Treatment-resistant Depression Nursing Trial Dataset

[Brief introduction about the study] The dataset of "Treatment-resistant Depression Nursing Trial" is created in the National Taiwan University under the project led by Professor Chia-Yi Wu. The dataset includes two-group comparison in a variety of demographic, psychosocial, and suicide-related variables. The study hypothesized that after an 8-week nurse-led group intervention, the experimental group would have enhanced resilient coping and other psychosocial responses. The findings indicated that an 8-week nurse-led group intervention enhanced the TRD patients’ resilient coping and mental distress levels while providing the potentials for community reintegration after mental health psychoeducation engagement. [Description of the dataset gathering & interpretation] The study participants were recruited from two psychiatric daycare and outpatient units in two general teaching hospitals in northern Taiwan. Randomized sampling was performed in a patient cohort established by the research team to reach the required sample size of 46, which was divided into an experimental group (n=23) and an age-and-gender matched control group (n=23). Face-to-face interviews were performed at five points of time with multiple outcome measures in the longitudinal observation period. The two groups were assessed at baseline (T0), 8-week post-baseline (T1), and at 3, 6, and 9 months after T1 (T2-4). The questionnaires included demographic and physical or mental health information, the 5-item Brief Symptom Rating Scale, the 9-item Concise Mental Health Checklist, the Brief Resilient Coping Scale, the Revised-Community Integration Questionnaire, and the 3-Level EuroQoL-5 Dimension scale assessing the quality of life. Thus, in this dataset the readers will find the above-mentioned varibales in either categorical or nominal form. [How to use it] Take SPSS statistics as an example, the readers may want to perform basic descriptive or correlational statistics using this dataset. Specific statistical analysis such as T-test, ANOVA, Chi-square tests can be considered as appropriate.