Suppr超能文献

埃塞俄比亚哈拉马亚大学学生的抑郁症状:一项横断面研究。

Depressive Symptoms among Haramaya University Students in Ethiopia: A Cross-Sectional Study.

作者信息

Teshome Hambisa Mitiku, Derese Andualem, Abdeta Tilahun

机构信息

Haramaya University, College of Health and Medical Sciences, School of Public Health, Harar, Ethiopia.

Haramaya University, College of Health and Medical Sciences, School of Nursing and Midwifery, Department of Psychiatry, Harar, Ethiopia.

出版信息

Depress Res Treat. 2020 Jan 31;2020:5027918. doi: 10.1155/2020/5027918. eCollection 2020.

Abstract

BACKGROUND

The prevalence of mental health problems including depression is increasing in severity and number among higher institution students, and it has a lot of negative consequences like poor academic performance and committing suicide. Identifying the prevalence and associated factors of mental illness among higher institution students is important in order to administer appropriate preventions and interventions. In Ethiopia, only a few studies tried to report associated factors of depression among university students.

OBJECTIVE

The objective of this study was to determine the prevalence and factors associated with depressive symptoms among Haramaya University students, Ethiopia.

METHODS

Institution-based, cross-sectional study design was conducted among 1040 students. A standard, self-administered questionnaire was used to get data from a sample of randomly selected 1040 undergraduate university students using a multistage systematic random sampling technique. The questionnaire used was the Beck Depression Inventory (BDI) scale which is a self-report 21-item scale that is used to assess the presence of depressive symptoms. All 21 items are rated on a three-point scale (0 to 3). Each question is scored on a 0 to 3 scale, and total scores range from 0 to 63, with higher scores reflecting greater levels of depressive symptoms. The questionnaire has been well validated as a measure of depressive symptomatology with scores 1-13 indicating minimal depressive symptoms, 14-19 showing mild depressive symptoms, 20-28 showing moderate depressive symptoms, and 29-63 indicating severe depressive symptoms. Logistic regression analysis was used to identify variables independently associated with depressive symptoms after we dichotomized the depressive symptoms screening tool to "yes/no" depressive symptoms. This means students who did not report any depressive symptoms were given "no" depressive symptoms and who reported at least one (≥1) depressive symptoms were given "yes" (depressive symptoms).

RESULTS

A total of 1022 (98.3%) out of 1040 students participated in this study. The mean age of participants was 20.9 years (SD ± 2.17), and the majority of them (76.0%) were male students. Prevalence of depressive symptoms among undergraduate students was 26.8% (95% CI: 24.84, 28.76). Among those who had reported depressive symptoms: 10%, 12%, 4%, and 1% of students reported minimal, mild, moderate, and severe depressive symptoms, respectively. Multivariable logistic regression analysis in the final model revealed that being a first-year student (AOR 6.99, 95% CI: 2.31, 21.15, value < 0.001), being a second-year student (AOR 6.25, 95% CI: 2.05, 19.07, value < 0.001), being a second-year student (AOR 6.25, 95% CI: 2.05, 19.07, value < 0.001), being a second-year student (AOR 6.25, 95% CI: 2.05, 19.07, value < 0.001), being a second-year student (AOR 6.25, 95% CI: 2.05, 19.07, value < 0.001), being a second-year student (AOR 6.25, 95% CI: 2.05, 19.07, value < 0.001), being a second-year student (AOR 6.25, 95% CI: 2.05, 19.07, value < 0.001), being a second-year student (AOR 6.25, 95% CI: 2.05, 19.07.

CONCLUSIONS

The prevalence of depressive symptoms among university students in this study is high relative to the general population. Sociodemographic factors year of study and current substance use were identified as associated factors of depressive symptoms. . This finding suggests the need for the provision of mental health services at the university, including screening, counseling, and effective treatment. Families need to closely follow their students' health status by having good communication with the universities, and they have to play their great role in preventing depression and providing appropriate treatment as needed. The governments and policy-makers should stand with universities by supporting and establishing matured policies which helps universities to have mental health service centers. Generally, the university and other stakeholders should consider these identified associated factors for prevention and control of mental health problems of university students.

摘要

背景

包括抑郁症在内的心理健康问题在高等院校学生中的严重程度和数量正在增加,并且会产生许多负面后果,如学业成绩不佳和自杀。识别高等院校学生中精神疾病的患病率及其相关因素对于进行适当的预防和干预很重要。在埃塞俄比亚,只有少数研究试图报告大学生抑郁症的相关因素。

目的

本研究的目的是确定埃塞俄比亚哈拉马亚大学学生中抑郁症状的患病率及其相关因素。

方法

在1040名学生中进行了基于机构的横断面研究设计。使用标准的自填式问卷,通过多阶段系统随机抽样技术从随机选择的1040名本科大学生样本中获取数据。所使用的问卷是贝克抑郁量表(BDI),这是一个21项的自我报告量表,用于评估抑郁症状的存在。所有21项均采用三分制评分(0至3)。每个问题的评分范围是0至3分,总分范围是0至63分,分数越高表明抑郁症状越严重。该问卷作为抑郁症状学的一种测量方法已得到充分验证,分数1 - 13表示轻度抑郁症状,14 - 19表示中度抑郁症状,20 - 28表示重度抑郁症状,29 - 63表示极重度抑郁症状。在将抑郁症状筛查工具分为“有/无”抑郁症状后,使用逻辑回归分析来识别与抑郁症状独立相关的变量。这意味着未报告任何抑郁症状的学生被归类为“无”抑郁症状,而报告至少一种(≥1)抑郁症状的学生被归类为“有”(抑郁症状)。

结果

1040名学生中共有1022名(98.3%)参与了本研究。参与者的平均年龄为20.9岁(标准差±2.17),其中大多数(76.0%)是男学生。本科生中抑郁症状的患病率为26.8%(95%置信区间:24.84,28.76)。在报告有抑郁症状的学生中:分别有10%、12%、4%和1%的学生报告有轻度、中度、重度和极重度抑郁症状。最终模型中的多变量逻辑回归分析显示,作为一年级学生(优势比6.99,95%置信区间:2.31,21.15,p值<0.001),作为二年级学生(优势比6.25,95%置信区间:2.05,19.07,p值<0.001),作为二年级学生(优势比6.25,95%置信区间:2.05,19.07,p值<0.001),作为二年级学生(优势比6.25,95%置信区间:2.05,19.07,p值<0.001),作为二年级学生(优势比6.25,95%置信区间:2.05,19.07,p值<0.001),作为二年级学生(优势比6.25,95%置信区间:2.05,19.07,p值<0.001),作为二年级学生(优势比6.25,95%置信区间:2.05,19.07,p值<0.001),作为二年级学生(优势比6.25,95%置信区间:2.05,19.07,p值<0.001)。

结论

本研究中大学生抑郁症状的患病率相对于一般人群较高。社会人口统计学因素、学年和当前物质使用被确定为抑郁症状的相关因素。这一发现表明需要在大学提供心理健康服务,包括筛查、咨询和有效治疗。家庭需要通过与大学保持良好沟通密切关注学生的健康状况,并在预防抑郁症和根据需要提供适当治疗方面发挥重要作用。政府和政策制定者应通过支持和制定成熟的政策来支持大学,帮助大学建立心理健康服务中心。总体而言,大学和其他利益相关者应考虑这些已确定的相关因素,以预防和控制大学生的心理健康问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b846/7013291/a4dc823f4444/DRT2020-5027918.001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验