Just-in-time Adaptive Interventions Research Articles

Toward Tailoring Just-in-Time Adaptive Intervention Systems for Workplace Stress Reduction: Exploratory Analysis of Intervention Implementation.

Integrating stress-reduction interventions into the workplace may improve the health and well-being of employees, and there is an opportunity to leverage ubiquitous everyday work technologies to understand dynamic work contexts and facilitate stress reduction wherever work happens. Sensing-powered just-in-time adaptive intervention (JITAI) systems have the potential to adapt and deliver tailored interventions, but such adaptation requires a comprehensive analysis of contextual and individual-level variables that may influence intervention outcomes and be leveraged to drive the system's decision-making. This study aims to identify key tailoring variables that influence momentary engagement in digital stress reduction microinterventions to inform the design of similar JITAI systems. To inform the design of such dynamic adaptation, we analyzed data from the implementation and deployment of a system that incorporates passively sensed data across everyday work devices to send just-in-time stress reduction microinterventions in the workplace to 43 participants during a 4-week deployment. We evaluated 27 trait-based factors (ie, individual characteristics), state-based factors (ie, workplace contextual and behavioral signals and momentary stress), and intervention-related factors (ie, location and function) across 1585 system-initiated interventions. We built logistical regression models to identify the factors contributing to momentary engagement, the choice of interventions, the engagement given an intervention choice, the user rating of interventions engaged, and the stress reduction from the engagement. We found that women (odds ratio [OR] 0.41, 95% CI 0.21-0.77; P=.03), those with higher neuroticism (OR 0.57, 95% CI 0.39-0.81; P=.01), those with higher cognitive reappraisal skills (OR 0.69, 95% CI 0.52-0.91; P=.04), and those that chose calm interventions (OR 0.43, 95% CI 0.23-0.78; P=.03) were significantly less likely to experience stress reduction, while those with higher agreeableness (OR 1.73, 95% CI 1.10-2.76; P=.06) and those that chose prompt-based (OR 6.65, 95% CI 1.53-36.45; P=.06) or video-based (OR 5.62, 95% CI 1.12-34.10; P=.12) interventions were substantially more likely to experience stress reduction. We also found that work-related contextual signals such as higher meeting counts (OR 0.62, 95% CI 0.49-0.78; P<.001) and higher engagement skewness (OR 0.64, 95% CI 0.51-0.79; P<.001) were associated with a lower likelihood of engagement, indicating that state-based contextual factors such as being in a meeting or the time of the day may matter more for engagement than efficacy. In addition, a just-in-time intervention that was explicitly rescheduled to a later time was more likely to be engaged with (OR 1.77, 95% CI 1.32-2.38; P<.001). JITAI systems have the potential to integrate timely support into the workplace. On the basis of our findings, we recommend that individual, contextual, and content-based factors be incorporated into the system for tailoring as well as for monitoring ineffective engagements across subgroups and contexts.

Usability Testing of a Multi-Level Modeling Framework for Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health.

The JITAI is an intervention design to support health behavior change. We designed a multi-level modeling framework for JITAIs and developed a proof-of-concept prototype (POC). This study aimed at investigating the usability of the POC by conducting two usability tests with students. We assessed the usability and the students' workload and success in completing tasks. In the second usability test, however, they faced difficulties in completing the tasks. We will work on hiding the complexity of the framework as well as improving the frontend and the instructions.

Integrating Intensive Longitudinal Data (ILD) to Inform the Development of Dynamic Theories of Behavior Change and Intervention Design: a Case Study of Scientific and Practical Considerations.

The increasing sophistication of mobile and sensing technology has enabled the collection of intensive longitudinal data (ILD) concerning dynamic changes in an individual's state and context. ILD can be used to develop dynamic theories of behavior change which, in turn, can be used to provide a conceptual framework for the development of just-in-time adaptive interventions (JITAIs) that leverage advances in mobile and sensing technology to determine when and how to intervene. As such, JITAIs hold tremendous potential in addressing major public health concerns such as cigarette smoking, which can recur and arise unexpectedly. In tandem, a growing number of studies have utilized multiple methods to collect data on a particular dynamic construct of interest from the same individual. This approach holds promise in providing investigators with a significantly more detailed view of how a behavior change processes unfold within the same individual than ever before. However, nuanced challenges relating to coarse data, noisy data, and incoherence among data sources are introduced. In this manuscript, we use a mobile health (mHealth) study on smokers motivated to quit (Break Free; R01MD010362) to illustrate these challenges. Practical approaches to integrate multiple data sources are discussed within the greater scientific context of developing dynamic theories of behavior change and JITAIs.

Just-in-time adaptive ecological momentary assessment (JITA-EMA)

Interest in just-in-time adaptive interventions (JITAI) has rapidly increased in recent years. One core challenge for JITAI is the efficient and precise measurement of tailoring variables that are used to inform the timing of momentary intervention delivery. Ecological momentary assessment (EMA) is often used for this purpose, even though EMA in its traditional form was not designed specifically to facilitate momentary interventions. In this article, we introduce just-in-time adaptive EMA (JITA-EMA) as a strategy to reduce participant response burden and decrease measurement error when EMA is used as a tailoring variable in JITAI. JITA-EMA builds on computerized adaptive testing methods developed for purposes of classification (computerized classification testing, CCT), and applies them to the classification of momentary states within individuals. The goal of JITA-EMA is to administer a small and informative selection of EMA questions needed to accurately classify an individual’s current state at each measurement occasion. After illustrating the basic components of JITA-EMA (adaptively choosing the initial and subsequent items to administer, adaptively stopping item administration, accommodating dynamically tailored classification cutoffs), we present two simulation studies that explored the performance of JITA-EMA, using the example of momentary fatigue states. Compared with conventional EMA item selection methods that administered a fixed set of questions at each moment, JITA-EMA yielded more accurate momentary classification with fewer questions administered. Our results suggest that JITA-EMA has the potential to enhance some approaches to mobile health interventions by facilitating efficient and precise identification of momentary states that may inform intervention tailoring.

The association between physical behavior, affective states, and contextual factors: Using ambulatory assessment to characterize moderating effects

Introduction&#x0D; Physical behavior is a key lifestyle factor in regulating and preventing diseases across the lifespan. Researchers identified affective, cognitive, and contextual factors like weather conditions, as significant contributors in determining if individuals are physically active. However, there is scarce empirical evidence about potential associations between physical behavior and affective states influenced by weather conditions in daily life. Therefore, we investigated the within-subject association between momentary affective states and physical behavior, and weather conditions and physical behavior. Further, we additionally explored if weather conditions moderated the within-subject association between momentary affective states and subsequent physical behavior.&#x0D; Methods&#x0D; Utilizing ambulatory assessment, 79 participants completed electronic diaries about their affective states (i.e., valence, energetic arousal, and calmness) up to six times a day over five days, and their physical behavior (i.e., physical activity and sedentariness) was simultaneously recorded via accelerometers. Weather conditions (i.e., temperature and precipitation) recorded near participants’ locations served as moderators in the multilevel analyses.&#x0D; Results&#x0D; We showed, that the association of affective states and physical activity was moderated by temperature. Higher temperatures enhanced the positive effects of valence on physical activity (β = .001, p = .023) and attenuated the negative effects of calmness on physical activity (β = .001, p = .021). Moreover, higher temperatures enhanced the positive effects of valence on reduced sedentary behavior (β = -0.011, p = .043). In addition, we revealed a significant positive association between temperature, as a momentary weather condition, and physical activity (β = 0.025; p = .015). Furthermore, we confirmed earlier findings associating affective states with physical behavior. Increased valence and energetic arousal were positively associated with physical activity (β = 0.007; p &lt; .001), whereas calmness predicted lower levels of physical activity (β = -0.006; p &lt; .001). Higher levels of calmness showed a positive association with sedentary behavior (β = 0.054; p = .003).&#x0D; Conclusion&#x0D; Moderating effects, such as higher temperatures enhancing the positive effects of valence on PA, provide mechanistic real-life insights as a basis for future health technologies. Just-in-time adaptive interventions (JITAI) offer the possibility to incorporate weather conditions and allow triggering individuals within their preferred contextual condition to promote physical activity. Such personalized real-time systems have recently been promoted by the WHO as most promising.

Using Digital Health Technology to Prevent and Treat Diabetes.

Using Digital Health Technology to Prevent and Treat Diabetes.

A Community Participatory Approach to Creating Contextually Tailored mHealth Notifications: myBPmyLife Project.

Just-in-time adaptive interventions (JITAIs) are a novel approach to mobile health (mHealth) interventions, sending contextually tailored behavior change notifications to participants when they are more likely to engage, determined by data from wearable devices. We describe a community participatory approach to JITAI notification development for the myBPmyLife Project, a JITAI focused on decreasing sodium consumption and increasing physical activity to reduce blood pressure. Eighty-six participants were interviewed, 50 at a federally qualified health center (FQHC) and 36 at a university clinic. Participants were asked to provide encouraging physical activity and low-sodium diet notifications and provided feedback on researcher-generated notifications to inform revisions. Participant notifications were thematically analyzed using an inductive approach. Participants noted challenging vocabulary, phrasing, and culturally incongruent suggestions in some of the researcher-generated notifications. Community-generated notifications were more direct, used colloquial language, and contained themes of grace. The FQHC participants' notifications expressed more compassion, religiosity, and addressed health-related social needs. University clinic participants' notifications frequently focused on office environments. In summary, our participatory approach to notification development embedded a distinctive community voice within our notifications. Our approach may be generalizable to other communities and serve as a model to create tailored mHealth notifications to their focus population.

Assessment and Disruption of Ruminative Episodes to Enhance Mobile Cognitive Behavioral Therapy Just-in-Time Adaptive Interventions in Clinical Depression: Pilot Randomized Controlled Trial.

A just-in-time adaptive intervention (JITAI) is "designed to address the dynamically changing needs of individuals via the provision of the type or amount of support needed, at the right time when needed." If and how rumination-focused cognitive behavioral therapy (RFCBT), the gold standard, blocks emotional cascades underlying rumination is unclear. Furthermore, cognitive behavioral therapy has been successfully used as a mobile variant, but RFCBT has not been adapted for a mobile variant (mobile RFCBT [MRFCBT]) or for a JITAI variant. This study aimed to pilot-test a fully automated JITAI leveraging RFCBT and ways to identify and block cascading depressive rumination. Patients in therapy for clinical depression were recruited for a randomized controlled trial (RCT). After consenting to be part of the RCT, they were randomly assigned to either of the 2 mobile versions of the RFCBT conditions personalized to the individual's rumination timing patterns (JITAI-MRFCBT) or a no-treatment control condition through a double-blind procedure. Although the initial design was to have a 3-armed trial with 2 JITAI conditions (a JITAI and a narrative JITAI condition), we later opted to collapse those 2 conditions into 1 JITAI condition because of the low number of participants. All participants were recruited and participated through their smartphones, receiving 5 SMS text message reminders on each of the 35 days to self-report their rumination-related symptoms (eg, rumination episodes and duration). In the JITAI-MRFCBT condition, they also received treatment materials. The first 7 days provided a rumination baseline, and the last 7 days provided a postintervention rumination value. In total, 42% (25/59) of volunteers were eligible and provided their phone numbers, 20% (5/25) of whom never replied to the SMS text message reminding them to start the RCT. A total of 90% (18/20) of volunteers completed it (ie, finishing, as prespecified, 80% of the questionnaires and training tasks) and, therefore, were included in the analysis. Using independent 2-tailed t tests with bootstrapping, results showed that participants in the JITAI-MRFCBT condition, compared with those in the control condition, reported a greater reduction in counts of rumination episodes (mean -25.28, SD 14.50 vs mean 1.44, SD 4.12, P<.001) and greater reduced average time (minutes) spent in rumination (mean -21.53, SD 17.6 vs mean 1.47, SD 1.5; P=.04). Results also suggest that, compared with those in the control group, those in treatment reduced ruminative carryover from one episode to the next. The results suggest that JITAI-MRFCBT may reduce negative rumination by providing RFCBT just in time following rumination, thereby blocking the next rumination episode using the same trigger. This study supports a subsequent, full-scale JITAI and the importance of leveraging mobile smartphone technology with MRFCBT to curb depressive symptoms. ClinicalTrials.gov NCT04554706; https://clinicaltrials.gov/ct2/show/NCT04554706.

Using a complexity science approach to evaluate the effectiveness of just-in-time adaptive interventions: A meta-analysis.

Just-in-time adaptive interventions (JITAIs), which allow individuals to receive the right amount of tailored support at the right time and place, hold enormous potential for promoting behavior change. However, research on JITAIs' implementation and evaluation is still in its early stages, and more empirical evidence is needed. This meta-analysis took a complexity science approach to evaluate the effectiveness of JITAIs that promote healthy behaviors and assess whether key design principles can increase JITAIs' impacts. We searched five databases for English-language papers. Study eligibility required that interventions objectively measured health outcomes, had a control condition or pre-post-test design, and were conducted in the real-world setting. We included randomized and non-randomized trials. Data extraction encompassed interventions' features, methodologies, theoretical foundations, and delivery modes. RoB 2 and ROBINS-I were used to assess risk of bias. The final analysis included 21 effect sizes with 592 participants. All included studies used pre- and post-test design. A three-level random meta-analytic model revealed a medium effect of JITAIs on objective behavior change (g = 0.77 (95% confidence interval (CI); 0.32 to 1.22), p < 0.001). The summary effect was robust to bias. Moderator analysis indicated that design principles, such as theoretical foundations, targeted behaviors, and passive or active assessments, did not moderate JITAIs' effects. Passive assessments were more likely than a combination of passive and active assessments to relate to higher intervention retention rates. This review demonstrated some evidence for the efficacy of JITAIs. However, high-quality randomized trials and data on non-adherence are needed.

Using Continuous Glucose Monitoring to Detect and Intervene on Dietary Restriction in Individuals With Binge Eating: The SenseSupport Withdrawal Design Study.

Dietary restraint is a key factor for maintaining engagement in binge eating among individuals with binge eating disorder (BED) and bulimia nervosa (BN). Reducing dietary restraint is a mechanism of change in cognitive behavioral therapy (CBT) for individuals with BN and BED. However, many individuals who undergo CBT fail to adequately reduce dietary restraint during treatment, perhaps owing to difficulty in using treatment skills (eg, regular eating) to reduce dietary restraint during their daily lives. The SenseSupport system, a novel just-in-time, adaptive intervention (JITAI) system that uses continuous glucose monitoring to detect periods of dietary restraint, may improve CBT to reduce dietary restraint during treatment by providing real-time interventions. This study aimed to describe the feasibility, acceptability, and initial evaluation of SenseSupport. We presented feasibility, acceptability, target engagement, and initial treatment outcome data from a small trial using an ABAB (A=continuous glucose monitoring data sharing and JITAIs-Off, B=continuous glucose monitoring data sharing and JITAIs-On) design (in which JITAIs were turned on for 2 weeks and then turned off for 2 weeks throughout the treatment). Participants (N=30) were individuals with BED or BN engaging in ≥3 episodes of ≥5 hours without eating per week at baseline. Participants received 12 sessions of CBT and wore continuous glucose monitors to detect eating behaviors and inform the delivery of JITAIs. Participants completed 4 assessments and reported eating disorder behaviors, dietary restraint, and barriers to app use weekly throughout treatment. Retention was high (25/30, 83% after treatment). However, the rates of continuous glucose monitoring data collection were low (67.4% of expected glucose data were collected), and therapists and participants reported frequent app-related issues. Participants reported that the SenseSupport system was comfortable, minimally disruptive, and easy to use. The only form of dietary restraint that decreased significantly more rapidly during JITAIs-On periods relative to JITAIs-Off periods was the desire for an empty stomach (t43=1.69; P=.049; Cohen d=0.25). There was also a trend toward greater decrease in overall restraint during JITAs-On periods compared with JITAIs-Off periods, but these results were not statistically significant (t43=1.60; P=.06; Cohen d=0.24). There was no significant difference in change in the frequency of binge eating during JITAIs-On periods compared with JITAIs-Off periods (P=.23). Participants demonstrated clinically significant, large decreases in binge eating (t24=10.36; P<.001; Cohen d=2.07), compensatory behaviors (t24=3.40; P=.001; Cohen d=0.68), and global eating pathology (t24=6.25; P<.001; Cohen d=1.25) from pre- to posttreatment. This study describes the successful development and implementation of the first intervention system combining passive continuous glucose monitors and JITAIs to augment CBT for binge-spectrum eating disorders. Despite the lower-than-anticipated collection of glucose data, the high acceptability and promising treatment outcomes suggest that the SenseSupport system warrants additional investigation via future, fully powered clinical trials. ClinicalTrials.gov NCT04126694; https://clinicaltrials.gov/ct2/show/NCT04126694.

Microrandomized Trials: Developing Just-in-Time Adaptive Interventions for Better Public Health.

Just-in-time adaptive interventions (JITAIs) represent an intervention design that adapts the provision and type of support over time to an individual's changing status and contexts, intending to deliver the right support on the right occasion. As a novel strategy for delivering mobile health interventions, JITAIs have the potential to improve access to quality care in underserved communities and, thus, alleviate health disparities, a significant public health concern. Valid experimental designs and analysis methods are required to inform the development of JITAIs. Here, we briefly review the cutting-edge design of microrandomized trials (MRTs), covering both the classical MRT design and its outcome-adaptive counterpart. Associated statistical challenges related to the design and analysis of MRTs are also discussed. Two case studies are provided to illustrate the aforementioned concepts and designs throughout the article. We hope our work leads to better design and application of JITAIs, advancing public health research and practice. (Am J Public Health. 2023;113(1):60-69. https://doi.org/10.2105/AJPH.2022.307150).

Health Data Integration Architecture for Continuous Behavioral Health Monitoring and Delivering Personalised, Just-in Time Adaptive Interventions in the ADLIFE Project

The International Journal of Integrated Care (IJIC) is an online, open-access, peer-reviewed scientific journal that publishes original articles in the field of integrated care on a continuous basis.IJIC has an Impact Factor of 2.913 (2021 JCR, received in June 2022)The IJIC 20th Anniversary Issue was published in 2021.

Development of an Android Mobile Application for Reducing Sitting Time and Increasing Walking Time in People with Type 2 Diabetes

Breaking up prolonged sitting with short bouts of light physical activity including standing and walking has been shown to be beneficial for people with type 2 diabetes (T2D). This paper presents the development of an android mobile app to deliver a just-in-time adaptive intervention (JITAI) to reduce sedentary time in people with T2D. A total of six design workshops were conducted with seven experts to identify design requirements, a behavioural framework, and required contextual adaptations for the development of a bespoke mobile app (iMOVE). Moreover, a focus group was conducted among people with T2D as potential end-users (N = 10) to ascertain their perceptions of the app. Feedback from the focus group was used in subsequent iterations of the iMOVE app. Data were analysed using an inductive qualitative thematic analysis. Based on workshops, key features of iMOVE were developed, including simplicity (e.g., navigation, login), colours and font sizes, push notifications, messaging algorithms, and a triggering system for breaking up sitting time and moving more. Based on the user testing results, a goal-setting tab was added, font sizes were made larger, the brightness of colours was reduced, and a colour indicator was used to indicate device connectivity with an activity tracker. A user-centric app was developed to support people with T2D to transition from sedentary to active lifestyles.

Effectiveness and Minimum Effective Dose of App-Based Mobile Health Interventions for Anxiety and Depression Symptom Reduction: Systematic Review and Meta-Analysis.

BackgroundMobile health (mHealth) apps offer new opportunities to deliver psychological treatments for mental illness in an accessible, private format. The results of several previous systematic reviews support the use of app-based mHealth interventions for anxiety and depression symptom management. However, it remains unclear how much or how long the minimum treatment “dose” is for an mHealth intervention to be effective. Just-in-time adaptive intervention (JITAI) has been introduced in the mHealth domain to facilitate behavior changes and is positioned to guide the design of mHealth interventions with enhanced adherence and effectiveness.ObjectiveInspired by the JITAI framework, we conducted a systematic review and meta-analysis to evaluate the dose effectiveness of app-based mHealth interventions for anxiety and depression symptom reduction.MethodsWe conducted a literature search on 7 databases (ie, Ovid MEDLINE, Embase, PsycInfo, Scopus, Cochrane Library (eg, CENTRAL), ScienceDirect, and ClinicalTrials, for publications from January 2012 to April 2020. We included randomized controlled trials (RCTs) evaluating app-based mHealth interventions for anxiety and depression. The study selection and data extraction process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We estimated the pooled effect size using Hedge g and appraised study quality using the revised Cochrane risk-of-bias tool for RCTs.ResultsWe included 15 studies involving 2627 participants for 18 app-based mHealth interventions. Participants in the intervention groups showed a significant effect on anxiety (Hedge g=–.10, 95% CI –0.14 to –0.06, I2=0%) but not on depression (Hedge g=–.08, 95% CI –0.23 to 0.07, I2=4%). Interventions of at least 7 weeks’ duration had larger effect sizes on anxiety symptom reduction.ConclusionsThere is inconclusive evidence for clinical use of app-based mHealth interventions for anxiety and depression at the current stage due to the small to nonsignificant effects of the interventions and study quality concerns. The recommended dose of mHealth interventions and the sustainability of intervention effectiveness remain unclear and require further investigation.

A Gambling Just-In-Time Adaptive Intervention (GamblingLess: In-The-Moment): Protocol for a Microrandomized Trial.

BackgroundThe presence of discrete but fluctuating precipitants, in combination with the dynamic nature of gambling episodes, calls for the development of tailored interventions delivered in real time, such as just-in-time adaptive interventions (JITAIs). JITAIs leverage mobile and wireless technologies to address dynamically changing individual needs by providing the type and amount of support required at the right time and only when needed. They have the added benefit of reaching underserved populations by providing accessible, convenient, and low-burden support. Despite these benefits, few JITAIs targeting gambling behavior are available.ObjectiveThis study aims to redress this gap in service provision by developing and evaluating a theoretically informed and evidence-based JITAI for people who want to reduce their gambling. Delivered via a smartphone app, GamblingLess: In-The-Moment provides tailored cognitive-behavioral and third-wave interventions targeting cognitive processes explicated by the relapse prevention model (cravings, self-efficacy, and positive outcome expectancies). It aims to reduce gambling symptom severity (distal outcome) through short-term reductions in the likelihood of gambling episodes (primary proximal outcome) by improving craving intensity, self-efficacy, or expectancies (secondary proximal outcomes). The primary aim is to explore the degree to which the delivery of a tailored intervention at a time of cognitive vulnerability reduces the probability of a subsequent gambling episode.MethodsGamblingLess: In-The-Moment interventions are delivered to gamblers who are in a state of receptivity (available for treatment) and report a state of cognitive vulnerability via ecological momentary assessments 3 times a day. The JITAI will tailor the type, timing, and amount of support for individual needs. Using a microrandomized trial, a form of sequential factorial design, each eligible participant will be randomized to a tailored intervention condition or no intervention control condition at each ecological momentary assessment across a 28-day period. The microrandomized trial will be supplemented by a 6-month within-group follow-up evaluation to explore long-term effects on primary (gambling symptom severity) and secondary (gambling behavior, craving severity, self-efficacy, and expectancies) outcomes and an acceptability evaluation via postintervention surveys, app use and engagement indices, and semistructured interviews. In all, 200 participants will be recruited from Australia and New Zealand.ResultsThe project was funded in June 2019, with approval from the Deakin University Human Research Ethics Committee (2020-304). Stakeholder user testing revealed high acceptability scores. The trial began on March 29, 2022, and 84 participants have been recruited (as of June 24, 2022). Results are expected to be published mid-2024.ConclusionsGamblingLess: In-The-Moment forms part of a suite of theoretically informed and evidence-based web-based and mobile gambling interventions. This trial will provide important empirical data that can be used to facilitate the JITAI’s optimization to make it a more effective, efficient, and scalable tailored intervention.Trial RegistrationAustralian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12622000490774; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380757&isClinicalTrial=FalseInternational Registered Report Identifier (IRRID)PRR1-10.2196/38958

A Just-In-Time Adaptive intervention (JITAI) for smoking cessation: Feasibility and acceptability findings

Smoking cessation treatments that are easily accessible and deliver intervention content at vulnerable moments (e.g., high negative affect) have great potential to impact tobacco abstinence. The current study examined the feasibility and acceptability of a multi-component Just-In-Time Adaptive Intervention (JITAI) for smoking cessation. Daily smokers interested in quitting were consented to participate in a 6-week cessation study. Visit 1 occurred 4 days pre-quit, Visit 2 was on the quit day, Visit 3 occurred 3 days post-quit, Visit 4 was 10 days post-quit, and Visit 5 was 28 days post-quit. During the first 2 weeks (Visits 1–4), the JITAI delivered brief mindfulness/motivational strategies via smartphone in real-time based on negative affect or smoking behavior detected by wearable sensors. Participants also attended 5 in-person visits, where brief cessation counseling (Visits 1–4) and nicotine replacement therapy (Visits 2–5) were provided. Outcomes were feasibility and acceptability; biochemically-confirmed abstinence was also measured. Participants (N = 43) were 58.1 % female (AgeMean = 49.1, mean cigarettes per day = 15.4). Retention through follow-up was high (83.7 %). For participants with available data (n = 38), 24 (63 %) met the benchmark for sensor wearing, among whom 16 (67 %) completed at least 60 % of strategies. Perceived ease of wearing sensors (Mean = 5.1 out of 6) and treatment satisfaction (Mean = 3.6 out of 4) were high. Biochemically-confirmed abstinence was 34 % at Visit 4 and 21 % at Visit 5. Overall, the feasibility of this novel multi-component intervention for smoking cessation was mixed but acceptability was high. Future studies with improved technology will decrease participant burden and better detect key intervention moments.

Development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention for adults with alcohol misuse who are experiencing homelessness.

Adults experiencing homelessness have much higher rates of alcohol misuse than housed individuals. This study describes the development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention (JITAI) to reduce alcohol use among adults experiencing homelessness. We conducted a pilot trial (N= 41; mean age [SD]=45.2 [11.5]; 19.5% women) of the Smart-T Alcohol JITAI where participants completed brief ecological momentary assessments (EMAs) each day, received personalized treatment messages following each EMA, and accessed on-demand intervention content for 4 weeks. The prediction algorithm and treatment messages were developed based on an independent but similar sample as part of the trial. We examined three drinking outcomes: daily drinking (yes/no), drinks per day, and heavy episodic drinking, controlling for scores on the Alcohol Use Disorders Identification Test (AUDIT) at baseline, age, and sex using quadratic growth curve models. Over the 4-week period, participants showed a decline in all alcohol use outcomes. Participants also reported high levels of satisfaction with the JITAI. Use of the Smart-T Alcohol JITAI was well received and provided encouraging evidence that it may reduce any drinking, drinks per day, and heavy episodic drinking among adults experiencing homelessness.

Smartphone App Delivery of a Just-In-Time Adaptive Intervention for Adult Gamblers (Gambling Habit Hacker): Protocol for a Microrandomized Trial

BackgroundPeople with gambling problems frequently report repeated unsuccessful attempts to change their behavior. Although many behavior change techniques are available to individuals to reduce gambling harm, they can be challenging to implement or maintain. The provision of implementation support tailored for immediate, real-time, individualized circumstances may improve attempts at behavior change.ObjectiveWe aimed to develop and evaluate a Just-In-Time Adaptive Intervention (JITAI) for individuals who require support to adhere to their gambling limits. JITAI development is based on the principles of the Health Action Process Approach with delivery, in alignment with the principles of self-determination theory. The primary objective was to determine the effect of action- and coping planning compared with no intervention on the goal of subsequently adhering to gambling expenditure limits.MethodsGambling Habit Hacker is delivered as a JITAI providing in-the-moment support for adhering to gambling expenditure limits (primary proximal outcome). Delivered via a smartphone app, this JITAI delivers tailored behavior change techniques related to goal setting, action planning, coping planning, and self-monitoring. The Gambling Habit Hacker app will be evaluated using a 28-day microrandomized trial. Up to 200 individuals seeking support for their own gambling from Australia and New Zealand will set a gambling expenditure limit (ie, goal). They will then be asked to complete 3 time-based ecological momentary assessments (EMAs) per day over a 28-day period. EMAs will assess real-time adherence to gambling limits, strength of intention to adhere to goals, goal self-efficacy, urge self-efficacy, and being in high-risk situations. On the basis of the responses to each EMA, participants will be randomized to the control (a set of 25 self-enactable strategies containing names only and no implementation information) or intervention (self-enactable strategy implementation information with facilitated action- and coping planning) conditions. This microrandomized trial will be supplemented with a 6-month within-group follow-up that explores the long-term impact of the app on gambling expenditure (primary distal outcome) and a range of secondary outcomes, as well as an evaluation of the acceptability of the JITAI via postintervention surveys, app use and engagement indices, and semistructured interviews. This trial has been approved by the Deakin University Human Research Ethics Committee (2020-304).ResultsThe intervention has been subject to expert user testing, with high acceptability scores. The results will inform a more nuanced version of the Gambling Habit Hacker app for wider use.ConclusionsGambling Habit Hacker is part of a suite of interventions for addictive behaviors that deliver implementation support grounded in lived experience. This study may inform the usefulness of delivering implementation intentions in real time and in real-world settings. It potentially offers people with gambling problems new support to set their gambling intentions and adhere to their limits.Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12622000497707; www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=383568International Registered Report Identifier (IRRID)DERR1-10.2196/38919

Just-in-Time Adaptive Interventions for Suicide Prevention: Promise, Challenges, and Future Directions

The suicide rate (currently 14 per 100,000) has barely changed in the United States over the past 100 years. There is a need for new ways of preventing suicide. Further, research has revealed that suicidal thoughts and behaviors and the factors that drive them are dynamic, heterogeneous, and interactive. Most existing interventions for suicidal thoughts and behaviors are infrequent, not accessible when most needed, and not systematically tailored to the person using their own data (e.g., from their own smartphone). Advances in technology offer an opportunity to develop new interventions that may better match the dynamic, heterogeneous, and interactive nature of suicidal thoughts and behaviors. Just-In-Time Adaptive Interventions (JITAIs), which use smartphones and wearables, are designed to provide the right type of support at the right time by adapting to changes in internal states and external contexts, offering a promising pathway toward more effective suicide prevention. In this review, we highlight the potential of JITAIs for suicide prevention, challenges ahead (e.g., measurement, ethics), and possible solutions to these challenges.

Ask the Users

Just-in-Time Adaptive Interventions (JITAIs) are envisioned to harness rich data on users' contexts. However, many JITAIs fall short in leveraging the value of the data while sculpting the interventions. Investigating the literature reveals a lack of user-centered design (UCD) methods in designing JITAIs. Our case study of applying a UCD process revealed that even without deploying a JITAI, UCD could uncover user interactions that inform critical design decisions of a JITAI's components. We reflect on our experiences engaging in a user-centered JITAI design process and urge the broader human-computer interaction (HCI) community to devise concrete design guidelines for JITAIs. We take the first step toward that goal by proposing a checklist of key design considerations for future JITAIs. Together, this case study contributes insights on applying UCD to the design of all components of a JITAI, which can help capture users' needs and provide actionable interventions.