ArticleJMIR human factors2018
Development of a Just-in-Time Adaptive mHealth Intervention for Insomnia: Usability Study.
Article in JMIR human factors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 44 citations in OpenAlex.
- Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review.Frontiers in digital health · 2025Pooled it
- Framework for the Design Engineering and Clinical Implementation and Evaluation of mHealth Apps for Sleep Disturbance: Systematic Review.Journal of medical Internet research · 2021Pooled it
- How are Consumer Sleep Technology Data Being Used to Deliver Behavioral Sleep Medicine Interventions? A Systematic Review.Behavioral sleep medicinePooled it
- Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture.JMIR mHealth and uHealth · 2024Trial
- The Effects of Objective Push-Type Sleep Feedback on Habitual Sleep Behavior and Momentary Symptoms in Daily Life: mHealth Intervention Trial Using a Health Care Internet of Things System.JMIR mHealth and uHealth · 2022Trial
- Reducing sleep medication via parallel delivery of clinical pharmacist-led deprescribing and clinician-supervised asynchronous CBT for insomnia: the SEDATIVE trial.Journal of behavioral medicine · 2026Article
- Review
- Continuous At-Home Monitoring of Nighttime Bed Behavior in Frontotemporal Dementia.Neurology open access · 2026Article
- Article
- Mobile Health (mHealth) for Chronic Low Back Pain Assessment: Design, Development, and Usability Evaluation.JOR spine · 2025Article
- Suitability of just-in-time adaptive intervention in post-COVID-19-related symptoms: A systematic scoping review.PLOS digital health · 2025Article
- Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Experience with the use of a digital sleep diary in symptom management by individuals with insomnia -a pilot mixed method study.Sleep medicine: X · 2023Article
- Article
- Reduction of Sleep Medications via a Combined Digital Insomnia and Pharmacist-Led Deprescribing Intervention: Protocol for a Feasibility Trial.JMIR research protocols · 2023Article
- Are Machine Learning Methods the Future for Smoking Cessation Apps?Sensors (Basel, Switzerland) · 2021Article
- Article
- Article
- Clinical Feasibility of a Just-in-Time Adaptive Intervention App (iREST) as a Behavioral Sleep Treatment in a Military Population: Feasibility Comparative Effectiveness Study.Journal of medical Internet research · 2018Article
- Wearable Devices: Current Status and Opportunities in Pain Assessment and Management.Digital biomarkersReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundHealthy sleep is a fundamental component of physical and brain health. Insomnia, however, is a prevalent sleep disorder that compromises functioning, productivity, and health. Therefore, developing efficient treatment delivery methods for insomnia can have significant societal and personal health impacts. Cognitive behavioral therapy for insomnia (CBTI) is the recommended first-line treatment of insomnia but access is currently limited for patients, since treatment must occur in specialty sleep clinics, which suffer from an insufficient number of trained clinicians. Smartphone-based interventions offer a promising means for improving the delivery of CBTI. Furthermore, novel features such as real-time monitoring and assessment, personalization, dynamic adaptations of the intervention, and context awareness can enhance treatment personalization and effectiveness, and reduce associated costs. Ultimately, this "Just in Time Adaptive Intervention" for insomnia-an intervention approach that is acceptable to patients and clinicians, and is based on mobile health (mHealth) platform and tools-can significantly improve patient access and clinician delivery of evidence-based insomnia treatments.
objectiveThis study aims to develop and assess the usability of a Just in Time Adaptive Intervention application platform called iREST ("interactive Resilience Enhancing Sleep Tactics") for use in behavioral insomnia interventions. iREST can be used by both patients and clinicians.
methodsThe development of iREST was based on the Iterative and Incremental Development software development model. Requirement analysis was based on the case study's description, workflow and needs, clinician inputs, and a previously conducted BBTI military study/implementation of the Just in Time Adaptive Intervention architecture. To evaluate the usability of the iREST mHealth tool, a pilot usability study was conducted. Additionally, this study explores the feasibility of using an off-the-shelf wearable device to supplement the subjective assessment of patient sleep patterns.
resultsThe iREST app was developed from the mobile logical architecture of Just in Time Adaptive Intervention. It consists of a cross-platform smartphone app, a clinician portal, and secure 2-way communications platform between the app and the portal. The usability study comprised 19 Active Duty Service Members and Veterans between the ages of 18 and 60. Descriptive statistics based on in-app questionnaires indicate that on average, 12 (mean 12.23, SD 8.96) unique devices accessed the clinician portal per day for more than two years, while the app was rated as "highly usable", achieving a mean System Usability Score score of 85.74 (SD 12.37), which translates to an adjective rating of "Excellent". The participants also gave high scores on "ease of use and learnability" with an average score of 4.33 (SD 0.65) on a scale of 1 to 5.
conclusionsiREST provides a feasible platform for the implementation of Just in Time Adaptive Intervention in mHealth-based and remote intervention settings. The system was rated highly usable and its cross-platformness made it readily implemented within the heavily segregated smartphone market. The use of wearables to track sleep is promising; yet the accuracy of this technology needs further improvement. Ultimately, iREST demonstrates that mHealth-based Just in Time Adaptive Intervention is not only feasible, but also works effectively.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.