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The health belief model and theory of planned behavior applied to mammography screening: A systematic review and meta‐analysis
Author(s) -
Ritchie David,
Van den Broucke Stephan,
Van Hal Guido
Publication year - 2020
Publication title -
public health nursing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.471
H-Index - 55
eISSN - 1525-1446
pISSN - 0737-1209
DOI - 10.1111/phn.12842
Subject(s) - theory of planned behavior , health belief model , theory of reasoned action , meta analysis , psychology , variance (accounting) , explanatory model , explanatory power , medicine , clinical psychology , social psychology , statistics , public health , health education , control (management) , nursing , computer science , mathematics , pathology , philosophy , accounting , epistemology , artificial intelligence , business
Background The Health Belief Model (HBM) and the Theory of Planned Behavior (TPB) are used to explain screening behavior. Although reviews of each model have been conducted independently, none have compared the application of both to mammography screening. Methods A systematic review of literature published in five databases from 1974 to 2020 was performed. Meta‐analysis of the explanatory value of the HBM and TPB and effect sizes of their cognitive variables was conducted. Results Altogether, 673 papers reporting HBM studies and 577 reporting TPB studies were recovered, of which 43 HBM studies and 15 TPB studies met the eligibility criteria. Twelve studies reported on the explanatory value of either model. The explained variance for HBM ranged from 25% to 89% (mean R 2 = .55), while the explained variance for TPB ranged from 16% to 81% (mean R 2 = .24 [screening behavior as outcome] and 0.46 [intention as outcome]). The component of “cue to action” had the greatest effect size (mean OR 1.80 [95% CI: 1.58–2.04]). Conclusions While the HBM and TPB both demonstrated positive explanatory value, most studies examined the individual constructs of each model and failed to report consistently on the effectiveness of the models.