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RCT·nutrition, obesity, behavioural medicine, digital health, psychiatry·PMC10151942

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

BMJ Open · 4 authors, 2 centres

AI SUMMARY

FIDELITY 100%

POPULATIONGerman-speaking adults aged 18–60 years who intend to change their eating behaviour and do not have a diagnosed eating disorder or pregnancy

INTERVENTIONSmartphone-based approach-avoidance intervention (AAI): participants physically move the phone toward (approach) personalised 'increase-foods' and away (avoid) personalised 'decrease-foods' across six training sessions over 12 days

COMPARISONSham-training (measurement AAT): food images are paired equally often with approach and avoidance responses, with no contingency between food type and movement direction

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AGENT 01 · STRUCTURED SUMMARY

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TL;DR

This protocol describes a double-blind randomised controlled trial testing whether a smartphone-based approach-avoidance intervention (AAI), where participants physically move the phone toward or away from personalised food images, can help people change their eating behaviour. The study combines the intervention with ecological momentary assessment (EMA) twice daily over 20 days to capture short-term and long-term effects on food intake, craving, and approach bias. If effective, this mobile AAI could provide a low-threshold, scalable tool to support dietary behaviour change in everyday life.

Full summary

5,586 CHARS

**Background:** Unhealthy eating is a major contributor to obesity and related diseases. Traditional models assume reflective decision-making, but the 'intention-behaviour gap' shows that intentions often fail to translate into action. Approach-avoidance biases—measured via reaction-time tasks like the Approach Avoidance Task (AAT)—predict food intake beyond self-report, especially in impulsive individuals and those prone to external or emotional eating. Approach-Avoidance Interventions (AAIs) repeatedly pair unhealthy foods with avoidance and healthy foods with approach to modify these biases. Evidence is mixed, possibly due to single-session designs, non-personalised stimuli, and lack of ecological delivery. Smartphone-based AAIs could overcome these limitations by enabling repeated, context-sensitive intervention delivery in daily life. This study tests a mobile AAI using physical phone movements (toward/away from the body) combined with ecological momentary assessment (EMA) to capture dynamic intervention effects.

**Methods:** This is a two-arm, double-blind RCT conducted at the University of Salzburg, Austria. Participants (target N=150, based on power analysis: g=0.50, power=0.80) are recruited via university email lists, social networks, and word of mouth. Inclusion criteria: age 18–60, intention to change eating behaviour. Exclusion: pregnancy, diagnosed eating disorder. At baseline, participants complete web-based questionnaires (demographics, DEBQ subscales, Salzburg Emotional Eating Scale, Salzburg Stress Eating Scale, Perceived Self-Regulatory Success in Dieting, short UPPS Impulsivity Scale) and rate 90 food/drink images on recent intake and intended intake over the past/next 3 weeks. The six foods with the largest negative difference (eaten less than intended = 'increase-foods') and six with the largest positive difference (eaten more than intended = 'decrease-foods') are selected per participant. Four of each are used in training; two remain untrained to test specificity. Eight office-item images serve as control stimuli. After a set-up call, participants complete a 20-day EMA period (two prompts/day: pre-lunch and evening). Days 1–3: EMA only. Day 4: pre-intervention measurement AAT. Days 5–16: intervention phase—on every second day, participants complete a training AAT after the midday prompt (six sessions total). Day 17: post-intervention measurement AAT. Days 17–20: post-intervention EMA. A 1-day follow-up EMA and measurement AAT occur 4 weeks later. The AAT uses physical phone movements: approach = move phone toward self, avoidance = move away. Each training session: 4 blocks × 16 trials + 4 practice trials/block = 80 trials total. Active training: only increase-foods in approach blocks, only decrease-foods in avoid blocks. Sham training: both food types appear equally in both block types. Measurement AATs (pre, post, follow-up) use all 24 images (6 increase, 6 decrease, 12 objects) across 4 blocks × 24 trials + 16 practice = 112 trials. EMA items assess hunger, emotions (happy, lonely, depressed, angry, tense, anxious), craving and intake for each food (slider 0–100), dietary intentions, impulsivity items, and contingency awareness at follow-up.

**Key Results:** This is a study protocol; no results are reported. The primary outcomes are: (1) self-reported intake of increase/decrease foods (EMA slider 0–100), (2) self-reported craving for those foods (same scale), and (3) approach bias derived from RT and force in the AAT. Approach bias is operationalised as double-difference scores: ((food-specific avoidance − food-specific approach) − (average object avoidance − average object approach)). Secondary outcomes include dietary intentions. Data analysis will use multilevel models. For overall intervention effectiveness, intake/craving/bias are predicted by timepoint (pre vs post), condition (intervention vs control), and their interaction. Specificity is tested by adding a trained vs untrained variable. Immediate intervention effects during the intervention phase are modelled with group, training day (yes/no), and days-since-start predictors. Trait/state components of approach bias are examined within the control group only, testing within- and between-subject associations between bias, negative emotions, craving, and intake. Sensitivity analyses will test the effect of number of completed sessions. Exclusion criteria: error trials, RTs >±3 SD from individual session mean, and entire sessions with >25% excluded trials.

**Clinical Implications:** If effective, this mobile AAI could provide a scalable, low-threshold intervention to support dietary behaviour change in real-world settings. The repeated, personalised, context-sensitive delivery may overcome limitations of single-session laboratory interventions. Combining AAI with EMA allows examination of temporal dynamics of approach bias and its relationship with craving, intake, and affect—potentially identifying optimal moments for intervention delivery. The study also addresses key methodological debates: personalised vs generic stimuli, relevant-feature vs irrelevant-feature tasks, and single vs multi-session designs. Null or negative findings would contribute important evidence on the limitations of mobile AAIs, particularly given mixed prior results. The study is registered (DRKS00030780) and approved by the University of Salzburg Ethics Committee. Data will be disseminated via peer-reviewed journals and conferences, with deidentified data made public on the Open Science Framework after planned publications.

PICO

PPOPULATION

German-speaking adults aged 18–60 years who intend to change their eating behaviour and do not have a diagnosed eating disorder or pregnancy

IINTERVENTION

Smartphone-based approach-avoidance intervention (AAI): participants physically move the phone toward (approach) personalised 'increase-foods' and away (avoid) personalised 'decrease-foods' across six training sessions over 12 days

OOUTCOME

Primary: self-reported intake and craving for increase/decrease foods (EMA slider 0–100), and approach bias (reaction time and force in the AAT). Secondary: dietary intentions, contingency awareness, moderating effects of trait variables

STUDY TYPE

RCT

SPECIALTY

nutrition

SUMMARISED BY

AI pipeline

FIDELITY CHECK

100% · A

ORIGINAL PAPER

PMC10151942

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

BMJ Open

READ THE FULL PAPER

ABSTRACT

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.

CITATION EXPORT

Matthias Burkard Aulbach, Hannah van Alebeek, Sercan Kahveci et al.. 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. BMJ Open. (2023). https://doi.org/10.1136/bmjopen-2022-070443

AUTHORS

4 · 2 CENTRES

Matthias Burkard Aulbach, Hannah van Alebeek, Sercan Kahveci, Jens Blechert

1Department of Psychology, Paris Lodron Universitat Salzburg, Salzburg, Austria
2Department of Psychology, Centre for Cognitive Neuroscience, Salzburg, Austria