BMJ public health最新文献

Introduction: Burnout, low motivation, and poor job satisfaction among community health workers (CHWs) have negative impacts on health workers and on patients. This study aimed to characterize levels of burnout, motivation, and job satisfaction in CHWs in Madhya Pradesh, India and to determine the relation between these levels and participant characteristics. This study can inform efforts to promote wellbeing and address stress in this population.

Methods: In this cross-sectional study, we recruited participants via simple random sampling without replacement. We administered two validated questionnaires, the Copenhagen Burnout Inventory and a Motivation and Job Satisfaction Assessment, to CHWs who had enrolled in a training program to deliver a brief psychological intervention for depression. We calculated mean scores for each questionnaire item, examined the reliability of the measures, and analyzed associations between participant demographic characteristics and questionnaire scores.

Results: 339 CHWs completed the questionnaires. The personal burnout domain had the highest mean burnout score (41.08, 95% CI 39.52-42.64, scale 0-100) and 33% of participants reported moderate or greater levels of personal burnout. Items that reflected physical exhaustion had the highest item-test correlations. The organization commitment domain had the highest mean motivation score (mean 3.34, 95% CI 3.28 - 3.40, scale 1-4). Items describing pride in CHWs' work had the highest item-test correlations. Several pairwise comparisons showed that higher education levels were associated with higher motivation levels (degree or higher vs. 8^th standard [p=0.0044] and 10^th standard [p=0.048], and 12^th standard vs. 8^th standard [p= 0.012]). Cronbach's alpha was 0.82 for the burnout questionnaire and 0.86 for the motivation and job satisfaction questionnaire.

Conclusion: CHWs report experiencing burnout and feeling physically tired and worn out. A sense of pride in their work appears to contribute to motivation. These findings can inform efforts to address burnout and implement effective task-sharing programs in low-resource settings.

Introduction: There is a growing emphasis on improving primary health care services and granting frontline service providers more decision-making autonomy. In October 2023, Kenya enacted legislation mandating nationwide facility autonomy. There is limited understanding of the effects of health facility autonomy on primary health care (PHC) facilities performance. It is recognized that stakeholder interests influence reforms, and gender plays a critical role in access to health and its outcomes. This protocol outlines the methods for a study that plans to evaluate the effects, implementation experience, political economy, and gendered effects of health facility autonomy reforms in Kenya.

Methods and analysis: The research will use a before-and-after quasi-experimental study design to measure the effects of the reform on service readiness and service utilization, and a cross-sectional qualitative study to explore the implementation experience, political economy, and gendered effects of these reforms. Data to measure the effects of autonomy will be collected from a sample of 80 health facilities and 1600 clients per study arm. Qualitative interviews will involve approximately 83 facility managers and policymakers at the county level, distributed across intervening (36), and planning to intervene (36) counties. Additionally, 11 interviews will be conducted at the national level with representatives from the Ministry of Health, the National Treasury, the Controller of Budget, the Council of Governors, the Auditor General, and development partners. Given the uncertainty surrounding the implementation of the reforms, this study proposes two secondary designs in the event our primary design is not feasible - a cross-sectional study, and a quasi-experimental interrupted time series design. The study will use a difference-in-difference analysis for the quantitative component to evaluate the effects of the reforms, while using thematic analysis for the qualitative component to evaluate the political economy and the implementation experience of the reforms.

Ethics and dissemination: This study was approved by the Kenya Medical Research Institute Scientific and Ethics Review Unit (KEMRI/SERU/CGMR-C/294/4708) and the National Commission for Science, Technology and Innovation (NACOSTI/P/23/28111). We plan to disseminate the findings through publications, policy briefs and dissemination workshops.

Background: About 16% of worldwide dementia cases are in India. Evaluating the prospects for dementia prevention in India requires knowledge of context-specific risk factors, as relationships between risk factors and dementia observed in high-income countries (HICs) may not apply.

Methods: We computed population attributable fractions (PAFs) for dementia in India by estimating associations between risk factors and dementia, their prevalence and communality, within the same nationally representative sample of 4,096 Indians aged 60 and older, surveyed through the Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD).

Results: The risk factor with the largest PAF (>20%) was no education, followed by vision impairment (14%), physical inactivity (12%), and social isolation (8%). According to our estimates, eliminating exposure to risk factors significantly associated with dementia would potentially prevent up to 70% of dementia cases in India.

Discussion: Previous estimates, based on samples limited to specific geographic areas and using risk factors' definitions and relative risks from HICs, may not correctly estimate the real opportunities for preventing dementia in India or identify the most critical areas for intervention.

Introduction: There is growing interest in using electronic health records (EHRs) for chronic disease surveillance. However, these data are convenience samples of in-care individuals, which are not representative of target populations for public health surveillance, generally defined, for the relevant period, as resident populations within city, state, or other jurisdictions. We focus on using EHR data for estimation of diabetes prevalence among young adults in New York City, as rising diabetes burden in younger ages call for better surveillance capacity.

Methods: This article applies common nonprobability sampling methods, including raking, post-stratification, and multilevel regression with post-stratification, to real and simulated data for the cross-sectional estimation of diabetes prevalence among those aged 18-44 years. Within real data analyses, we externally validate city- and neighborhood-level EHR-based estimates to gold-standard estimates from a local health survey. Within data simulations, we probe the extent to which residual biases remain when selection into the EHR sample is non-ignorable.

Results: Within the real data analyses, these methods reduced the impact of selection biases in the citywide prevalence estimate compared to gold standard. Residual biases remained at the neighborhood-level, where prevalence tended to be overestimated, especially in neighborhoods where a higher proportion of residents were captured in the sample. Simulation results demonstrated these methods may be sufficient, except when selection into the EHR is non-ignorable, depending on unmeasured factors or on diabetes status.

Conclusions: While EHRs offer potential to innovate on chronic disease surveillance, care is needed when estimating prevalence for small geographies or when selection is non-ignorable.