Factors affecting recruitment and retention of community health workers in a newborn care intervention in Bangladesh.

BACKGROUND: Well-trained and highly motivated community health workers (CHWs) are critical for delivery of many community-based newborn care interventions. High rates of CHW attrition undermine programme effectiveness and potential for implementation at scale. We investigated reasons for high rates of CHW attrition in Sylhet District in north-eastern Bangladesh. METHODS: Sixty-nine semi-structured questionnaires were administered to CHWs currently working with the project, as well as to those who had left. Process documentation was also carried out to identify project strengths and weaknesses, which included in-depth interviews, focus group discussions, review of project records (i.e. recruitment and resignation), and informal discussion with key project personnel. RESULTS: Motivation for becoming a CHW appeared to stem primarily from the desire for self-development, to improve community health, and for utilization of free time. The most common factors cited for continuing as a CHW were financial incentive, feeling needed by the community, and the value of the CHW position in securing future career advancement. Factors contributing to attrition included heavy workload, night visits, working outside of one's home area, familial opposition and dissatisfaction with pay. CONCLUSIONS: The framework presented illustrates the decision making process women go through when deciding to become, or continue as, a CHW. Factors such as job satisfaction, community valuation of CHW work, and fulfilment of pre-hire expectations all need to be addressed systematically by programs to reduce rates of CHW attrition.

Community-based health workers achieve high coverage in neonatal intervention trials: a case study from Sylhet, Bangladesh.

A large proportion of four million neonatal deaths occur each year during the first 24 hours of life. Research is particularly needed to determine the efficacy of interventions during the first 24 hours. Large cadres of community-based workers are required in newborn-care research both to deliver these interventions in a standardized manner in the home and to measure the outcomes of the study. In a large-scale community-based efficacy trial of chlorhexidine for cleansing the cord in north-eastern rural Bangladesh, a two-tiered system of community-based workers was established to deliver a package of essential maternal and newborn-care interventions and one of three umbilical cord-care regimens. At any given time, the trial employed approximately 133 community health workers--each responsible for 4-5 village health workers and a population of approximately 4,000. Over the entire trial period, 29,760 neonates were enrolled, and 87% of them received the intervention (their assigned cord-care regimen) within 24 hours of birth. Approaches to recruitment, training, and supervision in the study are described. Key lessons included the importance of supportive processes for community-based workers, including a strong training and field supervisory system, community acceptance of the study, consideration of the setting, study objectives, and human resources available.

Community-based validation of assessment of newborn illnesses by trained community health workers in Sylhet district of Bangladesh.

OBJECTIVES: To validate trained community health workers' recognition of signs and symptoms of newborn illnesses and classification of illnesses using a clinical algorithm during routine home visits in rural Bangladesh. METHODS: Between August 2005 and May 2006, 288 newborns were assessed independently by a community health worker and a study physician. Based on a 20-sign algorithm, sick neonates were classified as having very severe disease, possible very severe disease or no disease. The physician's assessment was considered as the gold standard. RESULTS: Community health workers correctly classified very severe disease in newborns with a sensitivity of 91%, specificity of 95% and kappa value of 0.85 (P < 0.001). Community health workers' recognition showed a sensitivity of more than 60% and a specificity of 97-100% for almost all signs and symptoms. CONCLUSION: Community health workers with minimal training can use a diagnostic algorithm to identify severely ill newborns with high validity.