Background: Many mobile health (mHealth) apps for mental health have been made available in recent years. Although there is reason to be optimistic about their effect on improving health and increasing access to care, there is a call for more knowledge concerning how mHealth apps are used in practice. Objective: This study aimed to review the literature on how usability is being addressed and measured in mHealth interventions for mental health problems. Methods: We conducted a systematic literature review through a search for peer-reviewed studies published between 2001 and 2018 in the following electronic databases: EMBASE, CINAHL, PsycINFO, PubMed, and Web of Science. Two reviewers independently assessed all abstracts against the inclusion and exclusion criteria, following the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. Results: A total of 299 studies were initially identified based on the inclusion keywords. Following a review of the title, abstract, and full text, 42 studies were found that fulfilled the criteria, most of which evaluated usability with patients (n=29) and health care providers (n=11) as opposed to healthy users (n=8) and were directed at a wide variety of mental health problems (n=24). Half of the studies set out to evaluate usability (n=21), and the remainder focused on feasibility (n=10) or acceptability (n=10). Regarding the maturity of the evaluated systems, most were either prototypes or previously tested versions of the technology, and the studies included few accounts of sketching and participatory design processes. The most common reason referred to for developing mobile mental health apps was the availability of mobile devices to users, their popularity, and how people in general became accustomed to using them for various purposes. Conclusions: This study provides a detailed account of how evidence of usability of mHealth apps is gathered in the form of usability evaluations from the perspective of computer science and human-computer interaction, including how users feature in the evaluation, how the study objectives and outcomes are stated, which research methods and techniques are used, and what the notion of mobility features is for mHealth apps. Most studies described their methods as trials, gathered data from a small sample size, and carried out a summative evaluation using a single questionnaire, which indicates that usability evaluation was not the main focus. As many studies described using an adapted version of a standard usability questionnaire, there may be a need for developing a standardized mHealth usability questionnaire.

Wearable sensors measuring different parts of people's activity are a common technology nowadays. In research, data collected using these devices also draws attention. Nevertheless, datasets containing sensor data in the field of medicine are rare. Often, data is non-public and only results are published. This makes it hard for other researchers to reproduce and compare results or even collaborate. In this paper we present a unique dataset containing sensor data collected from patients suffering from depression. The dataset contains motor activity recordings of 23 unipolar and bipolar depressed patients and 32 healthy controls. For each patient we provide sensor data over several days of continuous measuring and also some demographic data. The severity of the patients' depressive state was labeled using ratings done by medical experts on the Montgomery-Asberg Depression Rating Scale (MADRS). In this respect, the here presented dataset can be useful to explore and Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored.

Prompt mental health care (PMHC) is a Norwegian initiative, inspired by the English ‘Improving Access to Psychological Therapy’ (IAPT), aimed to provide low-threshold access to primary care treatment for persons with symptoms of anxiety and depression. The objectives of the present study are to describe the PMHC service, to examine changes in symptoms of anxiety and depression following treatment and to identify predictors of change, using data from the 12 first pilot sites. A prospective cohort design was used. All participants were asked to complete questionnaires at baseline, before each treatment session and at the end of treatment. Effect sizes (ES) for pre-post changes and recovery rates were calculated based on the Patient Health Questionnaire and the Generalized Anxiety Disorder scale. Multiple imputation (MI) was used in order to handle missing data. We examined predictors through latent difference score models and reported the contribution of each predictor level in terms of ES. In total, N = 2512 clients received treatment at PMHC between October 2014 and December 2016, whereof 61% consented to participate. The changes from pre- to post-treatment were large for symptoms of both depression (ES = 1.1) and anxiety (ES = 1.0), with an MI-based reliable recovery rate of 58%. The reliable recovery rate comparable to IAPT based on last-observation-carried-forward was 48%. The strongest predictors for less improvement were having immigrant background (ES change depression − 0.27, ES change anxiety − 0.26), being out of work at baseline (ES change depression − 0.18, ES change anxiety − 0.35), taking antidepressants (ES change anxiety − 0.36) and reporting bullying as cause of problems (ES change depression − 0.29). Taking sleep medication did on the other hand predict more improvement (ES change depression 0.23, ES change anxiety 0.45). Results in terms of clinical outcomes were promising, compared to both the IAPT pilots and other benchmark samples. Though all groups of clients showed substantial improvements, having immigrant background, being out of work, taking antidepressant medication and reporting bullying as cause stood out as predictors of poorer treatment response. Altogether, PMHC was successfully implemented in Norway. Areas for improvement of the service are discussed.

Objective: Insomnia is a major health problem, and the need for effective and accessible treatment is urgent. The aim of the current study was to evaluate the short-term efficacy of an unguided Internet-based cognitive-behavioral treatment program for insomnia (CBTi), called SHUTi (Sleep Healthy Using the Internet). Methods: This study used a parallel arm randomized controlled trial in Norway. Participants were randomly allocated to the SHUTi condition or a Web-based patient education condition. Both groups were assessed before and after the nine-week intervention period (online sleep diaries and questionnaires). The SHUTi participants were reassessed in a six-month nonrandomized follow-up. Primary outcome measures were the Insomnia Severity Index (ISI) and the Bergen Insomnia Scale (BIS). Results: A total of 181 participants were included in the study; SHUTi condition (n = 95), patient education condition (n = 86). Intention-to-treat mixed-model repeated-measures analysis revealed that the SHUTi group had better short-term outcomes compared with the patient education group on most sleep measures. The SHUTi group showed a significant decrease on the primary outcomes, the ISI (d_between = –1.77, 95% CI = –2.23, –1.31) and the BIS (d_between = –1.00, 95% CI = –1.32, –.68). Improvements were maintained among the completing SHUTi participants at the six-month nonrandomized follow-up. However, dropout attrition was high. Conclusion: Unguided Internet-based CBTi produced significant short-term improvements in sleep in patients with chronic insomnia. This highlights the benefits of making Internet-delivered CBTi programs available as a standard first-line treatment option in public health services. Nevertheless, the rate of dropout attrition (participants not completing post-assessment) in this trial limits the generalizability of the findings.

Social anxiety disorder (SAD) is a common mental disorder with high persistence when untreated. As access to effective treatment is limited, guided internet-based cognitive behavioral therapy (ICBT) has been proposed as an effective alternative to face-to-face treatment. In this study, we examined the effectiveness of a 14-week therapist-guided ICBT program for patients with SAD undergoing routine care. From 2014 to 2017, 169 patients were included in the study, of which 145 started the treatment. The sample was all general practitioner-referred and had a lower educational level and higher rate of work absence compared to similar effectiveness studies. Regarding social anxiety symptoms, we identified significant within-group effect sizes (post-treatment: d = 1.00-1.10; six-month follow-up: d = 1.03-1.55). We also found significant effects on secondary depression symptoms (d = 0.67). Clinically significant improvement was reported by 66.2% of the participants, and 16.6% had a significant deterioration. Clinical implications of the current study are that guided ICBT for SAD is an effective treatment for the majority of the patients undergoing routine care. Future studies should explore interventions targeting non-responders and deteriorated patients.

Panic disorder is a common mental disorder. Guided Internet-based cognitive behavioural therapy (Guided Internet-based cognitive behaviour therapy (ICBT)) is a promising approach to reach more people in need of help. In the present effectiveness study, we investigated the outcome of guided ICBT for panic disorder after implementation in routine care. A total of 124 patients were included in the study, of which 114 started the treatment. Large within-group effect sizes were observed on the primary panic disorder symptoms (post-treatment: d = 1.24; 6-month follow-up: d = 1.39) and moderate and large effects on secondary panic disorder symptoms and depressive symptoms at post-treatment and follow-up (d = .55–1.13). More than half (56.1%) of the patients who started treatment recovered or improved at post-treatment. Among treatment takers (completed at least five of the nine modules), 69.9% recovered or improved. The effectiveness reported in the present trial is in line with previous effectiveness and efficacy trials of guided ICBT for panic disorder. This provides additional support for guided ICBT as a treatment alternative in routine care.