Can Goal-Based Health Management Improve the Health Knowledge, Health Belief and Health Behavior in People at High Risk of Stroke? A Non-Randomized Controlled Trial

Factors associated with health behaviours among stroke survivors: A mixed-methods study using COM-B model

AIMS

To identify factors associated with health behaviours among stroke survivors, through a multi-centre study.

DESIGN

A sequential mixed methods design.

METHODS

In the quantitative research phase, a total of 350 participants were recruited through multi-stage sampling from December 2022 to June 2023. General information questionnaires, The Stroke Prevention Knowledge Questionnaire (SPKQ), Short Form Health Belief Model Scale (SF-HBMS), Health Promoting Lifestyle Profile (HPLPII), and the WHOQOL-BREF (World Health Organization Quality of Life Questionnaire, Brief Version) were distributed across five tertiary hospitals in Henan province, China. For the qualitative research component, semi-structured interviews were conducted to explore the barriers and facilitators of health behaviour. This study adheres to the GRAMMS guidelines.

RESULTS

A total of 315 participants (90.0%) completed the survey. Identified barriers to health behaviour included residing in rural areas, higher scores on the Charlson Comorbidity Index (CCI) and mRS, as well as lower scores on SPKQ, SF-HBMS and WHOQOL-BREF. Twenty-four individuals participated in qualitative interviews. Twenty-eight themes were identified and categorised by frequency, covering areas such as knowledge, skills, intentions, social influences, social/professional role and identity, environmental context and resources, beliefs about capabilities, beliefs about consequences and behavioural regulation. Both quantitative and qualitative data suggested that health behaviour among stroke survivors is at a moderate level, and the identified barrier factors can be mapped into the COM-B model (Capability, Opportunity, Motivation and Behaviour).

CONCLUSION

The study indicates that key barriers to health behaviour among stroke survivors align with the COM-B model. These identified factors should be carefully considered in the planning of future systematic interventions aimed at improving health behaviours among stroke survivors.

PATIENT OR PUBLIC CONTRIBUTION

Patients were invited to completed questionnaires in the study and semi-structured interviews. The investigators provided explanation of this study' content, purpose and addressed issues during the data collection.

Effectiveness of health management among individuals at high risk of stroke: An intervention study based on the health ecology model and self-determination theory (HEM-SDT)

Background

Stroke is the second leading cause of death in adults worldwide. However, up to 80% of strokes can be prevented by modifying risk factors.

Objective

The study aims to assess the effectiveness of the Health Ecology Model and Self-Determination Theory (HEM-SDT) based health management intervention among individuals at high risk of stroke.

Methods

A randomized controlled trial was conducted in Zhengzhou from May 1st, 2020, to December 31st, 2020. A total of 229 participants were recruited for the study, with 116 individuals at high risk of stroke being randomly assigned to the HEM-SDT health management group, while 113 participants were enrolled in the control group, following their current routine practices. The Generalized Estimating Equation model (GEE) was used to analyze the differences in health knowledge, belief and, behavior between the two groups at the beginning of the intervention, and at 6-month intervals after the intervention. The chi-square test was utilized to assess the control rate of risk factors.

Results

After 6 months of intervention, there were significant improvements in health knowledge, behavior, and belief among the participants. The study found significant differences in the interaction effects between time and group for health knowledge (Mean, SD = 25.62 ± 3.88, 95%CI: 7.944-9.604, P＜0.001), health belief (Mean, SD = 87.18 ± 14.21, 95%CI: 23.999-29.887, P＜0.001), and health behavior (Mean, SD = 173.28 ± 24.22, 95%CI: 22.332-36.904, P＜0.001). Additionally, the rates of hypertension, hyperglycemia, dyslipidemia, high or medium risk condition of stroke, obesity, hyperhomocysteinemia, smoking, alcohol consumption, and lack of exercise also showed statistical significance (P＜0.05) after the intervention.

Conclusion

The HEM-SDT health management model improves the health knowledge, behavior, and beliefs in people at high risk of stroke and remarkably it shows improvement in modifiable risk factors. It can be recommended for systematic health management in people at high-risk of stroke.

Association between ethnicity and health knowledge among the floating population in China

Background

Health equity remains a priority concerns by central government in China. This study aimed to explore ethnic gaps in access to health knowledge categories and sources based on the survey data from a publicly available dataset.

Methods

Data were from 2015 China Migrants Dynamic Survey issued by The National Health Commission in China. Descriptive analyses were performed to reflect geodemographic differences in the floating population of ethnic minority (EMFP) and Han majority (HMFP) with Chi-square test. Ethnic gaps in access to health knowledge categories and sources were explored with Poisson regressions, logistic regressions, and bivariate ordered probit regressions.

Results

In the sample, most of participants had inadequate health information literacy. There were significant differences regarding geodemographic factors between EMFP and HMFP. Illiterate EMFP had likelihood to obtain less health knowledge categories (IRR = 0.80, 95% CI 0.77–0.84) and sources (IRR = 0.83, 95% CI 0.80–0.86) as compared to illiterate HMFP. Most of correlations between health knowledge categories and sources were weak in the samples of EMFP and HMFP.

Conclusion

Ethnic disparities in access to health knowledge categories and sources among the floating population in China were confirmed. Further effective efforts should be provided to reduce ethnic disparities in access to health knowledge under the ethnicity-orientated support of public health resource.