Associations of Menstrual Cycle and Progesterone-to-Estradiol Ratio With Alcohol Consumption in Alcohol Use Disorder: A Sex-Separated Multicenter Longitudinal Study.

OBJECTIVE: Alcohol use disorder (AUD) constitutes a critical public health issue and has sex-specific characteristics. Initial evidence suggests that progesterone and estradiol might reduce or increase alcohol intake, respectively. However, there is a need for a better understanding of how the menstrual cycle in females and the ratio of progesterone to estradiol in females and males influence alcohol use patterns in individuals with AUD. METHODS: In this sex-separated multicenter longitudinal study, the authors analyzed 12-month data on real-life alcohol use (from 21,460 smartphone entries), menstrual cycle, and serum progesterone-to-estradiol ratios (from 667 blood samples at four individual study visits) in 74 naturally cycling females and 278 males with AUD between 2020 and 2022, using generalized and general linear mixed modeling. RESULTS: Menstrual cycle phases were significantly associated with binge drinking and progesterone-to-estradiol ratio. During the late luteal phase, females showed a lower predicted binge drinking probability of 13% and a higher predicted marginal mean of progesterone-to-estradiol ratio of 95 compared with during the menstrual, follicular, and ovulatory phases (binge drinking probability and odds ratios vs. late luteal phase, respectively: 17%, odds ratio=1.340, 95% CI=1.031, 1.742; 19%, odds ratio=1.523, 95% CI=1.190, 1.949; and 20%, odds ratio=1.683, 95% CI=1.285, 2.206; difference in progesterone-to-estradiol ratios, respectively: -61, 95% CI=-105.492, -16.095; -78, 95% CI=-119.322, -37.039; and -71, 95% CI=-114.568, -27.534). In males, a higher progesterone-to-estradiol ratio was related to lower probabilities of binge drinking and of any alcohol use, with a 10-unit increase in the hormone ratio resulting in odds ratios of 0.918 (95% CI=0.843, 0.999) and 0.914 (95% CI=0.845, 0.988), respectively. CONCLUSIONS: These ecologically valid findings suggest that high progesterone-to-estradiol ratios can have a protective effect against problematic alcohol use in females and males with AUD, highlighting the progesterone-to-estradiol ratio as a promising treatment target. Moreover, the results indicate that females with AUD may benefit from menstrual cycle phase-tailored treatments.

Food approach dynamics in daily life: Speed and force of food approach movements fluctuate with hunger, but less so for people with high BMI.

Researchers have suggested that the overconsumption of food, alcohol, and drugs could be explained by chronically elevated approach tendencies to rewarding but unhealthy stimuli. Here, we use the example of food to show that dysregulated rather than chronically elevated approach tendencies are associated with adverse health outcomes. To this end, we developed a new smartphone-based paradigm to measure dynamic changes in food approach tendencies outside the laboratory (piloted with n = 48). We demonstrated in three preregistered experiments (total N = 367) that food approach tendencies decrease from before to after people have eaten. We further show that in overweight and obese participants, these dynamics are disrupted as their food approach tendencies increase rather than decrease after meals. In addition to showing these effects based on traditional reaction time-based food approach tendencies, we also demonstrate these patterns in a novel measure of response force-a measure that has long been used to study motivation in animals but has received little attention in humans. Together, our findings suggest that both reaction time-based and force-based approach tendencies change dynamically in accordance with people's need states and that disruptions in these dynamics are associated with adverse health outcomes, such as overweight and obesity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Test-retest reliability of a smartphone-based approach-avoidance task: Effects of retest period, stimulus type, and demographics.

The approach-avoidance task (AAT) is an implicit task that measures people's behavioral tendencies to approach or avoid stimuli in the environment. In recent years, it has been used successfully to help explain a variety of health problems (e.g., addictions and phobias). Unfortunately, more recent AAT studies have failed to replicate earlier promising findings. One explanation for these replication failures could be that the AAT does not reliably measure approach-avoidance tendencies. Here, we first review existing literature on the reliability of various versions of the AAT. Next, we examine the AAT's reliability in a large and diverse sample (N = 1077; 248 of whom completed all sessions). Using a smartphone-based, mobile AAT, we measured participants' approach-avoidance tendencies eight times over a period of seven months (one measurement per month) in two distinct stimulus sets (happy/sad expressions and disgusting/neutral stimuli). The mobile AAT's split-half reliability was adequate for face stimuli (r = .85), but low for disgust stimuli (r = .72). Its test-retest reliability based on a single measurement was poor for either stimulus set (all ICC1s < .3). Its test-retest reliability based on the average of all eight measurements was moderately good for face stimuli (ICCk = .73), but low for disgust stimuli (ICCk = .5). Results suggest that single-measurement AATs could be influenced by unexplained temporal fluctuations of approach-avoidance tendencies. These fluctuations could be examined in future studies. Until then, this work suggests that future research using the AAT should rely on multiple rather than single measurements.

Development of Novel Tasks to Assess Outcome-Specific and General Pavlovian-to-Instrumental Transfer in Humans.

INTRODUCTION: The emergence of Pavlovian-to-instrumental transfer (PIT) research in the human neurobehavioral domain has been met with increased interest over the past two decades. A variety of PIT tasks were developed during this time; while successful in demonstrating transfer phenomena, existing tasks have limitations that should be addressed. Herein, we introduce two PIT paradigms designed to assess outcome-specific and general PIT within the context of addiction. MATERIALS AND METHODS: The single-lever PIT task, based on an established paradigm, replaced button presses with joystick motion to better assess avoidance behavior. The full transfer task uses alcohol and nonalcohol rewards associated with Pavlovian cues and instrumental responses, along with other gustatory and monetary rewards. We constructed mixed-effects models with the addition of other statistical analyses as needed to interpret various behavioral measures. RESULTS: Single-lever PIT: both versions were successful in eliciting a PIT effect (joystick: p < 0.001, ηp2 = 0.36, button-box: p < 0.001, ηp2 = 0.30). Full transfer task: it was determined that the alcohol and nonalcoholic reward cues selectively primed their respective reward-associated responses (gustatory version: p < 0.001, r = 0.59, and monetary version: p < 0.001, r = 0.84). The appetitive/aversive cues resulted in a general transfer effect (gustatory: p < 0.001, ηp2 = 0.09, and monetary: p < 0.001, ηp2 = 0.17). DISCUSSION/CONCLUSION: Single-lever PIT: PIT was observed in both task versions. We posit that the use of a joystick is more advantageous for the analysis of avoidance behavior. It evenly distributes movement between approach and avoid trials, which is relevant to analyzing fMRI data. Full transfer task: While gustatory conditioning has been used in the past to elicit transfer effects, we present the first paradigm that successfully elicits both specific and general transfers in humans with gustatory alcohol rewards.

Automatic Approach Behaviors in Alcohol Dependence: Does a Cognitive Bias Modification Training Affect Pavlovian-to-Instrumental Transfer Effects?

INTRODUCTION: Positively conditioned Pavlovian cues tend to promote approach and negative cues promote withdrawal in a Pavlovian-to-instrumental transfer (PIT) paradigm, and the strength of this PIT effect was associated with the subsequent relapse risk in alcohol-dependent (AD) patients. When investigating the effect of alcohol-related background cues, instrumental approach behavior was inhibited in subsequent abstainers but not relapsers. An automatic approach bias towards alcohol can be modified using a cognitive bias modification (CBM) intervention, which has previously been shown to reduce the relapse risk in AD patients. Here we examined the effects of such CBM training on PIT effects and explored its effect on the relapse risk in detoxified AD patients. METHODS: N = 81 recently detoxified AD patients performed non-drug-related and drug-related PIT tasks before and after CBM versus placebo training. In addition, an alcohol approach/avoidance task (aAAT) was performed before and after the training to assess the alcohol approach bias. Patients were followed up for 6 months. RESULTS: A stronger alcohol approach bias as well as a stronger non-drug-related PIT effect predicted relapse status in AD patients. No significant difference regarding relapse status or the number of heavy drinking days was found when comparing the CBM training group versus the placebo group. Moreover, there was no significant modulation effect of CBM training on any PIT effect or the aAAT. CONCLUSION: A higher alcohol approach bias in the aAAT and a stronger non-drug-related PIT effect both predicted relapse in AD patients, while treatment outcome was not associated with the drug-related PIT effect. Unlike expected, CBM training did not significantly interact with the non-drug-related or the drug-related PIT effects or the alcohol approach bias.

Mobile Data Collection of Cognitive-Behavioral Tasks in Substance Use Disorders: Where Are We Now?

INTRODUCTION: Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. METHOD: In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. RESULTS: Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that - although more systematic studies are necessary - task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. CONCLUSION: Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.

Measuring Implicit Approach-Avoidance Tendencies towards Food Using a Mobile Phone outside the Lab.

Implicit ('unconscious') approach-avoidance tendencies towards stimuli can be measured using the Approach Avoidance Task (AAT). We recently expanded a toolbox for analyzing the raw data of a novel, mobile version of the AAT (mAAT), that asks participants to move their phone towards their face (pull) or away (push) in response to images presented on the phone. We here tested the mAAT reaction time and the mAAT distance in a study with 71 Dutch participants that were recruited online and performed an experiment without coming to the laboratory. The participants used both the mAAT and (explicit) rating scales to respond to photographic images of food. As hypothesized, the rated wanting, rated valence and mAAT reaction time indicated a preference for palatable over unpalatable food, and for Dutch over Asian food. Additionally, as expected, arousal was rated higher for unpalatable than for palatable food, and higher for Dutch than for Asian food. The mAAT distance indicated that the unpalatable food images were moved across larger distances, regardless of the movement direction (pull or push), compared to the palatable food images; and the Dutch food images were moved across larger distances than the Asian food images. We conclude that the mAAT can be used to implicitly probe approach-avoidance motivation for complex images in the food domain. The new measure of mAAT distance may be used as an implicit measure of arousal. The ratings and the mAAT measures do not reflect the exact same information and may complement each other. Implicit measures, such as mAAT variables, are particularly valuable when response biases that can occur when using explicit ratings are expected.

A mobile approach-avoidance task.

Approach and avoidance tendencies have helped explain phenomena as diverse as addiction (Mogg, Field, & Bradley, 2005), phobia (Rinck & Becker, 2007), and intergroup discrimination (Bianchi, Carnaghi, & Shamloo, 2018; Degner, Essien, & Reichardt, 2016). When the original approach-avoidance task (AAT; Solarz, 1960) that measures these tendencies was redesigned to run on regular desktop computers, it made the task much more flexible but also sacrificed some important behavioral properties of the original task-most notably its reliance on physical distance change (Chen & Bargh, 1999). Here, we present a new, mobile version of the AAT that runs entirely on smartphones and combines the flexibility of modern tasks with the behavioral properties of the original AAT. In addition, it can easily be deployed in the field and, next to traditional reaction time measurements, includes the novel measurement of response force. In two studies, we demonstrate that the mobile AAT can reliably measure known approach-avoidance tendencies toward happy and angry faces both in the laboratory and in the field.