Evidence map›Paper›PMID 33979776›Full record

SynthesisJournal of medical Internet research2021

Predictors of Health Information-Seeking Behavior: Systematic Literature Review and Network Analysis.

Ardalan Mirzaei, Parisa Aslani, Edward Joseph Luca, Carl Richard Schneider

Erratum issuedAbstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 36 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Exploring Health Information-Seeking Behavior and Information Source Preferences Among a Diverse Sample of Cancer Survivors: Implications for Patient Education.Journal of cancer education : the official journal of the American Association for Cancer Education · 2024
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ardalan Mirzaei *The University of Sydney School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Australia.ORCID 0000-0002-1398-0648
Parisa Aslani *The University of Sydney School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Australia.ORCID 0000-0002-7976-8236
Edward Joseph LucaThe University of Sydney Library, The University of Sydney, Australia.ORCID 0000-0001-6604-2463
Carl Richard Schneider *The University of Sydney School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Australia.ORCID 0000-0002-2921-5609

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPeople engage in health information-seeking behavior to support health outcomes, and being able to predict such behavior can inform the development of interventions to guide effective health information seeking. Obtaining a comprehensive list of the predictors of health information-seeking behavior through a systematic search of the literature and exploring the interrelationship of these predictors are critical first steps in this process.

objectiveThis study aims to identify significant predictors of health information-seeking behavior in the primary literature, develop a common taxonomy for these predictors, and identify the evolution of the concerned research field.

methodsA systematic search of PsycINFO, Scopus, and PubMed was conducted for all years up to and including December 10, 2019. Quantitative studies identifying significant predictors of health information-seeking behavior were included. Information seeking was broadly defined and not restricted to any source of health information. Data extraction of significant predictors was performed by 2 authors, and network analysis was conducted to observe the relationships between predictors with time.

resultsA total of 9549 articles were retrieved, and after the screening, 344 studies were retained for analysis. A total of 1595 significant predictors were identified. These predictors were categorized into 67 predictor categories, with the most central predictors being age, education, gender, health condition, and financial income. With time, the interrelationship 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.

conclusionsA common taxonomy was developed to classify 67 significant predictors of health information-seeking behavior. A time-aggregated network method was developed to track the evolution of the research field, showing the maturation of new predictor terms and an increase in primary studies reporting multiple significant predictors of health information-seeking behavior. The literature has evolved with a decreased characterization of novel predictors of health information-seeking behavior. In contrast, we identified a parallel increase in the complexity of predicting health information-seeking behavior, with an increase in the literature describing multiple significant predictors.

Indexed as

Health BehaviorInformation Seeking BehaviorBibliometricsHumansSocial Networkinghealthinformation seekingmobile phonenetwork analysisreviewtemporal analysis

Identifiers

PMID33979776
PMCPMC8285748

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.