Integrated Technology-Based Intervention to Reduce Heavy Drinking and Chronic Pain Among Patients in Primary Care
Phase: NA
Conditions: Alcohol Drinking, Chronic Pain
Sponsor: Boston University Charles River Campus

 
NCT04958200    
 
 
 
 
8/10/24 
Alcohol Use and Chronic Pain among Primary Care Patients 
Protocol and Statistical Analysis 
 
 

 
PROTOCOL 
Design.  The study was a block randomized two-group, between-subjects design. Participants 
were randomized to one of two intervention conditions (i.e., Smartphone Intervention Program 
vs. Treatment-as-Usual Control) following baseline based on a block randomization schedule 
stratified by sex at birth and level of heavy drinking (+/- 5 heavy drinking episodes). 
Inclusion/Exclusion.  Eligible participants were 18 years of age or older, fluent in English, 
engaged in primary care (i.e., had a primary care physician), experienced chronic non-cancer 
related pain, and reported heavy drinking. The chronic pain inclusion criterion was pain of 
moderate severity or greater in the past week that lasted for at least 3 months. Heavy drinking 
was determined by past month drinking that exceeded NIAAA limits (>7 for women > 14 for 
men) and/or the occurrence of one or more heavy drinking episodes in the past month. 
Participants currently using pharmacological approaches for pain or alcohol use were permitted 
in the study if medication doses were stable for at least two months. Exclusion criteria were: 
history of bipolar disorder/schizophrenia/ complicated alcohol withdrawal, psychological 
treatment for pain or alcohol use within the past 3 months, and planned surgery for a pain-
related condition in the subsequent six months. Participants were also excluded if they did not 
have a smartphone.  
Recruitment.  Recruitment took place within primary clinic waiting rooms in a large urban 
hospital, through recruitment letters sent to patients from a hospital data base by permission of 
primary care provider, and social media.  Patients from hospital-based recruitment efforts who 
expressed interest were then screened by phone. Study advertisements delivered through 
social media were linked to a preliminary, web-based screening form. Individuals who met initial 
eligibility criteria based on the web-based screening were contacted by a member of the 
research team for phone screening to determine eligibility.   
 
 

 
Assessments 
 
Sample characteristics. Participants completed a series of measures to assess 
demographic characteristics including race/ethnicity, marital status, education, and employment.  
 
Pain outcomes.  The primary pain outcome for the trial was the Pain, Enjoyment of 
Life, and General Activity (PEG; Krebs et al., 2009).  Participants rated the severity of their pain 
and the degree to which their pain interfered with enjoyment in life and general activity “in the 
past 7 days” using 0-10 scales. The PEG has excellent reliability and validity and has been 
widely established with medical populations.  Secondary pain outcomes were past week pain 
severity rated on an 11-point scale and pain interference composite scores from the Brief Pain 
Inventory-Short Form (BPI), (Dworkin et al., 2005). 
 
Alcohol outcomes.  The primary alcohol outcomes were frequency of heavy drinking 
episodes (women > 3 per occasion, men > 4 per occasion) in the past 30-days and mean 
number of drinks per week as assessed by the 30-day alcohol Timeline Follow-Back calendar 
method (Alcohol TLFB-30) (Sobell et al., 1979). Alcohol-related consequences were assessed 
with the Short Inventory of Problems-Revised (Kiluk et al., 2013). 
 
Additional outcome assessments.  Participants completed additional assessments to 
examine the transdiagnostic effects of the intervention including depressive symptoms with the 
PHQ-8 (Kroenke et al., 2009), days of cannabis use in the past 30 days (Rosen et al., 2000) 
and physical functioning from the PROMIS-29 v2.0 (Hays et al., 2018).   
 
Feasibility, acceptability, health behavior change processes.  A series of assessments 
were taken approximately 8-weeks following baseline to assess participant experiences with the 
intervention conditions and assess health behavior change.  All participants completed indices 
of intervention satisfaction using a modified version of the Client Satisfaction Questionnaire-8 
(CSQ-8), an 8-item validated measure of perceived value of treatment services (Kelly et al., 
2018; Larsen et al., 1979).  In addition, we used study specific Likert-type items based on the 
Perceptions of Treatment Questionnaire (PTQ-17), (Pincus et al., 2010) that provides descriptive 

 
information about perceived comprehensibility and utility of the intervention.  Finally, to provide 
initial data regarding hypothesized mechanisms underlying the intervention, we utilized pain and 
alcohol specific measures of the Goal Systems Assessment Battery (Karoly and Ruehlman, 
1995). Participants rated their self-regulatory processes related to the behavior change goals of 
“pain management” and “moderating/limiting alcohol use” using 4-point 16-item Likert-scale 
measures (“not at all” to “very much”).  To gather usability and acceptability data on the 
smartphone intervention itself, we examined rates of completion for the video modules, 
adherence to health coach instant messaging sessions, and completion of smartphone daily 
activities to assess intervention acceptability. We also assessed whether participants engaged 
with the optional skills library. Participants in the smartphone intervention condition also 
completed 3-items selected from the Systems Usability Scale (Brooke, 1996) to provide 
information about the experience of program use through subjective ratings 
Conditions 
 
Smartphone Intervention Program [MCBMAP Intervention (INTV]). The intervention 
utilized a self-regulation framework (Karoly, 2012) to integrate evidence-based approaches for 
hazardous drinking and pain including Motivational Interviewing (Miller and Rollnick, 2013) and 
cognitive-behavioral and self-management training (Morgenstern et al., 2007; Otis, 2007; 
Ruehlman et al., 2012; Sobell and Sobell, 1996). Participants first met with the health coach, 
who introduced the program, reviewed participants’ experience of pain and prior treatment, 
provided psychoeducation on the interaction between pain and alcohol use, and presented the 
program rationale. Participants were then provided access to the smartphone app. Intervention 
content was delivered through a series of app-based video modules that were supplemented 
with a brief (15 minute) weekly health coaching session delivered through instant messaging. 
Each of the eight intervention weeks were conducted through the app and included viewing one 
or two short video modules, completing two daily check-in and activity surveys. In addition, 

 
participants had access to a Skills Library which contained a brief summary of each of the skills 
learned throughout the program.  
 
Control (CTL). Those in the CTL condition completed a single videoconferencing 
session with the health coach which consisted of a brief review of the participant’s pain and 
treatment history, psychoeducation about the interactive effects of pain and alcohol, discussion of 
resources available for pain and alcohol use, and the option to review information regarding 
available local and web-based behavioral health and wellness resources to address pain and 
alcohol use. These procedures are consistent with a treatment-as-usual-strategy to address 
these conditions in the clinic setting with available resources. 
 
Training, supervision and fidelity assessment. The health coaches were advanced level 
PhD clinical psychology students who were trained for content related to both conditions. 
Supervision was provided biweekly and involved individual discussion of ongoing cases. 
Intervention fidelity assessment was conducted through a checklist of session components 
(specific to condition) conducted by research assistants based on audio-recordings and instant 
messaging transcripts.  
Procedures 
 
Participants were screened by phone and, if eligible, scheduled for an initial visit 
conducted through a videoconferencing platform.  During the initial visit, participants were 
consented, completed a 50-minute baseline assessment, and were then randomized to the 
Control or Intervention condition. Participants then met with a study health coach for 
approximately 20 minutes through the videoconferencing platform.  Those randomized to 
smartphone intervention program concluded the initial videoconferencing visit by downloading 
the study smartphone application and learning the procedures for using the app.  The post-
intervention and primary follow-up assessments were conducted 8 and 16-weeks following 
baseline respectively by a research assistant who was blind to study condition. All assessments 
were conducted using a videoconferencing interviewing assessment method supplemented with 

 
on-screen displayed measures. Study data were collected and managed using REDCap 
electronic data capture tools (Harris et al., 2009).   Participants were compensated for their time 
and effort related to assessments and paid $50 for each assessment session.   
 
Participants in the smartphone intervention condition, completed 8-weekly video-
modules to learn new skills through the app and then completed two daily surveys to practice 
skills and evaluate outcomes over the subsequent week. Brief (approximately 15 minute) weekly 
health coaching sessions conducted through text messaging were scheduled to reinforce 
learning, identify barriers, and support program engagement.  Participants were provided with 
technology support via a “troubleshooting” form designed for the program and the study 
research assistant. Participants were reminded via text message the day before and the day of 
each weekly instant messaging health coaching session.   
 
 
 

 
STATISTICAL ANALYSES 
 
The goals of this study were to provide information about the feasibility and acceptability 
of the intervention and preliminary information about the utility of this approach for reducing pain 
and heavy drinking (primary outcomes).  Descriptive analyses provided information about 
intervention engagement, usability, and satisfaction while effect size estimates were computed 
to provide preliminary information about intervention efficacy.   
Feasibility of methods and procedures were evaluated with descriptive data on the 
percent of patients screened, percent of eligible patients enrolled, and percent of patients who 
completed assessments. For those in the Intervention condition, adherence rates for the percent 
of modules completed and the percent of coaching sessions attended were assessed. Patient 
satisfaction with the intervention and treatment adherence, mean and median treatment 
satisfaction ratings were calculated based on measures described above.  
Analyses of intervention impact were based on the full sample of participants who 
completed baseline and were randomized to condition. Lost to follow-up primary and secondary 
outcomes was defined as missing the 16-week assessment. For the primary analyses (i.e., 
PEG, heavy drinking, weekly drinking), multiple imputation was used to address missing 
outcome data and the full randomized sample was included. Completer analyses were 
conducted as sensitivity analyses for the primary outcomes and for all remaining outcomes. We 
estimated effect sizes using f2 calculated from regression analyses, controlling for 
corresponding baseline values. For pain analyses, we also followed recommendations from the 
IMMPACT trial (Turk et al., 2008), and examined the percent of participants who exhibited 
moderate clinical improvement based on reductions of 30% and substantial clinical 
improvement based on 50% reduction in PEG scores. 
Because the primary alcohol outcomes (i.e., number of heavy drinking episodes, number 
of drinks per week) were skewed, transformations to drinking data were required to provide an 
effect size estimate to parallel pain outcomes (i.e., f2).  To reduce the effects of extreme values, 

 
one drinking quantity outcome greater than 3 SD was recoded to one greater than the next 
largest value (Tabachnick and Fidell, 2013).  Alcohol outcomes were square root transformed in 
each analysis.  Due to sex differences in consumption, analyses with alcohol outcomes were 
conducted with sex at birth as a covariate along with the corresponding baseline alcohol 
variable. Pooled estimates from multiple imputations were used for each of these primary 
outcomes.   
 
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