The mediating effect of post‐stroke depression between social support and quality of life among stroke survivors: A meta‐analytic structural equation modeling

Kuang, Jinke; Yang, Li; Lv, Runtian; Li, Jia; Zhou, Kexin; Xu, Mengfan

doi:10.1002/gps.5820

Cited by 5 publications

(5 citation statements)

References 99 publications

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“…Our results showed a significant negative correlation between the level of social support and depression scores, consistent with previous studies. 35,36 Lack of support from others can lead to a lack of spiritual comfort, inadequate financial support, and the capacity for basic health needs. 37 Likewise, they become more passive in social contact due to decreased general well-being, which contributes to the development of PSD.…”

Section: Discussionmentioning

confidence: 99%

Predictors of post‐stroke depression: the perspective from the social convoy model

et al. 2023

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BackgroundPost‐stroke depression (PSD) as one of the most common neuropsychiatric disorders after a stroke and is caused by many factors. However, the relationships among different factors and their potential contributions to PSD remain unclear.MethodsTwo hundred and seventy‐six patients were recruited into this study. The general information questionnaire, the Patient Health Questionnaire‐9, the Perceived Social Support Scale, the Family Assessment Device, the General Well‐Being Scale, the Barthel Index, and the modified Rankin Scale were used to assess the condition of patients. Subsequently, we identify the main causes associated with the PSD and then performed a path analysis to clarify the direct, indirect and total effects among the variables.ResultsWe found that age, stroke with coronary heart disease, neurological function, family function, social support, and general well‐being had a significant impact on PSD (P < 0.05). Of these, neurological function had the largest total effect on PSD (β = 0.451), social support contributed the most as a direct effect (β = −0.306), and family function showed the largest indirect effect (β = −0.264).ConclusionIndividual, disease, and social‐psychological factors all contributed to the development of PSD. We should pay more attention to comprehensive assessment, especially for those with poor neurological function, and lacking family or social support. In addition, it would be preferable to provide them with necessary support and care strategies to reduce the incidence of PSD.

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Section: Discussionmentioning

confidence: 99%

Predictors of post‐stroke depression: the perspective from the social convoy model

et al. 2023

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“…This study has found that “help from others” and “opportunities for community activities” are the most important predictors of quality of life. Previous studies have shown that social support and community involvement are interrelated, and either is strongly associated with quality of life and also depression 36 . Depression in a stroke survivor is likely to be reflected in a low role‐emotion (RE) score, which is characteristic of type I individuals with a poor quality of life.…”

Section: Discussionmentioning

confidence: 99%

“…Depression in a stroke survivor is likely to be reflected in a low role‐emotion (RE) score, which is characteristic of type I individuals with a poor quality of life. Previous studies have shown that social support is a significant predictor of quality of life, mediated by poststroke depression 36 . Among aphasic stroke survivors, depression is known to be strongly correlated with decreased community participation and impaired quality of life 37 .…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have shown that social support is a significant predictor of quality of life, mediated by poststroke depression. 36 Among aphasic stroke survivors, depression is known to be strongly correlated with decreased community participation and impaired quality of life. 37 Social support is an important predictor of successful community participation.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have shown that social support and community involvement are interrelated, and either is strongly associated with quality of life and also depression. 36 Depression in a stroke survivor is likely to be reflected in a low roleemotion (RE) score, which is characteristic of type I individuals with a poor quality of life. Previous studies have shown that social support is a significant predictor of For type Iworsen QoL subtype, help from others (nobody helping) was the most important variable, followed by opportunities for community activities (none), education (no experience), and rehabilitation needs (need).…”

Section: Community and Demographic Factors Predicting Quality Of Lifementioning

confidence: 99%

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An machine learning model to predict quality of life subtypes of disabled stroke survivors

Xu,

Lei,

Lin

et al. 2023

Ann Clin Transl Neurol

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ObjectiveStroke causes serious physical disability with impaired quality of life (QoL) and heavy burden on health. The goal of this study is to explore the impaired QoL typologies and their predicting factors in physically disabled stroke survivors with machine learning approach.MethodsNon‐negative matrix factorization (NMF) was applied to clustering 308 physically disabled stroke survivors in rural China based on their responses on the short form 36 (SF‐36) assessment of quality of life. Principal component analysis (PCA) was conducted to differentiate the subtypes, and the Boruta algorithm was used to identify the variables relevant to the categorization of two subtypes. A gradient boosting machine(GBM) and local interpretable model‐agnostic explanation (LIME) algorithms were used to apply to interpret the variables that drove subtype predictions.ResultsTwo distinct subtypes emerged, characterized by short form 36 (SF‐36) domains. The feature difference between worsen QoL subtype and better QoL subtype was as follows: role‐emotion (RE), body pain (BP) and general health (GH), but not physical function (PF); the most relevant predictors of worsen QoL subtypes were help from others, followed by opportunities for community activity and rehabilitation needs, rather than disability severity or duration since stroke.InterpretationThe results suggest that the rehabilitation programs should be tailored toward their QoL clustering feature; body pain and emotional‐behavioral problems are more crucial than motor deficit; stroke survivors with worsen QoL subtype are most in need of social support, return to community, and rehabilitation.

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Global research trends in acupuncture treatment for post-stroke depression: A bibliometric analysis

Li,

Tao,

Yang

et al. 2024

Complementary Therapies in Medicine

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The mediating effect of post‐stroke depression between social support and quality of life among stroke survivors: A meta‐analytic structural equation modeling

Cited by 5 publications

References 99 publications

Predictors of post‐stroke depression: the perspective from the social convoy model

Predictors of post‐stroke depression: the perspective from the social convoy model

An machine learning model to predict quality of life subtypes of disabled stroke survivors

Global research trends in acupuncture treatment for post-stroke depression: A bibliometric analysis

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