EMA O utcome M easures in a C linical T rial 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 ID: 773171
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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 outcomesIn 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
Current study: Effects of tDCS in smokers - Attentional bias for cigarettes- Less control over cravingChallenging to quit smoking
tDCS Promising new treatment intervention for smokers:transcranial Direct Current Stimulation (tDCS)How? Modulates membrane potentials by means of electrical currentstDCS over the DLPFC:Reduced craving and cigarette consumption (Jansen et al., 2013; Falcone et al., 2016)
Current study explores:1. How long the effects of tDCS last Ecological Momentary2. When the effect of tDCS kicks in Assessments (EMA)EMA to measure craving over time and in real time Why EMA?
Participants are 60 smokers: 10 cigarettes a day18-65 years (mostly students)EMA 4 times daily- CravingCigarettesMoodBaselineWeek2 Week 1 Day 5: tDCS Day 3: tDCS Day 1: tDCS + EEG Day 6: EEG 3 months follow-up… Method + Total amount end of the day UIS cigarettes
Analyses Outcomes: Craving and mood over time:Difference between tDCS and Sham groupAnalyses:Demographics in SPSSMultilevel analyses in HLM: Levels are dependent Corrects for missings
Results: Response rates Table 1. Characteristics of sample Response rateAge 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 nowReal time data caused different outcomes? Advantage of EMA data:Measures over time Insights in treatment interventions Fluctuations Interactions between outcomesOutcomes in real time = More ecologically valid Limitations: Low response rate: R ewards necessary? Use of smartphones…
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