Digital Self-Management in Support of Patients Living With Chronic Pain: Feasibility Pilot Study
Bibliographic record
Abstract
BACKGROUND: Chronic pain can be complex and taxing to live with, and treatment and support require a multicomponent approach, which may not always be offered or available. Smartphones, tablets, and personal computers are already incorporated into patients' daily lives, and therefore, they can be used to communicate, educate, and support self-management. Although some web-based self-management interventions exist, research examining the evidence and effect of digital solutions supporting self-management for patients living with chronic pain is limited, findings are inconclusive, and new innovative ideas and solutions are needed. OBJECTIVE: This feasibility pilot study aimed to explore the system use, perceived usefulness, ease of use, and preliminary effects of EPIO, an app-based cognitive-behavioral pain self-management intervention program for patients living with chronic pain. METHODS: The EPIO intervention was delivered in a blended-care model containing (1) one face-to-face introduction session, (2) nine cognitive behavior-based pain self-management modules, delivered in an app-based format for smartphones or tablets, and (3) one follow-up phone call at 2 to 3 weeks after the introduction session. Patients living with chronic pain (N=50) completed pre-post outcome measures at baseline and 3 months after the introduction session, with registration of system use (ie, log data) until 6 months. The use, perceived usefulness, and ease of use of the EPIO program were examined through system use data, as well as a study-specific use/usability questionnaire and the System Usability Scale (SUS). Outcome measures to test feasibility of use and estimate preliminary effects included the Brief Pain Inventory, health-related quality of life (HRQoL) scale, Hospital Anxiety and Depression Scale, Self-Regulatory Fatigue scale, Pain Catastrophizing Scale, and Chronic Pain Acceptance Questionnaire. RESULTS: Participants (N=50) had a median age of 52 years (range 29-74 years) at inclusion and were mainly female (40/50, 80%). Thirty-one participants completed at least six of the nine modules within the 3-month study period (62% completion rate). Forty-five participants completed outcome measures at 3 months, and the EPIO program was rated as useful (ie, "totally agree" or "agree"; 39/45, 87%) and easy to use (42/45, 93%), and as having easily understandable exercises (44/45, 98%). The average overall system usability (SUS) score was 85.7, indicating grade A and excellent system usability. Preliminary psychosocial outcome measure estimates showed primarily nonsignificant pre-post intervention improvements at 3 months, but with significant positive effects related to some aspects of HRQoL (bodily pain, P=.02 and change, P=.049). CONCLUSIONS: Digital self-management intervention programs may be of use and support for patients living with chronic pain. In this feasibility study, EPIO showed an acceptable program completion rate and was rated as useful and easy to use, with excellent user satisfaction. Program optimization and efficacy testing in a large-scale randomized controlled trial are warranted and in progress. TRIAL REGISTRATION: ClinicalTrials.gov NCT03705104; https://clinicaltrials.gov/ct2/show/NCT03705104.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".