Hospital visitation preferences and perceived stress in adults on medical units
Notice bibliographique
Résumé
Hospitalization is generally acknowledged as a stressful event.Social support as a coping resource has been shown to buffer the effects of stress.Prescribed visitation rules are prevalent in many hospital settings.Specific to the hospital environment, perceived or actual inadequate social support may heighten stress, increase susceptibility to illness, and delay recovery in patients.Previous research related to visitation preferences has focused on patients in critical care areas.The purpose of this study was to explore and describe the visitation preferences of patients on acute medical units.The conceptual framework was based on several theoretical perspectives related to social support, including Cohen and Wills' (1985) Stress Buffering Model, which was built on Lazarus and Folkman's theory of stress, coping, and adaptation, and Roy's Adaptation Model.A descriptive, correlational design was utilized to explore and describe the visitation preferences of 128 adults hospitalized on three general medical units in alarge tertiary care hospital in Manitoba.The relationship between perceived availability of social support and perceived stress was also explored.Relationships among preferences for visitation and perceived stress, and the variables of age, gender, marital status, socio- economic status, ethnicity, illness severity, frequency of hospitalizatíon, and days currently spent in hospital were also examined.Four research instruments operationalizedthe key variables of visitation preferences (i.e., The HospitalizedPatient Visiting Preference Questionnaire), perceived social support (i.e., The Perceived Social Support Scale), and perceived stress (i.e., The Perceived Stress Scale).Chi-square nonparametric tests, most notably, Pearson's, Breslow-D ay, and Mantel-Haenzel, were the principal method of data analysis, parametric tests including independent t-tests, ANOVA, and multiple regression and logistic regression analyses were also utilized.The results of this study indicate that visiting hours do matter to patients in a hospitalized environment.Although participants were satisfied with the current visiting hours, flexibility to visiting hours was a preference shared by almost all study participants.The inverse relationship between social support and stress in the hospitalized adult was approaching significance.Certain factors significantly influence visiting preferences, social support, and stress.Age was a significant factor in influencing #3: What is the relationship between the patients' perceived stress and visiting preference?between perceived stress and perceived social support?#4: Is there a relationship between the variables of age, gender, marital status, socio-economic status ethnicity, severity of illness, and perceived social support, perceived stress, and visiting preference?#5: Is there a relationship between the variables of Frequency of hospitalizatíon and the days currently spent in hospital, and the patients' visiting preferences, perceptions of social support, and perceptions of stress?#6: Is there a relationship between satisfaction with current visiting hours and overall length of stay? between perceptions of stress and overall length of stay?77 66
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».