Internet-Based Exercise Therapy Using Algorithms for Conservative Treatment of Anterior Knee Pain: A Pragmatic Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Conservative treatment remains the first-line option, and there is significant medical evidence showing that home-based exercise therapy for the treatment of common causes of knee pain is effective. SimpleTherapy created an online platform that delivers Internet-based exercise therapy for common causes of knee pain. The system is driven by an algorithm that can process the user's feedback to provide an adaptive exercise regimen. This triple-armed, pragmatic randomized pilot was designed to evaluate if this telerehabilitation platform is safe and effective. OBJECTIVE: We hypothesized that a home-based, algorithm-driven exercise therapy program can be safe for use and even improve compliance over the standard of care, the paper handout. METHODS: After an independent internal review board review and approval, the website trial.simpletherapy.com was opened. Once the trial was open for enrollment, no changes to the functionality or user interaction features were performed until the trial had closed. User accrual to the website was done using website optimization and social media postings tied to existence of knee pain. Consent was obtained online through checkboxes with third-party signature confirmation. No fees were charged to any patient. Patients were recruited online from an open access website. Outcomes were self-assessed through questionnaires with no face-to-face clinician interaction. A triple-arm randomized controlled trial was used with arm 1 being a static handout of exercises, arm 2 being a video version of arm 1, and arm 3 being a video-based, algorithm-driven system that took patient feedback and changed the exercises based on the feedback. Patients used household items and were not supervised by a physical therapist or clinician. Patients were reminded at 48-hour intervals to complete an exercise session. RESULTS: A total of 860 users found the trial and initiated the registration process. These 860 were randomized, and the demographic distribution shows the randomization was successful. In all, 70 users completed the 6-week regimen (8.1%): 20 users were in arm 1, 33 users in arm 2, and 17 users in arm 3. There were no adverse events reported in any of the 3 arms. All outcomes were self-assessed. No adverse events were reported during or after the trial. CONCLUSIONS: Because only 8.1% of those who enrolled completed the trial, an intent-to-treat analysis did not reach statistical significance in this pilot trial. However, the completion rates are comparable to those of previous online-only trials. Given an early phase trial, no adverse events were reported. Ongoing data collection continues and will form the basis for further data on the efficacy of this intervention. TRIAL REGISTRATION: Clinicaltrials.gov NCT01696162; https://clinicaltrials.gov/ct2/show/NCT01696162 (Archived by WebCite at http://www.webcitation.org/6lM8jC7Gu).
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,005 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».