The Relation of Attitude Toward Technology and Mastery Experience After an App-Guided Physical Exercise Intervention: Randomized Crossover Trial
Bibliographic record
Abstract
BACKGROUND: Physical exercise has been found to assert a positive impact on many muscular conditions. Exercise under face-to-face supervision is the gold standard, but access to it is limited, for instance, for economic reasons. App-guided therapy is an intervention that is more affordable and easily accessible. However, attitude toward technology is a key predictor for media adoption and is therefore expected to shape user experience during app-guided therapy. This might be of particular importance for mastery experience, which is crucial for promoting exercise-related self-efficacy and perceived usefulness of the interaction. Both should empower patients to continuously exercise. OBJECTIVE: This study sought to test whether attitudes toward technology predict mastery experience and perceived usefulness of the interaction after an app- versus a physiotherapist-guided treatment. We expect that attitudes toward technology positively predict both outcomes in case of the app-guided but not in case of the physiotherapist-guided treatment. METHODS: Patients (n=54) with clinically diagnosed hip osteoarthritis participated in 2 training sessions with the same exercise intervention, once guided by an app on a tablet computer and once guided by a physiotherapist in a German university hospital. The order of the sessions was randomized. Attitude toward technology was assessed as predictor before the first session, while mastery experience and the global perceived usefulness of interaction as self-reported outcomes after each session. RESULTS: In line with our hypotheses, attitude toward technology predicted mastery experience (b=0.16, standard error=0.07, P=.02) and usefulness of interaction (b=0.17, standard error=0.06, P=.01) after the app-based training but not after the training delivered by a physiotherapist (P>.3 in all cases). Mastery experience was lower for the app-based training but reached a very similar level as the physiotherapist-guided training for those holding a very positive attitude toward technology. CONCLUSIONS: The attitude toward technology predicts the extent of mastery experience after app-guided exercise therapy. As mastery experience is highly important for self-efficacy and future exercise behavior, attitudes toward technology should be considered when delivering app-guided exercise treatments. TRIAL REGISTRATION: German Clinical Trials Register DRKS00015759; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00015759.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".