Engagement with eHealth Self-Monitoring in a Primary Care-Based Weight Management Intervention

Patterns and Predictors of Engagement With Digital Self-Monitoring During the Maintenance Phase of a Behavioral Weight Loss Program: Quantitative Study

BACKGROUND

Long-term self-monitoring (SM) of weight, diet, and exercise is commonly recommended by behavioral weight loss (BWL) treatments. However, sustained SM engagement is notoriously challenging; therefore, more must be learned about patterns of engagement with digital SM tools during weight loss maintenance (WLM). In addition, insight into characteristics that may influence SM engagement could inform tailored approaches for participants at risk for poor adherence.

OBJECTIVE

This study explored patterns of digital SM of weight, diet, and exercise during WLM (aim 1) and examined timing, patterns, and rates of disengagement and reengagement (aim 2). This study also assessed relationships between individual-level factors (weight-related information avoidance and weight bias internalization) and SM engagement (aim 3).

METHODS

Participants were 72 adults enrolled in a BWL program consisting of a 3-month period of weekly treatment designed to induce weight loss (phase I), followed by a 9-month period of less frequent contact to promote WLM (phase II). Participants were prescribed daily digital SM of weight, diet, and exercise. At baseline, self-report measures assessed weight-related information avoidance and weight bias internalization. SM adherence was objectively measured with the days per month that participants tracked weight, diet, and exercise. Repeated-measures ANOVA examined differences in adherence across SM targets. Multilevel modeling examined changes in adherence across phase II. Relationships between individual-level variables and SM adherence were assessed with Pearson correlations, 2-tailed independent samples t tests, and multilevel modeling.

RESULTS

During WLM, consistently high rates of SM (≥50% of the days in each month) were observed for 61% (44/72) of the participants for exercise, 40% (29/72) of the participants for weight, and 21% (15/72) of the participants for diet. Adherence for SM of exercise was higher than that for weight or diet (P<.001). Adherence decreased over time for all SM targets throughout phase II (P<.001), but SM of exercise dropped off later in WLM (mean 10.07, SD 2.83 months) than SM of weight (mean 7.92, SD 3.23 months) or diet (mean 7.58, SD 2.92 months; P<.001). Among participants with a period of low SM adherence (ie, <50% of the days in a month), only 33% (17/51 for weight, 19/57 for diet) to 46% (13/28 for exercise) subsequently had ≥1 months with high adherence. High weight-related information avoidance predicted a faster rate of decrease in dietary SM (P<.001). Participants with high weight bias internalization had the highest rates of weight SM (P=.03).

CONCLUSIONS

Participants in BWL programs have low adherence to the recommendation to sustain daily SM during WLM, particularly for SM of diet and weight. Weight-related information avoidance and weight bias internalization may be relevant indicators for SM engagement. Interventions may benefit from innovative strategies that target participants at key moments of risk for disengagement.

Effectiveness of Mobile Phone and Web-Based Interventions for Diabetes and Obesity Among African American and Hispanic Adults in the United States: Systematic Review

Background

Mobile health (mHealth) and web-based technological advances allow for new approaches to deliver behavioral interventions for chronic diseases such as obesity and diabetes. African American and Hispanic adults experience a disproportionate burden of major chronic diseases.

Objective

This paper reviews the evidence for mHealth and web-based interventions for diabetes and obesity in African American and Hispanic adults.

Methods

Literature searches of PubMed/Medline, The Cochrane Library, EMBASE, CINAHL Plus, Global Health, Scopus, and Library & Information Science Source were conducted for relevant English-language articles. Articles identified through searches were reviewed by 2 investigators and, if they met the inclusion criteria, were extracted and assessed for risk of bias. Findings were summarized in tabular and narrative format. The overall strength of the evidence was assessed as high, moderate, low, or insufficient on the basis of risk of bias, consistency of findings, directness, precision, and other limitations.

Results

Searches yielded 2358 electronic publications, 196 reports were found to be eligible for inclusion, and 7 studies met the eligibility criteria. All 7 included studies were randomized control trials. Five studies evaluated the effectiveness of an mHealth intervention for weight loss, including one that evaluated the effectiveness for diabetes and two studies focused on diabetes. Of all the studies that focused on weight loss, 3 reported significant differences in weight loss in participants in the intervention group compared with those in the usual care group. Although all studies on diabetes control showed greater improvement in glycemic control for the intervention group compared to that in the control group, only one study showed a significant difference between the 2 groups.

Conclusions

This analysis indicates that there are few published studies that assessed mHealth interventions among minority populations and focused on weight or diabetes. Although the overall strength of evidence was low for diabetes control, it was moderate for weight loss, and our findings suggest that mHealth and web-based interventions may provide a promising approach for interventions among African American and Hispanic adults who have obesity or diabetes.

Digital Health Interventions to Enhance Prevention in Primary Care: Scoping Review

Background

Disease prevention is a central aspect of primary care practice and is comprised of primary (eg, vaccinations), secondary (eg, screenings), tertiary (eg, chronic condition monitoring), and quaternary (eg, prevention of overmedicalization) levels. Despite rapid digital transformation of primary care practices, digital health interventions (DHIs) in preventive care have yet to be systematically evaluated.

Objective

This review aimed to identify and describe the scope and use of current DHIs for preventive care in primary care settings.

Methods

A scoping review to identify literature published from 2014 to 2020 was conducted across multiple databases using keywords and Medical Subject Headings terms covering primary care professionals, prevention and care management, and digital health. A subgroup analysis identified relevant studies conducted in US primary care settings, excluding DHIs that use the electronic health record (EHR) as a retrospective data capture tool. Technology descriptions, outcomes (eg, health care performance and implementation science), and study quality as per Oxford levels of evidence were abstracted.

Results

The search yielded 5274 citations, of which 1060 full-text articles were identified. Following a subgroup analysis, 241 articles met the inclusion criteria. Studies primarily examined DHIs among health information technologies, including EHRs (166/241, 68.9%), clinical decision support (88/241, 36.5%), telehealth (88/241, 36.5%), and multiple technologies (154/241, 63.9%). DHIs were predominantly used for tertiary prevention (131/241, 54.4%). Of the core primary care functions, comprehensiveness was addressed most frequently (213/241, 88.4%). DHI users were providers (205/241, 85.1%), patients (111/241, 46.1%), or multiple types (89/241, 36.9%). Reported outcomes were primarily clinical (179/241, 70.1%), and statistically significant improvements were common (192/241, 79.7%). Results were summarized across the following 5 topics for the most novel/distinct DHIs: population-centered, patient-centered, care access expansion, panel-centered (dashboarding), and application-driven DHIs. The quality of the included studies was moderate to low.

Conclusions

Preventive DHIs in primary care settings demonstrated meaningful improvements in both clinical and nonclinical outcomes, and across user types; however, adoption and implementation in the US were limited primarily to EHR platforms, and users were mainly clinicians receiving alerts regarding care management for their patients. Evaluations of negative results, effects on health disparities, and many other gaps remain to be explored.

Effective behavior change techniques to promote physical activity in adults with overweight or obesity: A systematic review and meta-analysis

Multicomponent behavior change interventions are typically used in weight management, but results are largely heterogeneous and modest. Determining which techniques (behavior change technique [BCTs]) are more effective in changing behavior is thus required. This study aimed to identify the most effective BCTs for increasing physical activity (PA) in digital and face-to-face behavior change interventions in adults with overweight/obesity. Four databases were searched for eligible studies until October 2019. BCTs were coded using BCTTv1 and MBCT taxonomies. Sixty-two RCTs were included. Meta-regressions were performed to explore BCTs' moderating role. Five BCTs showed significant moderator effects on PA in digital interventions: goal setting behavior, goal setting outcome, graded tasks, social incentive, and self-monitoring of behavior (adjusted R² 's = 0.15-0.51). One BCT showed significant moderator effects on PA in face-to-face interventions, behavioral practice and rehearsal (adjusted R²  = 0.22). Multivariate and sensitivity analysis generally led to similar findings. Effective BCTs for increasing PA in adults with overweight/obesity in digital and face-to-face interventions seem to differ. Evidence suggests that using goal setting, social incentive, and graded tasks might help improve PA in digital interventions while avoiding inconsistent self-monitoring of behavior. In face-to-face interventions, prompting behavioral practice and rehearsal might lead to better PA outcomes. Still, further studies are needed. Implications of the current findings are discussed.

Patient characteristics associated with objective measures of digital health tool use in the United States: A literature review

OBJECTIVE

The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.

MATERIALS AND METHODS

We conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics.

RESULTS

We included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use.

DISCUSSION

Given the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed.

CONCLUSION

Few studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use.

Self-Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity

OBJECTIVE

Self-monitoring is a core component of behavioral obesity treatment, but it is unknown how digital health has been used for self-monitoring, what engagement rates are achieved in these interventions, and how self-monitoring and weight loss are related.

METHODS

This systematic review examined digital self-monitoring in behavioral weight loss interventions among adults with overweight or obesity. Six databases (PubMed, Embase, Scopus, PsycInfo, CINAHL, and ProQuest Dissertations & Theses) were searched for randomized controlled trials with interventions ≥ 12 weeks, weight outcomes ≥ 6 months, and outcomes on self-monitoring engagement and their relationship to weight loss.

RESULTS

Thirty-nine studies from 2009 to 2019 met inclusion criteria. Among the 67 interventions with digital self-monitoring, weight was tracked in 72% of them, diet in 81%, and physical activity in 82%. Websites were the most common self-monitoring modality, followed by mobile applications, wearables, electronic scales, and, finally, text messaging. Few interventions had digital self-monitoring engagement rates ≥ 75% of days. Rates were higher in digital- than in paper-based arms in 21 out of 34 comparisons and lower in just 2. Interventions with counseling had similar rates to standalone interventions. Greater digital self-monitoring was linked to weight loss in 74% of occurrences.

CONCLUSIONS

Self-monitoring via digital health is consistently associated with weight loss in behavioral obesity treatment.

The Effectiveness of Interactivity in Improving Mediating Variables, Behaviors and Outcomes of Web-Based Health Interventions: A Meta-Analytic Review

Despite the increasing amount of research investigating health interventions that applies to interactive computer technology, the effect sizes in Cohen's d obtained across these studies range from -0.32 to 1.74. The lack of systematic review of interactive health interventions leaves their overall effectiveness unknown. To address this, a meta-analysis of 67 studies examining the effects of web-based interactive health interventions was conducted. Results indicated that web-based interactive health interventions were effective in general, but the effects were moderated by health topic, theoretical framework, and design of treatment and control groups. The unique advantage of interactivity was small but significant when comparing to health interventions with comparable information in non-interactive version. Theoretical and practical implications of findings were discussed.

Sustaining eHealth engagement in a multi-year weight gain prevention intervention

INTRODUCTION

Digital tools are widely used and effective in weight management interventions; however, usage declines over time. Strategies to promote continued engagement should be explored. We examined the effects of offering additional modes of weight reporting as well as periodic online campaigns to promote engagement, assessed by frequency of weight reporting, in a weight gain prevention study for young adults.

METHODS

Using an observational design, self-reported weights obtained through digital tools were pooled across participants assigned to two interventions (n = 312). Analysis examined the effects before during and after introduction of an additional reporting modality (email) and for three time-limited refresher campaigns over 2 years.

RESULTS

Adding a new modality to the three existing modes (SMS, web, and mobile web) increased weight reporting as well as the number of modalities participants used to report weights. The use of several modes of reporting was associated with more weights submitted (p < 0.01). Refresher campaigns did not increase the proportion of participants reporting; however, the number of weights submitted during the 4-week campaigns increased compared with the 4 weeks before the campaign (p's ≥ 0.45, <0.001, respectively).

CONCLUSION

Using multiple digital modalities and periodic campaigns shows promise for sustaining engagement with weight reporting in a young adult population, and incorporating such strategies may mitigate typical declines in eHealth and mHealth interventions.

The My Body Knows When Program Increased Intuitive Eating Characteristics in a Military Population

Introduction

The purpose of this pilot study was to assess the effectiveness of the revised My Body Knows When (MBKW) program to promote intuitive eating behaviors within a sample of a military population through an online or in-person delivery mode.

Materials and Methods

Fifty-six overweight or obese adults (70% female); military service members (20%), retirees (38%) and family (42%) participated in the 10-week MBKW program at two military installations from 2012 to 2014. Body Mass Index, Intuitive Eating Scale-2 (IES-2; 23-item) and Motivation for Eating scale (MFES; 43-item) were collected at baseline and 10-weeks. Data were stratified by sex. Descriptive data were reported as mean ± standard deviation (SD), frequency, or percentage. A paired t-test was conducted with data at baseline and 10 weeks (α = 0.05, 80% power).

Results

Participants were predominantly female (70%); mean age of 51 ± 13 years; and BMI of 34.1 ± 5.5 kg/m2. There were no demographic, MFES, or IES-2 baseline differences between groups (in-person vs. online) or location. All subjects were collapsed into one group for a pre-post MBKW implementation assessment due to small sample size despite the original intent to stratify by online and in-person grouping. At 10 weeks, the remaining 26 participants exhibited a significant improvement (mean ± SD) in BMI (−0.4 ± 0.6 kg/m2; p = 0.012), environmental/social eating score (2.7 ± 0.4 points [pts]; −0.5 pt change; p < 0.001), emotional eating score (2.2 ± 0.5 pts; −0.6 pt change; p = 0.001), unconditional permission to eat score (3.4 ± 0.4 pts; +0.3 pt change; p = 0.017), eating for physical rather than emotional eating score (3.7 ± 0.8 pts; +1.0 pt change; p < 0.001), and reliance on hunger and satiety cues score (3.6 ± 0.5 pts; +0.8 pt change; p = 0.001). High attrition rates at the 10-week follow-up assessment precluded accurate assessment of long-term intervention effects.

Conclusions

The MBKW program was associated with improved intuitive eating behaviors and with less external eating influence on behavior; however, a larger sample is required to assess the effectiveness of MBKW delivery mode. Modest weight loss was attained but testing the efficacy of the MBKW program in a large diverse sample with alternate scenarios may be worthwhile (e.g., primary prevention against weight gain, or during weight maintenance to prevent weight regain).

Digital Weight Loss Intervention for Parents of Children Being Treated for Obesity: A Prospective Cohort Feasibility Trial

BACKGROUND

The prevalence of childhood obesity continues to increase, and clinic-based treatment options have failed to demonstrate effectiveness. One of the strongest predictors of child weight is parent weight. Parental treatment for weight loss may indirectly reduce obesity in the child. We have previously demonstrated the effectiveness among adults of a fully automated, evidence-based digital weight loss intervention (Track). However, it is unknown if it is feasible to deliver such a treatment directly to parents with obesity who bring their child with obesity to a weight management clinic for treatment.

OBJECTIVE

The objective of our study was to evaluate the feasibility of and engagement with a digital weight loss intervention among parents of children receiving treatment for obesity.

METHODS

We conducted a 6-month pre-post feasibility trial among parents or guardians and their children aged 4-16 years presenting for tertiary care obesity treatment. Along with the standard family-based treatment protocol, parents received a 6-month digital weight loss intervention, which included weekly monitoring of personalized behavior change goals via mobile technologies. We examined levels of engagement by tracking completed weeks of self-monitoring and feasibility by assessing change in weight.

RESULTS

Participants (N=48) were on average 39 years old, mostly female (35/42, 82% ), non-Hispanic Black individuals (21/41, 51%) with obesity (36/48, 75%). Over a quarter had a yearly household income of <US $25,000, and about a third had the equivalent of a high school education. Children were on average 10 years old and had a body mass index of 29.8 kg/m². The median percentage of weeks participants tracked their behaviors was 77% (18.5/24 total weeks; interquartile range [IQR] 6.3 to 100). The median number of attempts via phone or text message (short message service) required to complete one tracking week was 3.3 (IQR 2.6 to 4.9). Nearly half (23/48, 48%) had high levels of engagement, completing 80% (19/24) or more weeks of tracking. Of the 26 participants with weight measurements reported at 6 months, of which 81% (21/26) were self-reported, there was a median 2.44 kg (IQR -6.5 to 1.0) decrease in weight.

CONCLUSIONS

It is feasible to deliver an evidence-based digital weight loss intervention to parents or guardians whose children are enrolled in a weight management program. Given the feasibility of this approach, future studies should investigate the effectiveness of digital weight loss interventions for parents on child weight and health outcomes.

The Association Between Engagement and Weight Loss Through Personal Coaching and Cell Phone Interventions in Young Adults: Randomized Controlled Trial

Background

Understanding how engagement in mobile health (mHealth) weight loss interventions relates to weight change may help develop effective intervention strategies.

Objective

This study aims to examine the (1) patterns of participant engagement overall and with key intervention components within each intervention arm in the Cell Phone Intervention For You (CITY) trial; (2) associations of engagement with weight change; and (3) participant characteristics related to engagement.

Methods

The CITY trial tested two 24-month weight loss interventions. One was delivered with a smartphone app (cell phone) containing 24 components (weight tracking, etc) and included prompting by the app in predetermined frequency and forms. The other was delivered by a coach via monthly calls (personal coaching) supplemented with limited app components (18 overall) and without any prompting by the app. Engagement was assessed by calculating the percentage of days each app component was used and the frequency of use. Engagement was also examined across 4 weight change categories: gained (≥2%), stable (±2%), mild loss (≥2% to <5%), and greater loss (≥5%).

Results

Data from 122 cell phone and 120 personal coaching participants were analyzed. Use of the app was the highest during month 1 for both arms; thereafter, use dropped substantially and continuously until the study end. During the first 6 months, the mean percentage of days that any app component was used was higher for the cell phone arm (74.2%, SD 20.1) than for the personal coaching arm (48.9%, SD 22.4). The cell phone arm used the apps an average of 5.3 times/day (SD 3.1), whereas the personal coaching participants used them 1.7 times/day (SD 1.2). Similarly, the former self-weighed more than the latter (57.1% days, SD 23.7 vs 32.9% days, SD 23.3). Furthermore, the percentage of days any app component was used, number of app uses per day, and percentage of days self-weighed all showed significant differences across the 4 weight categories for both arms. Pearson correlation showed a negative association between weight change and the percentage of days any app component was used (cell phone: r=−.213; personal coaching: r=−.319), number of apps use per day (cell phone: r=−.264; personal coaching: r=−.308), and percentage of days self-weighed (cell phone: r=−.297; personal coaching: r=−.354). None of the characteristics examined, including age, gender, race, education, income, energy expenditure, diet quality, and hypertension status, appeared to be related to engagement.

Conclusions

Engagement in CITY intervention was associated with weight loss during the first 6 months. Nevertheless, engagement dropped substantially early on for most intervention components. Prompting may be helpful initially. More flexible and less intrusive prompting strategies may be needed during different stages of an intervention to increase or sustain engagement. Future studies should explore the motivations for engagement and nonengagement to determine meaningful levels of engagement required for effective intervention.

Trial Registration

ClinicalTrials.gov NCT01092364; https://clinicaltrials.gov/ct2/show/NCT01092364 (Archived by WebCite at http://www.webcitation.org/72V8A4e5X)

A Targeted and Tailored eHealth Weight Loss Program for Young Women: The Be Positive Be Healthe Randomized Controlled Trial

Young women are gaining weight rapidly. Evidence for effective weight loss interventions targeting young women is lacking. This randomized controlled trial assessed the efficacy and acceptability of a six-month targeted and tailored eHealth weight loss program for young women (Be Positive Be Healthe (BPBH)). Women aged 18–35 years were randomized to BPBH (n = 29) or control (n = 28). BPBH supported participants to modify diet and physical activity behaviours using evidenced-based strategies (e.g., self-monitoring) tailored for young women and delivered using e-health (website, social media, smartphone application, email, text messages). The primary outcome was a change in weight (kg) at six months. Acceptability was assessed via a process evaluation survey and usage of intervention components. No significant between-group differences were observed for weight, with significant mean differences favouring the intervention group observed for body fat (kg) (−3.10 (−5.69, 0.52), p = 0.019) and intakes of alcohol (g) (−0.69 (−1.33, 0.04), p = 0.037), vegetables (% energy/day) (4.71 (−2.20, 7.22), p < 0.001) and energy-dense, nutrient-poor foods (% energy/day) (−9.23 (−16.94, 1.52), p = 0.018). Retention, intervention usage and satisfaction were moderate. BPBH facilitated positive improvements in body fat and dietary intake, but not weight. Intervention acceptability findings support the use of some intervention components (e.g., Facebook, Smartphone app) with young women.

Wearable Activity Tracker Use Among Australian Adolescents: Usability and Acceptability Study

Background

Wearable activity trackers have the potential to be integrated into physical activity interventions, yet little is known about how adolescents use these devices or perceive their acceptability.

Objective

The aim of this study was to examine the usability and acceptability of a wearable activity tracker among adolescents. A secondary aim was to determine adolescents’ awareness and use of the different functions and features in the wearable activity tracker and accompanying app.

Methods

Sixty adolescents (aged 13-14 years) in year 8 from 3 secondary schools in Melbourne, Australia, were provided with a wrist-worn Fitbit Flex and accompanying app, and were asked to use it for 6 weeks. Demographic data (age, sex) were collected via a Web-based survey completed during week 1 of the study. At the conclusion of the 6-week period, all adolescents participated in focus groups that explored their perceptions of the usability and acceptability of the Fitbit Flex, accompanying app, and Web-based Fitbit profile. Qualitative data were analyzed using pen profiles, which were constructed from verbatim transcripts.

Results

Adolescents typically found the Fitbit Flex easy to use for activity tracking, though greater difficulties were reported for monitoring sleep. The Fitbit Flex was perceived to be useful for tracking daily activities, and adolescents used a range of features and functions available through the device and the app. Barriers to use included the comfort and design of the Fitbit Flex, a lack of specific feedback about activity levels, and the inability to wear the wearable activity tracker for water-based sports.

Conclusions

Adolescents reported that the Fitbit Flex was easy to use and that it was a useful tool for tracking daily activities. A number of functions and features were used, including the device’s visual display to track and self-monitor activity, goal-setting in the accompanying app, and undertaking challenges against friends. However, several barriers to use were identified, which may impact on sustained use over time. Overall, wearable activity trackers have the potential to be integrated into physical activity interventions targeted at adolescents, but both the functionality and wearability of the monitor should be considered.

Reducing non-injection drug use in HIV primary care: A randomized trial of brief motivational interviewing, with and without HealthCall, a technology-based enhancement

AIMS

In HIV-infected individuals, non-injection drug use (NIDU) compromises many health outcomes. In HIV primary care, the efficacy of brief motivational interviewing (MI) to reduce NIDU is unknown, and drug users may need greater intervention. We designed an enhancement to MI, HealthCall (HC), for daily patient self-monitoring calls to an interactive voice response (IVR) phone system, and provided participants with periodic personalized feedback. To reduce NIDU among HIV primary care patients, we compared the efficacy of MI+HealthCall to MI-only and an educational control condition.

DESIGN

Participants age >18 with >4days of NIDU during the prior 30days were recruited from large urban HIV primary care clinics. Of the 240 participants, 83 were randomly assigned to control, 77 to MI-only, and 80 to MI+HC. Counselors provided educational control, MI-only or MI+HC at baseline. At 30 and 60days (end-of-treatment), counselors briefly discussed drug use, moods and health behaviors, using HealthCall-generated graphs with MI+HC patients. Primary outcomes (last 30days) were number of days used primary drug (NumDU), and total quantity of primary drug used (dollar amount spent; QuantU), derived from the Time-Line Follow-Back.

FINDINGS

Across all groups, at end-of-treatment, frequency and quantity of NIDU decreased, with significantly greater reductions in the MI-Only group. A twelve-month post-treatment follow-up indicated sustained benefits of MI+HC and MI-only relative to control.

CONCLUSIONS

Brief interventions can be successfully used to reduce non-injection drug use in HIV primary care. IVR-based technology may not be sufficiently engaging to be effective. Future studies should investigate mobile technology to deliver a more engaging version of HealthCall to diverse substance abusing populations.

Ecological Interventionist Causal Models in Psychosis: Targeting Psychological Mechanisms in Daily Life

Integrated models of psychotic disorders have posited a number of putative psychological mechanisms that may contribute to the development of psychotic symptoms, but it is only recently that a modest amount of experience sampling research has provided evidence on their role in daily life, outside the research laboratory. A number of methodological challenges remain in evaluating specificity of potential causal links between a given psychological mechanism and psychosis outcomes in a systematic fashion, capitalizing on longitudinal data to investigate temporal ordering. In this article, we argue for testing ecological interventionist causal models that draw on real world and real-time delivered, ecological momentary interventions for generating evidence on several causal criteria (association, time order, and direction/sole plausibility) under real-world conditions, while maximizing generalizability to social contexts and experiences in heterogeneous populations. Specifically, this approach tests whether ecological momentary interventions can (1) modify a putative mechanism and (2) produce changes in the mechanism that lead to sustainable changes in intended psychosis outcomes in individuals' daily lives. Future research using this approach will provide translational evidence on the active ingredients of mobile health and in-person interventions that promote sustained effectiveness of ecological momentary interventions and, thereby, contribute to ongoing efforts that seek to enhance effectiveness of psychological interventions under real-world conditions.