Nagata Shinichi, McCormick Bryan, Brusilovskiy Eugene, Salzer Mark S
Department of Social and Behavioral Sciences, Temple University, Philadelphia, PA, USA.
Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, Japan.
Int J Soc Psychiatry. 2022 Dec;68(8):1689-1697. doi: 10.1177/00207640211052182. Epub 2021 Dec 11.
People with serious mental illnesses have elevated levels of depressive symptoms. Limited engagement in meaningful activities, such as work, social interactions, volunteering, and participation in faith, are one plausible explanation for this. Increased community participation over time may be associated with decreased depressive symptoms.
Examine whether an increase in participation over time predicts a decrease in depression after controlling for depression at the baseline.
Participants were 183 adults with schizophrenia spectrum, bipolar disorder, or major depressive disorder who completed the Hopkins Symptom Index - Depression subscale and the Temple University Community Participation Measure. Participants completed these measures at baseline and either a 12- or 24-month follow-up timepoint. Multiple regression analyses were conducted with the depression score as a dependent variable and changes in community participation as a predictor variable. Demographics, baseline depression score, and time interval between baseline and last observation were entered as control variables.
Endorsing more activities as important, participating in more important areas that are important, and participating 'enough' in more important areas over time were each significant predictors of decreases in depression.
These findings enhance the connection between community participation and depression and suggest that a focus on participation may be important in terms of boosting both community functioning and treatment goals.
患有严重精神疾病的人群抑郁症状水平较高。参与有意义活动(如工作、社交互动、志愿服务和宗教活动参与)受限可能是一个合理的解释。随着时间推移社区参与度增加可能与抑郁症状减轻相关。
在控制基线抑郁水平后,检验随时间推移参与度的增加是否预示着抑郁程度的降低。
183名患有精神分裂症谱系障碍、双相情感障碍或重度抑郁症的成年人参与研究,他们完成了霍普金斯症状自评量表-抑郁分量表以及天普大学社区参与度测量。参与者在基线期以及12个月或24个月的随访时间点完成这些测量。以抑郁得分作为因变量,社区参与度变化作为预测变量进行多元回归分析。将人口统计学特征、基线抑郁得分以及基线与最后一次观察之间的时间间隔作为控制变量纳入分析。
随着时间推移,认可更多活动很重要、参与更多重要领域以及在更多重要领域“充分”参与,均是抑郁程度降低的显著预测因素。
这些发现加强了社区参与与抑郁之间的联系,并表明关注参与度对于促进社区功能和治疗目标可能很重要。