The association between Colombian medical students' healthy personal habits and a positive attitude toward preventive counseling: cross-sectional analyses
Notice bibliographique
Résumé
BACKGROUND: Physician-delivered preventive counseling is important for the prevention and management of chronic diseases. Data from the U.S. indicates that medical students with healthy personal habits have a better attitude towards preventive counseling. However, this association and its correlates have not been addressed in rapidly urbanized settings where chronic disease prevention strategies constitute a top public health priority. This study examines the association between personal health practices and attitudes toward preventive counseling among first and fifth-year students from 8 medical schools in Bogotá, Colombia. METHODS: During 2006, a total of 661 first- and fifth-year medical students completed a culturally adapted Spanish version of the "Healthy Doctor = Healthy Patient" survey (response rate = 78%). Logistic regression analyses were used to assess the association between overall personal practices on physical activity, nutrition, weight control, smoking, alcohol use (main exposure variable) and student attitudes toward preventive counseling on these issues (main outcome variable), stratified by year of training and adjusting by gender and medical training-related factors (basic knowledge, perceived adequacy of training and perception of the school's promotion on each healthy habit). RESULTS: The median age and percentage of females for the first- and fifth-year students were 21 years and 59.5% and 25 years and 65%, respectively. After controlling for gender and medical training-related factors, consumption of >or= 5 daily servings of fruits and/or vegetables, not being a smoker or binge drinker were associated with a positive attitude toward counseling on nutrition (OR = 4.71; CI = 1.6-14.1; p = 0.006 smoking (OR = 2.62; CI = 1.1-5.9; p = 0.022), and alcohol consumption (OR = 2.61; CI = 1.3-5.4; p = 0.009), respectively. CONCLUSION: As for U.S. physician and medical students, a positive association was found between the personal health habits of Colombian medical students and their corresponding attitudes toward preventive counseling, independent of gender and medial training-related factors. Our findings, the first relating to this association in medical students in developing regions, also suggest that within the medical school context, interventions focused on promoting healthy student lifestyles can potentially improve future physician's attitudes toward preventive counseling.
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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 | 0,025 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 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 ».