Influence of Enthusiastic Language on the Credibility of Health Information and the Trustworthiness of Science Communicators: Insights From a Between-Subject Web-Based Experiment
Bibliographic record
Abstract
BACKGROUND: To decide whether online health information is reliable, information seekers apply 2 stretegies: first, information seekers can make credibility judgments by using their prior knowledge to evaluate the validity of the encountered health claim. Second, instead of evaluating the health claim itself, information seekers can make trustworthiness judgments by evaluating the character of the information source. In recent years, information givers from various professions have begun to use enthusiastic language to disseminate their information and persuade their audiences. OBJECTIVE: To systematically explore this phenomenon, the goal of this study was to answer the following research questions: (1) does an enthusiastic language style, in comparison with a neutral language style, increase the trustworthiness of a person arguing in an online health forum and the credibility of his or her information? (2) does working for a university, in comparison with working for a lobbying organization, increase the trustworthiness of a person arguing in an online health forum and the credibility of his or her information? (3) does working for a university in combination with using an enthusiastic language style result in especially high trustworthiness and credibility ratings? METHODS: In a 2x2 between-subject online experiment, 270 participants read a post from an online health forum and subsequently rated the trustworthiness of the forum post author and the credibility of his information. A total of 2 aspects of the forum post varied, namely the professional affiliation of the forum post author (whether the person introduced himself as a scientist or a lobbyist) and his language style (whether he used a neutral language style or an enthusiastic language style). RESULTS: When the forum post author used an enthusiastic language style, he was perceived as more manipulative (P<.001), less knowledgeable (P<.001), and his information was perceived as less credible (P<.001). Overall, scientists were perceived as less manipulative (P=.04) than lobbyists. Furthermore, language style and professional affiliation interacted: When the forum post author was a lobbyist, language style did not affect integrity (P=.96) and benevolence (P=.79) ratings. However, when the forum post author was a scientist, enthusiastic language led to lower integrity (P=.002) and benevolence (P<.001) ratings than neutral language. CONCLUSIONS: The current findings illustrate that health information seekers do not just react to online health information itself. In addition, they are also sensitive to the ways in which health information is presented ("Which langue style is used to communicate health information?") and who presents it ("Who does the health information source work for?").
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".