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Background: Despite severely burdened individuals, often being excluded from research studies on internet- and mobile-based interventions (IMIs), negative events (NEs) including suicidal thoughts and behaviors (STBs) can still occur during a trial. NEs require monitoring and adequate safety measures. However, study protocols frequently lack comprehensive descriptions of procedures for managing NEs., Aims: This study aimed to illustrate the assessment, monitoring, and procedures for addressing NEs in two studies on IMIs in adults and youth using case reports, to identify strengths and weaknesses of the NE management approaches, and to derive key learnings and recommendations., Methods: Two case reports were drawn from two distinct IMI studies. The first study, PSYCHOnlineTHERAPY, evaluates the combination of an IMI with on-site psychotherapy for anxiety and depressive disorders in adults (adult blended study). The second study evaluates a standalone, therapist-guided IMI for post-traumatic stress disorder (PTSD) in youth (youth standalone study). Potential NEs were predefined depending on the study sample. The case studies thoroughly document the systematic recording and ongoing monitoring of NEs through self-report and observer-based assessments during the interventions. The cases illustrate a variety of NE management strategies, including automated and personalized approaches, adapted to the specific nature and severity of the NEs. The NE management approaches are visualized using decision trees., Results: In the adult blended case study, online questionnaires detected STBs and triggered automated support information. As on-site therapy had already ended, a telephone consultation session allowed for the identification and discussion of the heightened intensity of suicidal thoughts, along with the development of specific additional help options. In the youth standalone case study, heightened tension in an adolescent with PTSD during trauma processing could be addressed in a telephone therapeutic session focusing on resource activation and emotion regulation. The referral to on-site treatment was supported. Overall, advantages of the NE management included automated procedures, multimodal assessment of a wide range of NEs, and standardized procedures tailored to different severity levels. Weaknesses included the use of single-item assessments for STBs and lack of procedures in case of deterioration or nonresponse to treatment., Conclusion: This study provides practical insights and derives key learnings and recommendations regarding the management of NEs in different IMI contexts for both adults and youth., Competing Interests: ACZ reports having received fees for lectures or workshops and for expert videos for an internet-based intervention for sexual dysfunction. IT reports having received fees for lectures/workshops in the e-mental-health context from training institutes and congresses for psychotherapists, but outside the submitted work. She was the project lead for the research project ImpleMentAll (funded by the European Commission) at GET.ON which aimed to investigate the effectiveness of tailored implementation strategies compared to implementation as usual for guided IMIs (11/2017–03/2021). HB received consultancy fees, reimbursement of congress attendance, and travel costs as well as payments for lectures from Psychotherapy and Psychiatry Associations as well as Psychotherapy Training Institutes in the context of E-Mental-Health topics. He has been the beneficiary of study support (third-party funding) from several public funding organizations. LBS received personal fees from Psychotherapy and Psychiatry Associations and Psychotherapy Training Institutes, including reimbursement of travel costs and payment for lectures in the context of E-Mental-Health but outside the submitted work. ChS, CeS, TS, and LS have no conflicts of interest to declare., (© 2024 The Authors.)

Background: Depression is highly prevalent among individuals with chronic back pain. Internet-based interventions can be effective in treating and preventing depression in this patient group, but it is unclear who benefits most from this intervention format., Method: In an analysis of two randomized trials ( N  = 504), we explored ways to predict heterogeneous treatment effects of an Internet-based depression intervention for patients with chronic back pain. Univariate treatment-moderator interactions were explored in a first step. Multilevel model-based recursive partitioning was then applied to develop a decision tree model predicting individualized treatment benefits., Results: The average effect on depressive symptoms was d  = -0.43 (95 % CI: -0.68 to -0.17; 9 weeks; PHQ-9). Using univariate models, only back pain medication intake was detected as an effect moderator, predicting higher effects. More complex interactions were found using recursive partitioning, resulting in a final decision tree with six terminal nodes. The model explained a large amount of variation (bootstrap-bias-corrected R 2  = 45 %), with predicted subgroup-conditional effects ranging from d i  = 0.24 to -1.31. External validation in a pilot trial among patients on sick leave ( N  = 76; R 2  = 33 %) pointed to the transportability of the model., Conclusions: The studied intervention is effective in reducing depressive symptoms, but not among all chronic back pain patients. Predictions of the multivariate tree learning model suggest a pattern in which patients with moderate depression and relatively low pain self-efficacy benefit most, while no benefits arise when patients' self-efficacy is already high. If corroborated in further studies, the developed tree algorithm could serve as a practical decision-making tool., Competing Interests: DDE reports to have received consultancy fees or served in the scientific advisory board from several companies such as Novartis, Sanofi, Lantern, Schön Kliniken, Minddistrict, and German health insurance companies (BARMER, Techniker Krankenkasse). DDE and MH are stakeholders of the Institute for Health Trainings Online (GET.ON/HelloBetter), which aims to implement scientific findings related to digital health interventions into routine care. HB reports to have received consultancy fees, fees for lectures or workshops from chambers of psychotherapists and training institutes for psychotherapists and license fees for an Internet intervention., (© 2023 The Authors.)

Background and Objective: Pain spans a broad spectrum of diseases and types that are highly prevalent and cause substantial disease burden for individuals and society. Up to 40% of people affected by pain receive no or inadequate treatment. Providing a scalable, time-, and location-independent way for pain diagnostic, management, prevention and treatment mobile health applications (MHA) might be a promising approach to improve health care for pain. However, the commercial app market is rapidly growing and unregulated, resulting in an opaque market. Studies investigating the content, privacy and security features, quality and scientific evidence of the available apps are highly needed, to guide patients and clinicians to high quality MHA.Contributing to this challenge, the present study investigates the content, quality, and privacy features of pain apps available in the European app stores., Methods: An automated search engine was used to identify pain apps in the European Google Play and Apple App store. Pain apps were screened and checked for systematic criteria (pain-relatedness, functionality, availability, independent usability, English or German). Content, quality and privacy features were assessed by two independent reviewers using the German Mobile Application Rating Scale (MARS-G). The MARS-G assesses quality on four objectives (engagement, functionality, aesthetics, information quality) and two subjective scales (perceived impact, subjective quality)., Results: Out of 1034 identified pain apps 218 were included. Pain apps covered eight different pain types. Content included basic information, advice, assessment and tracking, and stand-alone interventions. The overall quality of the pain apps was average M = 3.13 (SD = 0.56, min = 1, max = 4.69). The effectiveness of less than 1% of the included pain apps was evaluated in a randomized controlled trial. Major problems with data privacy were present: 59% provided no imprint, 70% had no visible privacy policy., Conclusion: A multitude of pain apps is available. Most MHA lack scientific evaluation and have serious privacy issues, posing a potential threat to users. Further research on evidence and improvements privacy and security are needed. Overall, the potential of pain apps is not exploited., Competing Interests: EMM, YT, LS, HB developed and run the German Mobile Health App Database project. The MHAD is a self-funded project at Ulm University with no commercial interests. HB, LS and EMM received payments for talks and workshops in the context of e-mental-health. All other authors declare no conflict of interest., (© 2021 The Authors. Published by Elsevier B.V.)