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Record W4413977178 · doi:10.1108/intr-05-2024-0743

Can anthropomorphism bring better persuasiveness? An empirical study on online health risk information

2025· article· en· W4413977178 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternet Research · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyHealth informationInternet privacyRisk communicationEmpirical researchAdvertisingSocial psychologyComputer scienceBusinessPolitical scienceRisk analysis (engineering)EpistemologyHealth care

Abstract

fetched live from OpenAlex

Purpose Anthropomorphism presents a promising strategy for improving information presentation in online health communication. Although showing significant potential, its underlying mechanisms and boundary conditions remain underexplored and warrant further research. This study, therefore, aims to investigate how anthropomorphic cues in online health risk information influence information persuasiveness, specifically examining the underlying mechanisms and boundary conditions. Design/methodology/approach Three experiments (Experiment 1: N = 198; Experiment 2: N = 118; Experiment 3: N = 146) were conducted to examine the impact of anthropomorphism on information persuasiveness, explore pertinent psychological mechanisms and investigate the moderating role of narrative perspective. Findings Anthropomorphic cues were found to enhance the persuasiveness of online health risk information by increasing perceived severity and vulnerability, and by reducing psychological reactance. Furthermore, narrative perspective was shown to moderate the relationships between anthropomorphic cues and both perceived severity and vulnerability. Practical implications Guidance is provided to health information providers on the effective application of anthropomorphic strategies in disseminating online health risk information. In addition, the study highlights the importance of selecting appropriate narrative perspectives that align with the specific characteristics of different diseases in health persuasion. Originality/value This study advances the understanding of anthropomorphic health risk information in online settings by demonstrating its efficacy in mitigating psychological reactance. The findings show that narrative perspectives of injurants versus victims moderate the influence of anthropomorphic health risk information on individuals’ perceived severity and vulnerability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.216
GPT teacher head0.496
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it