Hospital visitation preferences and perceived stress in adults on medical units
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".