1. Cognitive measures in EMA research
Andrew Jones and Matt Field

2. 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.

3. 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

4. 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)

5. 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)

6. 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’

7. 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

8. 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.

9. 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

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

11. 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.

12. 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…

13. Results: fluctuations over the day

14. 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

15. 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)?

16. 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)
ME!
TWEET ME!
@ajj_1988