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We sought to assess the feasibility of mainstreaming balanced energy protein supplementation, a maternal nutrition intervention, into Bangladesh's routine antenatal care system in tandem with an ongoing effectiveness trial in northwestern Bangladesh. Feasibility is an implementation science outcome defined as the extent to which a new intervention can be implemented successfully in a given context. We found feasibility difficult to measure using existing Anglophone quantitative tools translated into Bangla and identified particular challenges with using Likert scales. We also found it challenging to measure feasibility early in implementation, as recommended in the implementation science literature, due to potential respondents' unfamiliarity with the intervention and what implementation would look like. To address these issues, we explored alternative assessment methods, such as focus groups and workshops. These formats presented additional difficulties, including identifying the correct participants and moderating participant power dynamics. In conclusion, we question whether existing feasibility assessment tools, developed in English, are suitable for use in non-Anglophone contexts as well as whether Likert scales are appropriate for use in low-income and middle-income countries more broadly. We also question current recommendations on the timing of feasibility assessments. We feel that-particularly with new, difficult-to-conceptualise interventions-feasibility must be assessed later in implementation or only after providing detailed explanations of the intervention to respondents.
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http://dx.doi.org/10.1136/bmjgh-2024-017331 | DOI Listing |
BMC Glob Public Health
September 2025
Connell School of Nursing, Boston College, Chestnut Hill, MA, USA.
Background: Sierra Leone has the world's third highest incidence of maternal mortality, with 443 deaths per 100,000 live births. Strengthening the country's midwifery workforce is essential to providing adequate maternal healthcare and reducing preventable perinatal mortality. In support of this goal, we developed and implemented a midwifery preceptor program (MPP) to train experienced midwives to effectively mentor new and student midwives.
View Article and Find Full Text PDFAntimicrob Resist Infect Control
September 2025
School of Medicine and Health Management, Guizhou Province, Guizhou Medical University, GUI'an New District, 6 Ankang Avenue, Guiyang, People's Republic of China.
Background: Although current evidence supports the effectiveness of social norm feedback (SNF) interventions, their sustained integration into primary care remains limited. Drawing on the elements of the antimicrobial SNF intervention strategy identified through the Delphi-based evidence applicability evaluation, this study aims to explore the barriers and facilitators to its implementation in primary care institutions, thereby informing future optimization.
Methods: Based on the five domains of the Consolidated Framework for Implementation Research (CFIR), we developed semi-structured interview and focus group discussion guides.
J Hum Genet
September 2025
Division of Integrative Genomics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Comprehensive genomic profiling (CGP) expands treatment options for solid tumor patients and identifies hereditary cancers. However, in Japan, confirmatory tests have been conducted in only 31.6% of patients with presumed germline pathogenic variants (GPVs) detected through tumor-only testing.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
Global Health Economics Centre, Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Background: Artificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagnostic performance and its application when deployed in real-world conditions.
Objective: This study aimed to assess the technical feasibility of integration and diagnostic performance of validated DR screening (DRS) AI algorithms in real-world outpatient public health settings.