EMA Outcome Measures in a Clinical Trial Ilse Verveer, Freddy van der Veen, Danielle Remmerswaal, Ingmar Franken

EMA in clinical trials EMA to measure outcomes: Over time  Deeper insights in treatment outcomes In real time  -Outcome measures are often momentary -General cues in the lab illicit less craving -Generalization of outcomes to real life Other advantages: Easy in use High response rates (80%)

Examples of EMA studies EMA to study: -Association between smoking and craving/drug use (Epstein et al., 2010) -Link between craving and personal cues (Fatseas et al., 2015) -Treatment outcomes (Ferguson et al., 2006) Now… an example from our clinical trial with EMA outcomes will follow Epstein et al (2010): Studied association between smoking and craving for cigarettes, and craving for and use of heroine/cocaine Found that smoking and craving for cigarettes is associated with craving and drug use for heroine and cocaine Were able to do so, because addicted patients initiated an assessment whenever they had strong urges/cravings to use drugs and by random prompts so they could see whether soking or craving for cigarettes on a prompt before was associated with this craving/use (In real time and over time). However it is difficult to verify whether the patients always initiated a session when they felt craving or used.

Current study: Effects of tDCS in smokers - Attentional bias for cigarettes - Less control over craving Challenging to quit smoking

tDCS Promising new treatment intervention for smokers: transcranial Direct Current Stimulation (tDCS) How? Modulates membrane potentials by means of electrical currents tDCS over the DLPFC: Reduced craving and cigarette consumption (Jansen et al., 2013; Falcone et al., 2016)

Why EMA? Current study explores: 1. How long the effects of tDCS last Ecological Momentary 2. When the effect of tDCS kicks in Assessments (EMA) EMA to measure craving over time and in real time Real time: - Personal cues (triggers) induce craving - Craving is a momentary phenomenon - To avoid memory bias Over time: - Working mechanism (main research questions)

Method + Total amount end of the day UIS cigarettes Participants are 60 smokers: 10 cigarettes a day 18-65 years (mostly students) EMA 4 times daily - Craving Cigarettes Mood Total amount end of the day UIS cigarettes + Baseline Week 1 Week2 Day 1: tDCS + EEG Day 3: tDCS Day 5: tDCS Day 6: EEG 3 months follow-up…

Analyses Outcomes: Craving and mood over time: Difference between tDCS and Sham group Analyses: Demographics in SPSS Multilevel analyses in HLM: Levels are dependent Corrects for missings

Results: Response rates Table 1. Characteristics of sample   Response rate Age mean (SD) Sample characteristics (n = 45) Overall: 51.3 22 (5.33) Male 45 21.8 (2.66) Female 56.1 22.9 (6.94) tDCS: 50.6 24 (7.04) Sham: 52.6 21 (1.84)

Results: Craving over time

Individual data

Results: Craving over time (HLM) Group coefficient = -.44, SE=.50 t-ratio = -.88

Comparison with craving in lab Overall decrease in craving (F = 15,503, p <.001) No main effect of group

Conclusions clinical trial Results are inconclusive for now Real time data caused different outcomes? Advantage of EMA data: Measures over time  Insights in treatment interventions  Fluctuations  Interactions between outcomes Outcomes in real time = More ecologically valid Limitations: Low response rate: Rewards necessary? Use of smartphones… Small sample size Groups differed in craving at start Low response rate

Thank You! verveer@essb.eur.nl

References Epstein, D. H., Marrone, G. F., Heishman, S. J., Schmittner, J., & Preston, K. L. (2010). Tobacco, cocaine, and heroin: craving and use during daily life. Addictive behaviors, 35(4), 318-324. Falcone, M., Bernardo, L., Ashare, R. L., Hamilton, R., Faseyitan, O., McKee, S. A., ... & Lerman, C. (2016). Transcranial direct current brain stimulation increases ability to resist smoking. Brain stimulation, 9(2), 191-196. Fatseas, M., Serre, F., Alexandre, J. M., Debrabant, R., Auriacombe, M., & Swendsen, J. (2015). Craving and substance use among patients with alcohol, tobacco, cannabis or heroin addiction: A comparison of substance‐and person‐specific cues. Addiction, 110(6), 1035-1042. Fecteau, S., Agosta, S., Hone-Blanchet, A., Fregni, F., Boggio, P., Ciraulo, D., & Pascual-Leone, A. (2014). Modulation of smoking and decision-making behaviors with transcranial direct current stimulation in tobacco smokers: a preliminary study. Drug and alcohol dependence, 140, 78-84. Ferguson, S. G., Shiffman, S., & Gwaltney, C. J. (2006). Does reducing withdrawal severity mediate nicotine patch efficacy? A randomized clinical trial. Journal of consulting and clinical psychology, 74(6), 1153. Jansen, J. M., Daams, J. G., Koeter, M. W., Veltman, D. J., van den Brink, W., & Goudriaan, A. E. (2013). Effects of non-invasive neurostimulation on craving: a meta-analysis. Neuroscience & Biobehavioral Reviews, 37(10), 2472-2480. Swendsen, J. (2016). Contributions of mobile technologies to addiction research. Dialogues in clinical neuroscience, 18(2), 213.

95% confidence intervals