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Background: Online psychological interventions like behavioural activation (BA) can be provided with or without human support. Unguided online interventions require no human contact and are therefore easier to implement on a large scale than guided interventions. However, effectiveness and adherence rates to these interventions are generally lower. One way to increase adherence to unguided online interventions is to offer automated motivational support. Objective: This pilot randomized controlled trial (RCT) examined whether adherence to unguided online BA for low mood could be improved by adding automated support in the form of smartphone-delivered personalized motivational messages or a motivational virtual coach. Methods: A three-arm pilot RCT (n = 106) was conducted that compared an online intervention delivered with automated motivational support by a virtual coach (n = 35), or by automated personalized messages on their smartphone (n = 35), to the same intervention without support (control condition; n = 36). The primary outcome was level of adherence, operationalized as (1) the number of webpages of the intervention visited, and (2) the number of mood ratings completed on the smartphone application, both retrieved from participants' logfiles. Secondary outcomes were satisfaction with the intervention (CSQ-I), usability (SUS) depression scores (HADS), and motivation for treatment (SMFL), measured through online questionnaires administered at baseline or after 4 weeks. Results: Adherence was moderate overall, with participants visiting on average 23 pages of 55 webpages and completing on average 50 of 84 requested mood ratings. No evidence for differences in adherence rates were observed between the intervention conditions and the control condition. Satisfaction with the intervention was moderate to high. Usability scores were below the desirable threshold of 68. Depression symptoms did not change significantly across all participants (p = .053). No significant changes in motivation were found over time or between groups. Conclusions: Adding automated support to unguided online BA for depression did not improve overall adherence. The limited effectiveness may reflect a misalignment between the motivational strategies and the needs of the target population, who reported mild symptoms and high intrinsic motivation. The findings highlight the need to further improve both the quality of automated support and the usability of online platforms. Future research should explore additional adherence-related factors and investigate how personalization can better address different symptom severities in unguided mental health interventions. Trial registration: International Clinical Trials Registry Platform: trialsearch.who.int/Trial2.aspx?TrialID=NL8110. © 2025 The Authors

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Objective The aim of this scoping review was to map and describe the technological tools reported in the literature that have been designed for care management in Alzheimer's disease, with a particular focus on supporting patients living with the condition, their families, caregivers, and healthcare professionals. Methods The review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. A comprehensive literature search was performed across multiple databases, including Scopus, PubMed, Web of Science, and CINAHL, focusing on studies addressing technological resources aimed at supporting the care and management of Alzheimer's disease. Results A total of 23 studies were included in the final analysis. The most frequently utilized technologies were mobile applications and wearable devices. The most identified functionalities included cognitive training, location tracking, task reminders, communication support, fall detection, and vital signs monitoring, often integrated into comprehensive solutions to enhance patient care and safety. Conclusion Overall, these technologies were designed to support both patients and caregivers. However, despite the clear benefits and innovative potential of these technologies, significant limitations remain, particularly the lack of empirical validation in real-world clinical settings and the need to ensure greater usability for older adults and individuals with cognitive impairments.