Table_2_The relations between socio-demographic information and negative symptoms, mental health, and quality of life: a latent profile analysis with psychotic patients in Kosovo.DOCX

The current study aims to identify meaningful psychotic patients’ profiles by examining certain combinations of patient’s demographic and socio-economic variables (sex, age, marital status, number of children, cohabitant and level of education). Moreover, we aim to assess whether there is any significant effect of class membership (profile) on negative symptoms, health state, and quality of life among psychotic patients. A convenience sample of 103 patients (age: M = 22, SD = 1.75), was drawn from the clinical populations of Kosovo. Demographic and socio-economic data was obtained through individual interviews, meanwhile a battery of questionnaires was used to assess negative symptoms, mental health, and quality of life of patients. The 4-class solution was selected as the best fitting model and used in subsequent analyses. Results indicated a significant effect of class membership on health state, quality of life and negative symptoms. Practical implications are discussed.

本研究旨在通过分析精神疾病患者的人口统计学与社会经济变量组合（包括性别、年龄、婚姻状况、子女数量、同居情况及教育水平），识别具有临床意义的精神疾病患者分型。此外，本研究旨在评估患者的类别归属（即分型）是否对精神疾病患者的阴性症状、健康状况及生活质量存在显著影响。本研究采用便利抽样法，从科索沃临床诊疗人群中招募了103名患者（年龄：均值M=22，标准差SD=1.75）。人口统计学与社会经济资料通过一对一访谈收集，同时采用一套成套问卷评估患者的阴性症状、心理健康状况及生活质量。最终选定4类别模型为最优拟合模型，并应用于后续分析。结果显示，类别归属对患者的健康状况、生活质量及阴性症状均存在显著影响。本研究还探讨了其临床实践意义。