A Remotely Delivered, Personalized Music Therapy Pilot Intervention for Lonely Older Adults During the Covid-19 Pandemic.

Introduction: This study investigated a remotely delivered, therapist-facilitated, personalized music listening intervention for community-dwelling older adults experiencing loneliness during the Covid-19 pandemic. We assessed its feasibility and individuals' experiences of social connection and emotional well-being during the intervention. Methods: Ten cognitively unimpaired older adults who endorsed loneliness completed eight weekly sessions with a board-certified music therapist via Zoom. Participants were guided in developing two online personalized music playlists and were asked to listen to playlists for at least one hour daily. Feasibility metrics were attendance, accessibility, and compliance rates. Post-study interview responses were analyzed using a rapid qualitative methodology. Exploratory pre- and post-study measures of loneliness and other aspects of psychological well-being were obtained using validated questionnaires. Results: Ten participants (mean age 75.38 [65 to 85] years, 80% women) were enrolled from March to August 2021. Attendance and compliance rates were 100% and the accessibility rate was 90%. Most participants associated music with positive memories before the program and many reported that the intervention prompted them to reconnect with music or listen to music with greater intention. They cited increased connection from interacting with the music therapist and the music itself, as well as specific positive emotional impacts from integrating music into their daily lives. Median pre- to post-questionnaire measures of psychological function all changed in an improved direction. Discussion: Remotely delivered music therapy may be a promising intervention to promote regular music listening and socioemotional well-being in lonely older adults.

Perceived loneliness and social support in bipolar disorder: relation to suicidal ideation and attempts.

BACKGROUND: The suicide rate in bipolar disorder (BD) is among the highest across all psychiatric disorders. Identifying modifiable variables that relate to suicidal thoughts and behaviors (STBs) in BD may inform prevention strategies. Social connectedness is a modifiable variable found to relate to STBs in the general population, but differences exist across subgroups of the general population and findings specifically in BD have been equivocal. We aimed to clarify how perceived social connectedness relates to STBs in BD. METHOD: 146 adults (86 BD, 60 healthy controls) completed clinical interviews (Hamilton Depression Rating Scale; Structured Clinical Interview for DSM-5) and self-report measures of loneliness (UCLA Loneliness Scale) and social support (Interpersonal Support Evaluation List). Analyses explored differences in indicators of social connectedness (loneliness and social support) between BD participants and healthy controls, and explored relationships between STBs (lifetime suicide attempts and current suicidal ideation) and indicators of social connectedness in BD participants. RESULTS: BD participants reported significantly higher loneliness and lower social support than healthy controls. In BD participants, perceived social support was significantly related to both ever having attempted suicide and number of lifetime attempts. Interestingly, perceived loneliness, but not social support, was significantly associated with current suicidal ideation. CONCLUSIONS: Findings expand the evidence base supporting a relationship between perceived social connectedness and STBs in BD. They suggest that this modifiable variable could be a fruitful treatment target for preventing STBs in BD.

Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research.

Background: Mental illness remains a major global health challenge largely due to the absence of definitive biomarkers applicable to diagnostics and care processes. Although remote sensing technologies, embedded in devices such as smartphones and wearables, offer a promising avenue for improved mental health assessments, their clinical integration has been slow. Objective: This scoping review, following preferred reporting items for systematic reviews and meta-analyses guidelines, explores validation studies of remote sensing in clinical mental health populations, aiming to identify critical factors for clinical translation. Methods: Comprehensive searches were conducted in six databases. The analysis, using narrative synthesis, examined clinical and socio-demographic characteristics of the populations studied, sensing purposes, temporal considerations and reference mental health assessments used for validation. Results: The narrative synthesis of 50 included studies indicates that ten different sensor types have been studied for tracking and diagnosing mental illnesses, primarily focusing on physical activity and sleep patterns. There were many variations in the sensor methodologies used that may affect data quality and participant burden. Observation durations, and thus data resolution, varied by patient diagnosis. Currently, reference assessments predominantly rely on deficit focussed self-reports, and socio-demographic information is underreported, therefore representativeness of the general population is uncertain. Conclusion: To fully harness the potential of remote sensing in mental health, issues such as reliance on self-reported assessments, and lack of socio-demographic context pertaining to generalizability need to be addressed. Striking a balance between resolution, data quality, and participant burden whilst clearly reporting limitations, will ensure effective technology use. The scant reporting on participants' socio-demographic data suggests a knowledge gap in understanding the effectiveness of passive sensing techniques in disadvantaged populations.

The engagement problem: A review of engagement with digital mental health interventions and recommendations for a path forward.

Purpose of the review: Digital mental health interventions (DMHIs) are an effective and accessible means of addressing the unprecedented levels of mental illness worldwide. Currently, however, patient engagement with DMHIs in real-world settings is often insufficient to see clinical benefit. In order to realize the potential of DMHIs, there is a need to better understand what drives patient engagement. Recent findings: We discuss takeaways from the existing literature related to patient engagement with DMHIs and highlight gaps to be addressed through further research. Findings suggest that engagement is influenced by patient-, intervention- and systems-level factors. At the patient-level, variables such as sex, education, personality traits, race, ethnicity, age and symptom severity appear to be associated with engagement. At the intervention-level, integrating human support, gamification, financial incentives and persuasive technology features may improve engagement. Finally, although systems-level factors have not been widely explored, the existing evidence suggests that achieving engagement will require addressing organizational and social barriers and drawing on the field of implementation science. Summary: Future research clarifying the patient-, intervention- and systems-level factors that drive engagement will be essential. Additionally, to facilitate improved understanding of DMHI engagement, we propose the following: (a) widespread adoption of a minimum necessary 5-element engagement reporting framework; (b) broader application of alternative clinical trial designs; and (c) directed efforts to build upon an initial parsimonious conceptual model of DMHI engagement.