Fatigue Risk Management Preferences for Consumer Sleep Technologies and Data Sharing in Aviation.

INTRODUCTION: Employees from any type of aviation services industry were asked to give their opinions about the usefulness of consumer sleep technologies (CSTs) during operations and their willingness to share data from CSTs with their organizations for fatigue risk management purposes under a variety of circumstances.METHODS: Respondents provided information about position in aviation and use of CST devices. Respondents ranked sleep issues and feedback metrics by perceived level of importance to operational performance. Respondents rated their likelihood to share data with their organization under a series of hypothetical situations.RESULTS: Between January-July 2023, 149 (N = 149) aviation professionals responded. Pilots comprised 72% (N = 108) of respondents; 84% (N = 125) of all respondents worked short- or medium-haul operations. "Nighttime operations" and "inconsistent sleep routines" ranked as the most important issues affecting sleep. "Sleep quality history" and "projected alertness levels" ranked as most important feedback metrics for personal management of fatigue. Respondents were split between CST users (N = 64) and nonusers (N = 68). CST users did not indicate a strong preference for a specific device brand. The most-reported reason for not using a CST was due to not owning one or no perceived need. Respondents indicated greater likelihood of data sharing under conditions where the device was provided to them by their organization.DISCUSSION: These results suggest that aviation professionals are more concerned about schedule-related disturbances to sleep than they are about endogenous sleep problems. Organizations may be able to increase compliance to data collection for fatigue risk management by providing employees with company-owned CSTs of any brand.Devine JK, Choynowski J, Hursh SR. Fatigue risk management preferences for consumer sleep technologies and data sharing in aviation. Aerosp Med Hum Perform. 2024; 95(5):265-272.

Using behavioral economics to optimize safer undergraduate late-night transportation.

Many universities sponsor student-oriented transit services that could reduce alcohol-induced risks but only if services adequately anticipate and adapt to student needs. Human choice data offer an optimal foundation for planning and executing late-night transit services. In this simulated choice experiment, respondents opted to either (a) wait an escalating delay for a free university-sponsored "safe" option, (b) pay an escalating fee for an on-demand rideshare service, or (c) pick a free, immediately available "unsafe" option (e.g., ride with an alcohol-impaired driver). Behavioral-economic nonlinear models of averaged-choice data describe preference across arrangements. Best-fit metrics indicate adequate sensitivity to contextual factors (i.e., wait time, preceding late-night activity). At short delays, students preferred the free transit option. As delays extend beyond 30 min, most students preferred competing alternatives. These data depict a policy-relevant delay threshold to better safeguard undergraduate student safety.

Time Cost and Demand: Implications for Public Policy.

The success of policy involves not only good design but a good understanding of how the public will respond behaviorally to the benefits or detriments of that policy. Behavioral science has greatly contributed to how we understand the impact of monetary costs on behavior and has therefore contributed to policy design. Consumption taxes are a direct result of this; for example, cigarette taxes that aim to reduce cigarette consumption. In addition to monetary costs, time may also be conceptualized as a constraint on consumption. Time costs may therefore have policy implications, for example, long waiting times could deter people from accessing certain benefits. Recent data show that behavioral economic demand curve methods used to understand monetary cost may also be used to understand time costs. In this article we discuss how the impact of time cost can be conceptualized as a constraint on demand for public benefits utilization and public health when there are delays to receiving the benefits. Policy examples in which time costs may be relevant and demand curve methods may be useful are discussed in the areas of government benefits, public health, and transportation design.

Latent factor structure of behavioral economic heroin and cocaine demand curves.

Research has shown that behavioral economic demand curve indices can be characterized by a two-factor latent structure and that these factors can predict dimensions of substance use. No study to date has examined the latent factor structure of heroin and cocaine demand curves. The objective of this study was to use exploratory factor analysis to examine the underlying factor structure of the facets of heroin and cocaine reinforcement derived from heroin and cocaine demand curves. Participants were 143 patients from two samples that met the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5; American Psychiatric Association [APA], 2013) criteria for opioid dependance and were undergoing medication-assisted treatment (methadone or buprenorphine). Heroin and cocaine demand curves were generated via hypothetical purchase tasks (HPT) that assessed consumption at 9 or 17 levels of prices from $0 to $500. Five facets of demand were generated from the tasks (Q0, 1/α, Pmax, Omax, and break point). Principal components analysis was used to examine the latent structure among the variables. The results revealed a two-factor solution for both heroin and cocaine demand. These factors were interpreted as persistence, consisting of 1/α, Pmax, Omax, and break point, and amplitude, consisting of Q0 and Omax, and in one case, 1/α. Heroin factors had some predictive power for future substance use, but cocaine factors did not. These findings suggest that heroin and cocaine demand indices can be reduced to two factors indicating sensitivity and volume of consumption, and that these factors may be able to predict substance use for heroin. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Behavioral economic methods predict future COVID-19 vaccination.

Increasing vaccine utilization is critical for numerous diseases, including COVID-19, necessitating novel methods to forecast uptake. Behavioral economic methods have been developed as rapid, scalable means of identifying mechanisms of health behavior engagement. However, most research using these procedures is cross-sectional and evaluates prediction of behaviors with already well-established repertories. Evaluation of the validity of hypothetical tasks that measure behaviors not yet experienced is important for the use of these procedures in behavioral health. We use vaccination during the COVID-19 pandemic to test whether responses regarding a novel, hypothetical behavior (COVID-19 vaccination) are predictive of later real-world response. Participants (N = 333) completed a behavioral economic hypothetical purchase task to evaluate willingness to receive a hypothetical COVID-19 vaccine based on efficacy. This was completed in August 2020, before clinical trial data on COVID-19 vaccines. Participants completed follow-up assessments approximately 1 year later when the COVID-19 vaccines were widely available in June 2021 and November 2021 with vaccination status measured. Prediction of vaccination was made based on data collected in August 2020. Vaccine demand was a significant predictor of vaccination after controlling for other significant predictors including political orientation, delay discounting, history of flu vaccination, and a single-item intent to vaccinate. These findings show predictive validity of a behavioral economic procedure explicitly designed to measure a behavior for which a participant has limited-to-no direct prior experience or exposure. Positive correspondence supports the validity of these hypothetical arrangements for predicting vaccination utilization and advances behavioral economic methods.

A goal of behavioral science is to develop methods that can predict future behavior to inform preventive health efforts and identify ways people engage in positive health behaviors. Behavioral economic methods apply easy to use and rapid assessment tools to evaluate these mechanisms of health behavior engagement. Here, we show how similar methods can be applied to novel behaviors yet experienced like intentions to vaccinate against COVID-19. We find that responses on a behavioral economic task designed to measure vaccination likelihood closely corresponded to the likelihood of being vaccinated 1 year later. This prediction was above and beyond common predictors of vaccination including demographics like political orientation and age. These findings provide support for these novel methods in the context of the COVID-19 pandemic, specifically, and behavioral health, broadly.

Technical, Regulatory, Economic, and Trust Issues Preventing Successful Integration of Sensors into the Mainstream Consumer Wearables Market.

Sensors that track physiological biomarkers of health must be successfully incorporated into a fieldable, wearable device if they are to revolutionize the management of remote patient care and preventative medicine. This perspective article discusses logistical considerations that may impede the process of adapting a body-worn laboratory sensor into a commercial-integrated health monitoring system with a focus on examples from sleep tracking technology.

Applied behavioral economics and public health policies: Historical precedence and translational promise.

Behavioral economics is an approach to understanding behavior though integrating behavioral psychology and microeconomic principles. Advances in behavioral economics have resulted in quick-to-administer tasks to assess discounting (i.e., decrements in the subjective value of a commodity due to delayed or probabilistic receipt) and demand (i.e., effort exerted to defend baseline consumption of a commodity amidst increasing constraints)-these tasks are built upon decades of foundational work from the experimental analysis of behavior and exhibit adequate psychometric properties. We propose that the behavioral economic approach is particularly well suited, then, for experimentally evaluating potential public policy decisions, particularly during urgent times or crises. Using examples from our collaborations (e.g., cannabis legalization, happy hour alcohol pricing, severe weather alerts, COVID-19 vaccine marketing), we demonstrate how behavioral economic approaches have rendered novel insights to guide policy development and garnered widespread attention outside of academia. We conclude with implications on multidisciplinary work and other areas in need of behavioral economic investigations.

Behavioral economic methods to inform infectious disease response: Prevention, testing, and vaccination in the COVID-19 pandemic.

The role of human behavior to thwart transmission of infectious diseases like COVID-19 is evident. Psychological and behavioral science are key areas to understand decision-making processes underlying engagement in preventive health behaviors. Here we adapt well validated methods from behavioral economic discounting and demand frameworks to evaluate variables (e.g., delay, cost, probability) known to impact health behavior engagement. We examine the contribution of these mechanisms within a broader response class of behaviors reflecting adherence to public health recommendations made during the COVID-19 pandemic. Four crowdsourced samples (total N = 1,366) completed individual experiments probing a response class including social (physical) distancing, facemask wearing, COVID-19 testing, and COVID-19 vaccination. We also measure the extent to which choice architecture manipulations (e.g., framing, opt-in/opt-out) may promote (or discourage) behavior engagement. We find that people are more likely to socially distance when specified activities are framed as high risk, that facemask use during social interaction decreases systematically with greater social relationship, that describing delay until testing (rather than delay until results) increases testing likelihood, and that framing vaccine safety in a positive valence improves vaccine acceptance. These findings collectively emphasize the flexibility of methods from diverse areas of behavioral science for informing public health crisis management.

Purchase task sensitivity to drug and nondrug reinforcers in opioid-agonist treatment patients.

The behavioral economics of substance abuse has been increasingly recognized as a method of determining the value of abused substances for individuals who use those substances. It has been hypothesized that such analyses could serve as a clinical tool and that demand functions can be targeted predictors for the level of intervention necessary. This study evaluated the sensitivity of a demand task in 2 patient groups in a medication assisted treatment program (methadone maintenance), those who had used opioids in the last 2 months and those who had not used opioids in at least 18 months. Demand for 7 drugs and a control was assessed using hypothetical purchase tasks. Participants maintaining long-term abstinence had significantly higher α (sensitivity to price) and lower Q0 (intensity of demand) for heroin than participants who had recently used opioids. Further research is necessary to illustrate if treatment is responsible for this reduction in demand. If so, demand analyses may provide clinical utility as an aid for treatment planning or as a target for treatment.

Integrating Operant and Cognitive Behavioral Economics to Inform Infectious Disease Response: Prevention, Testing, and Vaccination in the COVID-19 Pandemic.

The role of human behavior to thwart transmission of infectious diseases like COVID-19 is evident. Yet, many areas of psychological and behavioral science are limited in the ability to mobilize to address exponential spread or provide easily translatable findings for policymakers. Here we describe how integrating methods from operant and cognitive approaches to behavioral economics can provide robust policy relevant data. Adapting well validated methods from behavioral economic discounting and demand frameworks, we evaluate in four crowdsourced samples (total N = 1,366) behavioral mechanisms underlying engagement in preventive health behaviors. We find that people are more likely to social distance when specified activities are framed as high risk, that describing delay until testing (rather than delay until results) increases testing likelihood, and that framing vaccine safety in a positive valence improves vaccine acceptance. These findings collectively emphasize the flexibility of methods from diverse areas of behavioral science for informing public health crisis management.

Behavioral economic demand in opioid treatment: Predictive validity of hypothetical purchase tasks for heroin, cocaine, and benzodiazepines.

BACKGROUND: Behavioral economics provides a framework in which to understand choice and motivation in the field of substance use disorders. Hypothetical purchase tasks (HPT), which indicate the amount or probability of purchasing substances at different prices, have been suggested as a clinical tool that can help predict future substance use and identify targets for intervention. METHODS: Hypothetical demand for heroin, cocaine, and benzodiazepines was assessed at baseline and after six-months in 52 opioid-agonist treatment patients. The results were analyzed using a novel exponential demand equation (normalized zero-bounded exponential model [ZBEn]) that uses a log-like transform that accommodates zero consumption values. RESULTS: Demand for these drugs was well described by the ZBEn model. After six months, demand intensity for heroin was decreased and demand metrics for cocaine and benzodiazepines increased. Multiple demand curve indices at baseline predicted the percentage of drug-positive urinalysis results at follow-up, even after controlling for covariates. Additionally, participants were divided into High and Low baseline demand groups for each drug based on demand indices. Participants with High demand at baseline for 8 out of 9 groups had significantly more drug-positive urine samples in the subsequent 6-month period. CONCLUSIONS: This report provides evidence that demand assessment is predictive of future substance use and could help guide treatment planning at intake. These results also demonstrated that the ZBEn model provides good fits to consumption data and allows for sensitive statistical analyses.

Quantifying the Impact of Public Perceptions on Vaccine Acceptance Using Behavioral Economics.

This study was conducted to evaluate the impact of public perceptions of vaccine safety and efficacy on intent to seek COVID-19 vaccination using hypothetical vaccine acceptance scenarios. The behavioral economic methodology could be used to inform future public health vaccination campaigns designed to influence public perceptions and improve public acceptance of the vaccine. In June 2020, 534 respondents completed online validated behavioral economic procedures adapted to evaluate COVID-19 vaccine demand in relation to a hypothetical development process and efficacy. An exponential demand function was used to describe the proportion of participants accepting the vaccine at each efficacy. Linear mixed effect models evaluated development process and individual characteristic effects on minimum required vaccine efficacy required for vaccine acceptance. The rapid development process scenario increased the rate of decline in acceptance with reductions in efficacy. At 50% efficacy, 68.8% of respondents would seek the standard vaccine, and 58.8% would seek the rapid developed vaccine. Rapid vaccine development increased the minimum required efficacy for vaccine acceptance by over 9 percentage points, γ = 9.36, p < 0.001. Past-3-year flu vaccination, γ = -23.00, p < 0.001, and male respondents, γ = -4.98, p = 0.037, accepted lower efficacy. Respondents reporting greater conspiracy beliefs, γ = 0.39, p < 0.001, and political conservatism, γ = 0.32, p < 0.001, required higher efficacy. Male, γ = -4.43, p = 0.013, and more conservative, γ = -0.09, p = 0.039, respondents showed smaller changes in minimum required efficacy by development process. Information on the vaccine development process, vaccine efficacy, and individual differences impact the proportion of respondents reporting COVID-19 vaccination intentions. Behavioral economics provides an empirical method to estimate vaccine demand to target subpopulations resistant to vaccination.

Predictive and proactive fatigue risk management approaches in commercial aviation.

In commercial aviation, sharing best practices of fatigue risk management (FRM) is important for the industry, its employees, and the community. Chronobiologists and sleep scientists have elucidated the impact of the biological clock and sleep/wake schedules on fatigue and captured their contributions in biomathematical models. The application of these models and other aspects of FRM requires expertise to which not all operators have access. We, therefore, describe some predictive and proactive approaches to FRM, including a collaborative process for evaluating and revising duty schedules to reduce fatigue risk and an innovative wake-up call program to better utilize planned napping opportunities.

An exact solution for unit elasticity in the exponential model of operant demand.

Research applying the behavioral economic demand framework is increasingly conducted across disciplines. With respect to psychopharmacology and substance abuse, real and hypothetical purchase tasks are regularly used to evaluate the demand for various substances and reinforcers, such as alcohol. At present, a variety of methods has been introduced to solve for the point of unit elasticity, or Pmax, in the exponential model of demand; however, these methods vary in their potential for error. Current methods for determining Pmax are presented here and a novel exact solution for Pmax in the exponential model of demand is introduced. This solution provides an exact calculation of Pmax using the omega function, as algebraic solutions are not possible. This novel approach is introduced, discussed, and systematically compared to earlier methods for determining Pmax using computer simulations and reanalyses of published study data. Systematic comparison indicated that this new approach, an exact analytic solution for Pmax, provides results that are identical to computationally intensive Pmax methods that directly evaluate the slope of the demand function. The exact analytic Pmax approach is reviewed, its calculations explained, and an easy-to-use web tool is provided to assist researchers in easily performing this calculation of Pmax. Implications for reducing potential sources of error are reviewed and future directions are also discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Behavioral economic demand metrics for abuse deterrent and abuse potential quantification.

INTRODUCTION: Behavioral economics provides a framework for quantifying drug abuse potential that can inform public health risk, clinical treatment, and research. Hypothetical purchase task (HPT) questionnaires may provide a low-cost and sensitive method by which to measure and predict the appeal of pharmaceutical drugs that differ by formulation. However, the validity of this type of analysis must be empirically established by comparing the "essential value" (EV) of different drugs across subgroups. PROCEDURES: This pilot study used HPT assessments and the Exponential Model of Demand to quantify the EV of opioid medications-specifically, easily tampered formulations versus (vs.) abuse-deterrent formulations-in patients with a history of opioid abuse. MAIN FINDINGS: Participants had more inelastic demand for opioid pills than for cigarettes and alcohol. Participants with experience manipulating pills (M group) had more inelastic demand for standard pills vs. participants with no manipulation experience (NM group), and the M group had a more elastic demand for the abuse-deterrent opioid pill than for the standard pill. There was no effect of formulation in the NM group and there was no difference in demand elasticity for abuse-deterrent pills between the two groups. There was a positive correlation between the EVs of different drugs, and between some behavioral economic indices and treatment variables. CONCLUSIONS: Our results suggest that HPTs may provide a sensitive measure of abuse potential that can distinguish between different formulations in at-risk populations.

The R package beezdemand: Behavioral Economic Easy Demand.

beezdemand: Behavioral Economic Easy Demand, a novel package for performing behavioral economic analyses, is introduced and evaluated. beezdemand extends the statistical program to facilitate many of the analyses performed in studies of behavioral economic demand. The package supports commonly used options for modeling operant demand and performs data screening, fits models of demand, and calculates numerous measures relevant to applied behavioral economists. The free and open source beezdemand package is compared to commercially available software (i.e., GraphPad Prism™) using peer-reviewed and simulated data. The results of this study indicated that beezdemand provides results consistent with commonly used commercial software but provides a wider range of methods and functionality desirable to behavioral economic researchers. A brief overview of the package is presented, its functionality is demonstrated, and considerations for its use are discussed.

Substitutability of nicotine alone and an electronic cigarette liquid using a concurrent choice assay in rats: A behavioral economic analysis.

BACKGROUND: For the Food and Drug Administration to effectively regulate tobacco products, the contribution of non-nicotine tobacco constituents to the abuse liability of tobacco must be well understood. Our previous work compared the abuse liability of electronic cigarette refill liquids (EC liquids) and nicotine (Nic) alone when each was available in isolation and found no difference in abuse liability (i.e., demand elasticity). Another, and potentially more sensitive measure, would be to examine abuse liability in a choice context, which also provides a better model of the tobacco marketplace. METHODS: Demand elasticity for Nic alone and an EC liquid were measured when only one formulation was available (alone-price demand) and when both formulations were concurrently available (own-price demand), allowing an assessment of the degree to which each formulation served as a substitute (cross-price demand) when available at a low fixed-price. RESULTS: Own-price demand for both formulations were more elastic compared to alone-price demand, indicating that availability of a substitute increased demand elasticity. During concurrent access, consumption of the fixed-price formulation increased as the unit-price of the other formulation increased. The rate of increase was similar between formulations, indicating that they served as symmetrical substitutes. CONCLUSION: The cross-price model reliably quantified the substitutability of both nicotine formulations and indicated that the direct CNS effects of non-nicotine constituents in EC liquid did not alter its abuse liability compared to Nic. These data highlight the sensitivity of this model and its potential utility for examining the relative abuse liability and substitutability of tobacco products.

Time constraints in the alcohol purchase task.

Hypothetical purchase tasks have advanced behavioral economic evaluations of demand by circumventing practical and ethical restrictions associated with delivering drug reinforcers to participants. Numerous studies examining the reliability and validity of purchase task methodology suggest that it is a valuable method for assessing demand that warrants continued use and evaluation. Within the literature examining purchase tasks, the alcohol purchase task (APT) has received the most investigation, and currently represents the most experimentally validated variant. However, inconsistencies in purchase task methodology between studies exist, even within APT studies, and, to date, none have assessed the influence of experimental economic constraints on responding. This study examined changes in Q0 (reported consumption when drinks are free), breakpoint (price that suppresses consumption), and α (rate of change in demand elasticity) in the presence of different hypothetical durations of access to alcohol in an APT. One hundred seventy-nine participants (94 males, 85 females) from Amazon Mechanical Turk completed 3 APTs that varied in the duration of time at a party (i.e., access to alcoholic beverages) as described in the APT instructions (i.e., vignette). The 3 durations included 5-hr (used by Murphy et al., 2013), 1-hr, and 9-hr time frames. We found that hypothetical duration of access was significantly related to Q0 and breakpoint at the individual level. Additionally, group-level mean α decreased significantly with increases in duration of access, thus indicating relatively higher demand for alcohol with longer durations of access. We discuss implications for conducting hypothetical purchase task research and alcohol misuse prevention efforts. (PsycINFO Database Record

Toward quantifying the abuse liability of ultraviolet tanning: A behavioral economic approach to tanning addiction.

Many adults engage in ultraviolet indoor tanning despite evidence of its association with skin cancer. The constellation of behaviors associated with ultraviolet indoor tanning is analogous to that in other behavioral addictions. Despite a growing literature on ultraviolet indoor tanning as an addiction, there remains no consensus on how to identify ultraviolet indoor tanning addictive tendencies. The purpose of the present study was to translate a behavioral economic task more commonly used in substance abuse to quantify the "abuse liability" of ultraviolet indoor tanning, establish construct validity, and determine convergent validity with the most commonly used diagnostic tools for ultraviolet indoor tanning addiction (i.e., mCAGE and mDSM-IV-TR). We conducted a between-groups study using a novel hypothetical Tanning Purchase Task to quantify intensity and elasticity of ultraviolet indoor tanning demand and permit statistical comparisons with the mCAGE and mDSM-IV-TR. Results suggest that behavioral economic demand is related to ultraviolet indoor tanning addiction status and adequately discriminates between potential addicted individuals from nonaddicted individuals. Moreover, we provide evidence that the Tanning Purchase Task renders behavioral economic indicators that are relevant to public health research. The present findings are limited to two ultraviolet indoor tanning addiction tools and a relatively small sample of high-risk ultraviolet indoor tanning users; however, these pilot data demonstrate the potential for behavioral economic assessment tools as diagnostic and research aids in ultraviolet indoor tanning addiction studies.

Dopamine D2-Like Receptors and Behavioral Economics of Food Reinforcement.

Previous studies suggest dopamine (DA) D2-like receptor involvement in the reinforcing effects of food. To determine contributions of the three D2-like receptor subtypes, knockout (KO) mice completely lacking DA D2, D3, or D4 receptors (D2R, D3R, or D4R KO mice) and their wild-type (WT) littermates were exposed to a series of fixed-ratio (FR) food-reinforcement schedules in two contexts: an open economy with additional food provided outside the experimental setting and a closed economy with all food earned within the experimental setting. A behavioral economic model was used to quantify reinforcer effectiveness with food pellets obtained as a function of price (FR schedule value) plotted to assess elasticity of demand. Under both economies, as price increased, food pellets obtained decreased more rapidly (ie, food demand was more elastic) in DA D2R KO mice compared with WT littermates. Extinction of responding was studied in two contexts: by eliminating food deliveries and by delivering food independently of responding. A hyperbolic model quantified rates of extinction. Extinction in DA D2R KO mice occurred less rapidly compared with WT mice in both contexts. Elasticity of food demand was higher in DA D4R KO than WT mice in the open, but not closed, economy. Extinction of responding in DA D4R KO mice was not different from that in WT littermates in either context. No differences in elasticity of food demand or extinction rate were obtained in D3R KO mice and WT littermates. These results indicate that the D2R is the primary DA D2-like receptor subtype mediating the reinforcing effectiveness of food.