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Different women experience hormonal contraceptives differently, reporting side effects on their well-being that range from adverse to beneficial. Research on such causal effects of hormonal contraceptives on psychological outcomes struggles both to identify average causal effects and to capture potential heterogeneity in women’s treatment responses. In this study, we leveraged longitudinal data to improve the separation of causal effects of hormonal contraceptives from other sources of association (e.g., confounding, reverse causality, attrition). In this programmatic registered report (stage 1 protocol: https://osf.io/kj3h2; date of in-principle acceptance: 28/09/2023), we analyzed up to 14 waves of data from up to 5,232 women aged 16 to 50 (24,306 observations) who participated in the German PAIRFAM panel. To deal with confounding and to probe the robustness of findings, we implemented two analysis approaches: adjusted regression analysis and inverse probability of treatment weighting. We found no evidence for average treatment effects of hormonal contraceptives on depressiveness, life satisfaction, or self-esteem. Furthermore, we found relatively low heterogeneity in individual treatment effects on depressiveness, life satisfaction, and self-esteem. Nevertheless, we found initial evidence that interindividual differences were systematically related to individual treatment effects. In particular, women higher in neuroticism tended to experience more beneficial effects on depressiveness and on life satisfaction. Individual treatment effects did not predict women’s decisions about which contraceptive method to use in the long run. These findings contribute to our understanding of the effects of hormonal contraceptives in a naturalistic setting. Public health efforts should avoid overstating risks to well-being since media-driven "pill scares" may ultimately harm individuals, including vulnerable populations.

Liebe Alle, Frau Nyenhuis wird wahrscheinlich auch am Mittwoch, den 17.12.2025 noch abwesend sein. Die Fachaufsicht übernimmt Mirjana Ruhleder. Liebe Grüße Anna TBZ-Büro

Posttraumatic stress disorder (PTSD) is maintained by dysfunctional trauma-related appraisals. Cognitive Bias Modification for Appraisals (CBM-APP) aims to train patients to make more functional trauma-related appraisals and has been shown to reduce PTSD symptoms. However, little is known about how this training affects the functional interrelations among symptoms and cognitive appraisals. In this secondary analysis of a randomized controlled trial involving 77 adult patients diagnosed with PTSD (CBM-APP: n = 37; control training: n = 40), we applied cross-sectional network analysis to examine changes in the structure and centrality of associations among PTSD symptom clusters (re-experiencing, avoidance, negative cognition and mood, hyperarousal) and trauma-related cognitive measures. To capture multiple levels of cognitive processing, we included responses during a scenario task (reflective, idiosyncratic, spontaneous appraisals) and the Implicit Association Test (automatic self-associations). Four Gaussian Graphical Models were estimated (pre-/post-training × CBM-APP vs. control group). While overall network connectivity did not differ significantly across networks, descriptive patterns indicated that Alterations in Cognition and Mood emerged as the most central node in both groups at post-training assessment. Further, in the CBM-APP group, the centrality of implicit trauma-related associations decreased pre- to post-training, suggesting potential decoupling of automatic negative self-associations from symptom activation. Given the small sample and moderate network stability, findings are preliminary but suggest that CBM-APP may influence the relational structure of PTSD symptoms and cognitions, offering insight into putative mechanisms of cognitive therapeutic change.

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