Role of Emotion Regulation Difficulties in Predicting Mental Health and W ell-being
Notice bibliographique
Résumé
The present study reports the relationship of emotion regulation difficulties and alexithymia with mental health and subjective wellbeing of an individual. Two hundred and eighty eight participants (218 males and 70 females) in the age range of 16 to 38 years (Mean age =20.78, SD= 2.95 years) were assessed on a measure of alexithymia, difficulties in emotion regulation, general mental health, and subjective well-being (assessed by Positive Negative Affect Schedule and Satisfaction with Life Scale). The results of the bi-variate correlation analysis revealed that difficulties in understanding and communicating as well as regulating emotions, in general, have a negative influence on health and wellbeing. However, the findings of step-wise multiple regression analysis indicated that some specific types of emotional deficits such as difficulties in identifying feelings, lack of emotional clarity and limited access to emotion regulation strategies were relatively more important in predicting the health status and well-being of an individual as compared to other emotional difficulties. Overall the findings imply that emotion regulation difficulties and alexithymia in general is associated with impaired mental health and lower level of happiness and life satisfaction, i.e., subjective well-being. The observed findings have been discussed in the light of the available empirical evidences. The role of emotions and emotional experiences in determining the health status of an individual, though, has been focus of psychological inquiry since long the last few decades have witnessed an invigorated interest in this area (see review by Pandey and Choubey, 2010). While emotions can be adaptive in many ways, emotions can also be maladaptive (Amstadter, 2008). For example, researchers have noted that while positive emotional experiences and emotional intelligence have a positive effect on mental health, suppression of emotions, inability or difficultly in understanding and communicating emotions (e.g. alexithymia), disposition to exaggerate emotional experiences may have health impairing effect (Pandey and Choubey, 2010). The functional role of emotions in mental health and subjective well being has been highlighted by several researchers (Quoidbach et al, 2010). The manner in which individuals are able to manage their emotional experiences to confirm adaptively to a given context appears to be important in mental health (Gross 1995).,
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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 | 0,000 | 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 | 0,000 |
| 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 ».