Predictors of weight loss in young adults who are over-weight or obese and have psychosocial problems: a post hoc analysis
Notice bibliographique
Résumé
BACKGROUND: The aim of this study is in a general practice trial setting to identify predictive factors for weight loss after 1 year among young adults who are over-weight or obese and who have several psychosocial problems. METHODS: Twenty-eight general practitioners recruited 495 patients aged 20-45 years with psychosocial problems for a randomized general preventive study to increase self-efficacy to achieve a self-prioritised goal for a better life by discussions of resources and barriers for reaching the goal. The present study is a post hoc analysis of possible predictors of weight loss among all 218 patients who have over-weight or obesity. A 23-pages questionnaire was completed before and 1 year after randomization. 111 patients had a one-hour preventive health consultation with their general practitioners focused on life coaching and a follow-up consultation within 3 months, and 107 patients had no preventive consultation. RESULTS: Twenty-two patients stated during the preventive consultation that weight loss was a prioritised goal. They had a mean weight loss of 4.7 kgs compared with 1.6 kgs in the group without this goal and 1.6 kgs in the group without preventive consultation. In a logistic regression model, predictors of weight loss or no weight loss were a) pre-interventional consideration of weight loss within 30 days, b) having weight loss as a prioritised goal for improved quality of life, c) being female, d) being in the oldest half of participants, and e) having many psychosocial problems. In a linear regression model, the predictors together explained about 11% of the weight loss. Important predictors were: obesity (explained 4%), pre-interventional consideration of weight loss within 30 days (3%), and having a preventive health consultation with weight loss as a prioritised goal (2%). CONCLUSIONS: Pre-interventional consideration of weight loss within 30 days and having weight loss as a prioritised goal during the health consultation were two important predictors for weight loss. By structured interventions focussing on the patients' priorities, self-chosen goals, their resources and barriers for reaching the goals, changes may be obtained; especially in participants with many problems who often do not accept participation in procedures on risks. CLINICALTRIALS GOV REGISTRATION: NCT 01231256 , Aug. 22. 2010.
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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 | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».