Longitudinal assessment of seasonal impacts and depression associations on circadian rhythm using multimodal wearable sensing

Background: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. Objective: This study aims to explore the associations between depression severity and wearable measured circadian rhythms while accounting for seasonal impacts. Methods: Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to two years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR Acrophase), and nonparametric features, such as the onset of the most active continuous 10- hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we employed three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable; (2) adding seasonality; and (3) adding an interaction term between season and the PHQ-8 score. Results: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (76.2% female, median age 48 years [IQR: 32-58]), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (β = -93.61, P Conclusions: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.</p

Assessing seasonal and weather effects on depression and physical activity using mobile health data

Seasonal and weather changes can significantly impact depression severity, yet findings remain inconsistent across populations. This study explored depression variations across the seasons and the interplays between weather changes, physical activity, and depression severity among 428 participants in a real-world longitudinal mobile health study. Clustering analysis identified four participant subgroups with distinct patterns of depression severity variations in one year. While one subgroup showed stable depression levels throughout the year, others peaked at various seasons. The subgroup with stable depression had older participants with lower baseline depression severity. Mediation analysis revealed temperature and day length significantly influenced depression severity, which in turn impacted physical activity levels indirectly. Notably, these indirect influences manifested differently or even oppositely across participants with varying responses to weather. These findings support the hypothesis of heterogeneity in individuals' seasonal depression variations and responses to weather, underscoring the necessity for personalized approaches in depression management and treatment.</p

Understanding the thoughts and preferences of older adults for technologies designed to detect feelings of loneliness: a qualitative study

Background: Loneliness is a negative emotional state which is common in later life. The accumulative effects of loneliness have significant impact on physical and mental health of older adults. Automatic methods for detection and prediction are an emerging field to support early identification of loneliness. Objectives: We aim to qualitatively explore the thoughts and preferences of people aged 65 and over regarding technologies to detect feelings of loneliness in later life. Methods: We conducted 60 semi-structured interviews with people aged 65 and over between September 2022 and August 2023. Data were analysed using a reflective thematic approach on NVIVO software. Results: Three themes were identified representing what older adults considered important in a system able to detect loneliness. 1) Interest and Control of Data, which was a priority for older adults; 2) Perceived Usefulness to Address Loneliness, which related to the importance of providing recommendations to reduce feelings of loneliness after detection; and 3) Personalisation as a Priority, which included the level of loneliness for which an alert was sent and selection of relevant individuals who would be sent a loneliness alert. Conclusion: Findings from this in-depth qualitative study provide important perspectives from people with lived-experience of loneliness on the context in which a sensor-based loneliness detection system would be most useful and acceptable to older adults. Future research will include such perspectives in the design of innovative technologies enabling the early detection of loneliness and access to timely interventions to tackle loneliness in later life.</p

Evaluation of carbon based interconnects for digital signalling in printed flexible electronics on sustainable substrates

Printed electronics using flexible substrates are an emerging area, allowing next generation electronics that can conform and flex with different surfaces, from human skin to in clothing. In the hybrid integration, or sea-of-rigids approach, conventional microchips are mounted onto (generally) plastic substrates such as polyethylene naphthalate (PEN), with (typically) printed silver tracks for interconnections between components. An ongoing research direction is to replace plastic substrates with biodegradable substrates, and to replace silver tracks with non-heavy metal-based tracks. While the substrates and tracks form only part of any overall system, replacing them is a step towards increased sustainability and helps to meet net-zero goals for printed electronic systems. Previously, several papers have investigated printed carbon tracks for lowfrequency analog sensing applications. This paper explores the feasibility of using printed carbon tracks on biodegradable substrates for high-frequency sensing applications such as digital signaling over a Serial-Peripheral Interface (SPI). We investigate the printability, thermal stability, and electrical conductivity of carbon ink screen-printed onto six commercially available sustainable and flexible substrates. This includes modeling the connection formed and testing with SPI communications over a range of clock frequencies.We explore multi-layer screen printing to reduce the electrical resistance of the carbon tracks enabling their use in high-frequency SPI communication. This method was evaluated successfully in a custom experimental setup composed of two digital electronic systems connected through a carbonbased flexible connector. Connectors made through two layers of carbon prints allowed short distance SPI communication at a clock frequency of 1 MHz. Connectors of three or more carbon prints allowed SPI communication at clock frequencies up to 16 MHz. The Natureflex™ substrate showed the best overall trade-off in printing versus electronic performance among the sustainable substrates. The results of this study provide guidelines for materials selection and device fabrication for printing onto emerging biodegradable substrates to be used effectively in digital electronic systems.</p

Historical nonsuicidal self-injury and current coping strategies: the role of emotion regulation

Supporting individuals to develop adaptive coping strategies is critical to improve health and wellbeing. A history of nonsuicidal self-harm (NSSI) is linked with increased risk of maladaptive coping strategies. We aimed to identify whether emotion regulation (ER) mediated the relationship between historical NSSI behaviours and coping strategy use in adults from the general population. Participants reported their lifetime frequency of NSSI; then they completed self-report measures of emotion regulation, maladaptive coping strategy use (behavioural disengagement, self-blame and substance use) and adaptive coping strategy use (active coping, instrumental support use and emotional support use). Regression analyses investigated relationships between historical NSSI and coping strategies, with mediation analysis testing for the mediating role of ER. A total of 303 individuals participated: 180 with a history of NSSI and 123 without. Results indicated that poor emotion regulation mediated the relationship between having a history of NSSI and the use of maladaptive coping strategies; however, there was no notable association between adaptive coping strategies and historical NSSI. These findings highlight the necessity for ER development in people with a history of NSSI and suggest important avenues for future research, including exploring the role of ER to support NSSI cessation.</p

Identifying and managing fraudulent participants: critical commentary from a qualitative study with older adults

We recently published findings from our qualitative study exploring the lived experiences of loneliness in later life to inform technology development (Rees et al., 2024). During recruitment for this study, we experienced the significant and emerging issue in qualitative research of fraudulent participants. This involved the same participant attempting to be interviewed multiple times to obtain monetary gain. By providing specific examples from our experience, we aim to raise awareness of this timely issue for the research community. We also present practical and actionable recommendations for the readership of this journal to address the methodological challenges of fraudulent participation in online qualitative interview studies.</p

Between sound and sleep: a perspective on Sonic Sleep Aids

Sleep disturbances are prevalent in the general population, coinciding with a surge in the availability and use of digital sleep aids. Among these, standalone audio-based tools, termed Sonic Sleep Aids (SSA), such as sleep music, ambient sounds, bedtime stories, and sleep skills (e.g. guided meditation, positive psychology techniques), have gained popularity. This perspective piece examines the phenomenon of SSA by discussing the existing evidence and highlighting the different levels of empirical support across SSA types. Music-based relaxation has demonstrated efficacy in improving sleep quality, whereas findings on ambient sounds (e.g. white, pink noise) are inconclusive. Empirical support for narrated content as a sleep aid remains limited. Guided practices like mindfulness and self-compassion show potential, yet further research is needed to support their effectiveness, particularly when limited to bedtime practice. In the broader context, the widespread use of app-based SSA raises questions about their alignment with sleep hygiene recommendations, which typically discourage bedtime screen use. This concern is compounded by a paucity of randomized controlled trials testing their effectiveness against well-matched controls, alongside the risk of increased dependency on technology and altered relationships with rest and introspection. Against these concerns, potential benefits include accessibility and reduced reliance on pharmacological aids. A research agenda is proposed to investigate the efficacy of digitally delivered SSA in naturalistic settings, their mechanisms of action, and their impact across different populations. Understanding these factors is crucial to determine whether SSA serve as beneficial tools or divert individuals from more effective, evidence-based approaches to sleep.</p

Understanding early treatment response in brief cognitive behavioural therapy for non-underweight eating disorders: a mixed methods study

Objective: Early change in eating disorder psychopathology is the most robust predictor of treatment outcomes in eating disorders. However, little is known about what predicts early change. Using mixed-methodology, this study explored predictors of early change in the first four sessions of 10-session cognitive behavioural therapy (CBT-T) for non-underweight eating disorders. Method: Phase 1: Interviews were conducted to explore CBT-T clinicians’ perspectives on predictors of early change. Phase 2: Robust multiple regressions were undertaken to examine whether any of five variables identified during interviews – diagnosis, wait time, therapeutic alliance, depression, and anxiety – were associated with early change in eating disorder psychopathology. Data were derived from outcome measures for service users (n = 107) receiving CBT-T in a community eating disorder service. Results: Phase 1: Eight themes were identified: attitudes to making change, diagnosis, external mitigating circumstances, therapeutic alliance, therapist confidence, pre-treatment variables, CBT-T format and therapeutic suitability. Phase 2: No significant associations were found between the five predictor variables (diagnosis type, wait time, baseline depression, baseline anxiety and therapeutic alliance) and early change in EDE-Q scores. These results have been certified as computationally reproducible by an independent statistician. Discussion: Qualitative findings identified several potential predictors of early change in eating disorder psychopathology in CBT-T, however quantitative data contradicted qualitative findings, finding no significant association for any of the tested variables. Further research is required to clarify theses conflicting findings and to quantitatively explore the additional predictors highlighted during qualitative analysis.</p

Feasibility of remote measurement in intensive longitudinal data collection for RA patients commencing a new treatment

ObjectivesThis paper aims to evaluate the feasibility and acceptability of intensive assessment of symptoms in Rheumatoid Arthritis patients starting a new biologic treatment.MethodsParticipant symptoms and experiences were collected six times a day for fourteen days, and once a day for sixteen days in a single cohort. Wearable devices were also given to participants to track sleep and physical activity. Qualitative interviews were conducted to provide feedback into the acceptability of methods. Recruitment and completion rates were used to test for feasibility. The mean and variability of data for each day were calculated to reflect on data quality. Qualitative interview data was analysed by deductive thematic analysis.ResultsOf the 110 patients approached, 27 (15.5%) could not be contacted and 12 (14.5%) were excluded due to meeting exclusion criteria. Of 71 contactable and eligible participants, 31 (43.7%) joined the study. The survey completion rate was 74.6% (1943/2604) for the first 14 days, ranging from 10.7% to 100%. Completion rates for days 15 to 30 ranged from 60 to 83%. Mean levels of severity of symptoms (pain, fatigue, joint stiffness) displayed a decrease after treatment, as expected. Qualitative interviews demonstrated that participants reported a positive experience, which was not overly burdensome. Surveys were described as quick and easy to complete, but repetitive for some participants.DiscussionRecruitment and completion rates were acceptable and comparable to similar studies in the field. Qualitative analysis showed largely positive reviews from participants with feedback mainly focusing on survey timings.</p