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Record W4401955352 · doi:10.1177/00139165241277340

Psychosocial Determinants of Lyme Disease Preventive Behavior Among Outdoor Recreationists

2024· article· en· W4401955352 on OpenAlexaff
Andrés M. Urcuqui-Bustamante, Katherine C. Perry, Jessica Leahy, Allison M. Gardner, Carly C. Sponarski

Bibliographic record

VenueEnvironment and Behavior · 2024
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsCanadian Forest Service
Fundersnot available
KeywordsPsychosocialLyme diseasePsychologyIllness behaviorGerontologyClinical psychologyEnvironmental healthMedicinePsychiatry

Abstract

fetched live from OpenAlex

The incidence of Lyme disease (LD) has grown over time despite extensive awareness campaigns of disease risk. While previous research has explored public knowledge, perceptions, and attitudes toward tick-borne diseases, there is minimal research in understanding preventive behavior among individuals frequently engaging in outdoor recreation. This study addresses this gap by investigating the perceptions of LD preventive behavior, focusing on psychosocial factors influencing behavior. Utilizing an integrative framework incorporating the Health Belief Model and Social Cognitive Theory, we examined outdoor recreationist performance of three key preventive behaviors: tick checks, tick repellent use, and protective clothing. Data were collected through intercept surveys at Bradbury Mountain State Park (Maine, US). Findings indicate that tick-related knowledge and experience have a limited impact on preventive behavior, while efficacy beliefs and perceived benefits significantly influence behavior. In this paper we discuss the implications of these factors to both theory and practice in LD prevention studies.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.303
Teacher spread0.286 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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