse life events and neuroticism. Size of association did not differ for IDEs and OAEs. Only IDEs interacted with neuroticism.

Background: Characterized by uncertainty and recurring periods of social isolation, the COVID-19 pandemic resulted in increases of loneliness and distress in young adults, such as university students. Despite the lifting of the last restrictions in Germany in April 2023, the state of mental health in vulnerable groups after the three-year global crisis remains to be investigated. Therefore, we aimed to assess university students' mental health after the pandemic.

Method: Between April and July 2023, N = 886 university students throughout Germany participated in a fully anonymous cross-sectional online survey. Psychological distress (BSI; Brief Symptom Inventory), loneliness (LS-SOEP; Loneliness Scale), and emotion regulation strategies (ERQ; Emotion Regulation Questionnaire) were assessed by standardized questionnaires, and mental health was compared to a survey of students in April 2020 (N = 1,062).

Results: Unexpectedly, we found higher levels of distress in 2023 than in 2020. Overall, R² _adj = 41% of variance in psychological distress was accounted for in a multiple linear regression, with loneliness emerging as the most important predictor. Additionally, emotion regulation, gender identity, and health behaviors such as keeping daily routines, sufficient sleep, and regular exercise were significant predictors. Analyses of variance (ANOVAs) revealed that students with past or present mental health conditions were significantly lonelier than those without.

Conclusion: These findings highlight the ongoing mental health challenges of university students in the aftermath of the COVID-19 pandemic, identifying non-binary and female students, as well as students with current or past mental health conditions as particularly lonely and distressed.

Background: Previous studies have documented that depression and hopelessness predict higher suicide risk in young people. However, the psychological mechanisms that may mediate these associations are unknown. The aim of this study was to analyze the effects of depression, hopelessness, and impulsivity on suicidal attempts and risk, and to explore the mediating role of impulsivity in these associations.

Method: A total of 1,645 young people participated with a mean age of 21.604 years (SD = 3.22) (68.8% female and 31.2% male). A sociodemographic form was applied to explore suicide attempts in the last year (SA), the Plutchik Suicide Risk (SR), Beck Hopelessness (BHS), Barratt Impulsivity (BIS), and Beck Depression Inventory (BDI) scales. Direct correlations were found among BHS, BDI, BIS, SA, and SR.

Results: The binary regression model showed that the variables BHS, BDI, and BIS explained between 33% and 49% of the variance of suicidal risk and 16% of the variance of suicide attempts. Structural equation analysis showed that impulsivity mediated the associations between depression, hopelessness, and suicidal risk, on the one hand, and mediated the associations between depression and suicide attempt, on the other hand, whose total direct and indirect effects were statistically significant.

Conclusion: The findings emphasize the importance of impulsivity as the mechanism influencing interactions between mood indicators and suicidal behavior in young populations.

Background: Non-suicidal self-injury (NSSI) is a major health problem. Functionally, it is related to affect instability and increased affective intensity. The role of negative emotions has already been extensively explored, only few studies have focused on positive emotions. The concept of dynamic complexity (DC) is particularly well suited to differentially analyze the dynamics of affect collected by ecological momentary assessment (EMA). This study examines DC of positive and negative emotions in individuals with and without NSSI history in an EMA setting.

Method: Participants from a clinical NSSI group (n = 28) and a comparable clinical non-NSSI control group (n = 33) completed the Positive and Negative Affect Schedule (PANAS) once a day between six to 37 days (M = 15.60, SD = 5.80). DC was calculated for the assessed time-series of daily affect. Additionally, we fitted a linear mixed model to predict positive and negative dynamic complexity with length of stay and group.

Results: Compared to controls, individuals with a history of NSSI showed significantly more positive affect and had significantly higher DC in affect in general. No significant difference for negative affect was found.

Conclusion: Our results suggest that it is important to assess dynamic emotional patterns and to analyze in detail the role of positive and negative affect in individuals with NSSI in order to better understand the complex interplay between the different emotional states and to be able to use it for diagnostic purposes and clinical interventions.

Background: Case formulations and treatment planning mostly rely on self-reports, observations, and third-party reports. We propose that these data sources can be complemented by idiographic networks of motive interactions, which are empirically derived from everyday life using the Experience Sampling Method (ESM). In these networks, positive edges represent concordance of motives whereas negative edges indicate discordance. Based on consistency theory, which states that discordance emerges when the activity of one motive (e.g., 'affiliation') is incompatible with the activity of another motive (e.g., 'autonomy'), we hypothesized that discordance would be associated with subclinical depressive symptoms.

Method: Fifty-one undergraduates completed a six-day ESM assessment period with 6 assessments of motive satisfaction per day. Based on the ESM data, idiographic networks of the seven most important motives per person were computed using mlVAR (https://doi.org/10.32614/CRAN.package.mlVAR). We extracted indices of motive dynamics from each person's network, namely the strength of negative edges compared to the overall network strength as well as the values of the single most negative and positive edges. These indices were then used to predict subclinical depressive symptoms, controlling for overall motive satisfaction.

Results: Discordant, conflicting motive relationships made up only 6% of network strengths, indicating high concordance overall. Neither conflict index predicted subclinical depressive symptoms but maximum concordance was associated with lower subclinical depressive symptoms. Motive satisfaction was a significant predictor across models.

Conclusion: The applicability and clinical utility of the motive network approach was promising. Insufficient variance due to a healthy sample and the small number of observations limit the interpretability of findings.

Background: Although evidence-based interventions for posttraumatic stress disorder (PTSD) are highly effective, on average about 20% of patients drop out of treatment. Despite considerable research investigating PTSD treatment dropout in randomized controlled trials (RCTs), findings in naturalistic settings remain sparse.

Objective: Therefore, the present study investigated the frequency and predictors of dropout in trauma-focused interventions for PTSD in routine clinical care.

Method: The sample included n = 195 adults with diagnosed PTSD, receiving trauma-focused, cognitive behavioral therapy in routine clinical care in three outpatient centers. We conducted a multiple logistic regression analysis with the following candidate predictors of dropout: patient variables (e.g., basic sociodemographic status and specific clinical variables) as well as therapist's experience level and gender match between therapist and patient.

Results: Results showed a dropout rate of 15.38%. Age (higher dropout probability in younger patients) and living situation (living with parents predicted lower dropout probability compared to living alone) were significant predictors of dropout. Dropout was not significantly associated with the therapist's experience level and gender match.

Conclusions: In conclusion, routinely assessed baseline patient variables are associated with dropout. Ultimately, this may help to identify patients who need additional attention to keep them in therapy.

Background: Grief reactions of relatives of palliative care patients are seldom addressed. Most interventions focus on Prolonged Grief Disorder (PGD) and not on its prevention. This is particularly relevant in palliative care, in which death is the result of a difficult period of a terminal illness, making caregivers particularly vulnerable to psychological distress. The purpose of the present exploratory trial is to test the efficacy of a selective intervention (Empower-Grief) for the initial problematic grief reactions and to study potential predictors of adherence and efficacy.

Method: This is an exploratory Randomized Controlled Trial (RCT) studying Empower-Grief compared with Treatment as Usual (TAU). Participants will be relatives or caregivers of palliative and oncological patients with initial indicators of risk of developing PGD and will be randomly allocated to Empower-Grief and TAU. Participants will be assessed prior, at the end and six months after the intervention. The primary outcome considered will be symptoms of PGD. The assessment includes measures of anxiety and depression, coping, attachment, psychological flexibility, posttraumatic growth, social support and therapeutic alliance.

Results: The trial is ongoing. Forty-four participants will be invited to participate.

Conclusion: This study addresses the need for the development of empirically grounded and feasible interventions aimed at dealing with initial problematic reactions in grief, exploring potential predictors and possible venues for personalizing intervention and understanding the mechanism through which these interventions operate.