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Abstract Background Job satisfaction is an important predictor of an individual's intention to leave the workplace. It is increasingly being used to consider the retention of health workers in low-income countries. However, the determinants of job satisfaction vary in different contexts, and it is important to use measurement methods that are contextually appropriate. We identified a measurement tool developed by Paul Spector, and used mixed methods to assess its validity and reliability in measuring job satisfaction among maternal and newborn health workers (MNHWs) in government facilities in rural Nepal. Methods We administered the tool to 137 MNHWs and collected qualitative data from 78 MNHWs, and district and central level stakeholders to explore definitions of job satisfaction and factors that affected it. We calculated a job satisfaction index for all MNHWs using quantitative data and tested for validity, reliability and sensitivity. We conducted qualitative content analysis and compared the job satisfaction indices with qualitative data. Results Results from the internal consistency tests offer encouraging evidence of the validity, reliability and sensitivity of the tool. Overall, the job satisfaction indices reflected the qualitative data. The tool was able to distinguish levels of job satisfaction among MNHWs. However, the work environment and promotion dimensions of the tool did not adequately reflect local conditions. Further, community fit was found to impact job satisfaction but was not captured by the tool. The relatively high incidence of missing responses may suggest that responding to some statements was perceived as risky. Conclusion Our findings indicate that the adapted job satisfaction survey was able to measure job satisfaction in Nepal. However, it did not include key contextual factors affecting job satisfaction of MNHWs, and as such may have been less sensitive than a more inclusive measure. The findings suggest that this tool can be used in similar settings and populations, with the addition of statements reflecting the nature of the work environment and structure of the local health system. Qualitative data on job satisfaction should be collected before using the tool in a new context, to highlight any locally relevant dimensions of job satisfaction not already captured in the standard survey.

BACKGROUND: Despite the centrality of health personnel to the health of the population, the planning, production and management of human resources for health remains underdeveloped in many low- and middle-income countries (LMICs). In addition to the general shortage of health workers, there are significant inequalities in the distribution of health workers within LMICs. This is especially true for countries like Fiji, which face major challenges in distributing its health workforce across many inhabited islands. METHODS: In this study, we describe and measure health worker distributional inequalities in Fiji, using data from the 2007 Population Census, and Ministry of Health records of crude death rates and health workforce personnel. We adopt methods from the economics literature including the Lorenz Curve/Gini Coefficient and Theil Index to measure the extent and drivers of inequality in the distribution of health workers at the sub-national level in Fiji for three categories of health workers: doctors, nurses, and all health workers (doctors, nurses, dentists and health support staff). Population size and crude death rates are used as proxies for health care needs. RESULTS: There are greater inequalities in the densities of health workers at the provincial level, compared to the divisional level in Fiji - six of the 15 provinces fall short of the recommended threshold of 2.3 health workers per 1,000 people. The estimated decile ratios, Gini co-efficient and Thiel index point to inequalities at the provincial level in Fiji, mainly with respect to the distribution of doctors; however these inequalities are relatively small. CONCLUSION: While populations with lower mortality tend to have a slightly greater share of health workers, the overall distribution of health workers on the basis of need is more equitable in Fiji than for many other LMICs. The overall shortage of health workers could be addressed by creating new cadres of health workers; employing increasing numbers of foreign doctors, including specialists; and increasing funding for health worker training, as already demonstrated by the Fiji government. Close monitoring of the equitable distribution of additional health workers in the future is critical.

Background: Despite the centrality of health personnel to the health of the population, the planning, production and management of human resources for health remains underdeveloped in many low- and middle-income countries (LMICs). In addition to the general shortage of health workers, there are significant inequalities in the distribution of health workers within LMICs. This is especially true for countries like Fiji, which face major challenges in distributing its health workforce across many inhabited islands. Methods: In this study, we describe and measure health worker distributional inequalities in Fiji, using data from the 2007 Population Census, and Ministry of Health records of crude death rates and health workforce personnel. We adopt methods from the economics literature including the Lorenz Curve/Gini Coefficient and Theil Index to measure the extent and drivers of inequality in the distribution of health workers at the sub-national level in Fiji for three categories of health workers: doctors, nurses, and all health workers (doctors, nurses, dentists and health support staff). Population size and crude death rates are used as proxies for health care needs. Results: There are greater inequalities in the densities of health workers at the provincial level, compared to the divisional level in Fiji – six of the 15 provinces fall short of the recommended threshold of 2.3 health workers per 1,000 people. The estimated decile ratios, Gini co-efficient and Thiel index point to inequalities at the provincial level in Fiji, mainly with respect to the distribution of doctors; however these inequalities are relatively small. Conclusion: While populations with lower mortality tend to have a slightly greater share of health workers, the overall distribution of health workers on the basis of need is more equitable in Fiji than for many other LMICs. The overall shortage of health workers could be addressed by creating new cadres of health workers; employing increasing numbers of foreign doctors, including specialists; and increasing funding for health worker training, as already demonstrated by the Fiji government. Close monitoring of the equitable distribution of additional health workers in the future is critical.

WHO recommends participatory learning and action cycles with women's groups as a cost-effective strategy to reduce neonatal deaths. Coverage is a determinant of intervention effectiveness, but little is known about why cost-effectiveness estimates vary significantly. This article reanalyses primary cost data from six trials in India, Nepal, Bangladesh and Malawi to describe resource use, explore reasons for differences in costs and cost-effectiveness ratios, and model the cost of scale-up. Primary cost data were collated, and costing methods harmonized. Effectiveness was extracted from a meta-analysis and converted to neonatal life-years saved. Cost-effectiveness ratios were calculated from the provider perspective compared with current practice. Associations between unit costs and cost-effectiveness ratios with coverage, scale and intensity were explored. Scale-up costs and outcomes were modelled using local unit costs and the meta-analysis effect estimate for neonatal mortality. Results were expressed in 2016 international dollars. The average cost was $203 (range: $61-$537) per live birth. Start-up costs were large, and spending on staff was the main cost component. The cost per neonatal life-year saved ranged from $135 to $1627. The intervention was highly cost-effective when using income-based thresholds. Variation in cost-effectiveness across trials was strongly correlated with costs. Removing discounting of costs and life-years substantially reduced all cost-effectiveness ratios. The cost of rolling out the intervention to rural populations ranges from 1.2% to 6.3% of government health expenditure in the four countries. Our analyses demonstrate the challenges faced by economic evaluations of community-based interventions evaluated using a cluster randomized controlled trial design. Our results confirm that women's groups are a cost-effective and potentially affordable strategy for improving birth outcomes among rural populations.