Evidence map›Paper›PMID 25894276›Full record

ArticleAnnals of behavioral medicine : a publication of the Society of Behavioral Medicine2015

Predicting Avoidance of Skin Damage Feedback Among College Students.

Laura A Dwyer, James A Shepperd, Michelle L Stock

Open access · bronzeAbstract read
In one paragraph

Article in Annals of behavioral medicine : a publication of the Society of Behavioral Medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
1.2field-weighted citation impact, top 20% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.

  1. Prevalence and predictors of medical information avoidance: a systematic review and meta-analysis.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2025
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  12. Valuation of knowledge and ignorance in mesolimbic reward circuitry.Proceedings of the National Academy of Sciences of the United States of America · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Laura A DwyerThe George Washington University, Washington, DC, USA, laura.dwyer@nih.gov.
James A Shepperd
Michelle L Stock
George Washington University · USUniversity of Florida · US

Funding

NCI NIH HHS Y99 CA999999
6 · The paper itself

Abstract

backgroundShowing people a personal ultraviolet (UV) photograph depicting skin damage can be an effective method for changing sun protection cognitions and behaviors. PURPOSE: We examined whether people opt not to see their UV photograph if given a choice. We also examined predictors of avoidance of skin damage feedback.

methodsCollege students (N = 257) completed questionnaires, viewed example UV photographs, and received the opportunity to see a UV photograph of their face.

resultsOver one-third of participants opted not to see their UV photograph. Greater perceived risk of sun damage and having fewer coping resources corresponded with greater avoidance, particularly among participants who reported infrequent sun protection behavior.

conclusionThe health benefits of UV photography are realized only if people are willing to view the photograph. Our findings suggest the need for interventions that increase receptivity to viewing one's UV photograph.

Indexed as

Avoidance LearningFeedback, PsychologicalHealth Knowledge, Attitudes, PracticeAdaptation, PsychologicalAdolescentAdultFemaleHumansMaleSkin DiseasesStudentsSunscreening AgentsYoung AdultSunscreening Agents

Identifiers

PMID25894276
PMCPMC4561214
OpenAlexW2012957863

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.