Evidence map›Paper›PMID 31746770›Full record

ArticleJournal of medical Internet research2019

A Typology of Patients Based on Decision-Making Styles: Cross-Sectional Survey Study.

Mary Anne FitzPatrick, Alexandra Claudia Hess, Lynn Sudbury-Riley, Peter Johannes Schulz

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

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  6. Patient participation in electronic nursing documentation: An interview study among home-care patients.Health expectations : an international journal of public participation in health care and health policy · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mary Anne FitzPatrick *School of Management and Marketing, Waikato Management School, University of Waikato, Hamilton, New Zealand.ORCID 0000-0001-9591-6334
Alexandra Claudia Hess *School of Communication, Journalism and Marketing, Massey University, Auckland, New Zealand.ORCID 0000-0003-1889-9539
Lynn Sudbury-Riley *Management School, University of Liverpool, Liverpool, United Kingdom.ORCID 0000-0001-5097-3407
Peter Johannes Schulz *Institute of Communication and Health, Faculty of Communication Science, University of Lugano, Lugano, Switzerland.ORCID 0000-0003-4281-489X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough previous research shows broad differences in the impact of online health information on patient-practitioner decision making, specific research is required to identify and conceptualize patient decision-making styles related to the use of online health information and to differentiate segments according to the influence of online information on patient decision making and interactions with health professionals.

objectiveThis study aimed to investigate patients' decision making in relation to online health information and interactions with health care practitioners. We also aimed to present a typology of patients based on significant differences in their decision making.

methodsWe applied a large-scale cross-sectional research design using a survey. Data, generated using a questionnaire that was administered by companies specializing in providing online panels, were collected from random samples of baby boomers in the United Kingdom, the United States, and New Zealand. The total sample comprised 996 baby boomers born between 1946 and 1964, who had used the internet in the previous 6 months to search for and share health-related information. Data were analyzed using hierarchical cluster analysis and confirmatory factor analysis, as well as one-way analysis of variance, chi-square tests, and paired sample t tests.

resultsAnalyses identified 3 key decision-making styles that served as the base for 4 unique and stable segments of patients with distinctive decision-making styles: the Collaborators (229/996, 23.0%), the Autonomous-Collaborators (385/996, 38.7%), the Assertive-Collaborators (111/996, 11.1%), and the Passives (271/996, 27.2%). Profiles were further developed for these segments according to key differences in the online health information behavior, demographics, and interactional behaviors of patients. The typology demonstrates that collaborative decision making is dominant among patients either in its pure form or in combination with autonomous or assertive decision making. In other words, most patients (725/996, 72.8%) show significant collaboration in their decision making with health care professionals. However, at times, patients in the combination Autonomous-Collaborative segment prefer to exercise individual autonomy in their decision making, and those in the combination Assertive-Collaborative segment prefer to be assertive with health professionals. Finally, this study shows that a substantial number of patients adopt a distinctly passive decision-making style (271/996, 27.2%).

conclusionsThe patient typology provides a framework for distinguishing practice-relevant and addressable segments with important implications for health care practitioners, including better-targeted communication programs for patients and more successful outcomes for health care services in the long term.

Indexed as

Cross-Sectional StudiesDecision MakingFemaleHealth BehaviorHumansMaleMiddle AgedSurveys and Questionnairesbaby boomersinternetonline health informationpatient decision makingpatient educationpatient-practitioner interactionpatient segmentspatient typology

Identifiers

PMID31746770
PMCPMC6893560

What OpenQuestion holds

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Registered trials

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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.