Methodological and ethical issues in research using social media: a metamethod of Human Papillomavirus vaccine studies
Bibliographic record
Abstract
BACKGROUND: Online content is a primary source of healthcare information for internet-using adults and a rich resource for health researchers. This paper explores the methodological and ethical issues of engaging in health research using social media. METHODS: A metamethod was performed on systematically selected studies that used social media as a data source for exploring public awareness and beliefs about Human Papillomaviruses (HPV) and HPV vaccination. Seven electronic databases were searched using a variety of search terms identified for each of three concepts: social media, HPV vaccine, and research method. Abstracts were assessed for eligibility of inclusion; six studies met the eligibility criteria and were subjected to content analysis. A 10-item coding scheme was developed to assess the clarity, congruence and transparency of research design, epistemological and methodological underpinnings and ethical considerations. RESULTS: The designs of the six selected studies were sound, although most studies could have been more transparent about how they built in rigor to ensure the trustworthiness and credibility of findings. Statistical analysis that intended to measure trends and patterns did so without the benefit of randomized sampling and other design elements for ensuring generalizability or reproducibility of findings beyond the specified virtual community. Most researchers did not sufficiently engage virtual users in the research process or consider the risk of privacy incursion. Most studies did not seek ethical approval from an institutional research board or permission from host websites or web service providers. CONCLUSIONS: The metamethod exposed missed opportunities for using the dialogical character of social media as well as a lack of attention to the unique ethical issues inherent in operating in a virtual community where social boundaries and issues of public and private are ambiguous. This suggests the need for more self-conscious and ethical research practices when using social media as a data source. Given the relative newness of virtual communities, researchers and ethics review boards must work together to develop expertise in evaluating the design of studies undertaken with virtual communities. We recommend that the principles of concern for welfare, respect for person, and justice to be applied in research using social media.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | medium |
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 | 0.768 | 0.728 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.027 | 0.018 |
| Science and technology studies | 0.011 | 0.071 |
| Scholarly communication | 0.020 | 0.023 |
| Open science | 0.007 | 0.021 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".