JMIR Publications

ABSTRACT

Background:

People engage in health information seeking behavior (HISB) to support health outcomes. Being able to predict a person’s behavior can inform the development of interventions to guide effective health information seeking. Obtaining a comprehensive list of the predictors of HISB through a systematic search of the literature and exploring the inter-relationship of these predictors are important first steps in this process.

Objective:

This study aimed to; identify significant predictors of health information seeking behavior (HISB) in the primary literature; develop a common taxonomy for predictors of HISB; and identify the evolution of the HISB research field.

Methods:

A systematic search of PsycINFO and Scopus was conducted for all years up to and including 10/12/2019. Quantitative studies identifying significant predictors of HISB were included. Information seeking was defined broadly and not restricted to any one source of health information. Data extraction of the significant predictors was performed by two authors. A network analysis was conducted to observe relationships between predictors over time.

Results:

A total of 6,402 articles were retrieved, and after screening, 300 studies were retained for analysis. A total of 1,413 significant predictors were identified. These predictors were categorized into 67 predictor clusters. The most central predictors were age, education, gender, health condition and financial income. Over time, the inter-relationship of predictors in the network became denser, with the growth of new predictor grouping reaching saturation (1 new predictor identified) in the past 7 years, despite increasing publication rates.

Conclusions:

A common taxonomy was developed, classifying 67 significant predictors of HISB. A novel temporal network was developed to track the evolution of research in HISB field, showing a maturation of new predictor terms and an increase in primary studies reporting multiple significant predictors of HISB. HISB research literature has experienced evolution with decreased characterization of novel predictors of HISB over time. A parallel increase in the complexity of predicting HISB has been identified with an increase in literature describing multiple significant predictors of HISB.