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Record W7004776150

An Occupational-based Experimental Study of Collective vs. Personal Efficacy to Encourage Sun Protective Behaviors in Head Start Preschool Teachers

2011· article· en· W7004776150 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scholars Repository - LLU (Loma Linda University) · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsHead startTeamworkIntervention (counseling)Skin cancerPopulationSun protectionRandomized controlled trialBehavior changeSelf-efficacy
DOInot available

Abstract

fetched live from OpenAlex

Background. Skin cancer is one of the most common types of cancers in the United States. An analysis of literature shows that skin cancer can be partially mitigated through personal behavior changes (Glanz, Buller, & Saraiya; 2007, Canadian Centre of Occupational Health and Safety [CCOHS], 2010). Currently national sun-safety educational campaigns promote sun-protective behaviors to individuals who receive exposure due to their work environment (Task Force on Community Preventive Services, 2004). Preschool teachers employed with San Bernardino County Head Start are inadvertently exposed to sunlight during mandatory recess periods posing risks to their health. Purpose. This study evaluated two instructional approaches to skin cancer prevention. The collective efficacy intervention was designed to promote sun-protective behaviors by enhancing teamwork and collaborative work friendships to achieve behavior change. The individual self-efficacy intervention was designed to promote sun protective behaviors by emphasizing personal, rather than collective, responsibility for behavior change. It was theorized that the collective efficacy approach would have a greater impact on knowledge, personal skin cancer attitudes, and lower sun risk-level behaviors than the individual self-efficacy approach. Methods. Teachers from San Bernardino County Head Start were the participants for this educational intervention. Twenty-four preschools were randomized into three groups (n = 8 schools per group); a Collective Efficacy Group (CE), Self-Efficacy Group (SE), or the Delayed Control Group (DC). A prospective multi-center pretest/posttest control group design was used, with data collected at baseline using a self-administered questionnaire. The study group was the independent variable. The dependent variables were population characteristics, participant demographics, sun risk-level (behavior, knowledge, and attitudes. Analysis and Results. Across study groups, the respondents (N = 175) were female (94.9%), married (59%), Hispanic/ Mexican American (53%), Black/African American (20%), and with some college (39%). MANCOVA analysis showed significant improvements for both the collective efficacy and self-efficacy groups in post-test knowledge, attitude, and sun risk-level when compared to the control group (p=.001). Multiple regression analyses assessed whether certain demographics (pretest knowledge, age Hispanic, Black, married, education and Fitzpatric Skin Color affected knowledge, attitude, and sun risk-level. For the three intervention groups the six demographic variables accounted for 36% to 53% of the variance in the regression models for predicting posttest knowledge, attitude, and sun risk-level (behavior). Conclusion. Both intervention types (CE and SE) produced positive results when compared to a delayed intervention control group. Although between-group effects for the two intervention groups were not found, both were superior to the control group indicating that either could be used successfully to teach skin cancer prevention. This study underscores the need for additional studies to determine if between group differences exist and provides initial evidence about using a collective efficacy approach for occupationally-based sun-protective educational interventions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2011
Admission routes1
Has abstractyes

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