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. 2023 Feb 1:7:e43557.
doi: 10.2196/43557.

A Digital Health Intervention for Concussion: Development and Clinical Feasibility Study

Christine d'Offay  1   2 , Xin Yi Ng  3 , Laura Alexander  4 , Alison Grant  5 , Julia Grahamslaw  5 , Claudia Pagliari  1 , Matthew J Reed  5   6 , Alan Carson  4 , David C Gillespie  4 , Aimun A B Jamjoom  2   4   7
Affiliations

A Digital Health Intervention for Concussion: Development and Clinical Feasibility Study

Christine d'Offay et al. JMIR Form Res. .

Abstract

Background: Concussion is a common condition that can lead to a constellation of symptoms that affect quality of life, social integration, and return to work. There are several evidence-based behavioral and psychological interventions that have been found to improve postconcussion symptom burden. However, these are not routinely delivered, and individuals receive limited support during their concussion recovery.

Objective: This study aimed to develop and test the feasibility of a digital health intervention using a systematic evidence-, theory-, and person-based approach.

Methods: This was a mixed methodology study involving a scoping review (n=21), behavioral analysis, and logic model to inform the intervention design and content. During development, the intervention was optimized with feedback from individuals who had experienced concussions (n=12) and health care professionals (n=11). The intervention was then offered to patients presenting to the emergency department with a concussion (n=50). Participants used the intervention freely and input symptom data as part of the program. A number of outcome measures were obtained, including participant engagement with the intervention, postconcussion symptom burden, and attitudes toward the intervention. A selection of participants (n=15) took part in in-depth qualitative interviews to understand their attitudes toward the intervention and how to improve it.

Results: Engagement with the intervention functionality was 90% (45/50) for the symptom diary, 62% (31/50) for sleep time setting, 56% (28/50) for the alcohol tracker, 48% (24/50) for exercise day setting, 34% (17/50) for the thought diary, and 32% (16/50) for the goal setter. Metrics indicated high levels of early engagement that trailed off throughout the course of the intervention, with an average daily completion rate of the symptom diary of 28.23% (494/1750). A quarter of the study participants (13/50, 26%) were classified as high engagers who interacted with all the functionalities within the intervention. Quantitative and qualitative feedback indicated a high level of usability and positive perception of the intervention. Daily symptom diaries (n=494) demonstrated a wide variation in individual participant symptom burden but a decline in average burden over time. For participants with Rivermead scores on completion of HeadOn, there was a strong positive correlation (r=0.86; P<.001) between their average daily HeadOn symptom diary score and their end-of-program Rivermead score. Insights from the interviews were then fed back into development to optimize the intervention and facilitate engagement.

Conclusions: Using this systematic approach, we developed a digital health intervention for individuals who have experienced a concussion that is designed to facilitate positive behavior change. Symptom data input as part of the intervention provided insights into postconcussion symptom burden and recovery trajectories.

Trial registration: ClinicalTrials.gov NCT05069948; https://clinicaltrials.gov/ct2/show/NCT05069948.

Keywords: behavior change; concussion; digital intervention; feasibility study.

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Conflict of interest statement

Conflicts of Interest: CD, AABJ, and DCG are shareholders in HeadOn Health Ltd, which has an exclusive license for the HeadOn intellectual property from the University of Edinburgh. AC is a paid editor for JNNP, an unpaid president of FNDsociety and gave testimony in Court on a range of neuropsychiatric topics including TBI.

Figures

Figure 1
Figure 1
The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram for the scoping review.
Figure 2
Figure 2
HeadOn logic model. CBT: cognitive behavioral therapy; mHealth: mobile health.
Figure 3
Figure 3
(A) The percentage of study participants completing the symptom diary. (B) Distribution of the symptom burden based on 494 symptom diary responses. (C) Temporal change in symptom burden over the course of HeadOn.
See this image and copyright information in PMC

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