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The health belief model's ability to predict COVID-19 preventive behavior: A systematic review.

ABSTRACT:

Objective

The health belief model specifies that individuals' perceptions about particular behavior can predict the performance of respective behavior. So far, the model has been used to explain why people did not follow COVID-19 preventive behavior. Although we are using it, to our best knowledge, its predictive ability in COVID-19 preventive behavior is unexplored. So, this review aimed to assess the model's predictive ability and identify the most frequently related construct.

Method

A systematic review was conducted to examine the predictive ability of health belief model in COVID-19 preventive behavior using research done all over the world. Preferred reporting items for systematic review and meta-analysis guidelines were used. Comprehensive literature was searched using databases such as PubMed, Google scholar, and African Online Journal to retrieve related articles. Descriptive analyses such as the proportion of studies that better explained COVID-19 prevention behavior and the significance ratio of each construct of the model were made.

Result

Overall, 1552 articles were retrieved using a search strategy and finally 32 articles fulfilling the inclusion criteria undergo the review. We found that in the majority (87.5%) of the studies health belief model has a good predictive ability of COVID-19-related behavior. Overall the explained variance for health belief model ranged from 6.5% to 90.1%. The perceived benefit was the most frequently significant predictor; highest significance ratio (96.7%) followed by self-efficacy, cues to action perceived barrier, susceptibility, and severity in decreasing order.

Conclusion

Health belief model has a good predictive ability of COVID-19-related behavior in the majority of reviewed studies. The perceived benefit was the most frequently significant predictor of COVID-19-related behavior. Professionals who are in need can effectively use health belief model in planning and designing interventions to prevent and control the pandemic.

SUBMITTER: Zewdie A

PROVIDER: S-EPMC9310284 | biostudies-literature |

REPOSITORIES: biostudies-literature

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