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Amazon Mechanical Turk (MTurk) is one of the most popular crowdsourcing platforms for online research. Although the recent MTurk data quality crisis has raised serious concerns regarding its utility, this issue can be mitigated by including quality control methods. To date, only a few studies have compared the effectiveness of the methods in preserving an experimental effect. To provide empirical guidance on which quality control methods to use for MTurk research, this study compared different methods on their effectiveness in preserving the magnitude effect in delay discounting, a robust finding in the behavioral economics literature. Two groups of MTurkers, whose HIT approval rate (%) was between 95 and 98 and 99 and 100, were recruited in October 2021. They completed a delay discounting task evaluating the magnitude effect and questions from different quality control methods. The results showed that the group with higher HIT approval rates (i.e., 99%--100%) showed a greater magnitude effect and were more likely to pass the quality control methods than those with lower rates. In addition, the majority of the quality control methods were able to preserve the magnitude effect at the expense of sample sizes. The best combinations of quality control methods that optimally maintained the effect were explored with a discussion of their implications. Although improving data quality is imperative, caution should be exercised as the quality control methods may potentially bias the sample in an undesirable manner (e.g., excluding individuals who show steep delay discounting). Keywords MTurk * Data quality * Online research * Delay discounting * Magnitude effect, Introduction The use of online crowdsourcing platforms to collect behavioral data has become popular in social science research in recent decades. These platforms provide evident scientific benefits, including efficiency and [...]

Introduction: Cigarette smoking accounts for >30% of the socioeconomic gap in life expectancy. Flavored restrictions claim to promote equity; however, no previous studies have compared the effect of cigarette and e-cigarette flavor restrictions among individuals who smoke with lower and higher socioeconomic status (SES). Aims and Methods: In a between-group within-subject design, individuals with lower (n = 155) and higher (n = 125) SES completed hypothetical purchasing trials in the experimental tobacco marketplace (ETM). Conditions were presented in a 2 × 2 factorial design (cigarette flavors restricted or unrestricted and e-cigarette flavors restricted or unrestricted) with increasing cigarette prices across trials. Results: Results show (1) SES differences in cigarette, e-cigarette, and NRT purchases under unrestricted policies, with lower SES showing higher cigarette demand and lower e-cigarette and NRT substitution than higher SES, (2) cigarette restrictions decreased cigarette and increased NRT purchases among lower SES, but no significant changes among higher SES, (3) decreased SES differences in cigarette demand under cigarette restrictions, but persistence under e-cigarette restrictions or their combination, (4) persistence of SES differences in e-cigarette purchases when all restrictions were enforced, and (5) waning of SES differences in NRT purchasing under all restrictions. Conclusions: Flavor restrictions differentially affected individuals based on SES. Within-group comparisons demonstrated restrictions significantly impacted lower SES, but not higher SES. Between-group comparisons showed SES differences in cigarette purchasing decreased under cigarette restrictions, but persisted under e-cigarette-restrictions or their combination. Additionally, SES differences in NRT substitution decreased under flavor restrictions. These findings highlight the utility of the ETM to investigate SES disparities. Implications: With increasing trends of socioeconomic differences in smoking prevalence and cessation rates, smoking-related health disparities are expected to continue to widen. Restricting menthol flavor in cigarettes while enhancing the availability and affordability of NRT have the potential to alleviate SES disparities in tobacco use, therefore, positively impacting health equity. However, this effect may depend on flavor availability in other tobacco products. [ABSTRACT FROM AUTHOR]

Background: Regulatory flexibility (RF) involves three distinct components of self‐regulation: context sensitivity, repertoire, and feedback responsiveness. Subgroups based on differences in RF have been identified in a general sample and are differentially associated with symptoms of anxiety and depression. However, potential RF profiles have not been examined in individuals with substance use disorders. This study examined RF subtypes in individuals with alcohol use disorder (AUD) and their associations with psychosocial outcomes (i.e., depression, anxiety, and stress) and delay discounting (a core feature of addiction). Methods: Individuals (n = 200) with an Alcohol Use Disorders Identification Test score of >16 (mean = 24.12 (±6.92)) were recruited from Amazon Mechanical Turk (mean = 37.26 years old (±11.41); 94 (47%) women). Participants completed the Context Sensitivity Index, the Flexible Regulation of Emotional Expression Scale, and the Coping Flexibility Scale to assess RF. Participants also completed an Adjusting Amount Delay Discounting Task and the Depression, Anxiety, and Stress Scale (DASS‐21). Latent profile analyses (LPA) were used to identify patterns in RF deficits. Kruskal–Wallis and Dunn's tests were performed to examine differences in discounting rates and symptoms of depression, anxiety, and stress across RF profiles. Results: The LPA revealed a 2‐profile characterization, including (1) context sensitive regulators (CSR; n = 39) and (2) moderate flexibility regulators (MFR; n = 161). CSR demonstrated significantly lower symptoms of depression (p = 0.004), anxiety (p < 0.001), and stress (p < 0.001) than MFR. CSR also displayed significantly lower AUDIT scores (p = 0.031). Conclusions: Findings illustrate that among individuals with moderate–severe AUD, those high in context sensitivity coupled with moderate abilities in repertoire and feedback responsiveness have fewer symptoms of depression, anxiety, and stress. Together, context sensitivity may be an important and protective component of RF among individuals with AUD. [ABSTRACT FROM AUTHOR]

[Please note that in order to respond to reviewers request we had exceed the 300 word limit. The following is NOT revised from the first submission, please see the actual revised manuscript file for the reviewer-driven changes]., Introduction: Recent addiction and obesity-related research suggest that episodic future thinking (EFT) can serve as a promising intervention to promote healthy decision making. This study investigated the neural effects of EFT in alcohol use disorder (AUD)., Methods: Participants received either a brief EFT or control intervention to examine differences in resting-state connectivity. We then used these findings to characterize psychophysiological interaction (PPI) differences during a delay discounting (DD) fMRI task. In addition, we used a second control group of AUD participants without any intervention to reproduce and aid in interpreting our key findings., Results: EFT participants, but not controls, showed statistically improved discounting rates - a behavioral marker for addiction. Resting state analyses of the left hippocampus revealed connectivity differences in the frontal poles. The directionality of this difference suggested that EFT reduced a hypoconnectivity relationship between these regions in AUD. We also found resting state connectivity differences between the salience network and the right dorsolateral prefrontal cortex (R DLPFC), which then led us to discover R-to-L DLPFC PPI differences during DD. Moreover, the resting state salience-to-DLPFC functional connectivity showed an inverse relationship to discounting rate while hyperconnectivity between left and right DLPFC reflected slower reaction times during difficult DD trials., Discussion: These findings suggest that EFT produces beneficial changes in neural connectivity patterns in AUD. The alterations in connectivity highlight potential mechanisms underlying the effectiveness of EFT in improving decision-making in AUD. Understanding these neural effects may contribute to the further development of targeted interventions for AUD and related disorders.