The Supportive Accountability Inventory: Psychometric properties of a measure of supportive accountability in coached digital interventions

Novel Smartphone App and Supportive Accountability for the Treatment of Childhood Disruptive Behavior Problems: Protocol for a Randomized Controlled Trial

BACKGROUND

Although evidence-based treatments have been developed for childhood behavior problems, many families encounter barriers to treatment access and completion (eg, local availability of services, transportation, cost, and perceived stigma). Smartphone apps offer a cost-efficient method to deliver content to families.

OBJECTIVE

The aim of this study is to evaluate the effectiveness of the UseIt! mobile health system as both stand-alone and coach-assisted interventions via a randomized controlled trial. The UseIt! System is designed to reduce disruptive behaviors in young children.

METHODS

A nationwide sample of parents of children aged 5 years to 8 years with disruptive behaviors (N=324 dyads) are randomly assigned to the stand-alone app (UseIt!; n=108), the coach-assisted app (UseIt! plus supportive accountability; n=108), or the control app (mindfulness app; n=108). The UseIt! App provides parents with tools and troubleshooting to address disruptive behaviors, along with a behavior diary to track behaviors and strategies over time. The coach-assisted condition includes a bachelor's level paraprofessional who provides weekly phone calls to promote engagement with the app. The control condition is composed of a mindfulness app. The web-based, self-assessed outcome measures (post treatment and 6-month follow-up) include measures of app usage, parenting knowledge (eg, knowledge of parent management training and cognitive behavioral therapy skills), and strategies (use of evidence-based parenting strategies), symptom reduction (eg, behavior problems), and parent mental health (eg, anxiety, stress, and depression). We hypothesize that both intervention conditions will show greater parent knowledge and use of skills along with greater symptom reduction relative to the control condition. Further, we hypothesize that those assigned to the coach assisted condition will report greater knowledge, skill use, and symptom reduction than the stand-alone app. We will use intent-to-treat analyses to regress outcomes on study conditions to evaluate for differences across conditions.

RESULTS

Recruitment of study participants began in December of 2022 and is ongoing. We have recruited over half of our intended sample of 324 parent-child dyads (n=214) as of December 2024. These dyads have been randomly allocated to each of the intervention conditions, with 71 assigned to the coach-assisted condition, 72 assigned to the stand-alone app, and 71 assigned to the control app condition. Data collection is projected to be completed by late 2026.

CONCLUSIONS

The current study aims to address a gap in the literature regarding the feasibility, effectiveness, and utility of a smartphone app that includes a coach-assisted arm. Digital therapeutics have the potential to enhance the reach and scalability of skills-based psychosocial interventions. Findings from this study will advance scientific knowledge and have implications for clinical practice.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05647772; https://clinicaltrials.gov/study/NCT05647772.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/67051.

Motivation, accountability, and outcomes in a randomized controlled trial of internet weight-loss programs in primary care

This study explored whether baseline autonomous motivation (AM), controlled motivation (CM), and relative autonomy index (RAI) scores predicted 12-month weight in a three-arm randomized controlled trial of internet weight loss programs in primary care. It also evaluated perceived accountability to a primary care provider for weight loss as a moderator and study engagement (operationalized as weeks logged into the study website) as a mediator of these relationships. Participants with complete data for all model variables (n = 428) were included. Multiple linear regression models controlling for baseline weight and covariates showed that one-unit increases in baseline CM and RAI scores predicted a 0.57 kg increase (p = 0.015; Cohen's f2 = 0.02) and 0.52 kg decrease (p = 0.019; Cohen's f2 = 0.02) in weight, respectively. AM was not associated with 12-month weight. No moderating or mediating effects were found. Findings suggest the need for greater attention to baseline CM in weight loss programs in primary care.

Addressing rural health disparities by optimizing "high-touch" intervention components in digital obesity treatment: The iREACH Rural study

BACKGROUND

Rural residents are more impacted by obesity and related comorbidities than their urban counterparts. Digital weight management interventions may produce meaningful weight loss among rural residents.

OBJECTIVES

The iREACH Rural Study aims to identify "high-touch" component(s) that contribute to meaningful weight loss (≥1.5 kg) at 6-months, over and above what the 24-week core online program produces. Three treatment components are assessed: group video sessions (yes/no); self-monitoring feedback (counselor-crafted/pre-scripted, modular); and individual coaching calls (yes/no).

DESIGN

The iREACH Rural Study is a factorial experiment (n = 616).

METHODS

Participants receive up to 3 "high-touch" components (weekly synchronous facilitated group video sessions, weekly counselor-crafted self-monitoring feedback, and individual coaching calls) to determine which contribute meaningfully to 6-month weight loss. Participants complete assessments at baseline, 2 months, 6 months, and 12 months. Weight loss at 6 months (primary outcome) and 12 months (secondary outcome) is measured by Bluetooth-enabled scales. The study seeks to identify the weight loss approach for underserved rural residents which optimizes weight change outcomes and also examines costs associated with delivering different treatment constellations.

SUMMARY

The iREACH Rural Study is the first of its kind to isolate digital weight loss intervention components to determine which meaningfully contribute to long-term weight loss among rural residing individuals. The results may be used to refine digital weight loss programs by enhancing their effectiveness to allow broad dissemination.

Internet-based, parent-led cognitive behavioral therapy for autistic youth with anxiety-related disorders: A randomized trial comparing email vs. telehealth support

This study tested two versions of parent-led, Internet-delivered cognitive behavioral therapy for anxiety among autistic youth; one that provided weekly email support (iCBT-Email), and one that provided alternating bi-weekly emails and video calls (iCBT-Video) across 12 weeks. It was expected that those in the iCBT-Video condition would complete more treatment content, which in turn would lead to more anxiety improvement. Fifty-seven autistic youth (7-15 years-old) with anxiety disorders were randomized to iCBT-Email or iCBT-Video. There were no significant differences in improvement in clinician-rated, child-reported, or parent-reported anxiety severity or functional impairment. Posttreatment response rates were 55% in iCBT-Email and 67% in iCBT-Video. Module completion predicted improved treatment outcome, though there was no difference in module completion across groups. Therapists spent an average of 16.29 min/family/week (SD = 7.11) in the iCBT-Email condition and 24.13 min/family/week (SD = 6.84) in the iCBT-Video condition. Email and telehealth-supported, parent-led iCBT both appear to be effective treatments for autistic youth with anxiety disorders that require reduced therapist effort. Future research should seek novel methods to enhance engagement with iCBT content. CLINICALTRIALS.GOV IDENTIFIER: NCT05284435.

Coach access to digital self-monitoring data: an experimental test of short-term effects in behavioral weight-loss treatment

OBJECTIVE

This study experimentally tested whether coach access to participants' digital self-monitoring data improved behavioral weight-loss outcomes.

METHODS

Participants (N = 322) received 12 weeks of group-based behavioral weight-loss sessions via videoconference and were instructed to engage in daily self-monitoring of weight, physical activity (PA), and dietary intake. For participants who were randomly assigned to Coach Share ON (n = 161), coaches regularly accessed a web-based portal that displayed data from the participants' scale, PA sensor, and food record.

RESULTS

Weight loss at 12 weeks was significantly greater in Coach Share ON versus OFF (6.2% vs. 5.3%; p = 0.04). Self-monitoring of PA (98.70% vs. 97.40% of days; p = 0.006) and eating (98.05% vs. 93.51% of days; p = 0.007) was more frequent in Coach Share ON versus OFF. There were no significant differences by condition in PA (p = 0.57), attendance (p = 0.42), working alliance (p = 0.62), or self-monitoring of weight (p = 0.12). Perceived supportive accountability was significantly greater in Coach Share ON versus OFF (p < 0.001).

CONCLUSIONS

The short-term efficacy of behavioral weight loss was greater when coaches had direct access to self-monitoring device data. Notably, there also was no evidence of iatrogenic effects of data sharing.

Sharing digital self-monitoring data with others to enhance long-term weight loss: A randomized controlled trial

BACKGROUND

Participants in behavioral weight loss (BWL) programs increasingly use digital tools to self-monitor weight, physical activity, and dietary intake. Data collected with these tools can be systematically shared with other parties in ways that might support behavior change.

METHODS

Adults age 18 to 70 with overweight/obesity (BMI 27-50 kg/m2) will enroll in a remotely delivered, 24-month BWL program designed to produce and maintain a 10% weight loss. Participants will be asked to use a wireless body weight scale, wearable activity sensor, and dietary intake app daily. All participants will receive individual and group counseling, engage in text messaging with members of their group, and appoint a friend or family member to serve in a support role. A 2x2x2 factorial design will test the effects of three types of data sharing partnerships: 1) Coach Share: The behavioral coach will regularly view digital self-monitoring data and address data observations. 2) Group Share: Participants will view each other's self-monitoring data in small-group text messages. 3) Friend/Family Share: A friend or family member will view the participant's data via automated message. The primary outcome is weight loss at 24 months. Mediators and moderators of intervention effects will be tested.

CONCLUSION

This study will provide a clear indication of whether data sharing can improve long-term weight loss. This study will be the first to discern the mechanisms of action through which each type of data sharing may be beneficial, and elucidate conditions under which the benefits of data sharing may be maximized.

Multilevel Determinants of Digital Health Equity: A Literature Synthesis to Advance the Field

Current digital health approaches have not engaged diverse end users or reduced health or health care inequities, despite their promise to deliver more tailored and personalized support to individuals at the right time and the right place. To achieve digital health equity, we must refocus our attention on the current state of digital health uptake and use across the policy, system, community, individual, and intervention levels. We focus here on (a) outlining a multilevel framework underlying digital health equity; (b) summarizingfive types of interventions/programs (with example studies) that hold promise for advancing digital health equity; and (c) recommending future steps for improving policy, practice, and research in this space.