Cognitive measures in EMA research Andrew Jones and Matt Field

Cognitive measure - Inhibitory control ‘the (in)ability to stop, change or delay a behaviour that is no longer appropriate, in the current environment (Logan et al 1988)’ Think of a traffic light Useful endophenotype for psychiatric disorders (Aron, 2011) 90% of all self-regulatory behaviours require some sort of inhibition, without it we would be doomed (Jones et al 2017). I am going to talk about a particular type of cognitive process called inhibitory control.

Measuring inhibition in the lab: So we can measure inhibition in the laboratory using tasks such as the Stop Signal and Go/No-Go tasks

Inhibitory control and alcohol use. Theoretical models of addiction suggest a key role for inhibitory control in the development and maintenance of addiction (Goldstein & Volkow, 2011; de Wit, 2009) Supported by empirical data…. And there is empirical evidence to back up these theoretical preductions… meta-analysis demonstrates that Smith et al (2014)

Does inhibitory control fluctuate? So whilst this meta-analysis suggests a relationship between alcohol use and inhibitory control – the effect sizes arte pretty small. This might be because the studies assume that inhibitory control is a variable that is stable over long periods of time. The research question I focused on during my PhD was to examine the transient nature of inhibitory control, and the variables which may cause changes in inhibition. Jones et al (2013)

Causality Treatment success / relapse (Rupp et al 2016) Escalation of drinking: Heavy > Dependence (Rubio et al 2008) Ad-libitum consumption following acute intoxication (Weafer et al, 2008) Short term episodes in lab increase drinking (Jones et al, 2011). No evidence from the ‘real-world’

Ecological Momentary Assessment for alcohol use Ideal for assessing alcohol consumption in the real world (Shiffman et al, 2009). Measures less prone to recall bias Behaviour in the laboratory can often be suppressed Context dependent Can take repeated assessments over time to improve reliability

Current study: Primary hypothesis: Day-to-day fluctuations in inhibitory control would predict day-to-day variation in alcohol consumption, when controlling for planned consumption, subjective craving and mood 100 Participants (54 female) Heavy drinkers (> 14 units per week) Motivated to cut down Loaned a smartphone for two weeks.

Methods First laboratory visit: Consent, TLFB, AUDIT, TRI, BIS. Brief intervention Second visit. Check compliance 28 random (signal contingent) assessments Temptation (event contingent) assessments Third visit. Motivation, Ability. Debrief

Results: Descriptives, compliance and alcohol use Participants reduced their alcohol consumption from a mean of 66.37 (± 27.18) units in the two weeks prior to the study to 55.39 (± 39.95).

Reliability and Sensitivity of Stop Signal Reaction time in the real-world Daily measures of SSRT demonstrated excellent internal reliability over the course of 14 days - (Cronbach’s α = .96) Distraction – increased SSRT Intoxication - increased SSRT Smoking – decreased SSRT Contaminated time-points removed from analyses, but even if included results did not change.

Results: Predictors of alcohol consumption Multi-level model of assessment day, within individual. Significant variance at each level of the model so justified in using a multi-level structure. (No variance in drinking at the assessment level, so not justified) Whole model predicted about 45% in alcohol use. The best predictor of how much people drank… was how much they said they were going to drink. Encoragingly, our covariates which we would expect to influence consumption also predicted…

Results: fluctuations over the day

Limitations and Future Directions No idea about the exact time participants started drinking Planned consumption may have lead to atypical drinking behaviour Did not measure reasons for inhibitory fluctuations No idea about the exact time participants started drinking – although we controlled

Conclusions Can reliably measure cognitive performance (inhibition) in the real-world on a smart phone device. Significant reduction in alcohol consumption during the assessment phase (indicative of motivation)? Day-to-day fluctuations did not predict consumption, however within-day fluctuations did Fluctuations in inhibitory control risk factor for drinking (more than planned)?

Thanks EMAIL ME! ajj@liv.ac.uk TWEET ME! @ajj_1988 Matt Field (UoL) Chantaal Nederkoorn (Maastricht) Katrijn Houben (Maastricht) Brain Tiplady (U of Edinburgh) EMAIL ME! ajj@liv.ac.uk TWEET ME! @ajj_1988