Human factor associations with safety events in radiation therapy.

BACKGROUND AND PURPOSE: Incident learning can reveal important opportunities for safety improvement, yet learning from error is challenged by a number of human factors. In this study, incident learning reports have been analyzed with the human factors analysis classification system (HFACS) to uncover predictive patterns of human contributing factors. MATERIALS AND METHODS: Sixteen hundred reports from the Safety in Radiation Oncology incident learning system were filtered for inclusion ultimately yielding 141 reports. A radiotherapy-specific error type was assigned to each event as were all reported human contributing factors. An analysis of associations between human contributing factors and error types was performed. RESULTS: Multiple associations between human factors were found. Relationships between leadership and risk were demonstrated with supervision failures. Skill-based errors (those done without much thought while performing familiar tasks) were found to pose a significant safety risk to the treatment planning process. Errors made during quality assurance (QA) activities were associated with decision-based errors which indicate lacking knowledge or skills. CONCLUSION: An application of the HFACS to incident learning reports revealed relationships between human contributing factors and radiotherapy errors. Safety improvement efforts should include supervisory influences as they affect risk and error. An association between skill-based and treatment planning errors showed a need for more mindfulness in this increasingly automated process. An association between decision and QA errors revealed a need for improved education in this area. These and other findings can be used to strategically advance safety.

Relationship between alpha-1 antitrypsin deficiency and obstructive sleep apnea.

PURPOSE: This study aimed to identify if individuals with mild to severe alpha-1 antitrypsin deficiency (AATD) are at higher risk for developing obstructive sleep apnea (OSA) than the general population. METHODS: A seven-question sleep apnea risk assessment questionnaire, STOP-BAG, was applied to 2338 participant responses from the Alpha-1 Coded Testing Study (ACT) and 4638 participant responses from the Kentucky Behavioral Risk Factor Survey (KyBRFS). Propensity scores were generated from a logistic regression model using continuous variables of age and body mass index (BMI). STOP-BAG scores were analyzed using chi-square analysis on this matched cohort to assess OSA risk in AATD. RESULTS: Self-reported OSA was higher in the KyBRFS cohort (14.5%) than in individuals with mild or severe AATD (11.2%) (p = 0.012). However, a higher percentage of the AATD cohort met clinically meaningful thresholds for STOP-BAG scores ≥ 5 (22.7%) than the KyBRFS cohort (13.0%) (p = 0.001). These differences persisted despite 1:1 propensity score matching on age and BMI to account for differences in baseline characteristics. No statistically significant difference in OSA risk between AATD genotypes was found. CONCLUSION: AATD appears to have higher risk for OSA than the general population. The 11.2% prevalence of diagnosed OSA in the AATD population is much lower than symptom scores would predict. Further studies are needed to validate the possibility that elastin loss is involved in OSA pathogenesis.

Time and resource limits on working memory: cross-age consistency in counting span performance.

This longitudinal study separated resource demand effects from those of retention interval in a counting span task among 100 children tested in grade 2 and again in grades 3 and 4. A last card large counting span condition had an equivalent memory load to a last card small, but the last card large required holding the count over a longer retention interval. In all three waves of assessment, the last card large condition was found to be less accurate than the last card small. A model predicting reading comprehension showed that age was a significant predictor when entered first accounting for 26% of the variance, but counting span accounted for a further 22% of the variance. Span at Wave 1 accounted for significant unique variance at Wave 2 and at Wave 3. Results were similar for math calculation with age accounting for 31% of the variance and counting span accounting for a further 34% of the variance. Span at Wave 1 explained unique variance in math at Wave 2 and at Wave 3.

Teaching psychology as a laboratory science in the age of the Internet.

For over 30 years, psychologists have relied on computers to teach experimental psychology. With the advent of experiment generators, students can create well-designed experiments and can test sophisticated hypotheses from the start of their undergraduate training. Characteristics of new Net-based experiment generators are discussed and compared with traditional stand-alone generators. A call is made to formally evaluate the instructional effectiveness of the wide range of experiment generators now available. Specifically, software should be evaluated in terms of known learning outcomes, using appropriate control groups. The many inherent differences between any two software programs should be made clear. The teacher's instructional method should be fully described and held constant between comparisons. Finally, the often complex interaction between the teacher's instructional method and the pedagogical details of the software must be considered.