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Internet interventions, technologies and digital innovations for mental health and behavior change
JMIR Mental Health (JMH, ISSN 2368-7959) is a PubMed-indexed, peer-reviewed sister journal of JMIR, the leading eHealth journal by Impact Factor. (The projected inofficial impact factor for JMIR Mental Health is about 3.0)
JMIR Mental Health focusses on digital health and Internet interventions, technologies and electronic innovations (software and hardware) for mental health, addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations.
JMIR Mental Health publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
JMIR Mental Health features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs. The journal is indexed in PubMed, PubMed Central, and ESCI (Emerging Sources Citation Index).
JMIR Mental Health adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics.
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Background: The use of the internet has the potential to increase individuals' access to cognitive behavioral therapy (CBT) for insomnia at low cost. However, treatment preferences regarding internet-...
Background: The use of the internet has the potential to increase individuals' access to cognitive behavioral therapy (CBT) for insomnia at low cost. However, treatment preferences regarding internet-based computerized CBT for insomnia have not been fully examined. Objective: We conducted an anonymous online survey to evaluate treatment preferences for insomnia among patients with insomnia and individuals without insomnia. Methods: We developed an online survey to recruit a total of 600 participants living in the Kanto district in Japan. There were three subgroups: 200 medicated individuals with insomnia, 200 un-medicated individuals with insomnia, and 200 individuals without insomnia. The survey asked questions about the severity of the respondent's insomnia (using the Athens Insomnia Scale), the frequency of sleep medication use and the level of satisfaction with sleep medication use, the respondent's knowledge of cognitive behavior therapy (CBT), his or her preference for CBT for insomnia before drug therapy, preference for CBT versus drug therapy, and preference for internet CBT versus face-to-face CBT. Results: Of the 600 respondents, 47.7% indicated that they received CBT before drug therapy, and 57.2% preferred CBT for insomnia to drug therapy. In addition, 47% preferred internet CBT for insomnia to face-to-face CBT. Although the respondents with insomnia who were taking an insomnia medication had a relatively lower preference for internet CBT (40.5%), the respondents with insomnia who were not taking an insomnia medication had a relatively higher preference for internet CBT (55.5%). Conclusions: The results of our online survey suggest that approximately half of the people queried preferred CBT for insomnia to drug therapy, and half of the respondents preferred internet CBT for insomnia to face-to-face CBT.
Background: The use of mobile phone apps to monitor and deliver health-care guidance and interventions has received considerable recent attention, particularly with respect to behavioral disorders, st...
Background: The use of mobile phone apps to monitor and deliver health-care guidance and interventions has received considerable recent attention, particularly with respect to behavioral disorders, stress relief, negative emotional state, and poor mood. Unfortunately, there is little experience with the long-term effects of apps meant to impact mood. Objective: We aim to determine the effects of immediate and long term use of a guided meditation and mindfulness application on user’s long term emotional state. We describe an analysis of data obtained from a mobile phone app developed by Stop, Breathe & Think, Inc. (SBT) for achieving emotional wellness. Methods: The SBT app collects information on the emotional state of the user prior to and after engagement in one or several mediation and mindfulness activities provided by the app. We considered data on over 120,000 users of the app who collectively engaged in over 5.5 million activities during an approximate two-year time period. We focused our analysis on users who had at least 10 uses of the app over an average 6 months. We compared the long-term emotional-wellbeing of individuals with different emotional states at the time of their initial use of the app using mixed effects models. We also compared two different methods of classifying emotional state 1) expert defined classification and 2) empirically driven clustering. Results: We found that the long-term use of the app has a positive effect on baseline emotional state (2% increase per 10x sessions). We also found that individuals who are anxious or depressed, tend to have a more favorable long-term emotional transition after using the app for an extended period (odds ratio 3.2 and 6.2). Conclusions: Our analyses suggest that there is great potential for the delivery of stress reduction and emotional wellness maintenance through mobile devices. We consider future analyses and further development of meditation and mindfulness-based stress reduction apps in light of our findings.
Background: Sleep disturbances play an important role in everyday affect and vice versa. However, the causal day-to-day interaction between sleep and mood has not been thoroughly explored, partly due...
Background: Sleep disturbances play an important role in everyday affect and vice versa. However, the causal day-to-day interaction between sleep and mood has not been thoroughly explored, partly due to lack of daily assessment data. Mobile phones enable us to collect ecological momentary assessment data on a daily basis in a non-invasive manner. Objective: We investigate the relationship between self-reported daily mood and sleep quality. Methods: 208 adult participants were recruited to report mood and sleep patterns daily via their mobile phones for 6 consecutive weeks. Participants were recruited in four roughly equal groups: depressed and anxious, depressed only, anxious only, and healthy controls. The effect of daily mood on sleep quality and vice versa were assessed using mixed effects models, and propensity score matching Results: All methods showed a significant effect of sleep quality on mood and vice versa. However, within individuals, the effect of sleep quality on next-day mood was much larger than the effect of previous-day mood on sleep quality. We did not find these effects to be confounded by the participants’ past mood and sleep quality, or other variables such as stress, physical activity, and weather conditions. Conclusions: We found that daily sleep quality and mood are related, with the effect of sleep quality on mood being significantly larger than the reverse. Correcting for participant fixed effects dramatically affected results. Causal analysis suggests that environmental factors included in the study, and sleep and mood history do not mediate the relationship.
Background: Understanding the characteristics of commenters on mental health-related online discussion forums is vital for the development of effective psychological interventions in these communities...
Background: Understanding the characteristics of commenters on mental health-related online discussion forums is vital for the development of effective psychological interventions in these communities. Previous research has typically investigated these characteristics using surveys or textual analyses of online content. However, the way in which commenters interact with each other can also elucidate the characteristics of these commenters. Objective: The current study applied text-mining and network analyses to profile eating disorder-related (EDR) forum commenters in terms of the other forums to which they tended to contribute. Methods: The researchers identified all public EDR-forums with ≥1000 comments posted between March 2017 and February 2018 on a large online discussion platform (Reddit), compiled lists of commenters (N=14024) on each of these forums, and identified other forums in which the commenters posted. Text-mining and a network analytic approach enabled the identification of four subgroups of forums (e.g., pro-eating disorder, thinspiration). Then, for each subgroup, further network analyses were conducted using the EDR-forum commenter-overlap between 50 forums on which the subgroup’s commenters also posted. Results: The results focus on two subgroups – pro-eating disorder and thinspiration – and communities of commenters within both subgroups. Within the pro-eating disorder subgroup, five communities of commenters were detected who posted on forums regarding the body, eating and exercise, women and appearance, mental health, and self-harm. Regarding the thinspiration subgroup, 75% of the commenters had also posted on pornographic subreddits, and 29% on forums concerning the body and eating. These thinspiration communities overlapped, with over a third of the commenters posting on body and eating-related subreddits also contributing to pornographic forums. Conclusions: The findings provide insight into the characteristics (i.e., interests) of EDR-forum commenters, and have implications for the design of online interventions. With the publicly available data and code provided, researchers can easily reproduce the analyses, or conduct the same analyses with different groups of commenters.
Background: Medication adherence is critical to the effectiveness of psychopharmacologic therapy. Psychiatric disorders present special adherence considerations, notably an altered capacity for decisi...
Background: Medication adherence is critical to the effectiveness of psychopharmacologic therapy. Psychiatric disorders present special adherence considerations, notably an altered capacity for decision making and the increased street value of controlled substances. A wide range of interventions designed to improve adherence in mental health and substance use disorders have been studied; recently, many have incorporated information technology (e.g., smartphone apps, electronic pill dispensers, and telehealth). Many of the same intervention components have been used across different disorders. Further, many interventions incorporate multiple components, making it difficult to evaluate the effect of individual components in isolation. Objective: To conduct a systematic scoping review of the literature in order to develop a literature-driven, transdiagnostic taxonomic framework of technology-based medication adherence intervention and measurement components used in mental health and substance use disorders. Methods: This review was conducted based on a published protocol (PROSPERO: CRD42018067902) in accordance with the PRISMA systematic review guidelines. We searched 7 electronic databases: MEDLINE, EMBASE, PsycINFO, The Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, Engineering Village, and ClinicalTrials.gov from January 2000 to September 2018. Two reviewers independently conducted title and abstract screens, full-text screens, and data extraction. We included all studies which evaluate populations or individuals with a mental health or substance use disorder, and which contain at least one technology-delivered component (e.g., website, smartphone app, biosensor, algorithm) designed to improve medication adherence or the measurement thereof. Given the wide variety of studied interventions, populations, and outcomes, we did not conduct a risk of bias assessment or quantitative meta-analysis. We developed a taxonomic framework for intervention classification and applied it to multi-component interventions across mental health disorders. Results: The initial search identified 19,280 results - following duplicate removal and two-stage screening, 128 included studies remained (Cohen’s kappa: 0.8, 0.72-0.87). Major intervention component categories include reminders, support messages, social support engagement, care team contact capabilities, data feedback, psychoeducation, adherence-based psychotherapy, remote care delivery, secure medication storage, and contingency management. Adherence measurement components include daily self-reports, remote direct visualization, fully-automated computer vision algorithms, biosensors, smart pill bottles, ingestible sensors, pill counts, and utilization measures. Intervention modalities included short message service (SMS), smartphone apps, websites, and interactive voice response (IVR). We provide graphical representations of intervention component categories and an element-wise breakdown of multicomponent interventions. Conclusions: Many technology-based medication adherence and monitoring interventions have been studied across psychiatric disease contexts. Interventions that are useful in one psychiatric disorder may be useful in other disorders, and further research is necessary to elucidate the specific effects of individual intervention components. Our framework is directly developed from the substance use disorder and mental health treatment literature, and allows for transdiagnostic comparisons and an organized conceptual mapping of interventions.
Background: Recent research has highlighted the “naturalistic uptake challenge” as a key barrier that limits the impact of technologies designed to support mental health interventions. While there...
Background: Recent research has highlighted the “naturalistic uptake challenge” as a key barrier that limits the impact of technologies designed to support mental health interventions. While there is increasing evidence regarding the efficacy of computerised interventions, as demonstrated through randomised controlled trials (RCTs), there is also increasing evidence that technologies are not succeeding as expected when deployed in real-world settings. Objective: This paper describes the results of a naturalistic, or uncontrolled, deployment of Pesky gNATs, a computer game designed to support Cognitive Behavioural Therapy (CBT) interventions for young people experiencing anxiety or low mood. The game is intended for use in face-to-face clinical sessions involving one therapist and young person. The design draws on several key principles in developmental and clinical psychology and in human computer interaction, with the aim of making CBT more accessible and engaging for young people. Methods: Pesky gNATs has been made available to mental health professionals worldwide through a not-for-profit organisation. After one year of use, we collected usage and user experience data from therapists who have used the game through an online survey and follow-up semi-structured interviews. The data collection addressed the expectations and experiences of both therapists and young people and also sought opinions on key themes including the flexibility of the technology and attitudes towards user-generated versus automated adaptations in future versions. We used thematic analysis across survey and interviews to identify key themes in the data. Results: 21 therapists who used the game with a total of 95 children completed the online survey. Five therapists participated in the follow-up interview. Confirming previous assessments, data suggests that the game can be helpful in delivering therapy and that the young people generally liked the approach. However, therapists shared diverse opinions regarding the young people for whom they deem the game appropriate. The following three themes were identified: 1) stages of use; 2) impact on the delivery of therapy; 3) further developments. We discuss therapists' reflections on the game with regard to their work practices and consider the question of customisation, including the delicate balance of adaptable interaction versus the need for fidelity to a therapeutic model. Conclusions: This research provides further evidence that therapeutic games can be helpful in the delivery of therapy in real intervention settings. However, therapists’ autonomy and decisions on when, with who and how to use technology varies strongly. This needs to be considered when designing technologies.