Radically different
Background: Completion of homework, defined as therapeutic activities assigned between sessions to reinforce skills and promote behavior change, is strongly linked to therapy outcomes. Yet, homework compliance remains low, potentially due to outdated delivery methods such as paper or email. Mobile health technologies may improve engagement by digitizing therapy tasks and tracking progress. Yosa is a mobile health app designed to facilitate homework delivery and enhance engagement between sessions for patients in therapy. Objective: The primary aim of this study was to evaluate the perceived acceptability of Yosa among licensed therapists and individuals currently receiving therapy. A secondary aim was to examine whether key Technology Acceptance Model (TAM) constructs predicted attitudes toward and intention to use Yosa. Qualitative feedback was also collected to inform iterative development and future deployment. Methods: Two cross-sectional surveys were conducted: study 1 with licensed therapists (N=45) and study 2 with current therapy patients (N=96). Participants viewed video demonstrations of Yosa, learned about Yosa’s features, and rated the app on TAM constructs, including perceived usefulness, perceived ease of use, perceived risk, attitude toward, and intention to use Yosa, using 0‐100 scales. For most constructs, higher scores reflected more favorable evaluations, whereas lower perceived risk scores reflected more favorable evaluations. Descriptive statistics and 95% CIs were generated for each construct in both samples, with scores interpreted relative to the neutral midpoint (50). Multiple regression analyses were conducted to examine predictors of attitude and intention to use. Qualitative feedback from the surveys was analyzed thematically. Results: Therapists and patients reported generally favorable perceptions of Yosa across TAM domains. Among therapists and patients, ratings of the perceived usefulness of the homework feature, therapy journal, and overall app; perceived ease of use; attitudes toward Yosa; and intention to use were all above the midpoint. Perceived risk scores were mild to moderate in patients and moderate in therapists, respectively. Regression analyses indicated that perceived usefulness was a positive predictor of both attitude toward and intention to use Yosa across therapists and patients, while perceived risk was negatively associated with these outcomes in several models. Qualitative themes included requests for additional features, usability enhancements, and data privacy concerns. Conclusions: Therapists and patients reported generally favorable perceptions of Yosa after reviewing descriptions and video demonstrations of the platform, particularly in terms of usefulness and ease of use, supporting favorable perceptions of its potential acceptability as a digital tool for between-session therapy support. Qualitative feedback informed refinements aimed at reducing perceived risks and enhancing the intention to use.
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Background: Temporal fluctuations in distress and suicidal ideation across daily, weekly, and seasonal cycles may influence the use and effectiveness of digital suicide prevention tools. Understanding patterns of app engagement, perceived suffering, and affective expression can inform the design of proactive, personalized digital interventions, thereby impacting adherence and efficacy. Objective: This study aimed to examine temporal patterns of engagement with 2 core components of the suicide prevention app SERO (Suicide Prevention: a Uniform Effort, Resource-Oriented; BFH, Lucerne Psychiatry), specifically the safety plan and the PRISM-S (Pictorial Representation of Illness and Self-Measure—Suicidality) self-assessment, using 3 years of interaction log data, assessing variations across circadian, weekly, and seasonal cycles, and evaluating the sentiment of free-text responses submitted immediately after PRISM-S self-assessments. Methods: We analyzed anonymized interaction logs from the SERO app collected over 3 years (November 2022 to December 2025). Engagement metrics included the frequency of use of the safety planning functionality and PRISM-S self-assessment entries. Free-text responses provided after PRISM-S assessments were analyzed using automated sentiment classification. Temporal analyses examined variations by the hour of the day, day of the week, and season. One-way ANOVAs, post hoc tests, and Pearson correlations were used to examine patterns and associations between perceived suffering and sentiment. Results: A total of 1076 users engaged with the safety planning functionality of the SERO app, generating 3502 entries, with coping strategies and warning signs showing the highest mean interactions and personal beliefs the lowest. Separately, 1212 app users accessed the PRISM-S self-assessment, producing 2329 entries (mean distance 12.91, 95% CI 12.39‐13.42 cm), with most app users recording only 1 or 2 registrations. Safety planning engagement showed clear diurnal patterns, peaking in the afternoon (2 PM to 3 PM) and being lowest at night (midnight to 3 AM), whereas PRISM-S scores were stable across time. Sentiment analysis revealed predominantly negative affect (mean score of −0.41, SD 0.51, 95% CI −0.44 to −0.39), correlated with PRISM-S distance, and was most negative at night (specifically at 11 PM) and during the afternoon (2 PM to 5 PM). Seasonal effects were small but significant for PRISM-S, with the lowest perceived suffering in summer. Conclusions: Digital suicide prevention tools can support routine patterns of coping behavior, but periods of increased reported distress, particularly at night, may be underaddressed. Integrating automated sentiment analysis alongside self-assessments could potentially enable personalized, time-adaptive interventions that detect changes in emotional state and deliver timely, tailored support, thereby strengthening proactive engagement and resilience.
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Using publicly available 2024 VISUCHIR (Visualisation de la Chirurgie) benchmarking indicators, we performed a descriptive ecological comparison of national private-sector values and 4 early-adopter French private departments implementing the Betty Coaching perioperative digital pathway; early-adopter departments showed a directionally favorable, unadjusted profile for same-day discharge, mean length of stay, and VISUCHIR-reported readmission-evolution indicators, without causal inference.
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Background: Loneliness is a prevalent concern across the United Kingdom. While validated scales exist to quantify the severity of loneliness across populations, there remains a gap in understanding how loneliness manifests and is addressed within therapeutic practice. Given the associated stigma surrounding loneliness, practitioner perspectives offer crucial insights into how clients express loneliness within digital therapeutic environments. These insights can inform more nuanced conceptualizations of loneliness. Objective: This study aimed to gather the practitioners’ perspectives on loneliness within a digital therapeutic context and were defined as follows: (1) understand how practitioners identify loneliness concerns, (2) identify how loneliness is elicited in digital mental health interventions, and (3) identify co-occurring themes (such as grief, shame, and social disconnection) that signal loneliness concerns in client communications within digital therapeutic environments. Methods: Semistructured interviews were conducted with 9 practitioners. Participants included specialists in grief counseling, lesbian, gay, bisexual, transgender, and queer or questioning plus support; and digital mental health therapists. Interview transcripts were analyzed using thematic analysis, using an inductive, data-driven approach to allow themes to emerge from participant accounts rather than fitting data to preexisting theoretical frameworks. Results: The following four themes were identified: (1) Conceptualizing Loneliness: practitioners distinguished between social contact and meaningful connection; (2) Contextual Causes: loneliness emerged from life transitions, stigmatized identities, and resource reduction (eg, youth services closures and social support); (3) Expressions and Language: clients rarely expressed loneliness directly, instead using proxy terms, with disclosure patterns varying by age; and (4) Mental Health Co-occurrence: severe mental health conditions created bidirectional cycles of loneliness, exacerbated by symptoms of mental health difficulties. Practitioners reported that many clients experienced loneliness concerns, yet direct disclosure was absent across all participants’ experiences. Conclusions: Practitioners identified multiple stigmatizing experiences as contextual drivers of loneliness, particularly demonstrating how loneliness emerges not only from individual experiences but from broader patterns of social exclusion and marginalization. For therapeutic practice, these insights suggest that practitioners can use awareness of stigmatizing experiences as potential indicators when assessing loneliness risk. The presence of contextual patterns was consistent across practitioners’ experiences, providing a foundation for developing more targeted interventions to address both the emotional experience of loneliness and the underlying social drivers.
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Background: The demand for sleep interventions is high and steadily growing. Digital therapeutics (DTx) can help individuals improve their sleep remotely, over an extended period, and with less effort from medical professionals. Obstructive sleep apnea (OSA), one of the most prevalent and consequential sleep disorders, can be treated with health-supporting behavior changes, such as physical exercise and weight loss, and, therefore, acts as a promising application for DTx. Objective: The study aimed to analyze a digital intervention from both medical and technological perspectives by moving beyond clinical markers and exploring more deeply how the DTx application was used. This study aimed to propose a novel way in which association rules can function as an exploratory tool to analyze the sleep, behavior, and engagement of participants with the DTx application on a day-to-day level. Methods: A lifestyle intervention study (N=192) targeted at adults with mild-to-moderate OSA aimed to reduce their OSA severity using a DTx application and an exercise program over a study period of 12 weeks. The participants’ OSA severity was assessed through polysomnography at the beginning and at the end of the study period, and the participants tracked their sleep with a digital sleep diary and a smartwatch over the course of the entire study. The DTx application provided data on when and how the participants pursued the proposed lifestyle interventions. These heterogeneous data sources were combined into one multimodal dataset, which was explored through descriptive statistics. Ultimately, the data were turned into a transaction-based format, and association rules were derived using the Apriori algorithm. Results: Analyzing the participants’ interaction with the application revealed the lifestyle interventions they pursued and how their behavior and sleep patterns changed over time. The Apriori algorithm generated a set of association rules with lift and confidence scores that were significantly higher than those for the co-occurrence of items through random chance. The rules show co-occurrence of missions and items from the sleep diary, as well as items derived from the watch measurements. Conclusions: The study showed the richness of the various data sources provided by a digital intervention using wearables and how they can be used to get an in-depth understanding of the study. The generated association rules showed the presence of significant co-occurrences across the different data modalities and highlighted their effectiveness as an exploratory tool for multimodal health data.
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Background: Alcohol and tobacco use frequently co-occur and contribute significantly to the global burden of disease. Despite the well-established benefits of addressing both behaviors simultaneously, health care professionals often face substantial challenges in delivering integrated interventions, including limited time, training, and resources. Digital health interventions offer a promising avenue to directly support patients in reducing alcohol and tobacco use, while bypassing some of the barriers encountered in clinical settings. However, there is a lack of consensus on the key behavior change techniques (BCTs) that must be incorporated to ensure that interventions are evidence based and contextually appropriate, making them effective. Objective: The study aims to identify expert opinions on the most suitable and effective BCTs (reflecting both behavioral relevance and delivery feasibility) to be included in a 1-time, self-guided digital intervention intended to initiate behavior change and support alcohol reduction among people trying to quit smoking. Methods: We conducted a 2-round modified Delphi study with 14 panelists with expertise in behavioral science, alcohol and tobacco treatment, and digital interventions. Panelists rated 20 BCTs identified in a previous rapid review using the acceptability, practicability, effectiveness, affordability, safety, and equity (APEASE) criteria. BCTs were deemed “appropriate” if at least 70% (n=10) of panelists agreed on all criteria. Results: Six BCTs were identified as appropriate for implementation: goal setting, action planning (individualized change plan), action planning (reduction strategies), feedback on behavior, reattribution, and pros and cons. These BCTs were considered effective for promoting behavior change through structured planning and personalized strategies. The panel reached partial consensus on several BCTs, while 8 BCTs were deemed inappropriate for a 1-time, unsupervised digital intervention. Conclusions: The results of this study offer a consensus-based view, reflecting expert opinion on the perceived appropriateness and feasibility of the BCTs that should be included in a 1-time digital intervention to address co-occurring alcohol and tobacco use.
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In traditional human psychotherapy, the therapeutic alliance (TA) is regarded as a fundamental factor that describes the client-therapist relationship, mainly due to strong evidence demonstrating its impact on treatment outcomes regardless of theoretical orientation. More recently, advances in artificial intelligence (AI) and other technologies have led to the emergence of the concept of digital TA, used to characterize the relationship between clients and AI-based therapeutic systems. This approach replicates human dynamics but overlooks key differences between human therapists and digital agents. Prematurely translating the concept of TA into the digital context fails to address issues such as the sycophantic tendencies of current systems and the inherent limitations of algorithmic interaction. We propose the digital therapeutic nexus, a framework that recognizes these differences and provides a set of structured criteria for categorizing digital interactions into 3 progressive levels. This Viewpoint argues that only at the highest level can parallels be drawn to the human TA and stratifies the main risks associated with each nexus level. Transitioning from the concept of alliance to that of a nexus offers a more precise conceptual basis for describing and evaluating digital therapeutic relationships, with implications for research, design, and the ethical development of AI-based mental health interventions.
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