A mobile approach-avoidance task

Virtual reality assessment of a high-calorie food bias: Replication and food-specificity in healthy participants

BACKGROUND

Theoretical models and behavioural studies indicate faster approach behaviour for high-calorie food (approach bias) among healthy participants. A previous study with Virtual Reality (VR) and online motion-capture quantified this approach bias towards food and non-food cues in a controlled VR environment with hand movements. The aim of this study was to test the specificity of a manual approach bias for high-calorie food in grasp movements compared to low-calorie food and neutral objects of different complexity, namely, simple balls and geometrically more complex office tools.

METHODS

In a VR setting, healthy participants (N = 27) repeatedly grasped or pushed high-calorie food, low-calorie food, balls and office tools in randomized order with 30 item repetitions. All objects were rated for valence and arousal.

RESULTS

High-calorie food was less attractive and more arousing in subjective ratings than low-calorie food and neutral objects. Movement onset was faster for high-calorie food in push-trials, but overall push responses were comparable. In contrast, responses to high-calorie food relative to low-calorie food and to control objects were faster in grasp trials for later stages of interaction (grasp and collect). Non-parametric tests confirmed an approach bias for high-calorie food.

CONCLUSION

A behavioural bias for food was specific to high-calorie food objects. The results confirm the presence of bottom-up advantages in motor-cognitive behaviour for high-calorie food in a non-clinical population. More systematic variations of object fidelity and in clinical populations are outstanding. The utility of VR in assessing approach behaviour is confirmed in this study by exploring manual interactions in a controlled environment.

How pre-processing decisions affect the reliability and validity of the approach-avoidance task: Evidence from simulations and multiverse analyses with six datasets

Reaction time (RT) data are often pre-processed before analysis by rejecting outliers and errors and aggregating the data. In stimulus-response compatibility paradigms such as the approach-avoidance task (AAT), researchers often decide how to pre-process the data without an empirical basis, leading to the use of methods that may harm data quality. To provide this empirical basis, we investigated how different pre-processing methods affect the reliability and validity of the AAT. Our literature review revealed 108 unique pre-processing pipelines among 163 examined studies. Using empirical datasets, we found that validity and reliability were negatively affected by retaining error trials, by replacing error RTs with the mean RT plus a penalty, and by retaining outliers. In the relevant-feature AAT, bias scores were more reliable and valid if computed with D-scores; medians were less reliable and more unpredictable, while means were also less valid. Simulations revealed bias scores were likely to be less accurate if computed by contrasting a single aggregate of all compatible conditions with that of all incompatible conditions, rather than by contrasting separate averages per condition. We also found that multilevel model random effects were less reliable, valid, and stable, arguing against their use as bias scores. We call upon the field to drop these suboptimal practices to improve the psychometric properties of the AAT. We also call for similar investigations in related RT-based bias measures such as the implicit association task, as their commonly accepted pre-processing practices involve many of the aforementioned discouraged methods. HIGHLIGHTS: • Rejecting RTs deviating more than 2 or 3 SD from the mean gives more reliable and valid results than other outlier rejection methods in empirical data • Removing error trials gives more reliable and valid results than retaining them or replacing them with the block mean and an added penalty • Double-difference scores are more reliable than compatibility scores under most circumstances • More reliable and valid results are obtained both in simulated and real data by using double-difference D-scores, which are obtained by dividing a participant's double mean difference score by the SD of their RTs.

Measuring self-regulation in everyday life: Reliability and validity of smartphone-based experiments in alcohol use disorder

Self-regulation, the ability to guide behavior according to one's goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test-retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures' construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks.

Easy to get, difficult to avoid: Behavioral tendencies toward high-calorie and low-calorie food during a mobile approach-avoidance task interact with body mass index and hunger in a community sample

In recent years, different studies highlighted the importance of assessing behavioral tendencies toward different food stimuli in healthy and pathological samples. However, heterogeneities in experimental approaches and small sample sizes make this literature rather inconsistent. In this study, we used a mobile approach-avoidance task to investigate the behavioral tendencies toward healthy and unhealthy foods compared to neutral objects in a large community sample. The role of some contextual and stable subjective variables was also explored. The sample included 204 participants. The stimuli comprised 15 pictures of unhealthy foods, 15 pictures of healthy foods, and 15 pictures of neutral objects. Participants were required to approach or avoid stimuli by respectively pull or push the smartphone toward or away from themselves. Accuracy and reaction time of each movement were calculated. The analyses were conducted using a generalized linear mixed-effect model (GLMMs), testing the two-way interaction between the type of movement and the stimulus category and the three-way interactions between type of movement, stimulus, and specific variables (BMI, time passed since the last meal, level of perceived hunger). Our results evidenced faster approaching movement toward food stimuli but not toward neutrals. An effect of BMI was also documented: as the BMI increased, participants became slower in avoiding unhealthy compared to healthy foods, and in approaching healthy compared to unhealthy stimuli. Moreover, as hunger increased, participants became faster in approaching and slower in avoiding healthy compared to unhealthy stimuli. In conclusion, our results show an approach tendency toward food stimuli, independent from caloric content, in the general population. Furthermore, approach tendencies to healthy foods decreased with increasing BMI and increased with perceived hunger, indicating the possible influence of different mechanisms on eating-related behavioral tendencies.

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.

Modifying Pavlovian-to-instrumental transfer by approach avoidance training in healthy subjects: a proof of concept study

The modulation of instrumental action by conditioned Pavlovian cues is hypothesized to play a role in the emergence and maintenance of maladaptive behavior. The Pavlovian to Instrumental transfer task (PIT) is designed to examine the magnitude of the influence of cues on behavior and we aim to manipulate the motivational value of Pavlovian cues to reduce their effect on instrumental responding. To this end, we utilized a joystick-based modification of approach and avoidance propensities that has shown success in clinical populations. To examine changes in PIT, we subjected 35 healthy participants to a series of experimental procedures: (1) Instrumental training was followed by (2) Pavlovian conditioning of neutral stimuli that were associated with monetary reward or loss. (3) In a subsequent joystick task, approach and avoidance tendencies toward conditioned cues were assessed. (4) In a transfer test, the PIT effect as the impact of conditioned cues on instrumental behavior was measured. (5) The explicit knowledge of cue-reward contingencies was assessed in a forced-choice phase. (6, 7) systematic joystick training was followed by a posttest (8) the transfer task and forced-choice test were repeated. We found no effect of training on approach-avoidance propensities in the context of this proof of concept study. A higher response rate towards negative stimuli during PIT after systematic training compared to sham training was seen. On the other hand, we saw an increased PIT effect after sham training. These results contribute to the understanding of the strength of the influence of cues on instrumental behavior. Our findings further stress the importance of context, instructions and operationalization of instrumental behavior in the framework of transfer effects.

Approach-Bias Retraining and Other Training Interventions as Add-On in the Treatment of AUD Patients

In the past two decades, a variety of cognitive training interventions have been developed to help people overcome their addictive behaviors. Conceptually, it is important to distinguish between programs in which reactions to addiction-relevant cues are trained (varieties of cognitive bias modification, CBM) and programs in which general abilities are trained such as working memory or mindfulness. CBM was first developed to study the hypothesized causal role in mental disorders: by directly manipulating the bias, it was investigated to what extent this influenced disorder-relevant behavior. In these proof-of-principle studies, the bias was temporarily modified in volunteers, either temporarily increased or decreased, with corresponding effects on behavior (e.g., beer consumption), in case the bias was successfully manipulated. In subsequent clinical randomized controlled trials (RCTs), training (away from the substance vs. sham training) was added to clinical treatment. These studies have demonstrated that CBM, as added to treatment, reduces relapse with a small effect of about 10% (similar effect size as for medication, with the strongest evidence for approach-bias modification). This has not been found for general ability training (e.g., working memory training), although effects on other psychological functions have been found (e.g., impulsivity). Mindfulness also has been found to help people overcome addictions, and different from CBM, also as stand-alone intervention. Research on (neuro-)cognitive mechanisms underlying approach-bias modification has pointed to a new perspective in which automatic inferences rather than associations are influenced by training, which has led to the development of a new variety of training: ABC training.

Testing the effectiveness of a mobile approach avoidance intervention and measuring approach biases in an ecological momentary assessment context: study protocol for a randomised-controlled trial

INTRODUCTION

Unhealthy eating behaviour is a major contributor to obesity and related diseases and is associated with a behavioural bias to approach rather than avoid desired foods, as measured with reaction time tasks. Approach-avoidance interventions (AAIs) have been proposed as a way to modify food evaluations and help people to eat in accordance with their dietary goals. Mobile implementations of AAI might be easily accessible, low threshold interventions, but their effectiveness has not been established yet.

METHODS AND ANALYSIS

Participants who aim to change their eating behaviour are randomised to intervention or control groups. They complete six sessions of a smartphone-based AAI, in which they push (ie, avoid) or pull (ie, approach) personalised food images. Intervention group participants always avoid foods that they personally want to eat less often and approach foods that they personally want to eat more often. In the control group, images are paired equally often with both response directions. To evaluate contextual and dynamic intervention effects, ecological momentary assessment (EMA) is measured throughout, with questions about food intake, hunger, stress, emotions, eating intentions, food craving and impulsivity twice a day. Additional EMA preintervention and postintervention measures are administered before and after the intervention phase (4 days each) with a 1-day follow-up EMA 4 weeks after the intervention. Multilevel models will examine the temporal covariance between approach bias and self-reported variables as well as short-term and long-term intervention effects on approach bias, food intake and craving.

ETHICS AND DISSEMINATION

The study was approved by the Ethics Committee of the University of Salzburg. Results will be published in peer-reviewed scientific journals and presented at scientific conferences.

TRIAL REGISTRATION NUMBER

German Clinical Trials Register DRKS, registration number DRKS00030780.

Quantifying aberrant approach-avoidance conflict in psychopathology: A review of computational approaches

Making effective decisions during approach-avoidance conflict is critical in daily life. Aberrant decision-making during approach-avoidance conflict is evident in a range of psychological disorders, including anxiety, depression, trauma-related disorders, substance use disorders, and alcohol use disorders. To help clarify etiological pathways and reveal novel intervention targets, clinical research into decision-making is increasingly adopting a computational psychopathology approach. This approach uses mathematical models that can identify specific decision-making related processes that are altered in mental health disorders. In our review, we highlight foundational approach-avoidance conflict research, followed by more in-depth discussion of computational approaches that have been used to model behavior in these tasks. Specifically, we describe the computational models that have been applied to approach-avoidance conflict (e.g., drift-diffusion, active inference, and reinforcement learning models), and provide resources to guide clinical researchers who may be interested in applying computational modeling. Finally, we identify notable gaps in the current literature and potential future directions for computational approaches aimed at identifying mechanisms of approach-avoidance conflict in psychopathology.

Same same, but different: A psychometric examination of three frequently used experimental tasks for cognitive bias assessment in a sample of healthy young adults

Cognitive bias research draws upon the notion that altered information processing is key for understanding psychological functioning and well-being. However, little attention has been paid to the question of whether the frequently used experimental paradigms hold adequate psychometric properties. The present study examined the psychometric properties of three widely used cognitive bias tasks: the Approach-Avoidance Task (AAT), the visual dot-probe-task, and the Implicit Association Test (IAT). Approach, attentional, and association biases towards valenced stimuli were repeatedly measured at five different time points in a sample of 79 healthy young adults. Two different devices were used for assessment: a personal computer (PC) and a touchscreen-based tablet. Reliability estimates included internal consistency and temporal stability. Validity was inferred from convergence across different behavioral tasks and correlations between bias scores and self-reported psychological traits. Reliability ranged widely amongst tasks, assessment devices, and measurement time points. While the dot-probe-task appeared to be completely unreliable, bias scores obtained from the PC-based version of the AAT and both (PC and touchscreen) versions of the IAT showed moderate reliability. Almost no associations were found across information processing tasks or between implicit and explicit measures. Cognitive bias research should adopt a standard practice to routinely estimate and report psychometric properties of experimental paradigms, investigate feasible ways to develop more reliable tools, and use tasks that are suitable to answer the precise research question asked.

Touchscreen-based approach-avoidance responses to appetitive and threatening stimuli

BACKGROUND AND OBJECTIVES

Individuals are thought to be biased towards approaching positive stimuli and avoiding negative stimuli. Yet, it is unclear whether this general pattern applies to all stimulus classes or whether biases are more specific. We expected significant approach biases towards two types of positive stimuli, appetitive foods and butterflies; and avoidance biases away from two types of negative stimuli, spoiled foods and spiders.

METHODS

A touchscreen-based Approach-Avoidance Task (AAT), using hand gestures toward or away from stimuli assessed biases. Questionnaires and image ratings assessed individual differences in stimulus evaluations.

RESULTS

Approach biases for butterflies and appetitive foods were found, the latter being strongest towards individually liked foods. There was no avoidance bias for spoiled foods. An avoidance bias for spiders was found in individuals with elevated spider fear.

LIMITATIONS

Incomplete counterbalancing precluded direct comparison between both positive and negative stimuli.

CONCLUSIONS

Behavioural biases in the touchscreen AAT generally co-vary with individuals' affective evaluation of the stimuli. Approach biases were elicited by positive stimuli independently of whether they were regularly (foods) or rarely (butterflies) approached in everyday life. This may hint towards a tendency to approach positive stimuli regardless of the specific category, whereas avoidance biases may be more stimulus specific.

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.

Approach-avoidance responses and categorical perception of ambiguous facial expressions

Emotion perception of facial expressions involves two processes: quick approach-avoidance responses and subsequent sorting into emotional categories (i.e., happiness, anger), considering the context. Sorting of morphed ambiguous facial expressions is known to occur categorically, but the occurrence of approach-avoidance responses for morphed facial expressions is yet to be investigated. The present study used morphed angry and fearful facial expressions and measured approach-avoidance responses among Japanese university students (Experiment 1, n = 29). Similar experiments with linguistic load (Experiment 2, n = 28) and visual load (Experiment 3, n = 29) were conducted. The results indicated categorical perception in the sorting of facial expressions but no approach-avoidance response for morphed expressions. Furthermore, linguistic load affected the categorisation of facial expressions, but neither linguistic load nor visual load affected the approach-avoidance response. These results support the idea that the non-linguistic approach-avoidance response and the linguistic categorisation of facial expressions are two different processes. The nature of the emotional perception process is also discussed.

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.

Comparison of different response devices to assess behavioral tendencies towards chocolate in the approach-avoidance task

Behavioral tendencies in the Approach-Avoidance Task (AAT) have mostly been assessed using a joystick as a response device. In recent years, other hardware devices such as tablets, smartphones, and computer mice have also been used. However, it remains unclear whether different response devices yield similar results and show comparable psychometric properties. The aim of the present study was to assess approach biases towards chocolate with different response devices and to compare their reliability and validity. Forty-five individuals with regular chocolate consumption completed three different AATs (joystick, computer mouse, touchscreen), each comprised of two blocks. In the compatible block of trials, chocolate-related pictures had to be pulled near while object-related pictures had to be pushed away. In the incompatible block of trials, instructions were reversed. Preregistered analyses revealed that participants were faster to pull than to push chocolate-related pictures relative to object-related pictures, indicating an approach bias for chocolate with no significant differences between response devices. Correlations among the three response devices were low to medium. Exploratory analyses revealed that approach biases were moderated by block order such that biases were only present and associated with craving (joystick AAT only) when the incongruent block was completed first. Internal consistencies of the bias score ranged between r_SB = 0.67-0.76. Results of the present study point to the existence of an approach bias to chocolate regardless of response device, albeit each task seems to measure a different aspect of it. Order effects point to specific temporal dynamics in the acquisition of stimulus response (e.g., chocolate-pull) mappings that require further study.

Computer-delivered behavioural activation and approach-avoidance training in major depression: Proof of concept and initial outcomes

OBJECTIVES

Individuals with major depressive disorder (MDD) have problems with engaging in approach behaviour to potentially rewarding encounters, which contributes to the maintenance of depressive symptoms. Approach-avoidance training (AAT) retrains implicit approach tendencies, and behavioural activation (BA) promotes explicit approach behaviour in MDD. As a novel MDD treatment strategy, this study aimed to implement a brief, computerized version of BA integrated with implicit AAT.

DESIGN

Adults with a principal diagnosis of MDD (N = 25) were randomly assigned to complete one of two versions of AAT - approach-positive faces (n = 12) or balanced approach of positive and neutral faces (n = 13) - concurrently with self-guided BA twice weekly for 2 weeks.

METHODS

Outcomes included treatment completion rates; bias scores for automatic approach towards positive social cues; and symptom scales for depression, positive affect, social relationship functioning, anhedonia, and anxiety.

RESULTS

Feasibility and acceptability of computerized BA + AAT were supported by moderate pre-treatment credibility and expectancy ratings and 80% treatment completion. Participants across both conditions displayed significant and large sized reductions in depression from pre- to post-assessment (Cohen's d = -1.23) that maintained three months later, as well as decreased anxiety and anhedonia and increased positive affect and social relationship functioning (medium to large effects).

CONCLUSION

Results support the feasibility and potential efficacy of brief, computerized BA + AAT. Research is needed to determine whether AAT is additive to BA, and what AAT parameters best enhance treatment outcomes.

PRACTITIONER POINTS

Brief, computerized behavioral activation plus approach/avoidance training (BA + AAT) may be acceptable and beneficial for some patients with moderate-to-severe major depression. Computer-delivered BA + AAT can be implemented as a largely self-guided program for MDD and could be administered remotely and/or with minimal clinician interaction. As this was a small proof of concept study, it cannot be determined which treatment components - AAT, BA, or both - contributed to positive clinical outcomes. Because BA + AAT was implemented in a research clinic, it remains unknown what treatment engagement and response would look like in community settings.

Food approach bias is moderated by the desire to eat specific foods

In a post-scarcity world, energy intake and excesses therein are mediated by psychological mechanisms, such as implicit inclinations to approach certain foods. We investigated how food deprivation, calorie content and individual food preferences affect this approach bias. Sixty women performed a touchscreen-based approach-avoidance task featuring a wide range of food items, once while satiated and once while food-deprived for 15 h. We found an overall approach bias towards food that was not influenced by food deprivation or calorie density of the food items. Instead, we found that approach bias related to the participants' (lack of) desire to eat specific food items, and to a lesser extent to how much their general desire to eat changed due to food deprivation. Links with food preference were selective to trials in which foods had to be approached, and were absent in trials in which foods had to be avoided, pointing to selectivity to appetitive brain systems and clarifying the nature of the bias. Approach bias was unrelated to overall state or trait food craving. We conclude approach bias for appetitive stimuli may primarily express itself as speeded approach rather than slowed avoidance. Additionally, our results show there is merit in personalizing stimulus selection for approach bias measurement and retraining, as approach bias was concordant with individual food preferences, rather than objective calorie content.