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Current status and variables associated with readiness for hospital discharge in patients with brucellosis in Ningxia; China: a cross-sectional study
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DOI：10.3389/fmed.2026.1795489.png)
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Abstract
En 中文
ObjectiveTo explore the relevant influencing variables of discharge readiness in patients with brucellosis; so as to provide evidence-based references for implementing precise clinical intervention; optimizing discharge management and enhancing patients’ overall discharge readiness.MethodsFollowing the STROBE guidelines; a cross-sectional study was conducted. A total of 270 inpatients with brucellosis were enrolled via convenience sampling from September 2024 to July 2025 in the Department of Infectious Diseases of a tertiary specialized hospital in Ningxia. Data were collected on the day of hospital discharge using a general information questionnaire; the Readiness for Hospital Discharge Scale (RHDS); the Kessler Psychological Distress Scale (K10); the Multidimensional Scale of Perceived Social Support (MSPSS); and the Quality of Discharge Teaching Scale (QDTS). The variable selection and model construction process is as follows: First; using R Studio software; variables showing statistically significant differences in univariate and correlation analyses were included in the random forest model. The IncMSE score was used to assess the weight of each variable’s influence on discharge readiness; Next; Lasso analysis was applied to determine the optimal lambda value for selecting core independent variables. Finally; multiple linear regression analysis was performed using the Enter method (αentry = 0.05; αexit = 0.10) to identify the variables influencing discharge readiness.ResultsThe score of discharge readiness in brucellosis patients was 88.00 (73.00; 100.25); indicating a moderate level. The scores of the other scales were as follows: K10 24.00 (18.00; 29.00); MSPSS 58.00 (48.75; 66.25); and QDTS 175.00 (150.00; 199.00). Spearman correlation analysis showed that discharge readiness was negatively correlated with psychological distress (r = −0.249; p < 0.001). It was also positively correlated with perceived social support (r = 0.271; p < 0.001) and discharge teaching quality (r = 0.413; p < 0.001). Univariate analysis revealed statistically significant differences (p < 0.05) in discharge readiness scores among patients with brucellosis based on age; educational level; occupations; household income; marital status; medical expense payment methods; residency; and the presence of symptoms. The ranking of feature importance in the Random Forest model (sorted by IncMSE score from highest to lowest) was as follows: QDTS; MSPSS; educational level; K10; marital status; household income; age; occupation; medical expense payment methods; residency; and presence of symptoms. In the Lasso analysis; when lambda.1se = 4.02848; the optimal number of variables was 4. Combining this with the variable importance ranking from the random forest analysis; the top 4 variables were included in the multiple linear regression analysis. Residual tests indicated that the data exhibited an approximately symmetrical distribution around the origin; supporting the suitability of the linear regression model. The results showed that educational level; K10; MSPSS; and QDTS were independent predictors of discharge readiness (all p < 0.05); collectively explaining 28.4% of the total variance.ConclusionBrucellosis patients had a moderate level of discharge readiness; Better discharge teaching quality; greater perceived social support; higher educational level; and lower psychological distress were associated with higher discharge readiness.LimitationOne limitation of this study is that the dataset was not split into training and validation sets for data analysis; therefore; the results are only of descriptive statistical value with limited generalizability.
Keywords:
psychological distress
random forest
brucellosis
perceived social support
readiness for hospital discharge
discharge teaching quality
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