Associations between measures of socio-economic status, beliefs about back pain, and exposure to a mass media campaign to improve back beliefs
Notice bibliographique
Résumé
Abstract Background Low back pain (LBP) is one of the most common and costly healthcare problems worldwide. Disability from LBP is associated with maladaptive beliefs about the condition, and such beliefs can be influenced by public health interventions. While socioeconomic status (SES) has been identified as an important factor in health literacy and inequalities, not much is known about the association between SES and beliefs about LBP. Therefore, this study examined the relationship between measures of SES and the belief that one should stay active through LBP in a representative sample of the general population in Alberta, Canada. We also examined the association between measures of SES and self-reported exposure to a LBP mass media health education campaign. Methods Population-based surveys from 2010 through 2014 were conducted among 9572 randomly selected Alberta residents aged 18–65 years. Several methods for measuring SES, including first language, education, employment status, occupation, and annual household income, were included in multivariable logistic regression modeling to test associations between measures of SES and outcomes. Results Univariable analysis showed that age, language, education, employment, marital status, and annual household income were significantly associated with the belief that one should stay active through LBP. In multivariable analysis, income was the variable most strongly correlated with this belief (odds ratios ranged from 1.04 to 1.62 for the highest income category, p = 0.005). Univariable analysis for exposure to the campaign showed age, language, education, employment, and occupation to be significantly associated with self-reported exposure, while only education (p = 0.01) and age (p = 0.001) remained significant in multivariable analysis. Conclusions Individuals with higher annual income appear more likely to believe that one should stay active during an episode of LBP. Additionally, targeted information campaigns are recalled more by low SES groups and may thus assist in reducing health disparities. More research is needed to fully understand the association between socioeconomic factors and LBP and to target campaigns accordingly.
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 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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,041 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».