Testing of a Self-administered 6-Minute Walk Test Using Technology: Usability, Reliability and Validity Study
Notice bibliographique
Résumé
BACKGROUND: The need to attend a medically supervised hospital- or clinic-based appointment is a well-recognized barrier to exercise participation. The development of reliable and accurate home-based functional tests has the potential to decrease the burden on the health care system while enabling support, information, and assessment. OBJECTIVE: This study aims to explore the usability (ie, acceptability, satisfaction, accuracy, and practicality) of the EasyMeasure app to self-administer the 6-minute walk test (6MWT) in young, healthy adults and determine parallel form reliability and construct validity of conducting a self-administered 6MWT using technology. METHODS: We used a usability study design. English-speaking, undergraduate university students who had access to an iPhone or iPad device running iOS 10 or later and self-reported ability to walk for 6 minutes were recruited for this study. Consenting participants were randomized to either a standard 6MWT group (ie, supervised without the use of the app) or a technology 6MWT group (ie, unsupervised with the app to mimic independent implementation of the test). All participants performed a maximal treadmill test. Participants in the 6MWT group completed the Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire and a satisfaction questionnaire after completing the assessment. Parallel form reliability of the 6MWT using technology was analyzed by comparing participant self-administered scores and assessor scores using Pearson correlation coefficients across and between trials. Construct validity was assessed by comparing participant 6MWT scores (both standard and using technology) with maximum treadmill test variables (peak oxygen uptake and ventilatory threshold [VT]). RESULTS: In total, 20 university students consented to participate in the study. All but 2 participants (8/10, 80%) in the technology 6MWT group had deviations that prevented them from accurately conducting the 6MWT using the app, and none of the participants were able to successfully score the 6MWT. However, a significantly strong correlation was found (r=.834; P=.003) when comparing participants' scores for the 6MWT using technology with the assessors' scores. No significant correlations were found between maximal treadmill test peak oxygen uptake scores and 6MWT prediction equations using standard 6MWT scores (equation 1: r=0.119; P=.78; equation 2: r=0.095; P=.82; equation 3: r=0.119; P=.78); however, standard 6MWT scores were significantly correlated with VT values (r=0.810; P=.02). The calculated submaximal treadmill scores and assessor 6MWT scores using technology also demonstrated a significant correlation (r=0.661; P=.04). CONCLUSIONS: This study demonstrated significant usability concerns regarding the accuracy of a self-administered 6MWT using the EasyMeasure app. However, the strong and significant correlation between the 6MWT and VT values demonstrates the potential of the 6MWT to measure functional capacity for community-based exercise screening and patient monitoring.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».