A longitudinal study of the predictors of quality of life in patients with major depressive disorder utilizing a linear mixed effect model

• Published in: Psychiatry research Vol. 198; no. 3; pp. 412 - 419
• Main Authors: Pan, Ay-Woan, Chen, Yun-Ling, Chung, Ly-Inn, Wang, Jung-Der, Chen, Tsyr-Jang, Hsiung, Ping-Chuan
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ireland Ltd 15.08.2012; Elsevier
• Subjects: Adult and adolescent clinical studies; Biological and medical sciences; Depression; Depressive Disorder, Major - psychology; Female; Humans; Linear Models; Longitudinal Studies; Male; Medical sciences; Middle Aged; Mixed effects model; Mood disorders; Outcome Assessment (Health Care) - statistics & numerical data; Psychiatric Status Rating Scales - statistics & numerical data; Psychiatry; Psychology. Psychoanalysis. Psychiatry; Psychopathology. Psychiatry; Quality of life; Quality of Life - psychology; Taiwan; Taiwan; Depression; Longitudinal studies; Mixed effects model; Quality of life; Mood disorder; Human; Follow up study; Predictive factor; Linear model
• ISSN: 0165-1781; 1872-7123; 1872-7123
• DOI: 10.1016/j.psychres.2012.02.001

We set out in this study to examine a longitudinal dataset using a linear mixed effects model. Our ultimate aim is to identify predictors of the quality of life (QOL) domains and items amongst patients suffering from major depressive disorders. Four categories of variables are included in our analysis, composed of ‘personal predisposition’, ‘psychosocial’, ‘illness-related’ and ‘time’, while the outcome variables for this study are the ‘physical’, ‘psychological’, ‘social’ and ‘environmental’ domains of QOL, in conjunction with all of the items within the scale. A total of 104 subjects from an outpatient clinic of a university-affiliated hospital participated in this longitudinal study, with a one-time follow up being carried out on 70 of these subjects (67.3%) who agreed to participate in the follow-up study. The ‘severity of depression’, ‘sense of competence’ and ‘sense of mastery’, ‘use of anti-depressant medication’ and ‘environmental resources’ are found to be significant predictors of the detailed aspects of QOL. Of these, ‘symptom severity’, ‘sense of competence’ and ‘sense of mastery’ were found to occur most often. Finally, the results of the present study demonstrate that ‘illness-related’ and ‘psychosocial’ categories are capable of predicting the various QOL domains for patients suffering from depression.