A new integrated conceptual framework of health insurance literacy
Results of a critical interpretive synthesis
Bibliographic Data
| ID | 21467903 |
|---|---|
| Authors | Reut Ron (0000-0001-9493-1356, Ben-Gurion University of the Negev, corresponding author), Paula Feder-Bubis (0000-0002-3724-3810, Ben-Gurion University of the Negev), Kierstin Trocha (Nationwide Children's Hospital), Moriah Ellen (0000-0001-7127-7283, Ben-Gurion University of the Negev) |
| Year | 2025 |
| Volume | 161 |
| Pages | 105394 |
| Publication date | 2025-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Health Policy (JOURNAL) |
| Journal identifiers | ISSN: 0168-8510 • E-ISSN: 1872-6054 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.healthpol.2025.105394 |
| PMID | 40669127 |
| OpenAlex | W4412455320 |
| Language | EN |
| References cited | 36 |
Health insurance literacy (HIL) is the knowledge, ability, and confidence to find and understand health insurance information, and choose, purchase and use an insurance plan. Despite the increasing volume of research on HIL, the approaches to this field remain fragmented. This review paper aims to develop a conceptual framework delineating the attributes, personal contexts, and environmental influences, which either influence or are influenced by an individual's HIL level. We have adopted a critical interpretive synthesis approach with purposive sampling and inductive analysis, integrating all existing models from the literature, with additional findings. The CIS methodology emphasizes iterative data synthesis to generate theory from diverse sources, ceasing data extraction upon achieving theoretical saturation. This reflects the stage at which further data collection no longer yields new conceptual insights. Four databases were systematically screened in September 2020 and July 2023, yielding 6096 articles. Following a review of titles and abstracts, 388 papers were deemed relevant, and 76 were included in the final synthesis. The resulting framework consists of eight categories, 17 subcategories, and 129 codes, with HIL level as its core. Other components include individual predictors, external influences, skills and abilities, perceptions and beliefs, preferences, decision-making processes, and outcomes. This framework provides a comprehensive tool for guiding interventions and research aimed at improving HIL. It allows researchers and policymakers to address the diverse and interconnected factors influencing HIL and to develop targeted, evidence-based strategies
Business · Conceptual framework · Data collection · Data extraction · Environmental health · Health care · Health literacy · Knowledge management · Management science · MEDLINE · Nonprobability sampling · Political science · Process management · Psychological intervention · Social science · Sociology · Applied Psychology · Chronic Disease Management Strategies · Computer Science · Engineering · Healthcare Policy and Management · Medicine · Primary Care and Health Outcomes · Psychology
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| Highly cited | No |
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