Abstract B5: Psychosocial mechanisms for explaining the relationship between physical activity and fatigue in breast cancer survivors
Notice bibliographique
Résumé
Abstract Fatigue is one of the most commonly reported and enduring symptoms experienced as a result of breast cancer treatment. One important behavior that has been identified as having the potential to reduce breast cancer related fatigue is physical activity. However, few attempts have been made to fully understand this relationship and it is not known whether physical activity directly influences fatigue or operates through other factors. The purpose of this study was to examine the role of psychosocial mechanisms, self-efficacy and depression, as potential pathways from physical activity to fatigue in a cross-sectional sample of breast cancer survivors (N=192). Participants completed measures of health status, physical activity, depression, fatigue, and self-efficacy. Data were analyzed using path analysis within a covariance modeling framework. This model proposed that that physical activity's influence on fatigue is indirect through its direct effect on self-efficacy which, in turn, has both a direct effect on fatigue and an indirect effect through depression. The hypothesized path model provided an excellent fit to the data (Ξ2 = 1.48, df = 2, p =.48; SRMR = 0.02, CFI = 1.00). All of the proposed path coefficients of the hypothesized model were significant. Overall, the model accounted for 45.2% of the variation in fatigue. As a result of the robust relationship between fatigue and depression (β =.51), the analysis was re-run using a depression score which excluded items assessing “somatic and retarded activity” symptoms. The fit of the model was almost identical to the previously described model (Ξ2 = 1.48, df = 2, p =.45; SRMR = 0.03, CFI = 1.00). A final analysis was conducted on the original model to test effects of for demographics (i.e., age, education, employment, income), time since diagnosis, breast cancer stage, current treatment, menopausal status, body mass index, and comorbidities on model fit and path coefficients, as well as the model components themselves. This model also was an excellent fit to the data (Ξ2 = 2.10, df = 2, p =.35; SRMR = 0.01, CFI = 1.00). In general, the magnitude and direction of the hypothesized relationships were unaffected by the inclusion of the covariates in the model. Our findings suggest support for one set of psychosocial pathways from physical activity to fatigue, an important concern in breast cancer survivors. Subsequent work might replicate such associations in other survivor populations and attempt to determine whether model relations change with physical activity interventions, and the extent to which other known correlates of fatigue such as impaired sleep and inflammation can be incorporated into this model. Citation Information: Cancer Prev Res 2010;3(1 Suppl):B5.
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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 | 0,000 |
| 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 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».