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

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

OBJECTIVE

Post-stroke depression (PSD) is a prevalent and severe sequela of stroke. It is an emotional disorder that significantly impacts functional recovery, prognosis, secondary stroke risk, and mortality among stroke survivors. The incidence rate of PSD is 18 %∼33 %, with symptoms such as low mood, decreased interest, sleep disorders, decreased appetite, impaired attention, and in severe cases, hallucinations and even suicidal tendencies. While diverse therapeutic modalities are employed globally to address PSD, each approach carries its inherent advantages and limitations. Notably, acupuncture stands out as a promising and effective intervention for ameliorating PSD symptoms and enhancing stroke prognosis. This study aims to conduct a bibliometric analysis to scrutinize the current landscape, identify hotspots, and explore frontiers in acupuncture research for PSD.

METHODS

A systematic search for acupuncture and PSD-related research was conducted from January 2014 to October 2023 on the Web of Science Core Collection (WoSCC). The data were downloaded and processed using Bibliometrix and VOSviewer to generate knowledge visualization maps.

RESULTS

A total of 11,540 articles related to acupuncture and PSD were retrieved. China emerged as the leading contributor with the highest volume of articles on acupuncture and PSD. Author Liu CZ attained the highest H-index, focusing primarily on investigating the compatibility effects and mechanisms of acupoints. Common hotspot keywords included pain, stimulation, mechanisms, complementary, and alternative medicine. The main research frontiers were mechanisms, neuroinflammation, gut microbiota, and therapeutic methods.

CONCLUSION

This study offered multifaceted insights into acupuncture for PSD, unveiling pivotal areas, research hotspots, and emerging trends. The findings aimed to guide researchers in exploring novel research directions and selecting appropriate journals for advancing the understanding and treatment of PSD through acupuncture interventions.

Social rhythm and implications on functionality of patients after stroke

The study aimed to assess the regularity, intensity, frequency, and period of activities comprising social rhythm and associate them with the functionality of stroke patients. The sample consisted of 73 patients (41 men and 32 women) with a mean age of 60 years (±10). Social rhythm was assessed by Social Rhythm Metric (SRM) and Activity Level Index (ALI). The functionality was evaluated using the International Classification of Functioning, Disability, and Health (ICF). Data were analyzed using Student's t-test, ANOVA, and Chi-square test. The mean SRM was 5.1 ± 0.9, and ALI was 58.3 ± 14.9. Notably, 40% of the patients exhibited both low regularity and low intensity of activities. Six SRM activities, performed with low frequency (going outside, starting work, exercising, snacking, watching other TV programs, and going home), exhibited a tendency to have periods that deviated from the expected 24-hour daily cycle. ICF domains most associated with SRM were: d2-General tasks and demands, d3-Communication, d4-Mobility, d5-Self care, d8-Major life areas, and d9-Community, social and civic life. The results indicated changes in social rhythm with implications for patient functionality. Screening for disruptions in social rhythm could be part of the functional assessment during the rehabilitation process for post-stroke patients.

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

OBJECTIVE

Stroke 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.

METHODS

Non-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.

RESULTS

Two 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.

INTERPRETATION

The 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.

Is sleep quality a moderated mediator between perceived stress and depression among stroke patients?

Background

Sleep quality can offer new insights into addressing depression among stroke patients. However, the current understanding of the mechanism by which sleep quality reduces depression is not clear in existing research.

Objectives

This study aimed to identify the relationships and mechanisms among perceived stress, sleep quality, social support, and depression in stroke patients.

Methods

A multicenter cross-sectional study was conducted from January to May 2023. Cluster random sampling was used to recruit 500 stroke patients from five hospitals in Henan Province, China. The Chinese Perceived Stress Scale (CPSS), Pittsburgh Sleep Quality Index (PSQI), Social Support Rating Scale (SSRS), and Hamilton Depression Scale (HAMD-24) were employed to assess perceived stress, sleep quality, social support, and depression, respectively. Data were analyzed using descriptive analysis, Pearson's correlation analysis, and moderated mediation analysis. The study adhered to the STROBE checklist for reporting.

Results

Out of 500 participants, 471 completed the survey (94.2%). After controlling for sex and age, mediation analysis revealed that poor sleep quality partially mediated the relationship between perceived stress and depression (β = 0.184, 95% CI: 0.110, 0.359). Additionally, social support played a moderating role in the mediation model.

Conclusion

This study explained the moderated mediation of sleep quality and social support between perceived stress and depression. It provided a theoretical basis for the development of a sleep quality intervention program for reducing depression among stroke patients.

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

BACKGROUND

Post-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.

METHODS

Two 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.

RESULTS

We 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).

CONCLUSION

Individual, 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.