An Occupational-based Experimental Study of Collective vs. Personal Efficacy to Encourage Sun Protective Behaviors in Head Start Preschool Teachers
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".