ArticleJournal of cancer education : the official journal of the American Association for Cancer Education2016
Sun Protection Belief Clusters: Analysis of Amazon Mechanical Turk Data.
Article in Journal of cancer education : the official journal of the American Association for Cancer Education, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Mapping of Crowdsourcing in Health: Systematic Review.Journal of medical Internet research · 2018Pooled it
- The application of crowdsourcing approaches to cancer research: a systematic review.Cancer medicine · 2017Pooled it
- Self-Care and Illness Perception in Inflammatory Bowel Disease: Identifying Adaptive and Maladaptive Profiles Through Person-Centered Analysis.The Psychiatric quarterly · 2026Article
- Home Cooking Quality Assessment Tool Validation Using Community Science and Crowdsourcing Approaches.Journal of nutrition education and behavior · 2022Article
- Comparing Amazon's Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature.Journal of general internal medicine · 2018Review
- Crowdsourced Health Data: Comparability to a US National Survey, 2013-2015.American journal of public health · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This study aimed (i) to determine whether people could be differentiated on the basis of their sun protection belief profiles and individual characteristics and (ii) explore the use of a crowdsourcing web service for the assessment of sun protection beliefs. A sample of 500 adults completed an online survey of sun protection belief items using Amazon Mechanical Turk. A two-phased cluster analysis (i.e., hierarchical and non-hierarchical K-means) was utilized to determine clusters of sun protection barriers and facilitators. Results yielded three distinct clusters of sun protection barriers and three distinct clusters of sun protection facilitators. Significant associations between gender, age, sun sensitivity, and cluster membership were identified. Results also showed an association between barrier and facilitator cluster membership. The results of this study provided a potential alternative approach to developing future sun protection promotion initiatives in the population. Findings add to our knowledge regarding individuals who support, oppose, or are ambivalent toward sun protection and inform intervention research by identifying distinct subtypes that may best benefit from (or have a higher need for) skin cancer prevention efforts.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.