Resilience in Stroke Patients: A Concept Analysis

Impact of perceived social support on family resilience in patients with ischemic stroke: A mediation model analysis

BACKGROUND

Ischemic stroke events impose a substantial burden on both families and society, underscoring the critical importance of early intervention and prevention strategies. The dearth of familial and societal support significantly impacts coping styles and family resilience, with negative coping styles potentially linked to diminished levels of family resilience. However, empirical evidence supporting these associations remains lacking.

OBJECTIVE

The aim of this study was to examine the association between simplified coping style, perceived social support and family resilience in patients with ischemic stroke, while also investigating the potential mediating role of simplified coping style in the relationship between perceived social support and family resilience.

METHODS

Convenience sampling was employed to select patients with ischemic stroke from three tertiary hospitals in Hunan Province between May and November 2021. A comprehensive investigation was conducted using a General data questionnaire, Simplified Coping Style Questionnaire, Perceived Social Support Scale and Family Resilience Rating Scale. The mediating effect was analyzed using PROCESS macros in SPSS, while the significance was tested through the Bootstrap method.

RESULTS

A total of 310 questionnaires were distributed, with 7 identified as containing errors, omissions, or losses. Of these, 303 valid questionnaires were collected, yielding an effective response rate of 97.74 %. The scores for family resilience among ischemic stroke patients showed significant positive correlations with simple coping style (r = 0.59, P < 0.01) and perceived social support (r = 0.69, P < 0.01). Additionally, there was a positive correlation between perceived social support and simple coping style (r = 0.56, P < 0.01). Furthermore, the simple coping style played a crucial mediating role in the relationship between perceived social support and family resilience by accounting for approximately 20.70 % of the effect size.

CONCLUSION

The findings suggest that enhancing positive coping styles and effective social support can enhance the level of family resilience in patients with ischemic stroke. Therefore, medical professionals should focus on improving social support while targeting coping styles as an intervention strategy to actively adjust the coping modes, ultimately elevating the level of family resilience in patients with ischemic stroke.

Self-efficacy and resilience in severe aphasia - an exploratory cross-sectional study of two psychosocial factors and their relation to functional communication

PURPOSE

Self-efficacy and resilience are important for various aspects of rehabilitation outcome after stroke. However, little is known about how these factors are affected and related to communication outcome in stroke survivors with aphasia. The purpose was to investigate self-efficacy and resilience, and associations to language and functional communication, in people with severe post-stroke aphasia.

MATERIALS AND METHODS

37 participants with severe aphasia rated their self-efficacy and resilience, using adapted versions of the existing instruments DLSES and CD-RISC. In addition, linguistic ability, executive function and functional communication were assessed.

RESULTS

Participants rated their self-efficacy and resilience as expected based on reports in the literature; somewhat lower than general populations and at similar levels as clinical populations. There were no association between self-efficacy, resilience and linguistic ability. In the sample as a whole, there were no associations between self-efficacy, resilience and functional communication. However, when results were stratified by executive function, associations emerged in the group with stronger executive function.

CONCLUSIONS

People with severe aphasia have decreased self-efficacy and resilience compared to general populations, but not necessarily in proportion to their language impairment. Among participants with relatively spared executive functions there were indications of an association between self-efficacy, resilience and functional communication.

The stroke outcome optimization project: Acute ischemic strokes from a comprehensive stroke center

Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired for acute stroke management. Publicly sharing these datasets can aid in the development of machine learning algorithms, particularly for lesion identification, brain health quantification, and prognosis. These algorithms thrive on large amounts of information, but require diverse datasets to avoid overfitting to specific populations or acquisitions. While there are many large public MRI datasets, few of these include acute stroke. We describe clinical MRI using diffusion-weighted, fluid-attenuated and T1-weighted modalities for 1715 individuals admitted in the upstate of South Carolina, of whom 1461 have acute ischemic stroke. Demographic and impairment data are provided for 1106 of the stroke survivors from this cohort. Our validation demonstrates that machine learning can leverage the imaging data to predict stroke severity as measured by the NIH Stroke Scale/Score (NIHSS). We share not only the raw data, but also the scripts for replicating our findings. These tools can aid in education, and provide a benchmark for validating improved methods.

Doctors and nurses subjective predictions of 6-month outcome compared to actual 6-month outcome for adult patients with spontaneous intracerebral haemorrhage (ICH) in neurocritical care: An observational study

Background

Acute spontaneous intracerebral haemorrhage is a devastating form of stroke. Prognostication after ICH may be influenced by clinicians' subjective opinions.

Purpose

To evaluate subjective predictions of 6-month outcome by clinicians' for ICH patients in a neurocritical care using the modified Rankin Scale (mRS) and compare these to actual 6-month outcome.

Method

We included clinicians' predictions of 6-month outcome in the first 48 h for 52 adults with ICH and compared to actual 6-month outcome using descriptive statistics and multilevel binomial logistic regression.

Results

35/52 patients (66%) had a poor 6-month outcome (mRS 4-6); 19/52 (36%) had died. 324 predictions were included. For good (mRS 0-3) versus poor (mRS 4-6), outcome, accuracy of predictions was 68% and exact agreement 29%. mRS 6 and mRS 4 received the most correct predictions. Comparing job roles, predictions of death were underestimated, by doctors (12%) and nurses (13%) compared with actual mortality (36%). Predictions of vital status showed no significant difference between doctors and nurses: OR = 1.24 {CI; 0.50-3.05}; (p = 0.64) or good versus poor outcome: OR = 1.65 {CI; 0.98-2.79}; (p = 0.06). When predicted and actual 6-month outcome were compared, job role did not significantly relate to correct predictions of good versus poor outcome: OR = 1.13 {CI;0.67-1.90}; (p = 0.65) or for vital status: OR = 1.11 {CI; 0.47-2.61}; p = 0.81).

Conclusions

Early prognostication is challenging. Doctors and nurses were most likely to correctly predict poor outcome but tended to err on the side of optimism for mortality, suggesting an absence of clinical nihilism in relation to ICH.