Engagement in digital interventions

The conceptualisation and measurement of engagement in digital health

Digital tools are an increasingly important component of healthcare, but their potential impact is commonly limited by a lack of user engagement. Digital health evaluations of engagement are often restricted to system usage metrics, which cannot capture a full understanding of how and why users engage with an intervention. This study aimed to examine how theory-based, multifaceted measures of engagement with digital health interventions capture different components of engagement (affective, cognitive, behavioural, micro, and macro) and to consider areas that are unclear or missing in their measurement. We identified and compared two recently developed measures that met these criteria (the Digital Behaviour Change Intervention Engagement Scale and the TWente Engagement with Ehealth Technologies Scale). Despite having similar theoretical bases and being relatively strongly correlated, there are key differences in how these scales aim to capture engagement. We discuss the implications of our analysis for how affective, cognitive, and behavioural components of engagement can be conceptualised and whether there is value in distinguishing between them. We conclude with recommendations for the circumstances in which each scale may be most useful and for how future measure development could supplement existing scales.

Understanding Social Media Information Sharing in Individuals with Depression: Insights from the Elaboration Likelihood Model and Schema Activation Theory

Purpose

How individuals engage with social media can significantly impact their psychological well-being. This study examines the impact of social media interactions on mental health, grounded in the frameworks of the Elaboration Likelihood Model and Schema Activation Theory. It aims to uncover behavioral differences in information sharing between the general population and individuals with depression, while also elucidating the psychological mechanisms underlying these disparities.

Methods

A pre-experiment (N=30) and three experiments (Experiment 1a N=200, Experiment 1b N=180, Experiment 2 N=128) were executed online. These experiments investigated the joint effects of information quality, content valence, self-referential processing, and depression level on the intention to share information. The research design incorporated within-subject and between-subject methods, utilizing SPSS and SPSS Process to conduct independent sample t-tests, two-factor ANOVA analyses, mediation analyses, and moderated mediation analyses to test our hypotheses.

Results

Information quality and content valence significantly influence sharing intention. In scenarios involving low-quality information, individuals with depression are more inclined to share negative emotional content compared to the general population, and this tendency intensifies with the severity of depression. Moreover, self-referential processing acts as a mediator between emotional content and intention to share, yet this mediation effect weakens as the severity of depression rises.

Conclusion

Our study highlights the importance of promoting viewpoint diversity and breaking the echo chamber effect in social media to improve the mental health of individuals with depression. To achieve this goal, tailoring emotional content on social media could be a practical starting point for practice.

Design of experiments with sequential randomizations on multiple timescales: the hybrid experimental design

Psychological interventions, especially those leveraging mobile and wireless technologies, often include multiple components that are delivered and adapted on multiple timescales (e.g., coaching sessions adapted monthly based on clinical progress, combined with motivational messages from a mobile device adapted daily based on the person's daily emotional state). The hybrid experimental design (HED) is a new experimental approach that enables researchers to answer scientific questions about the construction of psychological interventions in which components are delivered and adapted on different timescales. These designs involve sequential randomizations of study participants to intervention components, each at an appropriate timescale (e.g., monthly randomization to different intensities of coaching sessions and daily randomization to different forms of motivational messages). The goal of the current manuscript is twofold. The first is to highlight the flexibility of the HED by conceptualizing this experimental approach as a special form of a factorial design in which different factors are introduced at multiple timescales. We also discuss how the structure of the HED can vary depending on the scientific question(s) motivating the study. The second goal is to explain how data from various types of HEDs can be analyzed to answer a variety of scientific questions about the development of multicomponent psychological interventions. For illustration, we use a completed HED to inform the development of a technology-based weight loss intervention that integrates components that are delivered and adapted on multiple timescales.

Real-time personalized feedback in mHealth for adolescents

Mobile Health (mHealth) interventions have the potential to improve early identification, prevention, and treatment of mental health problems. Grow It! is a multiplayer smartphone app designed for youth aged 12-25, allowing them to monitor their emotions and engage in daily challenges based on Cognitive Behavioral Therapy (CBT) principles. Recently, a personalized mood profile was added to improve the app. We investigated whether real-time personalized feedback on mood enhances app engagement, user experience, and the effects on affective and cognitive well-being. Sample A (N = 1269, age = 18.60 SD = 3.39, 80.6% girls, 95.4% Dutch) played the original app without feedback on their mood, and an independent Sample B (N = 386, age = 16.04 SD = 3.21, 67.6% girls, 82.9% Dutch) received the renewed version with personalized real-time feedback on their mood. Participants who received personal feedback did not have higher app engagement (t(1750,400) = 1.39, P = .206, d = 0.07; t(692,905) = 0.36, P = .971, d = 0.0) nor higher user experience (t(177,596) = 0.21, P = .831, d = 0.02; (t(794) = 1.28, P = .202, d = 0.12; χ2 (659,141) = 2.83, P = .091). Players of the renewed version (Sample B) experienced significant improvements in affective (t(175) = 3.01, P = .003, d = 0.23) and cognitive well-being (t(175) = 3.48, P = <.001, d = 0.26) over the course of three weeks. The renewed version Grow It! has the potential to enhance youths' affective and cognitive well-being. However, adding real-time insights did not seem to affect app engagement nor user experience.

Online Support Groups for Family Caregivers: Scoping Review

BACKGROUND

Caregiving can affect people of all ages and can have significant negative health impacts on family caregivers themselves. Research has shown that social support acts as a buffer against many negative health impacts. A common source of social support is support groups. Although traditionally, these groups were conducted in a face-to-face setting, the advent of the internet, social media applications, and the smartphone have seen online support groups (OSGs) develop as a space where many caregivers seek support. The number of OSGs has increased exponentially, but there is no clear consensus on what factors or characteristics of OSGs contribute to social support development within them or what types of OSGs are available to family caregivers.

OBJECTIVE

This study aimed to conduct a scoping review to contribute to the understanding of the types and characteristics of OSGs for family caregivers.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines, the CINAHL, PsychInfo, Psych Articles, Social Sciences, Communication Source, Medline, and Web of Science databases were searched for studies (caregiver focused, adults aged 18 years or older, online social support groups, caring for a living person, peer-reviewed journal publications on empirical research). In total, 19 studies were included in the review. The research questions were (1) what type of social support groups are online for adult family caregivers, (2) what the communication mediums and characteristics of these OSGs are, and (3) what psychosocial or other factors make OSGs successful or unsuccessful for participants.

RESULTS

In response to the first research question, we found that the majority of OSGs took place on public text-based forums and were illness specific. Where demographics were reported, participants were predominately women, White, and working with university-level education. There were a variety of caregiving relationships. For the second research question, the most common communication medium found was text-based communication, with the use of emojis, photos, and GIF (Graphics Interchange Format) files as part of these exchanges. Most frequently, the OSGs were asynchronous with a degree of anonymity, not time-limited by the frequency of contact or duration, and moderated by peer or professional moderators or facilitators. Results for the third research question explored the overarching categories of safe communication and engagement and group management. These described successful OSGs as having a focus on similar others with shared lived experiences communicated in a nonjudgmental space overseen by trained peer or professional facilitators.

CONCLUSIONS

There are several key considerations for OSGs to be successful for family caregivers. A general recommendation for practitioners is to give importance to building active moderation and multifaceted structures of support to meet different levels of caregiver needs and the ability to engage.

A multilevel mHealth intervention boosts adherence to hydroxyurea in individuals with sickle cell disease

Hydroxyurea reduces sickle cell disease (SCD) complications, but medication adherence is low. We tested 2 mobile health (mHealth) interventions targeting determinants of low adherence among patients (InCharge Health) and low prescribing among providers (HU Toolbox) in a multi-center, non-randomized trial of individuals with SCD ages 15-45. We compared the percentage of days covered (PDC), labs, healthcare utilization, and self-reported pain over 24 weeks of intervention and 12 weeks post-study with a 24-week preintervention interval. We enrolled 293 patients (51% male; median age 27.5 years, 86.8% HbSS/HbSβ0-thalassemia). The mean change in PDC among 235 evaluable subjects increased (39.7% to 56.0%; P < 0.001) and sustained (39.7% to 51.4%, P < 0.001). Mean HbF increased (10.95% to 12.78%; P = 0.03). Self-reported pain frequency reduced (3.54 to 3.35 events/year; P = 0.041). InCharge Health was used ≥1 day by 199 of 235 participants (84.7% implementation; median usage: 17% study days; IQR: 4.8-45.8%). For individuals with ≥1 baseline admission for pain, admissions per 24 weeks declined from baseline through 24 weeks (1.97 to 1.48 events/patient, P = 0.0045) and weeks 25-36 (1.25 events/patient, P = 0.0015). PDC increased with app use (P < 0.001), with the greatest effect in those with private insurance (P = 0.0078), older subjects (P = 0.033), and those with lower pain interference (P = 0.0012). Of the 89 providers (49 hematologists, 36 advanced care providers, 4 unreported), only 11.2% used HU Toolbox ≥1/month on average. This use did not affect change in PDC. Tailoring mHealth solutions to address barriers to hydroxyurea adherence can potentially improve adherence and provide clinical benefits. A definitive randomized study is warranted. This trial was registered at www.clinicaltrials.gov as #NCT04080167.

Developing Message Strategies to Engage Racial and Ethnic Minority Groups in Digital Oral Self-Care Interventions: Participatory Co-Design Approach

BACKGROUND

The prevention of oral health diseases is a key public health issue and a major challenge for racial and ethnic minority groups, who often face barriers in accessing dental care. Daily toothbrushing is an important self-care behavior necessary for sustaining good oral health, yet engagement in regular brushing remains a challenge. Identifying strategies to promote engagement in regular oral self-care behaviors among populations at risk of poor oral health is critical.

OBJECTIVE

The formative research described here focused on creating messages for a digital oral self-care intervention targeting a racially and ethnically diverse population. Theoretically grounded strategies (reciprocity, reciprocity-by-proxy, and curiosity) were used to promote engagement in 3 aspects: oral self-care behaviors, an oral care smartphone app, and digital messages. A web-based participatory co-design approach was used to develop messages that are resource efficient, appealing, and novel; this approach involved dental experts, individuals from the general population, and individuals from the target population-dental patients from predominantly low-income racial and ethnic minority groups. Given that many individuals from racially and ethnically diverse populations face anonymity and confidentiality concerns when participating in research, we used an approach to message development that aimed to mitigate these concerns.

METHODS

Messages were initially developed with feedback from dental experts and Amazon Mechanical Turk workers. Dental patients were then recruited for 2 facilitator-mediated group webinar sessions held over Zoom (Zoom Video Communications; session 1: n=13; session 2: n=7), in which they provided both quantitative ratings and qualitative feedback on the messages. Participants interacted with the facilitator through Zoom polls and a chat window that was anonymous to other participants. Participants did not directly interact with each other, and the facilitator mediated sessions by verbally asking for message feedback and sharing key suggestions with the group for additional feedback. This approach plausibly enhanced participant anonymity and confidentiality during the sessions.

RESULTS

Participants rated messages highly in terms of liking (overall rating: mean 2.63, SD 0.58; reciprocity: mean 2.65, SD 0.52; reciprocity-by-proxy: mean 2.58, SD 0.53; curiosity involving interactive oral health questions and answers: mean 2.45, SD 0.69; curiosity involving tailored brushing feedback: mean 2.77, SD 0.48) on a scale ranging from 1 (do not like it) to 3 (like it). Qualitative feedback indicated that the participants preferred messages that were straightforward, enthusiastic, conversational, relatable, and authentic.

CONCLUSIONS

This formative research has the potential to guide the design of messages for future digital health behavioral interventions targeting individuals from diverse racial and ethnic populations. Insights emphasize the importance of identifying key stimuli and tasks that require engagement, gathering multiple perspectives during message development, and using new approaches for collecting both quantitative and qualitative data while mitigating anonymity and confidentiality concerns.

Digital Adaptive Behavioral Interventions to Improve HIV Prevention and Care: Innovations in Intervention Approach and Experimental Design

PURPOSE OF REVIEW

Recent advances in digital technologies can be leveraged to adapt HIV prevention and treatment services to the rapidly changing needs of individuals in everyday life. However, to fully take advantage of these technologies, it is critical to effectively integrate them with human-delivered components. Here, we introduce a new experimental approach for optimizing the integration and adaptation of digital and human-delivered behavioral intervention components for HIV prevention and treatment.

RECENT FINDINGS

Typically, human-delivered components can be adapted on a relatively slow timescale (e.g., every few months or weeks), while digital components can be adapted much faster (e.g., every few days or hours). Thus, the systematic integration of these components requires an experimental approach that involves sequential randomizations on multiple timescales. Selecting an experimental approach should be motivated by the type of adaptive intervention investigators would like to develop, and the scientific questions they have about its construction.

The impact of therapeutic persuasiveness on engagement and outcomes in unguided interventions: A randomized pilot trial of a digital parent training program for child behavior problems

Understanding how to design engaging unguided digital health interventions is key in our ability to utilize digital tools to improve access to care. Therapeutic persuasiveness (TP) is a design concept that relates to how the digital intervention features as a whole should be designed to encourage users to make positive changes in their lives, while reducing the experienced effort required from them to engage in these activities. In our previous work, we examined the user traffic of publicly available programs, finding programs' TP quality to be a reliable, robust, and stable predictor of real-world usage; however, these findings have not been subject to experimental manipulation in a controlled trial. The current study examined the impact of TP quality in digital parent training programs (DPTs) aimed at treating child's behavior problems. We conducted a pilot randomized controlled trial comparing two interventions that utilize the same evidence-based content of established DPTs, but that differ in terms of the quality of TP (standard: DPT-STD; enhanced: DPT-TP). Altogether, parents from 88 families who have a child with behavior problems were enrolled in the study. Compared to DPT-STD (n = 43), participants allocated to DPT-TP (n = 45) used the program significantly more (ps < 0.001; Cohen's ds = 0.91-2.22). In terms of program completion, 68.9 % of DPT-TP participants completed it compared to 27.9 % of DPT-STD participants. Significant differences between the interventions were also found in reported improvements in child behavior problems favoring DPT-TP (ps < 0.05; Cohen's ds = 0.43-0.54). The results point to the importance of adequate product design and the utilization of conceptual frameworks in order to improve user engagement challenges.

A Guided, Internet-Based Stress Management Intervention for University Students With High Levels of Stress: Feasibility and Acceptability Study

BACKGROUND

Transitioning to adulthood and challenges in university life can result in increased stress levels among university students. Chronic and severe stress is associated with deleterious psychological and physiological effects. Digital interventions could succeed in approaching and helping university students who might be at risk; however, the experiences of students with internet-based stress management interventions are insufficiently understood.

OBJECTIVE

This study aims to explore the feasibility; acceptability; and changes in perceived stress, depressive symptoms, and quality of life from baseline to posttest assessment of a 5-session, internet-based stress management intervention guided by an e-coach, developed for university students experiencing high levels of stress.

METHODS

A single-arm study was conducted. Students were recruited from different channels, mainly from a web survey. Students were eligible if they (1) scored ≥20 on the Perceived Stress Scale-10, (2) were aged ≥18 years, and (3) were studying at one of the participating universities. Feasibility and acceptability of the intervention were investigated using several indications, including satisfaction (Client Satisfaction Questionnaire-8) and usability (System Usability Scale-10). We also investigated the indicators of intervention adherence using use metrics (eg, the number of completed sessions). Our secondary goal was to explore the changes in perceived stress (Perceived Stress Scale-10), depressive symptoms (Patient Health Questionnaire-9), and quality of life (EQ-5D-5L scale) from baseline to posttest assessment. In addition, we conducted semistructured interviews with intervention completers and noncompleters to understand user experiences in depth. For all primary outcomes, descriptive statistics were calculated. Changes from baseline to posttest assessment were examined using 2-tailed paired sample t tests or the Wilcoxon signed rank test. Qualitative data were analyzed using thematic analysis.

RESULTS

Of 436 eligible students, 307 (70.4%) students started using the intervention. Overall, 25.7% (79/307) completed the core sessions (ie, sessions 1-3) and posttest assessment. A substantial proportion of the students (228/307, 74.3%) did not complete the core sessions or the posttest assessment. Students who completed the core sessions reported high satisfaction (mean 25.78, SD 3.30) and high usability of the intervention (mean 86.01, SD 10.25). Moreover, this group showed large reductions in perceived stress (Cohen d=0.80) and moderate improvements in depression score (Cohen d=0.47) and quality of life (Cohen d=-0.35) from baseline to posttest assessment. Qualitative findings highlight that several personal and intervention-related factors play a role in user experience.

CONCLUSIONS

The internet-based stress management intervention seems to be feasible, acceptable, and possibly effective for some university students with elevated stress levels. However, given the high dropout rate and qualitative findings, several adjustments in the content and features of the intervention are needed to maximize the user experience and the impact of the intervention.

TRIAL REGISTRATION

Netherlands Trial Register 8686; https://onderzoekmetmensen.nl/nl/trial/20889.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1016/j.invent.2021.100369.

Identifying Design Opportunities for Adaptive mHealth Interventions That Target General Well-Being: Interview Study With Informal Care Partners

BACKGROUND

Mobile health (mHealth) interventions can deliver personalized behavioral support to users in daily contexts. These interventions have been increasingly adopted to support individuals who require low-cost and low-burden support. Prior research has demonstrated the feasibility and acceptability of an mHealth intervention app (CareQOL) designed for use with informal care partners. To further optimize the intervention delivery, we need to investigate how care partners, many of whom lack the time for self-care, react and act in response to different behavioral messages.

OBJECTIVE

The goal of this study was to understand the factors that impact care partners' decision-making and actions in response to different behavioral messages. Insights from this study will help optimize future tailored and personalized behavioral interventions.

METHODS

We conducted semistructured interviews with participants who had recently completed a 3-month randomized controlled feasibility trial of the CareQOL mHealth intervention app. Of the 36 participants from the treatment group of the randomized controlled trial, 23 (64%) participated in these interviews. To prepare for each interview, the team first selected representative behavioral messages (eg, targeting different health dimensions) and presented them to participants during the interview to probe their influence on participants' thoughts and actions. The time of delivery, self-reported perceptions of the day, and user ratings of a message were presented to the participants during the interviews to assist with recall.

RESULTS

The interview data showed that after receiving a message, participants took various actions in response to different messages. Participants performed suggested behaviors or adjusted them either immediately or in a delayed manner (eg, sometimes up to a month later). We identified 4 factors that shape the variations in user actions in response to different behavioral messages: uncertainties about the workload required to perform suggested behaviors, concerns about one's ability to routinize suggested behaviors, in-the-moment willingness and ability to plan for suggested behaviors, and overall capability to engage with the intervention.

CONCLUSIONS

Our study showed that care partners use mHealth behavioral messages differently regarding the immediacy of actions and the adaptation to suggested behaviors. Multiple factors influence people's perceptions and decisions regarding when and how to take actions. Future systems should consider these factors to tailor behavioral support for individuals and design system features to support the delay or adaptation of the suggested behaviors. The findings also suggest extending the assessment of user adherence by considering the variations in user actions on behavioral support (ie, performing suggested or adjusted behaviors immediately or in a delayed manner).

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/32842.

Experiences of Using Digital Mindfulness-Based Interventions: Rapid Scoping Review and Thematic Synthesis

BACKGROUND

Digital mindfulness-based interventions (MBIs) are a promising approach to deliver accessible and scalable mindfulness training and have been shown to improve a range of health outcomes. However, the success of digital MBIs is reliant on adequate engagement, which remains a crucial challenge. Understanding people's experiences of using digital MBIs and identifying the core factors that facilitate or act as barriers to engagement is essential to inform intervention development and maximize engagement and outcomes.

OBJECTIVE

This study aims to systematically map the literature on people's experiences of using digital MBIs that target psychosocial variables (eg, anxiety, depression, distress, and well-being) and identify key barriers to and facilitators of engagement.

METHODS

We conducted a scoping review to synthesize empirical qualitative research on people's experiences of using digital MBIs. We adopted a streamlined approach to ensure that the evidence could be incorporated into the early stages of intervention development. The search strategy identified articles with at least one keyword related to mindfulness, digital, user experience, and psychosocial variables in their title or abstract. Inclusion criteria specified that articles must have a qualitative component, report on participants' experiences of using a digital MBI designed to improve psychosocial variables, and have a sample age range that at least partially overlapped with 16 to 35 years. Qualitative data on user experience were charted and analyzed using inductive thematic synthesis to generate understandings that go beyond the content of the original studies. We used the Quality of Reporting Tool to critically appraise the included sources of evidence.

RESULTS

The search identified 510 studies, 22 (4.3%) of which met the inclusion criteria. Overall, the samples were approximately 78% female and 79% White; participants were aged between 16 and 69 years; and the most used measures in intervention studies were mindfulness, psychological flexibility, and variables related to mental health (including depression, anxiety, stress, and well-being). All studies were judged to be adequately reported. We identified 3 themes characterizing barriers to and facilitators of engagement: responses to own practice (ie, negative reactions to one's own practice are common and can deplete motivation), making mindfulness a habit (ie, creating a consistent training routine is essential yet challenging), and leaning on others (ie, those engaging depend on someone else for support).

CONCLUSIONS

The themes identified in this review provide crucial insights as to why people frequently stop engaging with digital MBIs. Researchers and developers should consider using person-based coparticipatory methods to improve acceptability of and engagement with digital MBIs, increase their effectiveness, and support their translation to real-world use. Such strategies must be grounded in relevant literature and meet the priorities and needs of the individuals who will use the interventions.

The engagement problem: A review of engagement with digital mental health interventions and recommendations for a path forward

Purpose of the review

Digital mental health interventions (DMHIs) are an effective and accessible means of addressing the unprecedented levels of mental illness worldwide. Currently, however, patient engagement with DMHIs in real-world settings is often insufficient to see clinical benefit. In order to realize the potential of DMHIs, there is a need to better understand what drives patient engagement.

Recent findings

We discuss takeaways from the existing literature related to patient engagement with DMHIs and highlight gaps to be addressed through further research. Findings suggest that engagement is influenced by patient-, intervention- and systems-level factors. At the patient-level, variables such as sex, education, personality traits, race, ethnicity, age and symptom severity appear to be associated with engagement. At the intervention-level, integrating human support, gamification, financial incentives and persuasive technology features may improve engagement. Finally, although systems-level factors have not been widely explored, the existing evidence suggests that achieving engagement will require addressing organizational and social barriers and drawing on the field of implementation science.

Summary

Future research clarifying the patient-, intervention- and systems-level factors that drive engagement will be essential. Additionally, to facilitate improved understanding of DMHI engagement, we propose the following: (a) widespread adoption of a minimum necessary 5-element engagement reporting framework; (b) broader application of alternative clinical trial designs; and (c) directed efforts to build upon an initial parsimonious conceptual model of DMHI engagement.

Perspective: A Conceptual Framework for Adaptive Personalized Nutrition Advice Systems (APNASs)

Nearly all approaches to personalized nutrition (PN) use information such as the gene variants of individuals to deliver advice that is more beneficial than a generic "1-size-fits-all" recommendation. Despite great enthusiasm and the increased availability of commercial services, thus far, scientific studies have only revealed small to negligible effects on the efficacy and effectiveness of personalized dietary recommendations, even when using genetic or other individual information. In addition, from a public health perspective, scholars are critical of PN because it primarily targets socially privileged groups rather than the general population, thereby potentially widening health inequality. Therefore, in this perspective, we propose to extend current PN approaches by creating adaptive personalized nutrition advice systems (APNASs) that are tailored to the type and timing of personalized advice for individual needs, capacities, and receptivity in real-life food environments. These systems encompass a broadening of current PN goals (i.e., what should be achieved) to incorporate "individual goal preferences" beyond currently advocated biomedical targets (e.g., making sustainable food choices). Moreover, they cover the "personalization processes of behavior change" by providing in situ, "just-in-time" information in real-life environments (how and when to change), which accounts for individual capacities and constraints (e.g., economic resources). Finally, they are concerned with a "participatory dialog between individuals and experts" (e.g., actual or virtual dieticians, nutritionists, and advisors) when setting goals and deriving measures of adaption. Within this framework, emerging digital nutrition ecosystems enable continuous, real-time monitoring, advice, and support in food environments from exposure to consumption. We present this vision of a novel PN framework along with scenarios and arguments that describe its potential to efficiently address individual and population needs and target groups that would benefit most from its implementation.

Self-relevant appeals to engage in self-monitoring of alcohol use: A microrandomized trial

OBJECTIVE

While self-monitoring can help mitigate alcohol misuse in young adults, engagement with digital self-monitoring is suboptimal. The present study investigates the utility of two types of digital prompts (reminders) to encourage young adults to self-monitor their alcohol use. These prompts leverage information that is self-relevant (i.e., represents and is valuable) to the person.

METHOD

Five hundred ninety-one college students (Mage = 18; 61% = female, 76% = White) were enrolled in an 8-week intervention study involving biweekly digital self-monitoring of their alcohol use. At baseline, participants selected an item they would like to purchase for themselves and their preferred charitable organization. Then, biweekly, participants were microrandomized to a prompt highlighting the opportunity to either (a) win their preferred item (self-interest prompt); or (b) donate to their preferred charity (prosocial prompt). Following self-monitoring completion, participants allocated reward points toward lottery drawings for their preferred item or charity.

RESULTS

The self-interest (vs. prosocial) prompt was significantly more effective in promoting proximal self-monitoring at the beginning of the study, Est = exp(.14) = 1.15; 95% confidence interval (CI) [1.01, 1.29], whereas the prosocial (vs. self-interest) prompt was significantly more effective at the end, Est = exp(-.17) = 0.84; 95% CI [0.70, 0.98]. Further, the prosocial (vs. self-interest) prompt was significantly more effective among participants who previously allocated all their reward points to drawings for their preferred item, Est = exp(-.15) = 0.86; 95% CI [.75, .97].

CONCLUSIONS

These results suggest that the advantage of prompts that appeal to a person's self-interest (vs. prosocial) motives varies over time and based on what reward options participants prioritized in previous decisions. Theoretical and practical implications for intervention design are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The adoption and sustainability of digital therapeutics in justice systems: A pilot feasibility study

BACKGROUND

This study explored whether participants with substance use disorder (SUD) would adopt and use a smart-phone app with a cognitive behavioral therapy program, weekly Brief Addiction Monitor (BAM) assessments, daily check-ins, tools to track sobriety and treatment, and other patient-centered resources. In addition, participants with SUD could access a social worker and peer support specialists.

METHODS

The study sought participants from two groups: those referred by a justice-related agency and participants who responded to outreach from the Addiction Policy Forum (APF). The Connections smart-phone app was offered to both groups. The study examined use of the app and social worker/peer recovery support services by participants who downloaded and used the app; those referred by a justice-related agency and those who self-referred through APF. The app provided primary data, including socio-demographics, referral status, dates of use, activities completed, and BAM scores.

RESULTS

The app was offered to 1973 participants, 40% of whom downloaded it. Three groups emerged from among the 350 who used the app: those who used only the cognitive behavioral aspects of the app, those who used only the recovery support services offered, and those who used both the app and recovery support services. Looking at the two referral groups, the justice-referred group preferred telehealth recovery support services with the social worker; the self-referred group used the app and the app plus the recovery support services equally. Scores on the BAM improved across time. Justice-referred participants' protective behaviors improved more than those of the self-referred participants while self-referred participants' risk behaviors improved more than those of justice-referred participants. Older participants were more likely to use the app, and to report fewer risky behaviors, as measured by the BAM.

CONCLUSIONS

Use of a digital therapeutic appears to support recovery of participants with SUD although many clients need and want the integration of social worker-driven recovery support services. Basically, the app can be an extension to personal services, but many people with SUD (particularly during COVID-19) crave human interaction. It also appears that those who seek assistance on their own, rather than being referred by a justice-related agency, may be more likely to benefit from digital therapeutics such as the Connections app.

Trajectory classes of engagement with an alcohol text message intervention and predictors of intervention engagement

Digital interventions have increased our capacity to reach young adults who have hazardous alcohol use. Alcohol text message interventions have shown small effects in reducing hazardous drinking, leaving room for improvement. An important challenge to address in improving digital interventions is maintaining engagement, which reflects the "dose" of intervention received. This study aimed to identify trajectory classes of engagement with an alcohol text message intervention, and baseline predictors of the trajectory classes to determine "for whom" the digital intervention was more versus less engaging, to guide further intervention tailoring. This secondary analysis examined data from a study that compared five 12-week alcohol text message interventions designed to reduce hazardous drinking in young adults (aged 18-25; N = 1,131, 68% female) recruited from Emergency Departments in Western Pennsylvania. Engagement with the intervention was based on response (present/absent) to text message queries delivered twice per week during 2-week run-in and 12-week intervention. Repeated measures latent profile analysis identified five latent trajectory classes as having the best fit to the data: "High engagement" (55.1%), "Slow decrease, moderate engagement" (23.2%); "Mid-way decrease in engagement" (8.9%), "Steadily decreasing engagement" (8.1%); and "Fluctuating, moderate engagement" (4.6%). Females and individuals enrolled in college were overrepresented in the high engagement trajectory class, whereas individuals higher in impulsivity were more likely to be in decreasing (versus high) engagement trajectory classes. Methods to boost engagement using, for example, motivational enhancement for young adults with higher levels of impulsivity, at specific time points, such as the mid-point of the intervention, warrant consideration.

Time-varying model of engagement with digital self reporting: Evidence from smoking cessation longitudinal studies

Objective

Insufficient engagement is a critical barrier impacting the utility of digital interventions and mobile health assessments. As a result, engagement itself is increasingly becoming a target of studies and interventions. The purpose of this study is to investigate the dynamics of engagement in mobile health data collection by exploring whether, how, and why response to digital self-report prompts change over time in smoking cessation studies.

Method

Data from two ecological momentary assessment (EMA) studies of smoking cessation among diverse smokers attempting to quit (N = 573) with a total of 65,974 digital self-report prompts. We operationalize engagement with self-reporting in term of prompts delivered and prompt response to capture both broad and more granular engagement in self-reporting, respectively. The data were analyzed to describe trends in prompt delivered and prompt response over time. Time-varying effect modeling (TVEM) was employed to investigate the time-varying effects of response to previous prompt and the average response rate on the likelihood of current prompt response.

Results

Although prompt response rates were relatively stable over days in both studies, the proportion of participants with prompts delivered declined steadily over time in one of the studies, indicating that over time, fewer participants charged the device and kept it turned on (necessary to receive at least one prompt per day). Among those who did receive prompts, response rates were relatively stable. In both studies, there is a significant, positive and stable relationship between response to previous prompt and the likelihood of response to current prompt throughout all days of the study. The relationship between the average response rate prior to current prompt and the likelihood of responding to the current prompt was also positive, and increasing with time.

Conclusion

Our study highlights the importance of integrating various indicators to measure engagement in digital self-reporting. Both average response rate and response to previous prompt were highly predictive of response to the next prompt across days in the study. Dynamic patterns of engagement in digital self-reporting can inform the design of new strategies to promote and optimize engagement in digital interventions and mobile health studies.

Characterizing observed and effective behavioral engagement with smartphone cognitive behavioral therapy for body dysmorphic disorder: A methods roadmap and use case

Smartphone psychotherapies are growing in popularity, yet little is understood about (1) how people prefer to engage with psychotherapy apps, or (2) which engagement patterns constitute effective engagement. The present study uses secondary data from a 12-week randomized waitlist-controlled trial of smartphone-delivered cognitive behavioral therapy (CBT) for body dysmorphic disorder (BDD) (N = 77) to address these aims. Additionally, using the present study as a use-case, we seek to provide a roadmap for how researchers may improve upon methodological limitations of existing smartphone psychotherapy engagement research. We measured behavioral engagement via 19 objective variables derived from phone analytics data, which we reduced via factor analysis into two factors: 1) use volume and frequency, and 2) session duration. Cluster analysis based on engagement factors yielded three engager types, which mapped onto "deep" users, "samplers," and "light" users. The clusters did not differ significantly in improvement in BDD severity across treatment, although deep users improved more than light users at a marginally significant level. Results suggest that varying patterns of preferred engagement may be efficacious. Moreover, the study's methods provide an example of how researchers can measure and study behavioral engagement comprehensively and objectively. Trial Registration: ClinicalTrials.gov Identifier: NCT04034693.

Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review

BACKGROUND

Artificial intelligence (AI)-based chatbots can offer personalized, engaging, and on-demand health promotion interventions.

OBJECTIVE

The aim of this systematic review was to evaluate the feasibility, efficacy, and intervention characteristics of AI chatbots for promoting health behavior change.

METHODS

A comprehensive search was conducted in 7 bibliographic databases (PubMed, IEEE Xplore, ACM Digital Library, PsycINFO, Web of Science, Embase, and JMIR publications) for empirical articles published from 1980 to 2022 that evaluated the feasibility or efficacy of AI chatbots for behavior change. The screening, extraction, and analysis of the identified articles were performed by following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

Of the 15 included studies, several demonstrated the high efficacy of AI chatbots in promoting healthy lifestyles (n=6, 40%), smoking cessation (n=4, 27%), treatment or medication adherence (n=2, 13%), and reduction in substance misuse (n=1, 7%). However, there were mixed results regarding feasibility, acceptability, and usability. Selected behavior change theories and expert consultation were used to develop the behavior change strategies of AI chatbots, including goal setting, monitoring, real-time reinforcement or feedback, and on-demand support. Real-time user-chatbot interaction data, such as user preferences and behavioral performance, were collected on the chatbot platform to identify ways of providing personalized services. The AI chatbots demonstrated potential for scalability by deployment through accessible devices and platforms (eg, smartphones and Facebook Messenger). The participants also reported that AI chatbots offered a nonjudgmental space for communicating sensitive information. However, the reported results need to be interpreted with caution because of the moderate to high risk of internal validity, insufficient description of AI techniques, and limitation for generalizability.

CONCLUSIONS

AI chatbots have demonstrated the efficacy of health behavior change interventions among large and diverse populations; however, future studies need to adopt robust randomized control trials to establish definitive conclusions.

A pilot intervention of using a mobile health app (ONC Roadmap) to enhance health-related quality of life in family caregivers of pediatric patients with cancer

Background

The Roadmap mobile health (mHealth) app was developed to provide health-related quality of life (HRQOL) support for family caregivers of patients with cancer.

Methods

Eligibility included: family caregivers (age ≥18 years) who self-reported as the primary caregiver of their pediatric patient with cancer; patients (age ≥5 years) who were receiving cancer care at the University of Michigan. Feasibility was calculated as the percentage of caregivers who logged into ONC Roadmap and engaged with it at least twice weekly for at least 50% of the 120-day study duration. Feasibility and acceptability was also assessed through a Feasibility and Acceptability questionnaire and the Mobile App Rating Scale to specifically assess app-quality. Exploratory analyses were also conducted to assess HRQOL self- or parent proxy assessments and physiological data capture.

Results

Between September 2020-September 2021, 100 participants (or 50 caregiver-patient dyads) consented and enrolled in the ONC Roadmap study for 120-days. Feasibility of the study was met, wherein the majority of caregivers (N=32; 65%) logged into ONC Roadmap and engaged with it at least twice weekly for at least 50% of the study duration (defined a priori in the Protocol). The Feasibility and Acceptability questionnaire responses indicated that the study was feasible and acceptable with the majority (>50%) reporting Agree or Strongly Agree with positive Net Favorability [(Agree + Strongly Agree) - (Disagree + Totally Disagree)] in each of the domains (e.g., Fitbit use, ONC Roadmap use, completing longitudinal assessments, engaging in similar future study, study expectations). Improvements were seen across the majority of the mental HRQOL domains across all groups; even though underpowered, there were significant improvements in caregiver-specific aspects of HRQOL and anxiety and in depression and fatigue for children (ages 8-17 years), and a trend toward improvement in depression for children ages 8-17 years and in fatigue for adult patients.

Conclusions

This study supports that mHealth technology may be a promising platform to provide HRQOL support for caregivers of pediatric patients with cancer. Importantly, the findings suggest that the study protocol was feasible, and participants were favorable to participate in future studies of this intervention alongside routine cancer care delivery.

Intervention targeting and retention, engagement and abstinence outcomes among Latino and White users of Smokefree.gov text messaging programmes: a cross-sectional study

Background

We examined retention, engagement, and abstinence among Latino users of SmokefreeTXT en Español (SFTXTesp), a Latino-targeted text messaging smoking cessation intervention, and Latino and White users of SmokefreeTXT (SFTXT), a non-targeted intervention.

Methods

Data came from 12281 users (1562 Latino SFTXTesp users and 2301 Latino and 8418 White SFTXT users). We conducted time-to-dropout analyses by race/ethnicity. Using logistic regression, we examined associations between intervention targeting, race/ethnicity, and responses to smoking status prompts, an engagement metric, and self-reported abstinence on quit day, intervention end, and one-month follow-up. Age, gender, census region, smoking frequency, cigarettes smoked per day, prequit time, and number of quit attempts were covariates.

Results

Latinos in SFTXTesp (aOR 0.63) and SFTXT (0.88) were less likely to drop out of the intervention than Whites. SFTXTesp Latino users had higher response rates to smoking prompts than SFTXT Latinos users (aORs 1.35, quit day; 1.84, intervention end; 1.82, one-month follow-up). However, SFTXTesp and SFTXT Latino users had lower response rates than Whites (aORs 0.68, 0.45, quit day; 0.60, 0.30, intervention end; 0.64, 0.33, one-month follow-up). Abstinence was equivalent among Latinos in SFTXTesp and SFTXT interventions, but Latinos using SFTXTesp and SFTXT were less likely to be abstinent than Whites (aORs 0.42, 0.41, quit day; 0.45, 0.37, intervention end; and 0.53, 0.35, one-month follow-up).

Conclusion

Linguistic intervention targeting improved retention and engagement among Latinos, but not abstinence. Latinos had higher retention but lower engagement and abstinence rates than Whites. Cultural targeting may engage Latinos in smoking cessation interventions and improve abstinence.

End User Participation in the Development of an Ecological Momentary Intervention to Improve Coping With Cannabis Cravings: Formative Study

BACKGROUND

Cannabis misuse in young adults is a major public health concern. An important predictor of continued use is cannabis craving. Due to the time-varying nature of cravings, brief momentary interventions delivered while cravings are elevated may improve the use of strategies to cope with cravings and reduce cannabis use.

OBJECTIVE

The goal of this manuscript is to describe a formative study to develop coping strategy messages for use in a subsequent intervention.

METHODS

Young adults (aged 19-25 years; n=20) who reported using cannabis >10 of the past 30 days recruited via social media participated in this formative study. Participants rated an initial set of 15 mindfulness and 15 distraction coping strategies on a scale from 1 to 4 (very low degree to very high degree) for clarity, usefulness, and tone. They also provided comments about the content.

RESULTS

Participants found the initial distraction messages slightly clearer than mindfulness (mean 3.5, SD 0.4 and mean 3.4, SD 0.4, respectively), both were comparable in tone (mean 3.2, SD 0.5 and mean 3.2, SD 0.4, respectively), and mindfulness messages were more useful than distraction (mean 3.0, SD 0.5 and mean 2.8, SD 0.6, respectively). Of the 30 messages, 29 received a rating of very low or low (<2) on any domain by >3 participants or received a comment suggesting a change. We revised all these messages based on this feedback, and the participants rated the revised messages approximately 2 weeks later. Participants earned US $10 for completing the first and US $20 for the second survey. The ratings improved on usefulness (especially the distraction items) with very little change in clarity and tone. The top 10 messages of each coping type (mindfulness and distraction) were identified by overall average rating (collapsed across all 3 dimensions: all rated >3.0). The final items were comparable in clarity (distraction mean 3.6, SD 0.4; mindfulness mean 3.6, SD 0.4), tone (distraction mean 3.4, SD 0.4; mindfulness mean 3.4, SD 0.4), and usefulness (distraction mean 3.1, SD 0.5; mindfulness mean 3.2, SD 0.5).

CONCLUSIONS

The inclusion of end users in the formative process of developing these messages was valuable and resulted in improvements to the content of the messages. The majority of the messages were changed in some way including the removal of potentially triggering language. These messages were subsequently used in an ecological momentary intervention.

Patterns of Engagement With an Application-Based Dietary Self-Monitoring Tool Within a Randomized Controlled Feasibility Trial

Introduction

The Dietary Approaches to Stop Hypertension dietary pattern is a proven way to manage hypertension, but adherence remains low. Dietary tracking applications offer a highly disseminable way to self-monitor intake on the pathway to reaching dietary goals but require consistent engagement to support behavior change. Few studies use longitudinal dietary self-monitoring data to assess trajectories and predictors of engagement. We used dietary self-monitoring data from participants in Dietary Approaches to Stop Hypertension Cloud (N=59), a feasibility trial to improve diet quality among women with hypertension, to identify trajectories of engagement and explore associations between participant characteristics.

Methods

We used latent class growth modeling to identify trajectories of engagement with a publicly available diet tracking application and used bivariate and regression analyses to assess the associations of classifications of engagement with participant characteristics.

Results

We identified 2 latent classes of engagement: consistent engagers and disengagers. Consistent engagers were more likely to be older, more educated, and married or living with a partner. Although consistent engagers exhibited slightly greater changes in Dietary Approaches to Stop Hypertension score, the difference was not significant.

Conclusions

This study highlights an important yet underutilized methodologic approach for uncovering dietary self-monitoring engagement patterns. Understanding how certain individuals engage with digital technologies is an important step toward designing cost-effective behavior change interventions.

Trial registration

This study is registered at www.clinicaltrials.gov NCT03215472.

Digital mental health interventions for chronic serious mental illness: Findings from a qualitative study on usability and scale-up of the Life Goals app for bipolar disorder

The Life Goals (LG) application is an evidence-based self-management tool intended to help individuals with bipolar disorder (BD) by aligning symptom coping strategies with personal goals. The program has traditionally been offered in-person or via the web, but has recently been translated into an individualized, customizable mobile intervention to improve access to care and reduce provider burden. The LG app previously showed acceptability with ease of use and satisfaction with user interface, but less success in encouraging self-management. To better understand patient needs, our team conducted semi-structured interviews with 18 individuals with BD who used the LG app for 6 months. These interviews also investigated participant interest in sharing LG app data with their provider through an online dashboard. Using affinity mapping, a collaborative, qualitative data analysis technique, our team identified emerging common themes in the interviews. Through this process, team members identified 494 pieces of salient information from interviews that were mapped and translated into three main findings: (1) many participants found Mood Monitoring and LG modules helpful/interesting and stated the app overall had positive impacts on their mental health, (2) some components of the app were too rudimentary or impersonal to be beneficial, and (3) feedback was mixed regarding future implementation of an LG provider dashboard, with some participants seeing potential positive impacts and others hesitating due to perceived efficacy and privacy concerns. These findings can help researchers improve app-based interventions for individuals with BD by increasing app usage and improving care overall.

An app-based just-in-time-adaptive self-management intervention for care partners: The CareQOL feasibility pilot study

PURPOSE/OBJECTIVE

The primary objective of this study was to establish the feasibility and acceptability of an intensive data collection protocol that involves the delivery of a personalized just-in-time adaptive intervention (JITAI) in three distinct groups of care partners (care partners of persons with spinal cord injury [SCI], Huntington's disease [HD], or hematopoietic cell transplantation [HCT]).

RESEARCH METHOD/DESIGN

Seventy care partners were enrolled in this study (n = 19 SCI; n = 21 HD, n = 30 HCT). This three-month (90 day) randomized control trial involved wearing a Fitbit to track sleep and steps, providing daily reports of health-related quality of life (HRQOL), and completing end of month HRQOL surveys. Care partners in the JITAI group also received personalized pushes (i.e., text-based phone notifications that include brief tips or suggestions for improving self-care). At the end of three-months, care partners in both groups completed a feasibility and acceptability questionnaire.

RESULTS

Most (98.6%) care partners completed the study, average compliance was 88% for daily HRQOL surveys, 96% for daily steps, and 85% for daily sleep (from wearing the Fitbit), and all monthly surveys were completed with the exception of one missed 3-month assessment. The acceptability of the protocol was high; ratings exceeded 80% agreement for the different elements of the study. Improvements were seen for the majority of the HRQOL measures. There was no evidence of measurement reactivity.

CONCLUSIONS/IMPLICATIONS

Findings provide strong support for the acceptability and feasibility of an intensive data collection protocol that involved the administration of a JITAI. Although this trial was not powered to establish efficacy, findings indicated improvements across a variety of different HRQOL measures (~1/3 of which were statistically significant). (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Enhancing Resilience in Family Caregivers Using an mHealth App

BACKGROUND

We previously developed a mobile health (mHealth) app (Roadmap) to promote the resilience of family caregivers during the acute phases of care in patients undergoing hematopoietic cell transplantation (HCT).

OBJECTIVE

This study explored users' perspectives on the uptake of Roadmap's multicomponent features and the app's utility in promoting resilience.

METHODS

Fifteen participants were randomized to the full version of the app that included resilience-building activities and the other 15 were randomized to the control version that included a limited view of the app (i.e., without any resilience-building activities). They were instructed to use the app for 120 days. Semistructured qualitative interviews were then conducted with users as part of an ongoing, larger Roadmap study (NCT04094844). During the interview, caregiver participants were asked about their overall experiences with the app, frequency of use, features used, facilitators of and barriers to use, and their perspectives on its utility in promoting resilience. Data were professionally transcribed, coded, and categorized through content analysis.

RESULTS

Interviews were conducted with 30 participants, which included 23 females and 7 males. The median age of the population was 58 years (range, 23-82). The four main themes that emerged included app use, ease of use, user experiences, and ability to foster resilience. The subthemes identified related to facilitators (convenience and not harmful), barriers (caregiver burden and being too overwhelmed during the acute phases of HCT care), resilience (optimism/positivity and self-care), and app design improvements (personalization and notifications/reminders).

CONCLUSION

The qualitative evaluation provided insights into which components were utilized and how one, or a combination of the multicomponent features, may be enhancing users' experiences. Lessons learned suggest that the Roadmap app contributed to promoting resilience during the acute phases of HCT care. Nonetheless, features that provided enhanced personalization may further improve longer-term engagement.

Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series

BACKGROUND

Engagement with mental health smartphone apps is an understudied but critical construct to understand in the pursuit of improved efficacy.

OBJECTIVE

This study aimed to examine engagement as a multidimensional construct for a novel app called HabitWorks. HabitWorks delivers a personalized interpretation bias intervention and includes various strategies to enhance engagement such as human support, personalization, and self-monitoring.

METHODS

We examined app use in a pilot study (n=31) and identified 5 patterns of behavioral engagement: consistently low, drop-off, adherent, high diary, and superuser.

RESULTS

We present a series of cases (5/31, 16%) from this trial to illustrate the patterns of behavioral engagement and cognitive and affective engagement for each case. With rich participant-level data, we emphasize the diverse engagement patterns and the necessity of studying engagement as a heterogeneous and multifaceted construct.

CONCLUSIONS

Our thorough idiographic exploration of engagement with HabitWorks provides an example of how to operationalize engagement for other mental health apps.

Adaptation and Dissemination of a National Cancer Institute HPV Vaccine Evidence-Based Cancer Control Program to the Social Media Messaging Environment

Social media offers a unique opportunity to widely disseminate HPV vaccine messaging to reach youth and parents, given the information channel has become mainstream with 330 million monthly users in the United States and 4.2 billion users worldwide. Yet, a gap remains on how to adapt evidence-based vaccine interventions for the in vivo competitive social media messaging environment and what strategies to employ to make vaccine messages go viral. Push-pull and RE-AIM dissemination frameworks guided our adaptation of a National Cancer Institute video-based HPV vaccine cancer control program, the HPV Vaccine Decision Narratives, for the social media environment. We also aimed to understand how dissemination might differ across three platforms, namely Instagram, TikTok, and Twitter, to increase reach and engagement. Centering theory and a question-answer framework guided the adaptation process of segmenting vaccine decision story videos into shorter coherent segments for social media. Twelve strategies were implemented over 4 months to build a following and disseminate the intervention. The evaluation showed that all platforms increased following, but Instagram and TikTok outperformed Twitter on impressions, followers, engagement, and reach metrics. Although TikTok increased reach the most (unique accounts that viewed content), Instagram increased followers, engagement, and impressions the most. For Instagram, the top performer, six of 12 strategies contributed to increasing reach, including the use of videos, more than 11 hashtags, COVID-19 hashtags, mentions, and follow-for-follow strategies. This observational social media study identified dissemination strategies that significantly increased the reach of vaccine messages in a real-world competitive social media messaging environment. Engagement presented greater challenges. Results inform the planning and adaptation considerations necessary for transforming public health HPV vaccine interventions for social media environments, with unique considerations depending on the platform.

Mapping User Engagement in Digital Psychotherapy: An Integrative Engagement Model (Preprint)

BACKGROUND

Digital mental health interventions, such as 2-way and asynchronous messaging therapy, are a growing part of the mental health care treatment ecosystem, yet little is known about how users engage with these interventions over the course of their treatment journeys. User engagement, or client behaviors and therapeutic relationships that facilitate positive treatment outcomes, is a necessary condition for the effectiveness of any digital treatment. Developing a better understanding of the factors that impact user engagement can impact the overall effectiveness of digital psychotherapy. Mapping the user experience in digital therapy may be facilitated by integrating theories from several fields. Specifically, health science's Health Action Process Approach and human-computer interaction's Lived Informatics Model may be usefully synthesized with relational constructs from psychotherapy process-outcome research to identify the determinants of engagement in digital messaging therapy.

OBJECTIVE

This study aims to capture insights into digital therapy users' engagement patterns through a qualitative analysis of focus group sessions. We aimed to synthesize emergent intrapersonal and relational determinants of engagement into an integrative framework of engagement in digital therapy.

METHODS

A total of 24 focus group participants were recruited to participate in 1 of 5 synchronous focus group sessions held between October and November 2021. Participant responses were coded by 2 researchers using thematic analysis.

RESULTS

Coders identified 10 relevant constructs and 24 subconstructs that can collectively account for users' engagement and experience trajectories in the context of digital therapy. Although users' engagement trajectories in digital therapy varied widely, they were principally informed by intrapsychic factors (eg, self-efficacy and outcome expectancy), interpersonal factors (eg, the therapeutic alliance and its rupture), and external factors (eg, treatment costs and social support). These constructs were organized into a proposed Integrative Engagement Model of Digital Psychotherapy. Notably, every participant in the focus groups indicated that their ability to connect with their therapist was among the most important factors that were considered in continuing or terminating treatment.

CONCLUSIONS

Engagement in messaging therapy may be usefully approached through an interdisciplinary lens, linking constructs from health science, human-computer interaction studies, and clinical science in an integrative engagement framework. Taken together, our results suggest that users may not view the digital psychotherapy platform itself as a treatment so much as a means of gaining access to a helping provider, that is, users did not see themselves as engaging with a platform but instead viewed their experience as a healing relationship. The findings of this study suggest that a better understanding of user engagement is crucial for enhancing the effectiveness of digital mental health interventions, and future research should continue to explore the underlying factors that contribute to engagement in digital mental health interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04507360; https://clinicaltrials.gov/ct2/show/NCT04507360.

Hybrid Experimental Designs for Intervention Development: What, Why, and How

Advances in mobile and wireless technologies offer tremendous opportunities for extending the reach and impact of psychological interventions and for adapting interventions to the unique and changing needs of individuals. However, insufficient engagement remains a critical barrier to the effectiveness of digital interventions. Human delivery of interventions (e.g., by clinical staff) can be more engaging but potentially more expensive and burdensome. Hence, the integration of digital and human-delivered components is critical to building effective and scalable psychological interventions. Existing experimental designs can be used to answer questions either about human-delivered components that are typically sequenced and adapted at relatively slow timescales (e.g., monthly) or about digital components that are typically sequenced and adapted at much faster timescales (e.g., daily). However, these methodologies do not accommodate sequencing and adaptation of components at multiple timescales and hence cannot be used to empirically inform the joint sequencing and adaptation of human-delivered and digital components. Here, we introduce the hybrid experimental design (HED)-a new experimental approach that can be used to answer scientific questions about building psychological interventions in which human-delivered and digital components are integrated and adapted at multiple timescales. We describe the key characteristics of HEDs (i.e., what they are), explain their scientific rationale (i.e., why they are needed), and provide guidelines for their design and corresponding data analysis (i.e., how can data arising from HEDs be used to inform effective and scalable psychological interventions).

Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review

Background

Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions.

Objective

This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks.

Methods

A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings.

Results

The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%).

Conclusions

This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app’s intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.