Time-Varying Mediation of Negative Affect on Smoking Status: An Exploratory Analysis

-0.25 -0.50 -0.75 -1.00 Varenicline cNRT Craving Week 1 Week 2 Week 3-4 Week 1 Week 2 Week 3-4 Week 1 Week 2 Week 3-4 Week 1 Week 2 Week 3-4 Week 1 Week 2 Week 3-4 Week 1 Week 2 Week 3-4 0.00 -0.04 -0.08 -0.12 0.16 0.12 0.08 0.04 0.20 0.15 0.10 0.05 0.00 -0.20 -0.40 -0.80 -0.60 0.00 -0.03 -0.06 Time-Varying Mediation of Negative Affect on Smoking Status: An Exploratory Analysis Yajnaseni Chakraborti1, Donna Coffman, PhD1 1 Temple College of Public Health, Department of Epidemiology & Biostatistics College of Public Health The pharmacokinetic mechanism of action of tobacco makes smoking cessation an extremely challenging process Chronic exposure of nicotine negatively reinforces smoking Withdrawal symptoms peak in the first week of quitting, usually resolving over amonth These withdrawal symptoms often act as mediators regulating the pathway between cessation intervention and (un) successful smoking cessation Background Trigger the neuronal reward system Neuroadaptation Hedonic Dysregulation Data Data on NA includes `negative mood`, `cessation fatigue` and `craving` responses from 1086 smokers during the first 4weeks post target quit day (TQD)of the Wisconsin Smokers Health Study 2 (WSHS2) Subjects were randomly assigned to one of the 3pharmacotherapies (Nicotine Patch, Varenicline, Combination Nicotine Replacement Therapy –cNRT) The responses were collected via 42 Ecological Momentary Assessment (EMA)prompts Objective Study the variations in the mediated effect of withdrawal symptoms (primarily ‘Negative Affect’-NA) over time Identify peaks and/or drops in the mediated effect curve which could be suggestive of specific time-points of including mood-boosting/ coping techniques Methodology Our approach allows mediation effects to vary as afunction of time. Excluding individuals with no data, we have 1031 individuals in total, and the observed data are, {𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝒊𝒊,𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝒊𝒊, (𝒕𝒕𝒊𝒊𝒊𝒊,𝑵𝑵𝑵𝑵𝒊𝒊𝒊𝒊,𝑺𝑺𝒊𝒊𝒊𝒊)}, 𝑖𝑖= 1,2, … , 1031 𝑗𝑗= 1,2, … , 42 where, 𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝒊𝒊indicates whether the 𝒊𝒊𝒕𝒕𝒕𝒕 subject received Varenicline or not and 𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝒊𝒊indicates whether the 𝒊𝒊𝒕𝒕𝒕𝒕 subject received cNRT or not.The reference group includes those who received Nicotine Patch (NP). Components of NA were measured in 7-point Likert scale and Smoking status was derived in binary scale (Yes/No), from daily smoking count variables. Estimation in Time-Varying Model: 1. Time-varying mediation effect: 𝜶𝜶𝑵𝑵(𝒕𝒕 − ∆𝒕𝒕) × 𝜷𝜷(𝒕𝒕) ; 𝜶𝜶𝑵𝑵(𝒕𝒕 − ∆𝒕𝒕) × 𝜷𝜷(𝒕𝒕) 2. Two step estimation (Fan and Zhang 2000) 3. Point-wise confidence band for the time-varying mediation effect via percentile bootstrapping Results WSDS 2020 -Women in Statistics and Data Science Virtual Conference, October 1, 2020 Please contact Yajnaseni Chakraborti (ychakrabor[email protected]) for more details on the topic Negative Affect: 𝑁𝑁𝑁𝑁(𝑡𝑡 − ∆𝑡𝑡) Intervention: 𝐼𝐼𝐼𝐼𝑡𝑡 Smoking status: 𝑆𝑆(𝑡𝑡) 𝛼𝛼1𝑡𝑡 − ∆𝑡𝑡 , 𝛼𝛼2𝑡𝑡 − ∆𝑡𝑡 𝛽𝛽 𝑡𝑡 𝛾𝛾 𝑡𝑡 Figure 1: Mediation effect of craving and component indirect effects {𝜶𝜶 𝒕𝒕 ,𝜷𝜷 𝒕𝒕 }with 95%CI estimated for binary outcome (Smoking Status –Yes/No) Conclusions Compared to NP, the effect of Varenicline on the smoking status that is mediated by craving declines after quitting (first week), and stabilizes thereafter with an intermediate increase mid-week 2 Compared to NP,craving decreases steeply in the Varenicline group over the first week and stabilizes post mid-week 2after an increase The pattern for both 𝜶𝜶(𝒕𝒕 − ∆𝒕𝒕) × 𝜷𝜷 𝒕𝒕 and 𝜶𝜶(𝒕𝒕)curves observed in the cNRT group is similar to the Varenicline group initially, however post week 1, the effects lose its statistical significance The effect of craving on the smoking status remains stable after week-1 for both Varenicline and cNRT ,with some initial decline Collectively we can say that in week 1post TQD individuals were less likely to resort to smoking when they had cravings, and monitoring decline in cravings in the post week 1period, may be useful in identifying trigger time-points of some mood-boosting techniques Acknowledgements: Research was supported by National Institutes of Health grant 1 R01 CA229542-01 from the National Cancer Institute and the NIH Office of Behavioral and Social Science Research Disclaimer:Content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions mentioned above