ArticleInternational journal of healthcare management2021
Using Conjoint Analysis to Investigate Hospital Directors' Preference in Adoption of an Evidence-based Intervention.
Article in International journal of healthcare management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Identifying Key Intervention Attributes Driving Acceptability of Spouse/Partner-Centered HIV Interventions in Vietnam Using Conjoint Analysis.Patient preference and adherence · 2026Article
- Decision tool of medical endoscope maintenance service in Chinese hospitals: a conjoint analysis.BMC health services research · 2023Article
- Conjoint Analysis: A Research Method to Study Patients' Preferences and Personalize Care.Journal of personalized medicine · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
This study used conjoint analysis, a marketing research technique, to investigate hospital stakeholders' decision-making in adoption of evidence-based interventions (EBI). An efficacious hospital-based stigma-reduction intervention was used as a "product" to study adoption of EBI. Sixty hospital directors in Fujian, China evaluated the likelihood of adopting the EBI in their hospitals by rating across eight hypothetical scenarios with preferred and non-preferred levels of seven attributes, including 1) administrative support, 2) cost, 3) personnel involvement, 4) format, 5) duration, 6) technical support, and 7) priority alignment with the hospital. A hierarchical generalized linear model was fit to the likelihood of intervention adoption for the eight scenarios, with the seven attributes served as independent variables. Monetary cost of intervention implementation (impact score=2.12) had the greatest impact on the directors' reported likelihood of adopting the EBI, followed by duration of the intervention (impact score=0.88), availability of technical support (impact score=0.69), and flexibility of format (impact score=0.36). The impact scores of other attributes were not statistically significant. Conjoint analysis was feasible in modeling hospital directors' decision-making in adoption of EBI. The findings suggested the importance of considering cost, duration, technical support, and flexibility of format in development and dissemination of interventions in healthcare settings.
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Registered trials
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