# Optimizing digital health technologies to improve therapeutic skill use and acquisition

> **NIH NIH R01** · DREXEL UNIVERSITY · 2022 · $664,104

## Abstract

Project Summary
Binge eating (i.e., eating a large amount of food within a discrete time period accompanied by a sense of loss
of control over eating) is a key symptom of several eating disorders including bulimia nervosa (BN) and binge
eating disorder (BED). While cognitive behavioral therapy (CBT) can be an effective treatment approach for
binge eating, 40-50% of patients with BED and nearly 70% of patients with BN fail to achieve remission. A
growing body of research suggests that a key reason many patients may fail to benefit from CBT is suboptimal
rates of skill acquisition (i.e., the ability to successfully perform a skill learned in treatment) and utilization (i.e.,
the frequency with which a patient practices or employs therapeutic skills). Poor skill use and acquisition may
be particularly high among certain subsets of patients such as those who experience deficits in self-regulation.
This research suggests that treatment augmentations that could improve skill use and acquisition (particularly
for those who need additional support to succeed in CBT) could have high potential to enhance outcomes.
The NIMH has recently identified that digital health technologies (DHTs) have high potential to “promote
between-session skill practice/acquisition” and have selected this as a high priority research initiative (NOT-
MH-18-031). DHTs may be able to improve skill use and acquisition via several pathways, one of which is the
use of micro-interventions (i.e., short digital interventions delivered to people as they go about their daily lives).
Micro-interventions can range in complexity from something as simple as an automated reminder to practice a
therapeutic skill to advanced just-in-time adaptive intervention (JITAI) systems that use machine learning or
other advanced algorithms to deliver personally tailored interventions in specific moments of need. Recent
pilot work from our team supports the utility of JITAIs as a way to improve skill utilization and acquisition when
used as a treatment augmentation but did not compare JITAIs to more simple automated reminder micro-
interventions. Additionally, our pilot work also found that frequent monitoring of skill use was in and of itself a
surprisingly effective method for encouraging skill practice. These results suggest that the added complexity of
JITAIs may not be necessary for all individuals to experience benefit from a DHT augmentation.
The ability to develop maximally effective DHTs requires the use of a larger clinical trial that can help to identify
which digital components (and at which complexity) are most effective at improving skill use and acquisition as
well clinical outcomes. We propose to use a 2 x 3 full factorial design in which 264 individuals with BN or BED
are assigned to one of six treatment conditions, i.e., representing each permutation of self-monitoring
complexity (Skills-Monitoring On vs. Skills-Monitoring Off) and micro-intervention complexity (No Micro-
Interventions vs. ...

## Key facts

- **NIH application ID:** 10429134
- **Project number:** 1R01MH129478-01
- **Recipient organization:** DREXEL UNIVERSITY
- **Principal Investigator:** ADRIENNE SARAH JUARASCIO
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $664,104
- **Award type:** 1
- **Project period:** 2022-04-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10429134

## Citation

> US National Institutes of Health, RePORTER application 10429134, Optimizing digital health technologies to improve therapeutic skill use and acquisition (1R01MH129478-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10429134. Licensed CC0.

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