对重度抑郁症患者和健康人的职业表现特征进行判别分析。

PCN reports : psychiatry and clinical neurosciences Pub Date : 2024-11-26 eCollection Date: 2024-12-01 DOI:10.1002/pcn5.70038
Tomonari Hayasaka, Izumi Nagashima, Miku Hoshino, Koji Teruya, Yasuyuki Matumoto, Masami Murao, Taku Maruki, Masako Watanabe, Takeshi Katagiri, Yayoi Imamura, Mariko Kurihara, Yuki Oe, Yoshikazu Takaesu, Takashi Tsuboi, Koichiro Watanabe, Hitoshi Sakurai
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引用次数: 0

摘要

目的:评估重度抑郁障碍(MDD)患者的症状和日常功能可能具有挑战性,因为他们的自我监控能力有限,可能导致在结构化访谈中观察到的行为不能准确反映他们的日常生活。本研究旨在确定特定的职业行为能否将重度抑郁症患者与健康人区分开来:方法:从医疗记录和活动计划中收集基线数据。三位职业治疗师进行了内容分析,以评估职业表现特征。通过卡方检验比较了 MDD 患者和健康对照组之间这些特征的发生率。多变量逻辑回归控制了潜在的混杂因素,并根据临床相关性和样本大小选择了自变量(p 结果:共发现了 69 个职业表现特征,其中 12 个在 27 名 MDD 患者和 43 名健康对照者之间存在显著差异。主要鉴别变量包括 "提问和咨询"(p = 0.003,OR = 0.078,95% CI = 0.015-0.416)、"选择简单工作"(p = 0.004,OR = 17.803,95% CI = 2.446-129.597)和 "守时"(p = 0.017,OR = 0.030,95% CI = 0.002-0.530)。利用这些变量进行的判别分析得出的 Wilks' λ 为 0.493(p 结论:"职业绩效 "和 "守时 "是两个不同的变量:本研究强调了职业表现特征在定制 MDD 治疗策略中的重要性,提供了超越传统评估方法的见解。
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Discriminant analysis of occupational performance characteristics in patients with major depressive disorders and healthy individuals.

Aim: Assessing symptoms and daily functioning in patients with major depressive disorder (MDD) can be challenging, as their limited self-monitoring abilities may result in behavior observed during structured interviews not accurately reflecting their daily lives. This study aimed to determine if specific occupational behaviors could distinguish individuals with MDD from healthy individuals.

Methods: Baseline data were collected from medical records and activity programs. Three occupational therapists conducted content analysis to assess occupational performance characteristics. Chi-squared tests compared the prevalence of these characteristics between patients with MDD and healthy controls. Multivariable logistic regression controlled for potential confounders, with independent variables selected based on clinical relevance and sample size (p < 0.01). Discriminant analysis was used to enhance group differentiation, assessing prediction rates using area under the curve (AUC) values.

Results: A total of 69 occupational performance characteristics were identified, with 12 showing significant differences between 27 patients with MDD and 43 healthy controls. Key discriminators included "Ask questions and consult" (p < 0.001, odds ratio [OR] = 0.051, 95% confidence interval [CI] = 0.009-0.283), "Concentrate on work" (p = 0.003, OR = 0.078, 95% CI = 0.015-0.416), "Choose simple work" (p = 0.004, OR = 17.803, 95% CI = 2.446-129.597), and "Punctual" (p = 0.017, OR = 0.030, 95% CI = 0.002-0.530). Discriminant analysis using these variables yielded a Wilks' λ of 0.493 (p < 0.001), achieving an 88.6% accuracy rate. The receiver operating characteristic curve's AUC value was 0.911 (sensitivity = 95.3%, specificity = 77.8%).

Conclusion: This study highlights the importance of occupational performance characteristics in tailoring treatment strategies for MDD, providing insights beyond traditional assessment methods.

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