Appreciating the Persona Paradox: Lessons from Participatory Design Sessions with HIV+ Gay Men
Bibliographic record
Abstract
Eliciting user requirements from HIV-positive gay men who smoke can be challenging. This is because of the complex relationship between social stigma and gender identities (e.g., gay, masculine, HIV+, and smoking status). Inspired to engage HIV-positive gay men in the development of a web-assisted tobacco intervention, we used personas as a main communication tool in our participatory design sessions. Personas are characters created by users that embody part of their own behaviours, thoughts, and motivations. In an apparent paradox, this article is a description of how the use of personas to ensure less realistic self-representation provided an impetus for more self-disclosure. Findings and feedbacks from this study reveal that personas are an effective design tool to engage users in sensitive topics. Implications for future work are also discussed.
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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 | 0.084 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".