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Record W2766635086 · doi:10.1037/pha0000146

An initial study of behavioral addiction symptom severity and demand for indoor tanning.

2017· article· en· W2766635086 on OpenAlexafffund
Amel Becirevic, Derek D. Reed, Michael Amlung, James G. Murphy, Jerod L. Stapleton, Joel Hillhouse

Bibliographic record

VenueExperimental and Clinical Psychopharmacology · 2017
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsSt. Joseph’s Healthcare Hamilton
FundersPeter Boris Centre for Addictions ResearchUniversity of Kansas
KeywordsPsycINFOAddictionBehavioral addictionSunbathingEnvironmental healthPsychologyAddictive behaviorClinical psychologyMedicineMEDLINEPsychiatryDermatology

Abstract

fetched live from OpenAlex

Indoor tanning remains a popular activity in Western cultures despite a growing body of literature suggesting its link to skin cancer and melanoma. Advances in indoor tanning research have illuminated problematic patterns of its use. With problems such as difficulty quitting, devoting resources toward its use at the expense of healthy activities, and excessive motivation and urges to tan, symptoms of excessive indoor tanning appear consistent with behavioral addiction. The present study bridges the gap between clinical approaches to understanding indoor tanning problems and behavioral economic considerations of unhealthy habits and addiction. Eighty undergraduate females completed both the Behavioral Addiction Indoor Tanning Screener and the Tanning Purchase Task. Results suggest that behavioral economic demand for tanning significantly differs between risk classification groups, providing divergent validity to the Behavioral Addiction Indoor Tanning Screener and offering additional evidence of the sensitivity of the Tanning Purchase Task to differentiating groups according to tanning profiles. (PsycINFO Database Record

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.072
GPT teacher head0.516
Teacher spread0.444 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations58
Published2017
Admission routes2
Has abstractyes

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