Tainted by Stigma: The Interplay of Stigma and Moral Identity in Health Persuasion
Bibliographic record
Abstract
The current research examines the interactive effect of consumers’ moral identity and risk factor stigma on health message effectiveness. The authors theorize that engaging in advocated health behaviors has moral associations; however, a stigmatized risk factor in a message “taints” the morality of the advocated health behavior. Thus, consumers with high (vs. low) moral identity are more likely to comply with health messages when risk factor stigma is low, and this positive moral identity effect is undermined when risk factor stigma is high. The authors test stigma's threat to moral identity by measuring defensive processing (Studies 1 and 2) and the attenuating effect of self-affirmation on the negative effect of stigma (Studies 3 and 4). They apply the stigma-by-association principle to develop and test a messaging intervention (Study 5). The studies suggest that, depending on whether a health message contains stigmatized risk factors, marketers could employ a combination of tactics such as activating moral identity, offering self-affirming message frames, and/or highlighting low-stigma risk factors to bolster message effectiveness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".