Feasibility of Applied Gaming During Interdisciplinary Rehabilitation for Patients With Complex Chronic Pain and Fatigue Complaints: A Mixed-Methods Study
Bibliographic record
Abstract
BACKGROUND: Applied gaming holds potential as a convenient and engaging means for the delivery of behavioral interventions. For developing and evaluating feasible computer-based interventions, policy makers and designers rely on limited knowledge about what causes variation in usage. OBJECTIVE: In this study, we looked closely at why and by whom an applied game (LAKA) is demanded and whether it is feasible (with respect to acceptability, demand, practicality, implementation, and efficacy) and devised a complementary intervention during an interdisciplinary rehabilitation program (IRP) for patients with complex chronic pain and fatigue complaints. METHODS: A mixed-methods design was used. Quantitative process analyses and assessments of feasibility were carried out with patients of a Dutch rehabilitation center who received access to LAKA without professional support during a 16-week interdisciplinary outpatient program. The quantitative data included records of routinely collected baseline variables (t0), additional surveys to measure technology acceptance before (t1) and after 8 weeks of access to LAKA (t2), and automatic log files of usage behavior (frequency, length, and progress). Subsequently, semistructured interviews were held with purposively selected patients. Interview codes triangulated and illustrated explanations of usage and supplemented quantitative findings on other feasibility domains. RESULTS: Of the 410 eligible patients who started an IRP during the study period, 116 patients participated in additional data collections (108 with problematic fatigue and 47 with moderate or severe pain). Qualitative data verified that hedonic motivation was the most important factor for behavioral intentions to use LAKA (P<.001). Moreover, quotes illustrated a positive association between usage intentions (t1) and baseline level (t0) coping by active engagement (Spearman ρ=0.25; P=.008) and why patients who often respond by seeking social support were represented in a group of 71 patients who accessed the game (P=.034). The median behavioral intention to use LAKA was moderately positive and declined over time. Twenty patients played the game from start to finish. Behavioral change content was recognized and seen as potentially helpful by interview respondents who exposed themselves to the content of LAKA. CONCLUSIONS: Variation in the demand for applied gaming is generally explained by perceived enjoyment and effort and by individual differences in coping resources. An applied game can be offered as a feasible complementary intervention for more patients with complex chronic pain or fatigue complaints by embedding and delivering in alignment with patient experiences. Feasibility, effectiveness, and cost-effectiveness can be evaluated in a full-scale evaluation. New observations elicit areas of further research on the usage of computer-based interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".