Gamified Web-Delivered Attentional Bias Modification Training for Adults With Chronic Pain: Randomized, Double-Blind, Placebo-Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Attentional bias to pain-related information has been implicated in pain chronicity. To date, research investigating attentional bias modification training (ABMT) procedures in people with chronic pain has found variable success, perhaps because training paradigms are typically repetitive and monotonous, which could negatively affect engagement and adherence. Increasing engagement through the gamification (ie, the use of game elements) of ABMT may provide the opportunity to overcome some of these barriers. However, ABMT studies applied to the chronic pain field have not yet incorporated gamification elements. OBJECTIVE: This study aimed to investigate the effects of a gamified web-delivered ABMT intervention in a sample of adults with chronic pain via a randomized, double-blind, placebo-controlled trial. METHODS: A final sample of 129 adults with chronic musculoskeletal pain, recruited from clinical (hospital outpatient waiting list) and nonclinical (wider community) settings, were included in this randomized, double-blind, placebo-controlled, 3-arm trial. Participants were randomly assigned to complete 6 web-based sessions of nongamified standard ABMT (n=43), gamified ABMT (n=41), or a control condition (nongamified sham ABMT; n=45) over a period of 3 weeks. Active ABMT conditions trained attention away from pain-related words. The gamified task included a combination of 5 game elements. Participant outcomes were assessed before training, during training, immediately after training, and at 1-month follow-up. Primary outcomes included self-reported and behavioral engagement, pain intensity, and pain interference. Secondary outcomes included anxiety, depression, cognitive biases, and perceived improvement. RESULTS: Results of the linear mixed model analyses suggest that across all conditions, there was an overall small to medium decline in self-reported task-related engagement between sessions 1 and 2 (P<.001; Cohen d=0.257; 95% CI 0.13-0.39), sessions 1 and 3 (P<.001; Cohen d=0.368; 95% CI 0.23-0.50), sessions 1 and 4 (P<.001; Cohen d=0.473; 95% CI 0.34-0.61), sessions 1 and 5 (P<.001; Cohen d=0.488; 95% CI 0.35-0.63), and sessions 1 and 6 (P<.001; Cohen d=0.596; 95% CI 0.46-0.73). There was also an overall small decrease in depressive symptoms from baseline to posttraining assessment (P=.007; Cohen d=0.180; 95% CI 0.05-0.31) and in pain intensity (P=.008; Cohen d=0.180; 95% CI 0.05-0.31) and pain interference (P<.001; Cohen d=0.237; 95% CI 0.10-0.37) from baseline to follow-up assessment. However, no differential effects were observed over time between the 3 conditions on measures of engagement, pain intensity, pain interference, attentional bias, anxiety, depression, interpretation bias, or perceived improvement (all P values>.05). CONCLUSIONS: These findings suggest that gamification, in this context, was not effective at enhancing engagement, and they do not support the widespread clinical use of web-delivered ABMT in treating individuals with chronic musculoskeletal pain. The implications of these findings are discussed, and future directions for research are suggested. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620000803998; https://anzctr.org.au/ACTRN12620000803998.aspx. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/32359.
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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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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) | 0,001 | 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 ».