Second opinions: Do otolaryngologist demographics matter?

OBJECTIVE: Pediatric patients and their caregivers may receive information from their primary care physician (PCP) that does not match current American Academy of Otolaryngology (AAO) guidelines. The purpose of this study is to evaluate the frequency of parents deciding to seek a second opinion based on the demographics of pediatric otolaryngologists who deliver guideline supported advice, contrary to advice from their child's PCP. METHODS: A survey was distributed to parents in a pediatric otolaryngology clinic between June 2021 and July 2023. Demographics included parent age category, gender, race, and age of youngest child. The survey included a scenario depicting recurrent otitis media with clear ears and a suggestion to defer tympanostomy tube insertion per AAO guidelines after their child's PCP recommended tubes. Thirteen variations of otolaryngologist photos were used in the case, including a control case with no picture. RESULTS: Of the 658 participants, 460 (69.9 %) were female. 551 (83.7 %) were aged 30-49 years, 70 (10.7 %) were younger, and 37 (5.6 %) were older. 545 (82.8 %) were White, 30 (4.6 %) were Black, 20 (3.0 %) were Asian, and 31 (4.7 %) were Hispanic. 39.9 % of parents would seek a second opinion if an otolaryngologist recommended watchful waiting following evaluation of their child's otitis media. Participants given the control case were 2.23 times more likely to listen to the otolaryngologist's advice (p = .025). If a picture was provided, respondents were more likely to follow advice given if the pictured otolaryngologist was female (p = .025, OR = 1.47) or Asian (p = .042, OR = 1.53). CONCLUSION: In this group, there is evidence that physician race and gender may influence decision making when considering action versus monitoring in the context of recurrent otitis media.

Establishment-level safety analytics: a scoping review.

The use of data analytics has seen widespread application in fields such as medicine and supply chain management, but their application in occupational safety has only recently become more common. The purpose of this scoping review was to summarize studies that employed analytics within establishments to reveal insights about work-related injuries or fatalities. Over 300 articles were reviewed to survey the objectives, scope and methods used in this emerging field. We conclude that the promise of analytics for providing actionable insights to address occupational safety concerns is still in its infancy. Our review shows that most articles were focused on method development and validation, including studies that tested novel methods or compared the utility of multiple methods. Many of the studies cited various challenges in overcoming barriers caused by inadequate or inefficient technical infrastructures and unsupportive data cultures that threaten the accuracy and quality of insights revealed by the analytics.

Factors Affecting Medical Residents' Decisions to Work After Call.

BACKGROUND: Accreditation Council for Graduate Medical Education (ACGME) work-hour restrictions (WHRs) are intended to improve patient safety by reducing resident fatigue. Compliance with ACGME WHRs is not universal. PURPOSE: The purpose of this study was to identify factors that influence residents' decisions to take a postcall day (PCD) off according to ACGME WHRs. METHODS: Residents (N = 433) at one university were emailed a link to a survey in 2019. The survey included demographic details and a Discrete Choice Experiment examining influences on resident decisions to take a PCD off. RESULTS: One hundred seventy-five residents (40.4%) responded to the survey; 113 residents (26%) completed the survey. Positive feedback from attending physicians about taking PCDs off in the past had the greatest impact on respondents' decisions to take a PCD off, increasing the probability by 27.3%, followed by chief resident comments about the resident looking tired (16.6% increase), and having never heard their attendings comment about PCDs off as either positive or negative (13.9% increase). Factors that had the largest effect on decreasing the probability of taking a PCD were negative feedback about taking PCDs off (14.3% decrease), continuity of care concerns (10.8% decrease), and whether the resident was looking forward to an assignment (7.9% decrease). CONCLUSIONS: The most important influencer of residents' decisions to take a PCD off was related to feedback from their attending physicians, suggesting that compliance with WHRs can be improved by focusing on the residency program's safety culture.

Further Progress Toward Automating Functional Analysis Interpretation.

It is considered best practice to conduct a functional analysis and visually inspect data collected to determine the function of problem behavior, which then informs the intervention approaches applied. Visual inspection has been described as a "subjective" process that may be affected by factors unrelated to the data. Structured decision-making guidelines have been established to address some of these shortcomings. The current paper is a follow-up to earlier work describing positive outcomes related to the viability of a decision support system based on structured criteria from Roane et al. Here, we demonstrate important improvements in a computer script's interpretation of functional analysis data, including improvement in agreement between the updated computer script version and experienced human raters (89%) compared to our original agreement outcomes (81%). This paper further supports the use of decision support systems for functional analysis interpretation.

Establishment-level occupational safety analytics: Challenges and opportunities.

In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the "big" data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.

A hierarchical cluster analysis of young drivers based on their perceived risk and frequency of texting while driving.

INTRODUCTION: The present study attempted to provide a proof-of-concept of usefulness of cluster analysis for identifying distinct and practically meaningful subgroups of drivers who differed in their perceived risk and frequency of texting while driving (TWD). METHOD: Using a hierarchical cluster analysis, which involves sequential steps in which individual cases are merged together one at a time based on their similarities, the study first attempted to identify distinct subgroups of drivers who differed in their perceived risk and frequency of TWD. To further evaluate the meaningfulness of the subgroups identified, the subgroups were compared in terms of levels of trait impulsivity and impulsive decision making for each gender. RESULTS: The study identified the following three distinct subgroups: (a) drivers who perceive TWD as risky but frequently engage in TWD; (b) drivers who perceive TWD as risky and infrequently engage in TWD; and (c) drivers who perceive TWD as not so risky and frequently engage in TWD. The subgroup of male, but not female, drivers who perceive TWD as risky but frequently engage in TWD showed significantly higher levels of trait impulsivity, but not impulsive decision making, than the other two subgroups. DISCUSSION: This is the first demonstration that drivers who frequently engage in TWD can be categorized into two distinct subgroups that differ in terms of the perceived risk of TWD. PRACTICAL APPLICATIONS: For drivers who perceived TWD as risky yet frequently engage in TWD, the present study suggests that different intervention strategies may be needed for each gender.

Social interaction can function as a reinforcer for dogs: Effects of stimulus duration and session parameters.

Prior research has produced mixed results on whether human social interaction can function as a reinforcer for dog behavior. However, that research used either short durations of social interaction or rapid, repeated trials such that satiation could have been a factor. We investigated whether two durations of social interaction (30 s or 4 s petting plus vocal praise) would maintain more responding than extinction, than each other, or than food. We limited each session to 10 trials and temporally spaced sessions within and across days. Both durations of social interaction produced more responding than extinction, but there was no difference in responding between the two social interaction durations. When we compared responding in food sessions to 30-s and 4-s social interaction sessions, we could not determine differences in responses emitted per session for two dogs due to ceiling effects, but the third dog doubled her responding when food was provided. Additionally, latencies in food sessions for all dogs were significantly lower than expected from a random sampling of latencies. Our results suggest both durations of social interaction can function as a reinforcer, especially when delivered sporadically, but they are still not as effective as food as a reinforcer for most dogs.

Monte Carlo Analyses for Single-Case Experimental Designs: An Untapped Resource for Applied Behavioral Researchers and Practitioners.

Group-based experimental designs are an outgrowth of the logic of null-hypothesis significance testing and thus, statistical tests are often considered inappropriate for single-case experimental designs. Behavior analysts have recently been more supportive of efforts to include appropriate statistical analysis techniques to evaluate single-case experimental design data. One way that behavior analysts can incorporate statistical analyses into their practices with single-case experimental designs is to use Monte Carlo analyses. These analyses compare experimentally obtained behavioral data to simulated samples of behavioral data to determine the likelihood that the experimentally obtained results occurred due to chance (i.e., a p value). Monte Carlo analyses are more in line with behavior analytic principles than traditional null-hypothesis significance testing. We present an open-source Monte Carlo tool, created in shiny, for behavior analysts who want to use Monte Carlo analyses in addition as part of their data analysis.

An introduction to "discrete choice experiments" for behavior analysts.

In this paper, we introduce discrete choice experiments (DCEs) and provide foundational knowledge on the topic. DCEs are one of the most popular methods within econometrics to study the distribution of choices within a population. DCEs are particularly useful when studying the effects of categorical variables on choice. Procedurally, a DCE involves recruiting a large sample of individuals exposed to a set of choice arrays. The factors that are suspected to affect choice are varied systematically across the choice arrays. Most commonly, DCE data are analyzed with a multinomial logit statistical model with a goal of determining the relative utility of each relevant factor. We also discuss DCEs in comparison with behavioral choice models, such as those based on the matching law, and we show an example of a DCE to illustrate how a DCE can be used to understand choice with behavioral, social, and organizational factors.

Perceptions of Safety Climate and Fatigue Related to ACGME Residency Duty Hour Restrictions in Otolaryngology Residents.

OBJECTIVE: To compare otolaryngology residents' perceptions of safety climate with respect to duty hour compliance and self-perceived fatigue. STUDY DESIGN: Cross-sectional study. SETTING: Forty-one otolaryngology residencies distributed across the United States. METHODS: A national sample of otolaryngology residents was surveyed electronically in 2019. The survey included demographic details, on-call descriptors, an 18-point Safety Climate Survey (SCS) modified to measure perceptions of program attitudes and practices around resident duty hour compliance, and the 33-point Chalder Fatigue Questionnaire (CFQ). RESULTS: Of 397 surveyed residents, 205 (51.6%) responded. The mean modified SCS score was 11.29 out of 18 (95% CI, 10.76-11.81). Respondents were most likely to disagree with "Residents are told when they are at risk of working beyond ACGME [Accreditation Council for Graduate Medical Education] duty hour restrictions," where 100 (48.8%) disagreed or strongly disagreed. The mean CFQ score was 15.99 of 33 (95% CI, 15.17-16.81). As the modified SCS score improved, CFQ scores decreased, indicating an inverse relationship between duty hour safety climate and fatigue. Having a protected postcall day off and having the program director, chief resident, or senior resident decide that a resident should take a postcall day off were all associated with higher modified SCS scores. CONCLUSION: Otolaryngology residents perceived a safety climate that is suboptimal with regard to duty hour restriction issues. Additionally, an inverse relationship between fatigue and modified SCS scores suggests that fatigue among residents may be lower in programs where residents perceive that ACGME duty hour compliance is more important.

Toward an Automation of Functional Analysis Interpretation: A Proof of Concept.

The advent of functional analysis (FA) methodology paved the way for improved function-based behavioral interventions and ultimately client outcomes. Behavior analysts primarily rely on visual inspection to interpret FA results. However, the literature suggests interpretations may vary across raters resulting in poor interobserver agreement (IOA). To increase interpretation objectivity and address IOA issues, Hagopian et al. created visual-inspection criteria. They reported improved IOA, alongside criteria limitations. Following this, Roane et al. modified these criteria. The current project describes the first steps toward developing a decision support system to assist in FA interpretation. Specifically, we created a computer script, written in R, designed to evaluate FA data and produce an outcome (assign function) based on the Roane et al. criteria. Average agreement between experienced human raters and the computer script outcomes was 81%. We discuss criteria limitations (e.g., vague rules), study implications, and the significance of further research on this topic.

Texting while driving: A discrete choice experiment.

Texting while driving is one of the most dangerous types of distracted driving and contributes to a large number of transportation incidents and fatalities each year. Drivers text while driving despite being aware of the risks. Although some factors related to the decision to text while driving have been elucidated, more remains to be investigated in order to better predict and prevent texting while driving. To study decision making involved in reading a text message while driving, we conducted a discrete choice experiment with 345 adult participants recruited from Amazon's Mechanical Turk. Participants were presented with multiple choice sets, each involving two different scenarios, and asked to choose the scenario in which they would be more likely to text while driving. The attributes of the scenarios were the relationship to the text-message sender, the road conditions, and the importance of the message. The attributes varied systematically across the choice sets. Participants were more likely to read a text message while driving if the sender of the message was a significant other, the message was perceived to be very important, and the participant was driving on rural roads. Discrete choice experiments offer a promising approach to studying decision making in drivers and other populations because they allow for an analysis of multiple factors simultaneously and the trade-offs among different choices.

Two discrete choice experiments on laboratory safety decisions and practices.

INTRODUCTION: The path toward enhancing laboratory safety requires a thorough understanding of the factors that influence the safety-related decision making of laboratory personnel. METHOD: We developed and administered a web-based survey to assess safety-related decision making of laboratory personnel of a government research organization. The survey included two brief discrete choice experiments (DCEs) that allowed for quantitative analysis of specific factors that potentially influence safety-related decisions and practices associated with two different hypothetical laboratory safety scenarios. One scenario related to reporting a laboratory spill, and the other scenario involved changing protective gloves between laboratory rooms. The survey also included several brief self-report measures of attitude, perception, and behavior related to safety practices. RESULTS: Risk perception was the most influential factor in safety-related decision making in both scenarios. Potential negative consequences and effort associated with reporting an incident and the likelihood an incident was detected by others also affected reporting likelihood. Wearing gloves was also affected somewhat by perceived exposure risk, but not by other social or work-related factors included in the scenarios. CONCLUSIONS: The study demonstrated the promise of DCEs in quantifying the relative impact of several factors on safety-related choices of laboratory workers in two hypothetical but realistic scenarios. Participants were faced with hypothetical choice scenarios with realistic features instead of traditional scaling techniques that ask about attitudes and perceptions. The methods are suitable for addressing many occupational safety concerns in which workers face tradeoffs in their safety-related decisions and behavior. Practical Application: Safety-related decisions regarding laboratory practices such as incident reporting and use of PPE were influenced primarily by workers' perceptions of risk of exposure and severity of risks to health and safety. This finding suggests the importance of providing laboratory workers with adequate and effective education and training on the hazards and risks associated with their work. DCEs are a promising research method for better understanding the relative influences of various personal, social, and organizational factors that shape laboratory safety decisions and practices. The information gained from DCEs may lead to more targeted training materials and interventions.

An investigation of resurgence of reinforced behavioral variability in humans.

The present study examined resurgence of reinforced variability in college students, who completed a 3-phase computer-based variability task. In the first phase, baseline, points were delivered for drawing rectangles that sufficiently differed from previous rectangles in terms of a target dimension (size or location, counterbalanced) but were sufficiently similar in terms of the alternative dimension. In the second phase, alternative, points were only delivered for rectangles that were sufficiently different in terms of the alternative dimension, but repetitive in terms of the target dimension. In the third phase, extinction, no points were delivered. In baseline, participants made rectangles that were highly varied in terms of the target dimension and less varied in terms of the alternative dimension, and vice versa in the alternative phase. During extinction, levels of variability increased for the target dimension, providing evidence for resurgence of reinforced variability of a specific dimension of behavior. However, levels of variability also remained high for the alternative dimension, indicating that extinction-induced response variability may also have impacted the results. Although future research is needed to explore other explanations, the results of this study replicate prior research with pigeons and provide some support for the notion of variability as an operant.

Comparison of delay discounting of different outcomes in cigarette smokers, smokeless tobacco users, e-cigarette users, and non-tobacco users.

Delay discounting is the process by which a commodity loses value as the delay to its receipt increases. Rapid discounting predicts various maladaptive behaviors including tobacco use. Typically, delay discounting of different outcomes has been compared between cigarette smokers and nonsmokers. To better understand the relationship of delay discounting to different modes of tobacco use, we examined the differences in delay discounting of different outcomes between cigarette smokers, smokeless tobacco users, e-cigarette users, and non-tobacco users. In the present study, all participants completed 8 titrating delay-discounting tasks: $100 gain, $500 gain, $500 loss, alcohol, entertainment, food, a temporary health gain, and a temporary cure from a disease. Non-tobacco users discounted most outcomes less than tobacco users overall; however, there were no differences in discounting among the different types of tobacco users. These results suggest that nicotine consumption of any kind is associated with a higher degree of impulsivity compared to non-tobacco users. Adoption of tobacco products that have been perceived as less harmful (e.g., e-cigarettes) is not associated with a baseline difference or decrease in delay discounting if adopted after a history of cigarette use.

Delay discounting of different outcomes: Review and theory.

Steep delay discounting is characterized by a preference for small immediate outcomes relative to larger delayed outcomes and is predictive of drug abuse, risky sexual behaviors, and other maladaptive behaviors. Nancy M. Petry was a pioneer in delay discounting research who demonstrated that people discount delayed monetary gains less steeply than they discount substances with abuse liability. Subsequent research found steep discounting for not only drugs, but other nonmonetary outcomes such as food, sex, and health. In this systematic review, we evaluate the hypotheses proposed to explain differences in discounting as a function of the type of outcome and explore the trait- and state-like nature of delay discounting. We found overwhelming evidence for the state-like quality of delay discounting: Consistent with Petry and others' work, nonmonetary outcomes are discounted more steeply than monetary outcomes. We propose two hypotheses that together may account for this effect: Decreasing Future Preference and Decreasing Future Worth. We also found clear evidence that delay discounting has trait-like qualities: People who steeply discount monetary outcomes steeply discount nonmonetary outcomes as well. The implication is that changing delay discounting for one outcome could change discounting for other outcomes.

Effects of Acceptance and Commitment Therapy on Impulsive Decision-Making.

This study examined the transdiagnostic effect of acceptance and commitment therapy (ACT) on impulsive decision-making in a community sample. A total of 40 adults were randomized to eight individual sessions of ACT or an inactive control. Participants completed pre-, mid-, and post-assessments for psychological symptoms; overall behavior change; valued living; delay discounting; psychological flexibility; and distress tolerance. Data were analyzed with multilevel modeling of growth curves. Significant interaction effects of time and condition were observed for psychological flexibility, distress tolerance, psychological symptoms, and the obstruction subscale of valued living. No significant interaction effect was found for two delay discounting tasks nor the progress subscale of valued living. The ACT condition had a significantly larger reduction of problem behavior at post-assessment. The results support use of ACT as a transdiagnostic treatment for impulsive behaviors. The lack of change in delay discounting contrasts previous research.

A cluster analysis of text message users based on their demand for text messaging: A behavioral economic approach.

The goal of this study was to determine whether cluster analysis could be used to identify distinct subgroups of text message users based on behavioral economic indices of demand for text messaging. Cluster analysis is an analytic technique that attempts to categorize cases based on similarities across selected variables. Participants completed a questionnaire about mobile phone usage and a hypothetical texting demand task in which they indicated their likelihood of paying an extra charge to continue to send text messages. A hierarchical cluster analysis was conducted on behavioral economic indices, such as demand intensity, demand elasticity, breakpoint, and the maximum expenditure. With the cluster analysis, we identified 3 subgroups of text message users. The groups were characterized by (a) high intensity and low elasticity, (b) high intensity and medium elasticity, and (c) low intensity and high elasticity. In a demonstration of convergent validity, there were statistically significant and conceptually meaningful differences across the subgroups in various measures of mobile phone use and text messaging. Cluster analysis is a useful tool for identifying and profiling distinct, practically meaningful groups based on behavioral indices and could provide a framework for targeting interventions more efficiently.

Social distance and texting while driving: A behavioral economic analysis of social discounting.

Objective: Texting while driving is a dangerous behavior. Drivers continue to engage in the behavior despite knowing its risks, and the factors responsible for the decision to text while driving are poorly understood. This study examined how the relationship of the sender to the driver, in addition to the delay to the destination, may affect the decision to text while driving with the use of a social- and delay-discounting paradigm. Methods: Ninety-four (N = 94) undergraduate students completed a hypothetical social- and delay-discounting task in which they rated their likelihood of replying to a text message immediately versus waiting to reply until arriving at a destination. The social distance of the sender and the delay to the destination were varied across trials. Results: For both social and delay discounting, the likelihood of replying and waiting, respectively, decreased as a function of social distance and delay to the destination. Participants were more likely to text while driving as the social distance of the sender decreased and the delay to the destination increased. Social discounting varied inversely as a function of delay to the destination: The shorter the delay to the destination, the greater the social discounting. Conclusion: The findings indicate that social distance of the sender is an important factor involved in the decision to text while driving. Participants were more likely to reply to a text while driving if the sender was less socially distant. When they were closer to their destination, they were less likely to reply to socially distant people than those closer to them. The roles that social consequences play in drivers' decision making to text while driving are discussed.

Threat appeals reduce impulsive decision making associated with texting while driving: A behavioral economic approach.

The primary purpose of the present study was to examine the effectiveness of threat appeals in influencing impulsive decision making associated with texting while driving. The participants in the treatment group were exposed to a threatening message about the danger of texting while driving, whereas those in the control group were exposed to a non-threatening message. Following the exposure to either message, the participants completed a delay-discounting task that assessed the degree of impulsive decision making in a hypothetical texting-while-driving scenario. A comparison between the groups revealed that the threat appeals reduced the degree of impulsive decision making associated with texting while driving. In addition, the threat appeals led to greater anticipated regret from texting while driving, less favorable attitudes toward texting while driving, and decreased intentions to text while driving in the future in the treatment group. These results suggest that video-based threat appeals are promising intervention strategies for the public health challenge of texting while driving. Implications from the behavioral economic perspective are discussed.