Loneliness, marriage and cardiovascular health
Notice bibliographique
Résumé
Social relationships, or the lack thereof, constitute a major psychosocial risk factor for health, rivaling the effect of well-established traditional cardiac risk factors. For example, the INTERHEART study, a casecontrol study of patients across 52 countries who had experienced an acute myocardial infarction, reported that adverse psychosocial factors accounted for a population attributable risk of 32.5%, which is similar to the population attributable risk for smoking of 35.7%. Social integration has been defined as the presence of social relationships that provide a sense of belonging, a subjective bond that individuals feel in relation to others and groups of others. A network of positive relationships can provide a tremendous source of support, meaning, and belonging, whereas the absence of relationships or a state of social isolation can have detrimental implications for health trajectories and well-being. Loneliness—the perception that one’s desired social relationships or connectivity are not being fulfilled—has been identified as a significant risk factor for depression and poor health behaviours. Although the prevalence of loneliness can vary with age or life stage, being married or with a partner does not necessarily ensure protection from loneliness. Poor marital quality or dissatisfaction has been associated with higher levels of reported loneliness, new onset depression, and poor long-term survival. The Framingham Offspring Study further documented that repressed marital communication, conflict, and strain were all associated with adverse health outcomes, especially in women. These data strongly suggest that psychosocial factors such as loneliness and marital quality, a component of social integration, exert considerable influence on the biopsychosocial experience of recovery and resulting health outcomes. In this issue of the European Journal of Preventive Cardiology, Roijers et al. present the results of a prospective cohort study for patients undergoing primary percutaneous coronary intervention who underwent cardiac rehabilitation (CR) for three months and were followed up for 12 months. These Dutch patients were representative of a typical population referred for CR. The population was analyzed for changes in subjective health status as determined by a Dutch normed SF-12. Of the many psychosocial variables that might influence health status, ‘‘loneliness’’ and ‘‘marital health quality’’ were chosen for analysis using standardized measures. They found that the ‘‘optimal married’’ versus ‘‘less optimal married’’ had similar improvements in a relative sense, even though the ‘‘less optimal married’’ started at a lower baseline value. After 12 months, the ‘‘optimal married’’ achieved and even surpassed the Dutch median population norm, whereas the ‘‘less optimal married’’, although showing improvement, did not reach this level. ‘‘Lonely’’ and ‘‘non-lonely’’ patients improved in a similar relative sense, but again the ‘‘lonely’’ patient group started at a lower level and did not reach the mean Dutch values for health perception. So, what are we to make of these intriguing findings? Interestingly, the improvements in the mental and physical perceived health status continued to improve after the end of the CR program until the 12-month followup. Further study could focus on the participants during the 3–12 month timeframe to specifically assess the reasons for this. For the ‘‘marital quality’’ groups, the cardiac event may have been the outside threat that galvanized improvement, or such couples may have received extra psychological counseling during and/or after the CR program. In a similar fashion, the ‘‘lonely’’ and ‘‘non-lonely’’ groups increased both during the CR program and afterwards. Although
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 | 0,010 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».