Pacing, Conventional Physical Activity and Active Video Games to Increase Physical Activity for Adults with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Protocol for a Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a serious illness of biological origin characterized by profound physical and cognitive exhaustion and postexertion malaise. Pacing is a common strategy used to manage available energy and complete activities of daily living; yet little research has investigated this as a strategy to increase physical activity levels. Typically, people living with ME/CFS are faced by unique barriers to physical activity participation and are less physically active than healthy peers. As such they are at increased risk of physical inactivity-related health consequences. Active video games may be a feasible and acceptable avenue to deliver physical activity intervention by overcoming many of the reported barriers to participation. OBJECTIVE: The primary objective of this pilot study is to determine the feasibility and acceptability of active video games to increase physical activity levels of people with ME/CFS. The secondary aims are to explore the preliminary effectiveness of pacing and active video gaming to pacing alone and pacing plus conventional physical activity to increase the physical activity levels of adults with ME/CFS and explore the relationship between physical activity and cumulative inflammatory load (allostatic load). METHODS: This study will use a mixed method design, with a 3-arm pilot randomized controlled trial, exit interviews, and collection of feasibility and process data. A total of 30 adults with ME/CFS will be randomized to receive either (1) pacing, (2) pacing and conventional physical activity, or (3) pacing and active video gaming. The intervention duration will be 6 months, and participants will be followed up for 6 months postintervention completion. The intervention will be conducted in the participant's home, and activity intensity will be determined by continuously monitored heart rate and ratings of perceived exertion. Feasibility and acceptability and process data will be collected during and at the end of the intervention. Health-related outcomes (eg, physical activity, blood samples, quality of life, and functioning) will be collected at baseline, end of intervention, and 6 months after intervention completion. RESULTS: This protocol was developed after 6 months of extensive stakeholder and community consultation. Enrollment began in January 2017; as of publication, 12 participants were enrolled. Baseline testing is scheduled to commence in mid-2017. CONCLUSIONS: This pilot study will provide essential feasibility and acceptability data which will guide the use of active video games for people with ME/CFS to increase their physical activity levels. Physical activity promotion in this clinical population has been poorly and under-researched, and any exploration of alternative physical activity options for this population is much needed. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry: ACTRN12616000285459; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370224 (Archived by WebCite at http://www.webcitation.org/6qgOLhWWf).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,028 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,011 | 0,006 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,059 | 0,009 |
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 ».