Transcranial Magnetic Stimulation (TMS) for Smoking Cessation in People Living With HIV/AIDS (PLWHA)
Phase: NA
Conditions: Smoking Cessation, HIV, Craving
Sponsor: Gopalkumar Rakesh

Document Coversheet 
 
 Study Title: Transcranial Magnetic Stimulation (TMS) for Smoking Cessation in People Living 
With HIV/AIDS (PLWHA) 
Institution/Site:  
University of Kentucky 
Document (Approval/Update) Date: 
2/7/2023 (IRB); 2/24/2022 (ICF) 
NCT Number: 
NCT04936594 
IRB Number 
64473 
Coversheet created: 
4/4/2023 
 
 

Section 1 Page 1 of 2
IRB Approval
2/7/2023
IRB # 64473
IRB3
CLOSED

Section 1 Page 2 of 2
64473
CLOSED

Section 2 Page 1 of 8
64473
CLOSED

Section 2 Page 2 of 8
64473
CLOSED

Section 2 Page 3 of 8
64473
CLOSED

Section 2 Page 4 of 8
64473
CLOSED

Section 2 Page 5 of 8
64473
CLOSED

Section 2 Page 6 of 8
64473
CLOSED

Section 2 Page 7 of 8
64473
CLOSED

Section 2 Page 8 of 8
64473
CLOSED

Section 3 Page 1 of 1
64473
CLOSED

Section 4 Page 1 of 2
64473
CLOSED

Section 4 Page 2 of 2
64473
CLOSED

Section 5 Page 1 of 1
64473
CLOSED

Section 6 Page 1 of 3
64473
CLOSED

Section 6 Page 2 of 3
64473
CLOSED

Section 6 Page 3 of 3
64473
CLOSED

Section 7 Page 1 of 4
64473
CLOSED

Section 7 Page 2 of 4
64473
CLOSED

Section 7 Page 3 of 4
64473
CLOSED

Section 7 Page 4 of 4
64473
CLOSED

Section 8 Page 1 of 1
64473
CLOSED

Section 9 Page 1 of 17
64473
CLOSED

Section 9 Page 2 of 17
64473
CLOSED

Section 9 Page 3 of 17
64473
CLOSED

Section 9 Page 4 of 17
64473
CLOSED

Section 9 Page 5 of 17
64473
CLOSED

Section 9 Page 6 of 17
64473
CLOSED

Section 9 Page 7 of 17
64473
CLOSED

Section 9 Page 8 of 17
64473
CLOSED

Section 9 Page 9 of 17
64473
CLOSED

Section 9 Page 10 of 17
64473
CLOSED

Section 9 Page 11 of 17
64473
CLOSED

Section 9 Page 12 of 17
64473
CLOSED

Section 9 Page 13 of 17
64473
CLOSED

Section 9 Page 14 of 17
64473
CLOSED

Section 9 Page 15 of 17
64473
CLOSED

Section 9 Page 16 of 17
64473
CLOSED

Section 9 Page 17 of 17
64473
CLOSED

Section 10 Page 1 of 1
64473
CLOSED

Section 11 Page 1 of 2
64473
CLOSED

Section 11 Page 2 of 2
64473
CLOSED

Section 12 Page 1 of 2
64473
CLOSED

Section 12 Page 2 of 2
64473
CLOSED

Section 13 Page 1 of 2
64473
CLOSED

Section 13 Page 2 of 2
64473
CLOSED

Section 14 Page 1 of 2
64473
CLOSED

Section 14 Page 2 of 2
64473
CLOSED

Section 15 Page 1 of 2
64473
CLOSED

Section 15 Page 2 of 2
64473
CLOSED

Section 16 Page 1 of 1
64473
CLOSED

Section 17 Page 1 of 1
64473
CLOSED

Section 18 Page 1 of 2
64473
CLOSED

Section 18 Page 2 of 2
64473
CLOSED

Section 19 Page 1 of 1
64473
CLOSED

IRB Approval
2/24/2022
IRB # 64473
IRB3

64473

64473

64473

64473

64473

64473

64473

Attentional Bias Analyses. Attentional bias for cigarette cues will be calculated 
separately for each set of trials, by subtracting the average fixation time on neutral cues 
from the average fixation time on cigarette cues. Fixation time on cigarette cues for 
each session and resultant cigarette cue attentional bias score will be entered into 
separate linear fixed effects regression models. Dependent variables for these models 
will be fixation time on cigarette cues and attentional bias for cigarette cues 
respectively.  
 
     Cigarette craving analyses. TCQ-SF scores will be entered into a linear fixed effects 
regression model. Outcome variables for this model will be TCQ-SF score.  
 
Resting state functional connectivity (rsFC) analyses. CONN functional 
connectivity toolbox (version 21.a) will be used for all preprocessing and neuroimaging 
analyses using standard procedures. Firstly, general linear model (GLM) analyses will 
explore if rsFC changed from two seeds (L. dlPFC and right insula) to all voxels 
following iTBS versus sham iTBS relative to baseline rsFC in participants who receive 
iTBS and sham iTBS. In first level analyses, a seed map will be created for every 
subject using respective seeds (L. dlPFC or right insula). In second level analyses, a 
between conditions contrast will be used to assess rsFC within-subject differences 
baseline, and following iTBS and sham ITBS. All second level analyses will use cluster 
level inferences based on Gaussian Random Field Theory. This will be done using 
general linear models (GLM) to generate a statistical map of t-values, that will 
subsequently threshold to reveal non overlapping clusters (https://web.conn-

toolbox.org/fmri-methods/cluster-level-inferences). Two-sided p-values will be
generated using cluster-level false discovery rate (FDR) correction 62.