What Role Does Positive Psychology Play in Understanding Pain Intensity and Disability Among Patients with Hand and Upper Extremity Conditions?
Notice bibliographique
Résumé
BACKGROUND: A large body of research shows that psychologic distress and ineffective coping strategies substantially contribute to more severe pain and increased physical limitations among patients with orthopaedic disorders. However, little is known about the relationship between positive psychology (constructs that enable individuals to thrive and adapt to challenges) and pain and physical limitations in this population. QUESTIONS/PURPOSES: (1) Which positive-psychology factors (satisfaction with life, gratitude, coping through humor, resilience, mindfulness, and optimism) are independently associated with fewer upper-extremity physical limitations after controlling for the other clinical and demographic variables? (2) Which positive-psychology factors are independently associated with pain intensity after controlling for relevant clinical and demographic variables? METHODS: In a cross-sectional study, we recruited patients presenting for a scheduled appointment with an orthopaedic surgeon at a hand and upper-extremity clinic of a major urban academic medical center. Of 125 approached patients, 119 (44% men; mean age, 50 ± 17 years) met screening criteria and agreed to participate. Patients completed a clinical and demographic questionnaire, the Numerical Rating Scale to assess pain intensity, the Patient-reported Outcomes Measurement Information System (PROMIS) Upper Extremity Physical Function computerized adaptive test to assess physical limitations, and six measures assessing positive-psychology constructs: The Satisfaction with Life Scale, the Gratitude Questionnaire, the Coping Humor Scale, the Brief Resilience Scale, the Cognitive and Affective Mindfulness Scale-Revised, and the Life Orientation Test-Revised. We first examined bivariate associations among physical limitations, pain intensity, and all positive-psychology factors as well as demographic and clinical variables. All variables that demonstrated associations with physical limitations or pain intensity at p < 0.05 were included in two-stage multivariable hierarchical regression models. RESULTS: After controlling for the potentially confounding effects of prior surgical treatment and duration since pain onset (step1; R total = 0.306; F[7,103] = 6.50), the positive-psychology variables together explained an additional 15% (R change = 0.145, F change [5, 103] = 4.297, p = 0.001) of the variance in physical limitations. Among the positive-psychology variables tested, mindfulness was the only one associated with fewer physical limitations (β = 0.228, t = 2.293, p = 0.024, 4% variance explained). No confounding demographic or clinical variables were found for pain intensity in bivariate analyses. All positive-psychology variables together explained 23% of the variance in pain intensity (R = 0.23; F[5,106] = 6.38, p < 0.001). Among the positive-psychology variables, satisfaction with life was the sole factor independently associated with higher intensity (β = -0.237, t = -2.16, p = 0.033, 3% variance explained). CONCLUSIONS: Positive-psychology variables explained 15% of the variance in physical limitations and for 23% of the variance in pain intensity among patients with heterogenous upper extremity disorders within a hand and upper extremity practice. Of all positive-psychology factors, mindfulness and satisfaction with life were most important for physical limitations and pain intensity, respectively. As positive-psychology factors are more easily modifiable through skills-based interventions than pain and physical limitations, results suggest implementation of such interventions to potentially improve outcomes in this population. Skills-based interventions targeting mindfulness and satisfaction with life may be of particular benefit. LEVEL OF EVIDENCE: Level II, prognostic study.
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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 | 0,006 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,003 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».