Using Mobile-based Contingency Management to Promote Daily Self-monitoring of Pain Severity and Prescription Opioid Use in a Primary Care Sample of Chronic Pain Patients
Phase: NA
Conditions: Pain, Chronic
Sponsor: Virginia Commonwealth University

 
 
Title: Mobile-Based Contingency Management to Promote Daily Self-monitoring in Primary Care Patients 
 
NCT #: NCT03962491 
 
Document date: December 10, 2020 
 
Document Type: Protocol and SAP 
 
 
 

 
 
 
 
 
Mobile-Based Contingency Management to Promote Daily Self-Monitoring of Pain Severity and 
Related Measures in an Online Sample of Individuals with Chronic Pain 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
by 
Kathryn M. Polak  
Master of Science, Clinical Psychology 
Virginia Commonwealth University, 2016 
 
 
Director: Dace S. Svikis, Ph.D. 
Professor, Department of Psychology 
Deputy Director, VCU Institute for Women’s Health 
 
 
 
 
 
 
Virginia Commonwealth University 
Richmond, Virginia 
 
 
 
 

                                                                                                                                                                                                        
 
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Introduction 
The opioid epidemic has spurred urgent and widespread legal, medical, and behavioral 
approaches to promote effective opioid prescribing.  Between 21-29% of chronic pain patients 
misuse prescription (Rx) opioids (Vowles et al., 2015).  Responsible opioid prescribing depends 
on accurate and early identification of misuse as well as comprehensive understanding of 
predictors of pain treatment seeking and successful pain management (Dowell et al., 2016).  One 
promising and practical pain management solution is remote self-monitoring, a state-of-the-art 
assessment tool shown to be superior to retrospective assessment (e.g., Heron & Smyth, 2010).  
Unfortunately, low rates of adherence have impeded the use of remote self-monitoring among 
chronic pain patients (e.g., Jamison et al., 2016), even when non-monetary rewards were 
included (Jamison et al., 2017).  One robust strategy for improving adherence is contingency 
management (CM).  While CM has been widely used in research, translation to clinical practice 
has been limited, due to practical barriers (e.g., costs) and counselor concerns (e.g., Polak et al., 
2020; Carroll, 2014).     
 
This Stage 1 behavioral therapies development project (Rounsaville et al., 2001) will 
pilot test a novel, fully automated CM app (DynamiCare Rewards) for promoting daily self-
monitoring of pain symptom severity and related variables (e.g., sleep, mood), as well as Rx 
opioid and alcohol use in a sample of chronic pain patients.  This study is the first to customize 
the DynamiCare Rewards app to target survey completion, followed by a pilot controlled trial, 
comparing participants randomized to receive CM for completing daily self-monitoring surveys 
(CM group) or receive only electronic daily reminders to complete the survey (control group) 
over a 28-day period.  Primary outcome measures include number of daily surveys completed 
and longest period of sustained adherence to survey completion.  The study tested the hypothesis 
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that CM group participants will complete more daily self-monitoring surveys and will have a 
longer sustained period of daily survey completion compared to control group participants.  
Secondarily, the study examined feasibility; acceptability; and accuracy of Rx opioid and alcohol 
use reporting.    
This dissertation will provide benchmark data on the efficacy and feasibility of CM to 
promote self-monitoring of pain severity, related factors, and Rx opioid use.  More 
comprehensive information about pain experience and Rx opioid use has the potential to help 
clinicians provide better care and make better opioid prescribing decisions.  Additionally, 
findings will inform future research on early identification, prevention, and intervention for 
Opioid Use Disorders.   
 
 
 
 
 
 
 
 
 
 
 
 
 

                                                                                                                                                                                                        
 
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Statement of Problem and Aims 
Problems and Clinical Relevance  
Prescription (Rx) opioid misuse is a significant public health problem and the CDC has 
declared an opioid epidemic (Dowell et al., 2016). Chronic pain patients, often prescribed 
opioids for pain management, represent a particularly vulnerable population (e.g., Boscarino et 
al., 2011). Responsible opioid prescribing depends on effective identification of misuse and 
comprehensive understanding of pain-related variables (Dowell et al., 2016; Tong et al., 2019). 
Self-report tracking via smartphone apps is a promising solution, but difficulties with adherence 
have been found to impede the use of remote self-monitoring among chronic pain patients (e.g., 
Jamison et al., 2016), even with the inclusion of non-monetary rewards (Jamison et al., 2017). 
One robust strategy for improving adherence is contingency management (CM). While CM has 
been widely used in research, the translation to clinical practice has met with resistance due, in 
large part, to practical barriers (e.g., Carroll, 2014).   
As a Stage 1 behavioral therapies development project (Rounsaville et al., 2001), the goal 
of this dissertation was to examine the efficacy and feasibility of CM, delivered using a novel, 
fully automated CM app (DynamiCare Rewards), to promote daily self-monitoring of pain 
symptom severity and related variables (e.g., mood, sleep), as well as quantity and frequency of 
Rx opioid and alcohol use in a sample of chronic pain patients. The target behavior was 
objectively defined as completing daily self-monitoring surveys via the app within a 12-hour 
window (8am-8pm) for which those randomized to CM earned incentives.    
The DynamiCare Rewards app was customized for the study, followed by RCT data 
collection. Participants completed baseline assessment, followed by random assignment to either 
the experimental (CM) or control (C) group. All participants then downloaded the app onto their 

                                                                                                                                                                                                        
 
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smartphone and were provided with instruction in its use. Based on the work of Petry et al. 
(2005a) and Olmstead and Petry (2009), the CM group received reinforcement escalating with 
continuous performance of the target behavior while the C group was asked to complete the 
survey, but did not receive incentives.  Both groups received reminders to complete the daily 
survey.  Follow-up assessments (including behavioral and psychological measures) occurred at 
intervention completion and both CM and C group members were compensated for their time 
and effort. 
Aims 
The specific aims of this Phase 1 therapy development project are to:  
Aim 1: Compare number of completed daily self-monitoring surveys in CM and C groups. One 
hypothesis was tested: 
Hypothesis 1: CM group participants will complete more daily self-monitoring surveys 
compared to control group participants. 
Aim 2: Compare longest sustained period of daily survey completion in CM and C groups. One 
hypothesis was tested: 
Hypothesis 1: CM group participants will have a longer sustained period of daily survey 
completion compared to control group participants.   
Aim 3: Examine agreement between daily survey and follow-up visit reports of alcohol and Rx 
opioid use in CM and C groups. 
Aim 4: Examine feasibility and acceptability of CM app implementation targeting self-
monitoring of pain severity, related factors, and use of Rx opioids and alcohol.  
Aim 5: Estimate effect-size to be used to perform power analyses and sample size calculations as 
part of the design of a larger RCT.  
 

                                                                                                                                                                                                        
 
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Review of the Literature 
Opioid Epidemic 
Prescription (Rx) opioid misuse is a significant public health concern and there is 
currently an epidemic of opioid overdose (CDC, 2014) (see Table 1 for definitions of relevant 
concepts).  Overdose deaths from Rx opioids have almost quadrupled since 1999, paralleled by a 
similar increase in emergency department visits, falls and fractures, and sales of Rx opioids 
(CDC, 2011; SAMHSA, 2016; WONDER, 2020).  In 2019, almost 50,000 people in the U.S. 
died as a result of an opioid-involved overdose (CDC/NCHS, 2019), representing a 4.6% 
increase from 2018 (SAMHSA, 2020). The total economic burden of the opioid epidemic in the 
U.S. has been estimated at $631 billion from 2015-2018 (AHA, 2019).  
The landscape of the opioid epidemic is complicated and changing over time. Findings 
from the 2019 National Survey on Drug Use and Health found that 10.1 million people in the 
U.S. reported past year opioid misuse (3.7% of the total population) (SAMHSA, 2020). From 
2018 to 2019, Rx opioid misuse rates declined for each type of Rx opioid except fentanyl, which 
appears to be the primary contributor to the increases in opioid-involved overdoses (SAMHSA, 
2020). Rx opioid misuse (9.7 million), Opioid Use Disorder involving Rx opioids (1.4 million), 
and opioid misuse initiation (1.6 million) remained unchanged (SAMHSA, 2020). While heroin 
initiation (50,000) significantly declined by 57%, heroin use (745,000) and Heroin Use Disorder 
(438,000) remain unchanged (SAMHSA, 2020). Additionally, there has been an increase in the 
use of methamphetamines in combination with opioids (O’Donnell et al., 2020). 
The COVID-19 pandemic appears to be exacerbating the opioid epidemic. Over 40 U.S. 
states have reported increases in opioid-related mortality, mainly attributable to illicitly 
manufactured fentanyl and fentanyl analogs (AMA, 2021). Wainwright et al. (2020) compared 

                                                                                                                                                                                                        
 
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urine drug screen results ordered by health care professionals nationwide four months before and 
after the COVID-19 national emergency declaration and found increases in fentanyl (3.80% to 
7.32%), heroin (1.29% to 2.09%), methamphetamine (5.89% to 8.16%), and cocaine (3.59% to 
4.76%).  
 
Table 1  
Common Definitions of Relevant Concepts 
Concept 
Definition 
Opioid misuse 
Use of any kind of opioids (prescription or illicit), including heroin and 
a variety of pain-relieving medications (e.g., oxycodone, morphine, and 
codeine) in a way other than how they were prescribed. 
Prescription (Rx) 
opioid misuse 
National Survey on Drug Use and Health (NSDUH) defines it as use “in 
any way that a doctor did not direct you to use them," including 
(1) taking someone else’s prescription; (2) taking one’s own 
prescription more frequently, at a higher dosage, or for longer than 
prescribed; (3) taking the prescription in any other way not directed by a 
doctor; or (4) getting the same prescription from more than one doctor 
(SAMHSA, 2016). 
Opioid Use 
Disorder (OUD) 
A type of DSM-5 Substance Use Disorder (SUD); DSM-IV categories 
of substance abuse and substance dependence were combined in favor 
of a broader conceptualization of SUDs on a continuum of severity, 
ranging from mild to severe (APA, 2013). 
Aberrant drug-
related behavior 
(AB) 
Any behavior outside of the boundaries of the agreed-on treatment plan 
between a doctor and patient (Gourlay & Heit, 2008). 
Prevention 
Interventions intended to prevent the development of a substance use 
problem, such as prescription medication misuse (SAMHSA, 2017).   
Early intervention 
While there is no standard definition, early intervention generally refers 
to the middle ground between prevention and treatment for SUDs 
(SAMHSA, 2017).   

                                                                                                                                                                                                        
 
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Tolerance 
A state of physiologic adaptation in which increased doses of a drug are 
required to produce the same effects over time (Savage et al., 2003).  
Physical 
dependence 
A state of physiologic adaptation that is manifested by a drug class 
specific withdrawal syndrome that can be produced by abrupt cessation, 
rapid dose reduction, decreasing blood level of the drug, and/or 
administration of an antagonist (Savage et al., 2003). 
Long-term opioid 
therapy (LTOT) 
Prescription use of opioid medications for an extended period of time, 
generally considered to be >1 year (e.g., Chou et al., 2015). 
 
Chronic Pain Epidemic 
In addition to opioids, a twin “epidemic” facing providers is chronic pain and the 
challenge of managing it safely.  Chronic pain, generally defined as pain lasting at least 3 months 
or past the normal injury healing time (IASP, 1986), interferes with sleep, employment, social 
functioning, and activities of daily living. It is the most significant contributor to disability 
globally (Rice et al, 2015). As a result, chronic pain imposes the greatest economic burden of all 
health conditions (Phillips, 2006), with an annual cost of $560-635 billion in direct medical 
expenses and lost productivity (Institute of Medicine, 2011).  
Between 11% and 40% of the US population report some level of chronic pain, with 
millions suffering from daily, severe, costly, and disabling pain (e.g., Carr, 2016; Johannes et al., 
2010; Nahin, 2015).  Based on the 2016 National Health Interview Survey data, 20.4% of U.S. 
adults endorsed chronic pain, with 8.0% reporting high-impact chronic pain (i.e., chronic pain 
that frequently limits life or work activities) (Dahlhamer et al., 2018). The following groups had 
higher rates of both chronic pain and high-impact chronic pain: females, older adults, previously 
employed but currently unemployed individuals, those living in poverty, individuals with public 
health insurance, and those living in rural areas (Dahlhamer et al., 2018). 

                                                                                                                                                                                                        
 
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Types of chronic pain vary widely, with definitions and categories often insufficient or 
inconsistently used (IASP, 1986).  Chronic pain encompasses a wide range of conditions, with 
pain most frequently variably categorized according to perceived location (e.g., headache), 
etiology (e.g., cancer pain), or the primarily impacted anatomical system (e.g., neuropathic 
pain).  However, some pain categories do not adhere to these classification principles (e.g., 
fibromyalgia; Rolf-Detlef Treede et al., 2015).   
Prescription Opioids  
Chronic pain patients represent a population particularly vulnerable to opioid misuse.  
About 21-29% of chronic pain patients misuse Rx opioids (Vowles et al., 2015). Additionally, 
more than one-third meet criteria for a lifetime Opioid Use Disorder (Boscarino et al., 2011).  
The prescribing of opioids for chronic pain has played a significant role in the opioid 
epidemic. Prescribers have traditionally been the source of most misused Rx opioids (SAMHSA, 
2013) and the majority of individuals with Rx opioid dependence report being initially exposed 
to Rx opioids by a physician (Back et al., 2010).  Between 2007 and 2012, the rate of opioid 
prescribing progressively increased among providers managing pain (increased 7.3%; Levy et 
al., 2015), with about one-fifth of pain patients prescribed opioids in outpatient medical settings 
(Daubresse et al., 2013).  In 2012, 259 million opioid prescriptions were written, enough for 
every US adult to have a bottle of pills (Paulozzi et al., 2012).  Despite a dose-dependent risk for 
negative consequences and insufficient evidence of the effectiveness of long-term opioid therapy 
(LTOT), discontinuation was historically uncommon (Chou et al., 2015; Martin et al., 2011; 
Vanderlip et al., 2014).  In fact, Larochelle et al. (2016) found that nearly all (91%) patients who 
experienced a nonfatal opioid overdose on LTOT continued to receive Rx opioids after the 
overdose.  

                                                                                                                                                                                                        
 
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The use of prescription opioids has been linked to other potential harms. Having a 
lifetime history of at least one Rx for opioids increases the risk for having an Opioid Use 
Disorder (OUD; Edlund et al., 2014; Zedler et al., 2014; Bohnert et al., 2011).  Higher dose of 
Rx opioids has been linked with risk for overdose (Bohnert et al., 2011; Gomes et al., 2011).  
Furthermore, misuse of Rx opioids is a significant risk factor for future or concurrent use of 
heroin (Cicero et al., 2014), with heroin initiation being 19 times more likely among Rx opioid 
misusers compared to non-misusers (Muhuri et al., 2013).   
Effective Opioid Prescribing 
Despite its traditionally widespread use, the evidence supporting the effectiveness of 
long-term opioid use for chronic pain management is limited. Busse et al. (2018) conducted a 
meta-analysis of 96 randomized clinical trials of patients with chronic noncancer pain and found 
that when compared with placebo, opioids were linked with significantly less pain and improved 
physical functioning, however, the magnitude was small. They also found that opioids and 
nonopioid alternatives may have similar benefits for pain and functioning, but these studies were 
of low to moderate quality (Busse et al., 2018). When paired with the risks associated with Rx 
opioid use, these findings highlight the need for providers to be judicious in the prescribing of 
opioids for pain management.  
Effective opioid prescribing is highly individualized and dependent upon identification of 
misuse and comprehensive understanding of clinically-relevant variables, such as pain severity, 
quality of life, function, mental health, and other substance use (e.g., alcohol use; CDC, 2016). 
However, opioid prescribing often relies upon generalizations, which do not adequately capture 
patients’ experience (e.g., Giske et al., 2010).   
 

                                                                                                                                                                                                        
 
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Identification of Prescription Opioid Misuse 
Identification and measurement of Rx opioid misuse is problematic.  There is no current 
gold standard for Rx opioid risk assessment and identification (Smith et al., 2015).  Disparate 
definitions of Rx opioid misuse exist across the literature (Cochran et al., 2015).  Little is known 
about risk factors for Rx opioid misuse and there have been no studies to date on protective 
factors.  Using biological measures to identify potential Rx opioid misuse is more difficult 
among chronic pain patients prescribed opioids as they would be expected to test positive for 
opioids (e.g., on a urine drug screen).  Furthermore, inconsistencies exist in measurement and 
categorization of Rx opioid use.  For instance, a recent review by Frank et al. (2017) examining 
outcomes in dose reduction or discontinuation of LTOT found measurement of opioid dose 
reduction is inconsistent, with no widely accepted standard for meaningful dose reduction.  
Problems associated with measurement of Rx opioid misuse have broad implications.  
Intervention for Rx opioid misuse and effective and responsible opioid prescribing depend upon 
provider ability to identify misuse (Dowell et al., 2016).  Providers, however, have few tools to 
determine which patients may abuse Rx medication (Rosenblatt et al., 2015; Tong et al., 2019).  
Despite recognizing misuse as a problem in their patients, providers report feeling unprepared to 
screen for and address Rx opioid misuse (e.g., Ceasar et al., 2016; Miller et al., 2001). Primary 
care providers also report a lack of confidence in prescribing opioids safely (Keller et al., 2012), 
and predicting (Payne et al., 2011) and discussing (Hagemeier et al., 2013) misuse with their 
patients.  Additionally, practices intended to decrease risk for misuse (e.g., opioid treatment 
agreements) are inconsistently used (Green et al., 2012; Ringwalt et al., 2015; Pergolizzi et al., 
2010; Starrels et al., 2014).  As a result, misuse often goes undetected, potentially leading to 
increased severity and consequences (Smith et al., 2015).  Not surprisingly, high-risk opioid 

                                                                                                                                                                                                        
 
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prescribing practices have been identified as contributing to the opioid epidemic (e.g., Bohnert et 
al., 2011; Liu et al., 2013).   
Role of Non-Pharmacological Interventions 
Treatment approaches that balance chronic pain management and mitigation of Rx opioid 
misuse are sorely needed.  Pharmacological interventions, such as abuse-deterrent formulations, 
play an important and well-established role in Rx opioid risk mitigation (e.g., Coplan et al., 
2016).  Abuse-deterrent formulations create barriers to abuse by making crushing or chewing 
medication difficult and/or including an opioid antagonist to block opioid effects (e.g., euphoria) 
(Cicero & Ellis, 2015).  However, such interventions are not a comprehensive solution to the 
problem of Rx opioid misuse as abuse-deterrent formulations are not abuse-proof (Becker & 
Fiellin, 2017).  In contrast, whereas clinical guidelines for chronic pain management generally 
include recommendations for non-pharmacological interventions as important components of Rx 
opioid risk mitigation (Dowell et al., 2016), few studies have empirically tested such 
interventions. 
Self-Monitoring 
Self-monitoring is a core element of self-regulation and self-management (e.g., Bandura, 
1991), and is well-established as an integral component of effective chronic pain management 
(Adams et al., 2017). Pain severity is typically assessed at one time point during medical visits, 
which has been shown to be less reliable and more inaccurate as a result of recall bias compared 
to more frequent reporting (Coughlin, 1990; Adams et al., 2017; Giske et al., 2010). 
Additionally, such assessments are not sensitive to the variable nature of pain severity over time 
(Jensen & McFarland, 1993; Adams et al., 2017).  

                                                                                                                                                                                                        
 
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While self-monitoring as a stand-alone intervention has not received much research 
attention, self-monitoring as a component of other effective interventions (Daniëls et al., 2021) is 
a burgeoning area of research. Self-management interventions have been shown to be effective in 
decreasing pain and improving physical functioning among individuals with chronic widespread 
pain (Geraghty et al., 2021). Consistent utilization of self-management strategies is predictive of 
improved outcomes (pain, disability, and depressive symptoms) among individuals with chronic 
pain, even after controlling for baseline core pain experience factors (e.g., pain catastrophizing 
and self-efficacy) (Nicholas et al., 2012). Additionally, the integration of ecological momentary 
assessment (EMA) and ecological momentary interventions (EMIs) provides opportunities for 
targeted treatment (Shaefer et al., 2020). For example, one promising approach for the treatment 
of eating disorders is EMIs that utilize EMA to identify high risk moments then trigger delivery 
of interventions (Shaefer et al., 2020; Juarascio et al., 2018).  
Remote Self-Monitoring 
In the US, over two-thirds of individuals own smartphones (Pew Research Center, 2014).  
There is a plethora of apps used to track health data and assist in management of chronic 
diseases, with multiple apps specifically developed for pain patients (Hundert et al., 2014; 
Stinson et al., 2013; Reynoldson et al., 2014; Vega et al., 2014).  Health apps provide an ideal 
platform for self-monitoring.   
There is substantial evidence that electronic monitoring via apps is significantly better 
than paper-and-pencil diaries with respect to compliance, user-friendliness, patient satisfaction, 
and test reliability and validity (e.g., Jamison et al., 2002; Hufford et al., 2002).  Momentary 
electronic assessment methods, including current symptom ratings, are considered to be state-of-
the-art measures for the evaluation of pain and other health-related outcomes and have been 

                                                                                                                                                                                                        
 
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shown to be superior to retrospective assessments (e.g., Heron & Smyth, 2010).  Thus, remote 
self-monitoring is a potentially promising solution to improving tracking of pain severity, related 
factors, and Rx opioid use, with effective use of such methods leading to more informed 
practitioners.   
Self-Monitoring Adherence  
Low rates of adherence have impeded the use of health apps and resulted in reduced 
utility across a range of behaviors, such as weight loss (e.g., Laing et al., 2014) and sleep 
disturbance (e.g., Huberty et al., 2021). Poor adherence has also been a major barrier to the more 
frequent self-monitoring that is essential for effective pain management (Bolger et al., 2003; 
Adams et al., 2017), including the use of smartphone apps promoting self-monitoring among 
chronic pain patients (e.g., Jamison et al., 2016), even when non-monetary rewards were 
included (i.e., supportive text messages; Jamison et al., 2017). Investigation into strategies to 
promote intervention adherence are thus needed. 
Contingency Management 
A robust strategy for promoting and maintaining behavior change is CM, systematic 
reinforcement of target behaviors based on principals of operant conditioning (e.g., Higgins et 
al., 1994a; Higgins et al., 1994b; Svikis et al., 1997; Kirby et al., 1998).  CM has long been used 
in Substance Use Disorder (SUD) treatment research and is one of the most effective strategies 
for promoting drug abstinence (Higgins et al., 1994a; Silverman et al., 1996; Polak et al., 2020; 
Benishek et al., 2014; Prendergast et al., 2006).  It does so by activating the brain’s reward and 
inhibitory systems through both positive and negative reinforcement using immediate, concrete 
incentives.  CM involves reinforcing a specific target behavior with tangible rewards (e.g., cash 
or vouchers).  CM has been used for a range of target behaviors, ranging from take-home doses 

                                                                                                                                                                                                        
 
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in methadone programs (Iguchi et al., 1988; Kidorf et al., 1994) to negative urine drug screens 
(Stitzer et al., 1986; Jones et al., 2001; Peirce et al., 2006), to attendance of counseling (Svikis et 
al., 1997; Svikis et al., 2007) or job-skills training (Wong & Silverman, 2007; Silverman et al., 
2001) sessions. 
Use of CM for Health Behavior Targets 
More recently, use of CM to promote health-related behavior change has received 
considerable attention (e.g., Higgins et al., 2012; Herrmann et al., 2017; Stitzer et al., 2020).  CM 
has been found effective at promoting physical activity (Kurti & Dallery, 2013; Pope & Harvey-
Berino, 2013) and medication adherence (Rigsby et al., 2000; Sorensen et al., 2007).  Despite its 
effectiveness, CM is underutilized (Herbeck et al., 2008).  Practical barriers to adoption include 
lack of funds, lack of training for staff, and difficulty in managing the rewards (Carroll, 2014; 
Polak et al., 2020). 
CM and Cost Effectiveness 
One barrier to use of CM has been that the monetary costs of incentives can be 
prohibitive.  Petry et al. (2000) developed and empirically tested a method for making CM more 
cost effective. It was an escalating variable-ratio schedule of reinforcement such that costlier 
rewards are provided less frequently. Using a lottery-based reward system, participants who 
continuously maintain drug abstinence earn the right to draw increasing numbers of tokens from 
a “fishbowl” containing hundreds of tokens.  With this prize-based approach, the monetary value 
of incentives remains more modest, thereby increasing the potential for translation to “real life” 
clinical settings.  Multiple studies have highlighted the potential of CM protocols that use 
variable-ratio reinforcement schedules as a cost-effective CM strategy (e.g., Petry et al., 2005b; 
Olmstead & Petry, 2009; Peirce et al., 2006).  

                                                                                                                                                                                                        
 
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Remote Delivery of CM 
An effective CM intervention requires frequent and objective monitoring of the target 
behavior, which has traditionally been cumbersome on staff and patients and can limit the range 
over which health services can be delivered (Kurti et al., 2016). The use of technology in 
remotely monitoring behaviors and delivering incentives eliminates the practical barriers 
associated with in-person monitoring (Kurti et al., 2016; Dallery et al., 2019). This emerging CM 
intervention strategy has been used for studies targeting substance abuse (e.g., Alessi & Petry, 
2013; Meredith et al., 2011; Oluwoye et al., 2020), weight loss (e.g., Unick et al., 2015), as well 
as medication adherence (Defulio et al., 2021a) and home-based health monitoring (Kurti et al., 
2016). While they provide ample evidence that a mobile-based CM procedure can work in 
practice, all still require human involvement.  
DynamiCare Rewards App 
DynamiCare is an iOS and Android app that provides several highly innovative features 
that overcome barriers to CM adoption, including fully automating CM methodology 
(monitoring/incentivizing of target behavior and dispersal of rewards). In addition to Virginia 
Commonwealth University, this app is currently being used at multiple research universities, 
such as Johns Hopkins University, Massachusetts Institute of Technology, University of 
Chicago, Western Michigan University, and University of Vermont. DynamiCare Health, Inc. 
has been awarded several grants and prizes for the development and implementation of the 
DynamiCare Rewards app, including Small Business Innovation Research (SBIR) Phase I and 
Phase II grants from NIH – NIAAA. To date, use of this app has focused exclusively on SUDs.  
Recent trials using the DynamiCare Rewards app have demonstrated its efficacy and 
utility in delivering CM. Kurti et al. (2020) conducted a pilot study of the DynamiCare Rewards 

                                                                                                                                                                                                        
 
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app targeting cigarette smoking in pregnant women. They demonstrated feasibility and found 
that those in the CM group had higher quit rates compared to controls (Kurti et al., 2020). 
DeFulio et al. (2021b) found CM delivered via the DynamiCare Rewards app significantly 
increased clinic appointment attendance and drug abstinence compared to matched controls 
among patients with Opioid Use Disorder. They also concluded that the DynamiCare Rewards 
app was usable, acceptable, and similarly effective to in-person CM (DeFulio et al., 2021b). 
Incentives for Self-Reporting of Prescription Opioid Use 
Finan et al. (2017) recently investigated the variability of Rx opioid use and associations 
with pain and related factors in patients with sickle cell disease who received incentives for 
completing a daily electronic diary (N=45). They found that greater pain and pain catastrophizing 
were associated with greater use of short-acting opioids, and negative affect was associated with 
greater use of long-acting opioids. Adherence to self-monitoring was problematic in their study, 
with one-fourth (25%) of the sample excluded for having <25% of self-reports, with an 
additional 25% of the remaining sample having missing data. These findings highlight the value 
of remote self-monitoring of pain severity, related factors, and Rx opioid use for providing 
information that aids effective opioid prescribing. Results also demonstrate the need to better 
understand how to improve adherence to self-monitoring of these variables.  
Summary 
Adherence is a problem in many fields of behavioral medicine and while CM has had the 
biggest impact, practical barriers have limited implementation in “real life” care. The present 
study sought to bridge the gap with an RCT of the DynamiCare Rewards app for promoting daily 
self-monitoring of pain severity, related factors, and Rx opioid and alcohol use in a sample of 
individuals with chronic pain. Comprehensive information on pain severity and medication use 

                                                                                                                                                                                                        
 
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has the potential to help physicians make better opioid prescribing decisions, addressing the 
opioid epidemic and improving public health. 
Methods 
Participants 
Participants will be individuals seeking to participate in research studies through 
ResearchMatch.org. Individuals will be eligible to participate in the study if they meet the 
following criteria: 1) at least 18 years of age; 2) own a study-compatible smartphone (iPhone or 
Android device); 3) report non-cancer related chronic pain of at least 3 months’ duration; 4) able 
to provide informed consent for study participation; 5) report having chronic pain as part of their 
ResearchMatch.org profile; and 6) prescribed >1 opioid medication(s) for pain management in 
their lifetime. Individuals will be excluded from study participation if they meet any of the 
following criteria: 1) currently pregnant; 2) presenting with language barriers, cognitive 
impairment, or serious medical or psychiatric illness that in the opinion of the Investigator would 
preclude them from providing informed consent or participating in the study; and 3) visual 
impairment or motor impairment that would interfere with use of a smartphone.  
Study Procedures  
Recruitment 
Participants will be recruited through ResearchMatch.Org. ResearchMatch.Org is an 
online platform that allows researchers to recruit from a pool of people who have signed up to 
receive emails about potential research study participation opportunities. A recruitment email 
will be distributed one to two times per week to 20 to 400 unique ResearchMatch.org 
participants each time from this potential research participation pool who listed chronic pain 
conditions as part of their ResearchMatch.org profile. The recruitment email will include a 

                                                                                                                                                                                                        
 
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description of the study and a link to the REDCap screening survey imbedded in a button labeled 
"Yes, I'm interested." 
Screening 
Individuals who indicate that they are interested in potentially participating will first be 
brought to the REDCap Screener Introduction. At this point, they will be asked if they want to be 
screened for study eligibility. Those who screen eligible for the study and are interested in study 
participation will be asked for contact information. No further data will be collected from those 
who screen ineligible or state they are not interested in study enrollment. The screening process 
will take approximately 5-10 minutes.  
Informed Consent 
Individuals who meet eligibility criteria, indicate that they want to participate in the 
study, and provide their contact information will be emailed a link to the REDCap study 
informed consent form within one business day of completing the screener. The VCU IRB 
granted a waiver for signed informed consent. This consent form describes the purpose of the 
study, involvement in the study (e.g., randomization to two study groups, completion of daily 
surveys for 28 days, baseline and follow-up assessments, compensation, etc.); the voluntary 
nature of the study; limits of confidentiality; as well as risks, benefits, and costs of participation. 
Additionally, participants will be told that they could stop participation at any point without 
negative repercussions. Participants select one of the following options: “Yes, I understand this 
and want to participate in the PROMOTING MONITORING: A PILOT TEST study” or “No, I 
do not want to participate in the study.” Those who provide consent to participate in the study 
will proceed to baseline assessment, followed by randomization to either the contingency 
management (CM) or control (Co) group.  

                                                                                                                                                                                                        
 
20 
 
Baseline Assessment 
Following informed consent, participants will complete a series of computer-
administered questions via REDCap (demographic information; medical and mental health 
history; The Brief Pain Inventory; Pain Self-Efficacy Questionnaire; Pain Catastrophizing Scale; 
Hospital Anxiety and Depression Scale; Pittsburgh Sleep Quality Index; and 28-day Timeline 
Followback). Baseline assessment will take approximately 30-45 minutes to complete. If 
participants do not complete the baseline survey within two days of completing the screener, 
they will be sent a reminder email to complete the survey. If participants do not complete the 
baseline survey within three days post screening, they will be called. At the end of their baseline 
survey, participants will be asked their preference for a 5-10-minute telephone or Zoom call to 
finish their baseline visit. They will then be informed that within the next business day they 
would receive a call or email from study staff to set up their Zoom or phone appointment to 
complete the baseline visit. Participants will be called daily for one week following baseline 
survey completion until they are reached to complete the baseline call. Participants who can not 
be reached by telephone or Zoom within one week of completing the baseline survey will not be 
enrolled or randomized into the study.  
Baseline Visit Call 
During the 5-10-minute Zoom or telephone call RAs will review the following with all 
study participants: verify study eligibility; complete randomization to CM or Co groups; set up 
the DynamiCare Rewards app on the participant’s smartphone; and remind them that they would 
receive daily text message reminders to complete the daily survey. RAs also will encourage 
participants to set an alarm or some other reminder of their own. In addition, for participants 
randomized to the CM condition, RAs will review CM procedures, including their debit card, 

                                                                                                                                                                                                        
 
21 
 
and they explain that they will receive an initial draw and reward for setting up the app. 
Participants will also be offered handouts summarizing the information discussed in the call.  
Randomization. Participants who complete the baseline visit call and are verified as 
eligible for the study will be randomly assigned to either the CM (n = 46) or Co (n = 35) 
condition. To determine group assignment, study staff will use an Excel spreadsheet with 
randomization groups determined by a random numbers app and prepared by Dr. Svikis in 
advance of study launch. Each row with a randomization group will be numbered sequentially 
and correspond to a participant’s study ID number. Study staff will not see the randomization 
group until they indicate that the participant is enrolled in the study and ready to be randomized. 
No stratification variables are proposed for this Stage I pilot study (see Rounsaville et al., 2001).  
DynamiCare Rewards App. DynamiCare is an iOS and Android app which fully 
automates CM methodology. The app will be customized for the present study, incorporating the 
daily self-monitoring survey and incentives plan. After randomization, all participants will be 
added to the DynamiCare Analytics portal and received an email with the link to download the 
app on their smartphone. Once participants successfully downloaded the app, RAs instructed 
them in the use of the app.  
All Participants. Day 1 of the daily surveys will start the day after the app isdownloaded 
and the account is set up. Participants will be encouraged to complete the daily survey and pick a 
time of day to set a personal reminder. They will receive a text reminder around noon each day 
from a study smartphone. The daily survey data will automatically be uploaded to the 
DynamiCare HIPAA-compliant server. Participants’ DynamiCare Rewards accounts will be 
manually archived after they completed the 28-day survey period.   

                                                                                                                                                                                                        
 
22 
 
CM Group. Participants randomized to the CM group will have the chance to receive 
incentives for complying with the target behavior (completing daily self-monitoring surveys 
within a 12-hour window (8am-8pm) over a 28-day period. Daily self-monitoring surveys and 
the delivery of incentives were completed using the DynamiCare Rewards app. The escalating 
variable-ratio reinforcement schedule used for the study was modeled after the fishbowl method 
developed by Petry et al. (2005a) and Olmstead and Petry (2009).   
 
Behavioral incentives will be managed remotely via the app to facilitate extrinsic 
motivation for participant follow-through with self-monitoring. Participants will be able to draw 
from a fishbowl via the app to determine their monetary prize. Participants will be given an 
initial draw for downloading the app and completing training during the baseline call, which will 
be set to $8. When they meet the target behavior, participants will be awarded additional draws 
through the app. The number of draws they earn will increase by one for every day they 
completed the survey. The maximum number of draws they could earn over the course of the 28-
day period was 236. Failure to complete a daily self-monitoring survey, however, resulted in a 
reset to baseline (1 draw per completed daily self-monitoring survey) and 3 consecutive 
completed daily self-monitoring surveys will be required for a participant to return to the highest 
level achieved prior to reset. Additional engagement with the app will not result in additional 
monetary reinforcement.  
Incentives.  Specifically, reward amounts ranged from $0-50 in value. Half (50%) of 
incentives will be “good job” and not associated with a monetary reward. The app will be 
connected to reloadable debit cards (The Next Step debit card, provided by True Link Financial, 
Inc.), which will be activated and mailed to CM participants within one to two weeks of their 
baseline call.  

                                                                                                                                                                                                        
 
23 
 
Co Group. The Co group will be asked to download the DynamiCare Rewards app 
during the baseline visit call and to complete the same daily self-monitoring survey as the CM 
group, but will not be provided with incentives for completing the survey. They also will receive 
the same reminders to complete the daily survey as the CM group. The only difference between 
the CM and Co groups will be the receipt of incentives for the 28-day trial. 
Post-Daily Survey Period Follow Up   
At the end of the 28-day self-monitoring survey period, participants will be emailed a 
link to the REDCap follow-up survey (approximately 30-45 minutes), including The Brief Pain 
Inventory; Pain Self-Efficacy Questionnaire; Pain Catastrophizing Scale; Hospital Anxiety and 
Depression Scale; acceptability questions; Pittsburgh Sleep Quality Index; Timeline Followback 
(TLFB); and self-report validity and accuracy questions. If participants do not complete the 
survey within two days, they will be sent a reminder email. If participants do not complete the 
survey after three days, they will be called. Participants will be asked if they would like to be 
provided with a document summarizing their daily survey ratings in the follow-up survey. Once 
participants complete their participation in the study, we will remove their contact information 
from the study database to protect their privacy.  
Participant Compensation 
Participants will be compensated with a 20-dollar Amazon electronic gift card for 
completing the baseline visit and a 30-dollar Amazon electronic gift card for completing the 
follow-up survey. Electronic gift cards will be distributed via email within 1-2 weeks of 
completing their visit.  
Measures 

                                                                                                                                                                                                        
 
24 
 
Assessment measures were carefully selected, based on domains to be studied, 
psychometric properties of existing measures, previous research in this population, and personal 
experiences from preliminary studies with the target population. The battery will take 
approximately 30-45 minutes to complete. Screening, baseline, and follow-up data will be 
collected and managed using REDCap hosted at Virginia Commonwealth University. Table 3 
provides an overview of measures and the baseline and follow-up surveys can be found in 
Appendix B.  
Baseline Survey Only 
Demographic Information. Participants were asked about race, ethnicity, age, gender, 
marital status, employment status, highest grade completed in school, and living situation.  
Medical and Mental Health History. Participants were asked about the number of days 
they experienced medical problems in the past 30 days; previous and current mental health and 
medical conditions; and if they were currently prescribed opioid, benzodiazepine, and other types 
of pain medications in the last 28 days.  
28-Day Monitoring Period 
 
Daily Self-Monitoring Survey. Once daily, all participants were asked to complete a 
self-monitoring survey using the app, which was designed to take approximately 5 minutes to 
complete. Survey items were derived from validated measures and previously tested pain self-
monitoring apps/electronic diaries and include the following domains: pain experience; impact of 
pain on function; sleep; mood; pain catastrophizing; prescription medication use (opioids and 
sedatives); alcohol use; marijuana use, cannabidiol (CBD) use (Cleeland & Ryan, 1994; Jamison 
et al., 2016; Finan et al., 2017; Watson et al., 1988; McNair et al., 1992; Sullivan et al., 1995). 
See Appendix A for the complete daily self-monitoring survey.  

                                                                                                                                                                                                        
 
25 
 
Mean Daily Self-Monitoring Survey Completion Time. The app measured the time it 
took participants to complete the daily self-monitoring survey; all survey completion times were 
averaged.  
Baseline & Follow-Up Survey 
Brief Pain Inventory (BPI; Cleeland & Ryan, 1994). The BPI is a well-known measure 
of clinical pain and has demonstrated sufficient reliability and validity. This self-report 
questionnaire asks about pain history, severity, and its impact on functioning. Participants rate 
the intensity of pain at its worst from the past 24 hours, at its least from the past 24 hours, on 
average, and “right now” on a 0-10 scale. Participants also rate how much pain has interfered 
with various aspects of their life on a 0-10 scale.  
Pain Catastrophizing Scale (PCS; Sullivan et al., 1995). The PCS is a 13-item measure 
of catastrophizing, including rumination, magnification, and helplessness. Each item is rated on a 
0-4 scale. Item responses are summed to generate a total score; higher scores indicate increased 
pain catastrophizing. It has been found to have adequate reliability and validity (Osman et al., 
1997).   
Pain Self-Efficacy Questionnaire (PSEQ; Nicholas, 1989; Nicholas, 2007). The PSEQ 
is a 10-item measure of pain self-efficacy. Each item is rated on a 0-6 scale. Items are summed to 
generate a total score, with a greater total score indicating increased pain self-efficacy. The 
PSEQ has been shown to be reliable and valid (Gibson & Strong, 1996; Asghari & Nicholas, 
2001). 
Hospital Anxiety and Depression Scale (HADS; Zigmond & Snaith, 1983; Bjelland 
et al., 2002). The HADS is a widely used 14-item measure of past-week presence and severity of 
anxious and depressive symptoms. Response options range from 0-3. Two scores are summed 

                                                                                                                                                                                                        
 
26 
 
from the responses, a depression score and an anxiety score, with higher values indicating 
heightened experience of symptoms. The HADS has adequate reliability and validity, and an 
optimal balance between sensitivity and specificity.  
Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989). The PSQI is a reliable and 
valid measure of sleep quality and disturbances over the past month. The questionnaire contains 
19 items focusing on subjective sleep quality, sleep latency, sleep duration, habitual sleep 
efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. 
Follow-Up Survey Only 
TLFB (Sobell & Sobell, 1992). The TLFB is a widely-used, semi-structured interview 
that uses a calendar to retrospectively collect daily information about substance use. It has been 
shown to have good reliability and validity and is widely considered the “gold standard” of 
quantity and frequency substance use assessment. To accommodate the remote study procedures, 
the TLFB was adapted from interviewer to computer administered (via REDCap), which has 
been found to be reliable and valid (e.g., Martin-Willett et al., 2020). The TLFB was used to 
obtain detailed past 28-days frequency of opioid pain medication and alcohol use information.  
Acceptability. Participants were asked to answer questions about satisfaction, 
acceptability, and feasibility on a 0-10 scale based on those used in a previous RCT investigating 
an app developed for chronic pain patients (Jamison et al., 2017).  
Validity and Accuracy of Responses. All participants were asked how honest they were 
in completing the daily survey (response options: I was very honest, I was honest most of the 
time, I was honest some of the time, I was honest once in a while, I was not honest at all). CM 
participants were additionally asked how much the rewards made a difference in how accurately 

                                                                                                                                                                                                        
 
27 
 
they reported information in the daily survey (response options: Not at all, very little, little, 
somewhat, much, to a great extent, completely). 
 
Self-Report of Impact of Behavioral Incentives to Adherence. CM participants were 
asked how much the rewards made a difference in whether they completed the daily survey 
(response options: Not at all, very little, little, somewhat, much, to a great extent, completely). 
 
Table 3 
Overview of Study Measures  
Measure 
Baseline 
Survey 
28-Day Monitoring 
Period 
Follow-Up 
Survey 
Demographic information, medical/mental 
health history 
X 
 
 
BPI, PCS, PSEQ, HADS, PSQI 
X 
 
X 
Daily self-monitoring survey (via app), 
daily self-monitoring survey completion 
time 
 
X 
 
TLFB, acceptability survey, validity of 
responses 
 
 
X 
 
Data Analysis Plan 
Effect Size Estimation 
The major goal of this Stage I pilot RCT is to estimate the effect size of the primary 
outcome variables (Rounsaville et al., 2001). This will be done by using the means and variances 
of the CM and Co groups on the primary outcome variables. This estimated effect-size will then 
be used to perform power analyses and sample size calculations to be used in the design of a 
larger clinical trial.    

                                                                                                                                                                                                        
 
28 
 
Sample Size Justification 
As this is a Stage I pilot study and no preliminary data are available, a power analysis is 
not provided. Sample size was determined by anticipating a medium effect size (.05), 80% 
power, alpha level=.05 (Cohen, 1988). For two-sided t-tests, 32 participants/group are needed. 
This would allow us to detect an effect size of d=.711, which falls between medium, d=.05 and 
large, d=.8 effect sizes. Recruitment of 80 subjects with 80% retention was expected to achieve 
this effect size.  
Assessing Randomization Success 
Randomization should ensure that no differences are found at baseline between the two 
conditions. However, the CM and Co groups will compared on core baseline measures 
(demographics and medical and mental health history) using t-tests for continuous and chi-square 
analyses for categorical variables to ensure no differences occurred by chance on important 
measures. 
Outcome Measures 
As shown in Table 4, the primary outcome measures are the number of completed daily 
self-monitoring surveys and the longest period of sustained adherence to survey completion. It is 
hypothesized that those in the CM group will complete more daily self-monitoring surveys and 
have a longer sustained period of daily survey completion compared to controls. The number of 
completed daily surveys and duration of continuous daily survey completion will be compared 
between CM and Co groups using independent t-tests. 
Secondarily, descriptive statistics will be used to summarize CM participants’ self-report 
of the impact of behavioral incentives on adherence. Mean time to complete the daily surveys 
between CM and Co groups will be compared using an independent t-test. Pain experience and 

                                                                                                                                                                                                        
 
29 
 
related variables from baseline will be compared to follow up responses for the total sample 
using paired t-tests. The daily survey item responses will be summarized for the overall sample 
using descriptive statistics. Associations between daily survey and follow-up TFLB for alcohol 
and prescription opioid use data for the overall sample and each study group will be examined 
using Spearman’s correlations. Descriptive statistics will be used to summarize self-report 
validity and accuracy of responses. Feasibility and acceptability of CM app implementation will 
be examined by comparing follow-up acceptability survey ratings for each group using 
independent t-tests.  
 
Table 4   
 
Outcome Measures Overview 
Name 
Time Frame 
Brief Description 
Number of daily 
surveys completed 
28-day daily 
survey period 
 
This primary outcome is consistent with previous CM 
studies. 
Longest period of 
sustained adherence to 
daily survey 
completion 
28-day daily 
survey period 
Largest number of consecutive days wherein daily 
surveys were completed. This primary outcome is 
consistent with previous CM studies. 
Mean frequency of 
alcohol and 
prescription opioid use 
(days of use) 
28-day daily 
survey period 
to follow up 
Spearman’s correlations between daily survey and 
TLFB data for alcohol and prescription opioid 
frequency (days of use) were conducted for the entire 
sample, the CM group, and the Co group. 
Mean time to complete 
the daily surveys 
28-day daily 
survey period 
Daily survey completion time (the amount of time from 
daily survey start to finish). 

                                                                                                                                                                                                        
 
30 
 
Name 
Time Frame 
Brief Description 
Mean CM app 
feasibility and 
acceptability survey 
ratings 
Follow up 
CM app satisfaction, acceptability, and feasibility 
survey ratings (on a 0-10 scale; administered at follow-
up) based on those used in a previous RCT investigating 
an app developed for chronic pain patients (Jamison et 
al., 2017). 
 
Self-report validity and 
accuracy of responses 
Follow up 
Ratings of how honest participants were in completing 
the daily survey and how much the rewards made a 
difference in how accurately CM participants reported 
information in the daily survey.  
 
 
 
 
 
 
 
 
 
 
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Washington, W. D., Banna, K. M., Gibson, A. L. (2014). Preliminary efficacy of prize-based 
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Psychiatrica Scand, 37, 361–370. 
 

                                                                                                                                                                                                        
 
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Appendix A 
Daily Self-Monitoring Survey (via DynamiCare Rewards app) 
How were you yesterday? 
 
1. What was your average pain? (rated on a 0-10 scale; 0=no pain, 10=worst pain) 
 
2. How much did your pain interfere with your daily activities? (rated on a 0-10 scale; 
0=did not interfere, 10=completely interfered) 
 
3. Overall, how much have things changed? (rated on a 0-10 scale; -5=worse; 0=the same; 
5=better) 
 
4. How would you rate your sleep quality? (Very good (0) Fairly good (1) Fairly bad (2) 
Very bad (3)) 
 
5. How sad were you yesterday? (rated on a 0-10 scale; 0=not at all and 10=very much) 
 
6. How anxious were you yesterday? (rated on a 0-10 scale; 0=not at all and 10=very much) 
 
7. How irritable were you yesterday? (rated on a 0-10 scale; 0=not at all and 10=very much) 
 
8. Did you take any prescription medications yesterday? (Yes or No) 
 
9. [If yes to the above] Which prescription medications did you take? (check all that apply) 
o Prescription opioid pain reliever (for example: Percocet, Vicodin) 
o Prescription medication for anxiety or sleep (for example: Xanax, Ativan, or 
Klonopin) 
o Other prescription medication (free response)  
 
10. [For those checked above] How did you take the [type of medication]? 
o Took as prescribed 
o Took less than prescribed 
o Took more than prescribed 
o It was not prescribed for me  
 
11. How many 12-ounce beers containing alcohol did you have? (free response) 
 
12. How many 5-ounce glasses of wine did you have? (free response) 
 
13. How many shots of liquor did you have (straight or in a mixed drink)? (free response) 
 
14. Did you use marijuana? (Yes or No) 
 
15. Did you use cannabidiol (CBD)? (Yes or No) 

                                                                                                                                                                                                        
 
53 
 
Appendix B 
 
Computer-Administered Survey  
 
Demographic Information [Baseline Visit Only] 
 
1. Of what race do you consider yourself? 
a. White or Caucasian 
b. American Indian or Alaskan Native 
c. Asian 
d. Black or African American 
e. Native Hawaiian or other Pacific Islander 
f. Other 
 
2. What is your ethnicity? 
a. Hispanic 
b. Not Hispanic 
 
3. What is your gender? (Female; Male; Other) 
 
4. What is your age? Click in the box, type your age, and click submit. (free response) 
 
5. What is your current marital status? 
a. Single  
b. In a relationship 
c. Married  
d. Divorced/separated  
e. Widowed 
 
6. What is your current employment status? 
a. Full time, 40 hours per week 
b. Part time 
c. Not working due to medical or mental health disability 
d. Retired 
e. Unemployed 
f. Student  
g. Homemaker or stay-at-home mom 
 
7. What is the highest grade you completed in school? 
a. Grades 1 through 8 
b. Grades 9 through 11  
c. Grade 12 or GED  
d. Some college  
e. Associate’s degree 
f. Bachelor’s degree 
g. Technical training (ex: cosmetology, computer, trade school) 

                                                                                                                                                                                                        
 
54 
 
h. Graduate degree (Master’s or Doctorate) 
 
12. Who do you currently live with? 
a. With my children and significant other/spouse 
b. With my significant other/spouse only 
c. With my children only 
d. With other family 
e. With friends 
f. Alone 
g. I move around a lot or am homeless 
h. Group home or assisted living facility 
 
Medical and Mental Health History [Baseline Visit Only] 
 
1. How many days have you experienced medical problems in the past 30 days? (response 
0-30) 
 
2. Check all of the following medical conditions that a doctor, nurse, or other health 
professional has told you that you have.  
a. Heart disease (e.g., angina, heart attack, or congestive heart failure)  
b. High blood pressure 
c. High cholesterol  
d. Migraines  
e. Diabetes  
 
3. As before, check all of the following medical conditions that a doctor, nurse, or other 
health professional has told you that you have.  
a. Hepatitis  
b. Liver disease  
c. Pancreatitis  
d. Asthma 
e. Chronic obstructive pulmonary disease (COPD) (e.g., emphysema or bronchitis)  
f. Arthritis 
g. Other (free response)  
 
4. Check all of the following mental health conditions that a doctor, psychologist, or other 
health professional has told you that you have.  
a. Depression  
b. Anxiety  
c. Bipolar Disorder 
d. Attention-Deficit/Hyperactivity Disorder 
e. Substance Use Disorder 
f. Other (free response)  
 
5. Are you currently prescribed any opioid medications (such as OxyContin, Vicodin, 
Tylenol 3, Percocet, or morphine)? (yes or no)  

                                                                                                                                                                                                        
 
55 
 
 
6. Are you currently prescribed any other types of pain medications (such as Gabapentin or 
Pregabalin)? (yes or no)  
 
7. Are you currently prescribed any benzodiazepine medications (such as Xanax, Ativan, 
Valium, or Klonopin)? (yes or no)  
 
 
The Brief Pain Inventory (BPI) [Baseline & Follow-Up Visits] 
 
 
 

                                                                                                                                                                                                        
 
56 
 
 
 
 
 
 
 
 

                                                                                                                                                                                                        
 
57 
 
Pain Self-Efficacy Questionnaire (PSEQ) [Baseline & Follow-Up Visits] 
 
Please rate how confident you are that you can do the following things at present, despite the 
pain. To indicate your answer circle one of the numbers on the scale under each item, where 0= 
not at all confident and 6= completely confident.  
 
Remember, this questionnaire is not asking whether of not you have been doing these things, but 
rather how confident you are that you can do them at present, despite the pain. 
 
1. I can enjoy things, despite the pain. 
 
2. I can do most of the household chores (e.g. tidying-up, washing dishes, etc.), despite the 
pain. 
 
3. I can socialise with my friends or family members as often as I used to do, despite the 
pain. 
 
4. I can cope with my pain in most situations. 
 
5. I can do some form of work, despite the pain. (“work” includes housework, paid and 
unpaid work). 
 
6. I can still do many of the things I enjoy doing, such as hobbies or leisure activity, despite 
pain. 
 
7. I can cope with pain without medication. 
 
8. I can still accomplish most of my goals in life, despite the pain. 
 
9. I can live a normal lifestyle, despite the pain. 
 
10. I can gradually become more active, despite the pain. 
 
 
Pain Catastrophizing Scale (PCS) [Baseline & Follow-Up Visits] 
 
Everyone experiences painful situations at some point in their lives. Such experiences may 
include headaches, tooth pain, joint or muscle pain. People are often exposed to situations that 
may cause pain such as illness, injury, dental procedures or surgery.  
 
We are interested in the types of thoughts and feelings that you have when you are in pain. 
Listed below are thirteen statements describing different thoughts and feelings that may be 
associated with pain. Using the following scale, please indicate the degree to which you have 
these thoughts and feelings when you are experiencing pain. (0=not at all; 1=to a slight degree; 
2=to a moderate degree; 3=to a great degree; 4=all the time) 
 

                                                                                                                                                                                                        
 
58 
 
When I’m in pain… 
 
1. I worry all the time about whether the pain will end.  
 
2. I feel I can’t go on.  
 
3. It’s terrible and I think it’s never going to get any better. 
  
4. It’s awful and I feel that it overwhelms me.  
 
5. I feel I can’t stand it anymore. 
 
6. I become afraid that the pain will get worse.  
 
7. I keep thinking of other painful events.  
 
8. I anxiously want the pain to go away. 
 
9. I can’t seem to keep it out of my mind.  
 
10. I keep thinking about how much it hurts.  
 
11. I keep thinking about how badly I want the pain to stop.  
 
12. There’s nothing I can do to reduce the intensity of the pain.  
 
13. I wonder whether something serious may happen.  
 
 
Hospital Anxiety and Depression Scale (HADS) [Baseline & Follow-Up Visits] 
 
Tick the box beside the reply that is closest to how you have been feeling in the past week. Don’t 
take too long over you replies: your immediate is best. 
 
1. I feel tense or 'wound up': 
3 Most of the time 
2 A lot of the time 
1 From time to time, occasionally 
0 Not at all 
 
2. I still enjoy the things I used to enjoy: 
0 Definitely as much 
1 Not quite so much 
2 Only a little 
3 Hardly at all 
 

                                                                                                                                                                                                        
 
59 
 
3. I get a sort of frightened feeling as if something awful is about to happen: 
3 Very definitely and quite badly 
2 Yes, but not too badly 
1 A little, but it doesn't worry me 
0 Not at all 
 
4. I can laugh and see the funny side of things: 
0 As much as I always could 
1 Not quite so much now 
2 Definitely not so much now 
3 Not at all 
 
5. Worrying thoughts go through my mind: 
3 A great deal of the time 
2 A lot of the time 
1 From time to time, but not too often 
0 Only occasionally 
 
6. I feel cheerful: 
3 Not at all 
2 Not often 
1 Sometimes 
0 Most of the time 
 
7. I can sit at ease and feel relaxed: 
0 Definitely 
1 Usually 
2 Not Often 
3 Not at all 
 
8. I feel as if I am slowed down: 
3 Nearly all the time 
2 Very often 
1 Sometimes 
0 Not at all 
 
9. I get a sort of frightened feeling like 'butterflies' in the stomach: 
0 Not at all 
1 Occasionally 
2 Quite Often 
3 Very Often 
 
10. I have lost interest in my appearance: 
3 Definitely 
2 I don't take as much care as I should 
1 I may not take quite as much care 

                                                                                                                                                                                                        
 
60 
 
0 I take just as much care as ever 
 
11. I feel restless as I have to be on the move: 
3 Very much indeed 
2 Quite a lot 
1 Not very much 
0 Not at all 
 
12. I look forward with enjoyment to things: 
0 As much as I ever did 
1 Rather less than I used to 
2 Definitely less than I used to 
3 Hardly at all 
 
13. I get sudden feelings of panic: 
3 Very often indeed 
2 Quite often 
1 Not very often 
0 Not at all 
 
14. I can enjoy a good book or radio or TV program: 
0 Often 
1 Sometimes 
2 Not often 
3 Very seldom 
  
 
Pittsburgh Sleep Quality Index (PSQI) [Baseline & Follow-Up Visits] 
The following questions relate to your usual sleep habits during the past month only. Your 
answers should indicate the most accurate reply for the majority of days and nights in the past 
month. Please answer all questions. 
 
1. When have you usually gone to bed? (free response option) 
2. How long (in minutes) has it taken you to fall asleep each night? (free response option) 
3. What time have you usually gotten up in the morning? (free response option) 
4. A. How many hours of actual sleep did you get at night? (free response option) 
B. How many hours were you in bed? (free response option) 

                                                                                                                                                                                                        
 
61 
 
 
 
Acceptability & Feedback Questions [Follow-Up Visit Only] 
 
Please rate the following questions on a 0-10 scale:  
 
1) How easy was it to use the smartphone app? 
 
 
0  
1  
2  
3  
4  
5  
6  
7  
8  
9  
10 
Completely                                                                                                                                                                                            Completely  
 difficult                                                                                                                                                                                                         easy  
 
2) Overall, how satisfied were you using the DynamiCare app? 
 
 
0  
1  
2  
3  
4  
5  
6  
7  
8  
9  
10 
Extremely dissatisfied                                                                                                                   Extremely satisfied 
 
3) How useful were the daily surveys? 
 
 
0  
1  
2  
3  
4  
5  
6  
7  
8  
9  
10 
Completely                                                                                                                                                                                          Completely 
useless                                                                                                                                                                                                         useful 

                                                                                                                                                                                                        
 
62 
 
 
4) How appealing was the smartphone app? 
 
 
0  
1  
2  
3  
4  
5  
6  
7  
8  
9  
10 
Completely                                                                                                                                                                                          Completely 
unappealing                                                                                                                                                                                            appealing                                               
 
5) How bothersome were the daily surveys? 
 
 
0  
1  
2  
3  
4  
5  
6  
7  
8  
9  
10 
Completely                                                                                                                                                                                          Completely 
bothersome                                                                                                                                                                                           convenient       
 
6) How willing were you to use the app every day? 
 
 
0  
1  
2  
3  
4  
5  
6  
7  
8  
9  
10 
Completely                                                                                                                                                                                            Completely  
unwilling                                                                                                                                                                                                      willing                                              
 
7) How easy was is to complete the daily surveys? 
 
 
0  
1  
2  
3  
4  
5  
6  
7  
8  
9  
10 
Completely                                                                                                                                                                                     Completely difficult                                      
easy  
 
 
8) How much did the app help you to cope with your pain? 
 
 
0  
1  
2  
3  
4  
5  
6  
7  
8  
9  
10 
Not at all                                                                                                                                                                           Completely  
 
9) How honest were you in completing the daily survey? (I was very honest, I was honest most 
of the time, I was honest some of the time, I was honest once in a while, I was not honest at 
all) 
 
10) [for CM group pts only] How much did the rewards make a difference in whether you 
completed the daily survey? (Not at all, very little, little, somewhat, much, to a great extent, 
completely) 
 
11) [for CM group pts only] How much did the rewards make a difference in how accurately you 
reported information in the daily survey? (Not at all, very little, little, somewhat, much, to a 
great extent, completely)