Matsumoto Yasuyuki, Sakurai Hitoshi, Aoki Yumi, Takaesu Yoshikazu, Okajima Isa, Tachimori Hisateru, Murao Masami, Maruki Taku, Tsuboi Takashi, Watanabe Koichiro
Department of Neuropsychiatry, Kyorin University Faculty of Medicine, Tokyo, Japan.
Psychiatric and Mental Health Nursing, Graduate School of Nursing Science, St. Luke's International University, Okinawa, Tokyo, Japan.
Front Psychiatry. 2024 Apr 17;15:1321611. doi: 10.3389/fpsyt.2024.1321611. eCollection 2024.
Depression significantly impacts the job performance and attendance of workers, leading to increased absenteeism. Predicting occupational engagement for individuals with depression is of paramount importance. This study aims to determine the cut-off score which predicts continuous employment for patients with mood disorders using the Quick Inventory of Depressive Symptomatology, Self-Report (QIDS-SR).
In a prospective observational trial conducted in Tokyo, 111 outpatients diagnosed with either major depressive disorder or bipolar depression were enrolled. Their employment statuses of these participants were tracked over a six-month period after their QIDS-SR scores were recorded. Based on their employment trajectories, participants were categorized into either continuous or non-continuous employment groups. Binary logistic regression was applied to examine the relationship between the QIDS-SR scores and employment outcomes, with adjustments for age, gender, and psychiatric diagnoses. Receiver operating characteristic curves were utilized to identify the optimal QIDS-SR cut-off values for predicting continuous employment.
Binary logistic regression demonstrated that a lower score on the QIDS-SR was linked to an elevated likelihood of continuous employment (adjusted odds ratio 1.15, 95% CI: 1.06-1.26, p=0.001). The optimal cut-off point, determined by the Youden Index, was 10/11, showcasing a 63% sensitivity and 71% specificity.
The results emphasize the potential of the QIDS-SR as a prognostic instrument for predicting employment outcomes among individuals with depressive disorders. These findings further underscore the importance of managing depressive symptoms to mild or lower intensities to ensure ongoing employment.
抑郁症对员工的工作表现和出勤情况有显著影响，导致旷工率上升。预测抑郁症患者的职业参与度至关重要。本研究旨在使用抑郁症状快速自评量表（QIDS-SR）确定能够预测情绪障碍患者持续就业的临界分数。
在东京进行的一项前瞻性观察性试验中，招募了111名被诊断为重度抑郁症或双相抑郁症的门诊患者。在记录他们的QIDS-SR分数后的六个月内，跟踪这些参与者的就业状况。根据他们的就业轨迹，将参与者分为持续就业组或非持续就业组。应用二元逻辑回归分析QIDS-SR分数与就业结果之间的关系，并对年龄、性别和精神疾病诊断进行调整。利用受试者工作特征曲线确定预测持续就业的最佳QIDS-SR临界值。
二元逻辑回归表明，QIDS-SR得分较低与持续就业的可能性增加有关（调整后的优势比为1.15，95%置信区间：1.06-1.26，p=0.001）。由约登指数确定的最佳临界点为10/11，灵敏度为63%，特异度为71%。
结果强调了QIDS-SR作为预测抑郁症患者就业结果的预后工具的潜力。这些发现进一步强调了将抑郁症状控制在轻度或更低强度以确保持续就业的重要性。
