目的 探究脑卒中患者夫妻二元抑郁类别及相关因素。 方法 2019年11月至2020年8月，在某三级综合医院神经内科招募脑卒中患者夫妻224对为研究对象，采用一般资料调查表、患者健康问卷-9（patient health questionnaire-9,PHQ-9） 、压力知觉量表（perceived stress scale,PSS）、改良Rankin量表（modified Rankin scale,mRS）、简体中文版创伤后成长评定量表（Chinese-posttraumatic growth inventory,C-PTGI）、照顾者获益感量表对其进行调查，利用潜在剖面分析探索二元抑郁类别，多元Logistic回归分析各类别的预测因子。 结果 脑卒中患者夫妻二元抑郁分为夫妻无抑郁组、患者重度抑郁-配偶轻度抑郁组、患者中度抑郁-配偶无抑郁组、患者轻度抑郁-配偶中度抑郁组，以夫妻无抑郁组为参照，C-PTGI得分、预后不良、病程≥1年、家庭月收入＜2000元、患者PSS得分、发病次数≥3次、配偶获益感是预测因子（均P＜0.05）。 结论 脑卒中患者夫妻二元抑郁共存，且存在不同类别；护士应从整体视角对不同抑郁特征的脑卒中患者夫妻开展心理干预，以改善其抑郁情绪。

Objective To explore the categories of dyadic depression and related factors among stroke patients and their spouses. Methods A total of 224 dyads of stroke patients and their spouses were recruited in the Neurology Department of a tertiary general hospital from November，2019 to August，2020.The general information questionnaire，PHQ-9，PSS，Modified Rankin Scale，C-PTGI and Caregiver Benefit Finding Scale were used for investigation.Latent profile analysis was adopted to explore the categories of dyadic depression，and multiple logistic regression was used to analyze the predictors of each category. Results Categories of dyadic depression among stroke patients and their spouses included patient and spouse with no depression，patient with severe depression-spouse with mild depression，patient with moderate depression-spouse with no depression，patient with mild depression-spouse with moderate depression.Taking the category of patient and spouse with no depression as the reference，the C-PTGI score，poor prognosis，disease duration (≥1 year)，monthly household income (＜ 2,000 yuan)，patients’ PSS score，stroke occurrence (≥3)，caregiver benefits were predictors (all P＜0.05). Conclusions Dyadic depression exists in the populations of stroke patients and their spouses，which demonstrates different categories.Nurses should carry out comprehensive psychological interventions for stroke patients and their spouses with different depressive characteristics，so as to alleviate their depression.

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国家自然科学基金资助项目（72004205）；中国博士后基金面上项目（2019M652589）；河南省高等学校重点科研项目（21A320068）