The untold story of late effects: a qualitative analysis of breast cancer survivors' emotional responses to late effects.

PURPOSE: Breast cancer survivors are at increased risk of adverse outcomes, called late effects, years after the completion of active treatment. Late effects can significantly impair physical functioning. The current study aimed to explore breast cancer survivors' experiences of late effects, their emotional responses to existing or potential late effects and their perceived impact. METHODS: A total of 36 women treated for breast cancer in the last 10 years participated in semi-structured telephone interviews. Participant views were sought with respect to knowledge, experience, and perceived longer-term risk. A thematic analysis was conducted. RESULTS: Four themes emerged from the data: (1) late effects awareness, (2) framing and coping, (3) uncertainty and (4) management. There was a range of emotional responses to late effects; however, many participants reported being unaware of their risk of late effects. Participants conceptualised late effects as any long-term effect of treatment regardless of the time of onset. Women reported living with constant uncertainty and feared cancer recurrence. Many were focused on managing long-term treatment side effects, rather than late effects. CONCLUSION: Many women undergo treatment and remain unaware of associated late effect risks. National guidelines recommend patients be informed about late effects; however, the results of this study suggest a gap between policy and practice. Evidence-based interventions are needed to equip women with strategies to physically and emotionally manage late effects.

Peering behind the mask: The roles of reactance and gender in the relationship between self-esteem and interpersonal problems.

OBJECTIVE: When a client feels a threat to their freedom or autonomy as a result of external feedback, they can act out and respond in maladaptive ways. This state-referred to as reactance-has potential ramifications on interpersonal functioning. However, the underlying factors exacerbating this response including self-esteem and gender are yet to be extensively explored in a clinical sample. The present study examined whether verbal and/or behavioural reactance mediate the relationship between self-esteem and interpersonal problems and if this mediational relationship differs between men and women. METHOD: Patients with personality dysfunction (N = 136) completed pretreatment assessments of reactance, self-esteem, and interpersonal problems, and a conditional process model using these constructs was tested. RESULTS: Findings indicated that the moderated mediation model was significant, pointing to behavioural reactance as a significant mediator in the association between self-esteem and interpersonal problems. Furthermore, the findings revealed that gender moderated the relationship between self-esteem and behavioural reactance, indicating that this association may apply specifically to men low in self-esteem. DISCUSSION: These results shed light on how behavioural reactance may be an important manifestation of low self-esteem for men and a key contributor to their interpersonal problems. The findings draw attention to the importance of considering different factors at play when working with reactant individuals in therapy.

Use of smartphone sensor data in detecting and predicting depression and anxiety in young people (12-25 years): A scoping review.

Digital phenotyping is a promising method for advancing scalable detection and prediction methods in mental health research and practice. However, little is known about how digital phenotyping data are used to make inferences about youth mental health. We conducted a scoping review of 35 studies to better understand how passive sensing (e.g., Global Positioning System, microphone etc) and electronic usage data (e.g., social media use, device activity etc) collected via smartphones are used in detecting and predicting depression and/or anxiety in young people between 12 and 25 years-of-age. GPS and/or Wifi association logs and accelerometers were the most used sensors, although a wide variety of low-level features were extracted and computed (e.g., transition frequency, time spent in specific locations, uniformity of movement). Mobility and sociability patterns were explored in more studies compared to other behaviours such as sleep, phone use, and circadian movement. Studies used machine learning, statistical regression, and correlation analyses to examine relationships between variables. Results were mixed, but machine learning indicated that models using feature combinations (e.g., mobility, sociability, and sleep features) were better able to predict and detect symptoms of youth anxiety and/or depression when compared to models using single features (e.g., transition frequency). There was inconsistent reporting of age, gender, attrition, and phone characteristics (e.g., operating system, models), and all studies were assessed to have moderate to high risk of bias. To increase translation potential for clinical practice, we recommend the development of a standardised reporting framework to improve transparency and replicability of methodology.

Protocol for a bandit-based response adaptive trial to evaluate the effectiveness of brief self-guided digital interventions for reducing psychological distress in university students: the Vibe Up study.

INTRODUCTION: Meta-analytical evidence confirms a range of interventions, including mindfulness, physical activity and sleep hygiene, can reduce psychological distress in university students. However, it is unclear which intervention is most effective. Artificial intelligence (AI)-driven adaptive trials may be an efficient method to determine what works best and for whom. The primary purpose of the study is to rank the effectiveness of mindfulness, physical activity, sleep hygiene and an active control on reducing distress, using a multiarm contextual bandit-based AI-adaptive trial method. Furthermore, the study will explore which interventions have the largest effect for students with different levels of baseline distress severity. METHODS AND ANALYSIS: The Vibe Up study is a pragmatically oriented, decentralised AI-adaptive group sequential randomised controlled trial comparing the effectiveness of one of three brief, 2-week digital self-guided interventions (mindfulness, physical activity or sleep hygiene) or active control (ecological momentary assessment) in reducing self-reported psychological distress in Australian university students. The adaptive trial methodology involves up to 12 sequential mini-trials that allow for the optimisation of allocation ratios. The primary outcome is change in psychological distress (Depression, Anxiety and Stress Scale, 21-item version, DASS-21 total score) from preintervention to postintervention. Secondary outcomes include change in physical activity, sleep quality and mindfulness from preintervention to postintervention. Planned contrasts will compare the four groups (ie, the three intervention and control) using self-reported psychological distress at prespecified time points for interim analyses. The study aims to determine the best performing intervention, as well as ranking of other interventions. ETHICS AND DISSEMINATION: Ethical approval was sought and obtained from the UNSW Sydney Human Research Ethics Committee (HREC A, HC200466). A trial protocol adhering to the requirements of the Guideline for Good Clinical Practice was prepared for and approved by the Sponsor, UNSW Sydney (Protocol number: HC200466_CTP). TRIAL REGISTRATION NUMBER: ACTRN12621001223820.