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Although many pain-related smartphone apps exist, little attention has been given to understanding how these apps are used over time and what factors contribute to greater compliance and patient engagement.
This retrospective analysis was designed to help identify factors that predicted the benefits and future use of a smartphone pain app among patients with chronic pain.
An app designed for both Android and iOS devices was developed by Brigham and Women’s Hospital Pain Management Center (BWH-PMC) for users with chronic pain to assess and monitor pain and communicate with their providers. The pain app offered chronic pain assessment, push notification reminders and communication, personalized goal setting, relaxation sound files, topics of interest with psychological and medical pain management strategies, and line graphs from daily assessments. BWH-PMC recruited 253 patients with chronic pain over time to use the pain app. All subjects completed baseline measures and were asked to record their progress every day using push notification daily assessments. After 3 months, participants completed follow-up questionnaires and answered satisfaction questions. We defined the number of completed daily assessments as a measure of patient engagement with the pain app.
The average age of participants was 51.5 years (SD 13.7, range 18-92), 72.8% (182/253) were female, and 36.8% (78/212) reported the low back as their primary pain site. The number of daily assessments ranged from 1 to 426 (average 62.0, SD 49.9). The app was easy to introduce among patients, and it was well accepted. Those who completed more daily assessments (greater patient engagement) throughout the study were more likely to report higher pain intensity, more activity interference, and greater disability and were generally overweight compared with others. Patients with higher engagement with the app rated the app as offering greater benefit in coping with their pain and expressed more willingness to use the app in the future (
Patients with chronic pain who appeared to manage their pain better were less likely to report benefits of a smartphone pain app designed for chronic pain management. They demonstrated lower patient engagement in reporting their daily progress, in part, owing to the perceived burden of regularly using an app without a perceived benefit. An intrinsically different pain app designed and targeted for individuals based on early identification of user characteristics and adapted for each individual would likely improve compliance and app-related patient engagement.
Pain is a major reason that individuals seek health care treatment, and it is estimated that more than 25 million US adults are affected by daily pain [
Innovative technology can be used by health care providers to track persons with chronic pain, engage the patients between clinic visits, and offer information and support to improve coping. There has been a rapid increase in smartphone apps used to monitor and record health data partly due to the increase in mobile device availability [
There is evidence that tracking real-time data using momentary ecological assessment is preferable to retrospective diary entry [
In a more recent review, Bhatterai et al [
The purpose of this analysis was to determine the long-term effects of using a smartphone pain app that offers pain management strategies and allows patients with chronic pain to assess, monitor, and communicate their condition to their health care providers
This is a retrospective analysis of data gathered from a smartphone pain app designed by Brigham and Women’s Hospital Pain Management Center (BWH-PMC) to assess longitudinal combined information about satisfaction and compliance with the use of a smartphone pain app for persons with chronic pain over 3 months. The analysis plan was approved by the hospital’s internal review board. A team from the BWH-PMC helped develop and test multiple versions of a smartphone pain app used on iOS and Android devices. Initial input from 20 patients with chronic pain was obtained to assist in the development process of the first version of the app (PainApp Pilot;
Data on the server were available only to BWH-PMC personnel through a secure password-protected administration portal. Components of the smartphone app included demographic and contact information, a comprehensive chronic pain assessment, 5-item daily assessments with push notification reminders (
Data were collected by BWH-PMC from a series of studies using the third version of the smartphone pain app (BWH PainApp) between February 2015 and May 2018 among patients with noncancer-related chronic pain. Previously conducted study methods have been reported earlier by BWH-PMC [
All participants were encouraged to complete a 5-item daily assessment on the pain app about their pain, sleep, mood, activity interference, and whether they had gotten better or worse on a visual analog scale (
Key development highlights from each version of the pain app. BWH: Brigham and Women's Hospital; PMC: Pain Management Center.
Pain app version 3 home page with links when scrolled down.
Pain app version 3 daily assessments and goal-setting tasks.
BWH-PMC recruited patients with chronic pain to participate in 1 of 4 published studies [
Acceptability, tolerability, feasibility, and effectiveness of the third version of the pain app were assessed by examining the number and frequency of daily assessments, the number of subjects who continued to use the app after the initial download, and the numeric and qualitative satisfaction ratings. Any reported safety issues were also documented. Overall outcome efficacy was determined through standardized paper-based measures administered at baseline and again after 3 months from this baseline assessment [
Pain intensity and pain description were assessed using the Brief Pain Inventory (BPI) [
Activity interference and disability was assessed with items from the BPI and the Pain Disability Inventory (PDI) [
Mood, negative affect, and emotional distress were assessed using the Hospital Anxiety and Depression Scale (HADS) [
After 3 months, participants were asked to respond to a 5-item paper-based satisfaction questionnaire designed to investigate the perceived benefit of how easy the pain app was to use and navigate, how useful the daily reminders were, how much the program helped them cope with their pain, and how willing they would be to use the pain app in the future. All items, which were developed in a previous study [
This retrospective analysis was conducted by BWH-PMC. Univariate and multivariate descriptive analyses were performed on all the dependent variables at baseline and at follow-up. Chi-square,
A total of 253 patients with chronic pain were engaged by BWH-PMC to use a revised third version of the smartphone pain app. The average age of patients was 51.4 years (SD 13.7, range 18-92); 73.1% (185/253) of patients were female and 82.9% (209/252) of patients were white (
Patient demographic characteristics (N=253).
Variable | Value | Range | |
Age (years), mean (SD) | 51.5 (13.8) | 18-92 | |
Gender, female, n (%) | 182 (72.7) | N/Aa | |
|
|||
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White | 206 (82.7) | N/A |
|
African American | 16 (6.4) | N/A |
|
Hispanic | 17 (6.8) | N/A |
|
Other | 10 (4.0) | N/A |
Pain duration (years), mean (SD) | 11.8 (10.7) | 0.5-50 | |
|
|||
|
Low back | 78 (36.8) | N/A |
|
Multiple sites | 77 (36.3) | N/A |
|
Cervical/upper extremity | 31 (14.6) | N/A |
|
Lower extremity | 11 (5.2) | N/A |
|
Abdominal/pelvic | 13 (6.1) | N/A |
|
Head/face | 2 (0.9) | N/A |
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|
Worst pain | 7.7 (2.1) | 1-10 |
|
Least pain | 3.3 (2.3) | 0-10 |
|
Average pain | 5.4 (1.8) | 1-10 |
Depth of pain, mean (SD) | 203.3 (48.0) | 0-270 | |
Take opioid medication, n (%)d | 97 (39.9) | N/A | |
BMI (kg/m2), mean (SD) | 30.1 (7.4) | 12.2-54.7 | |
Number of times wake during night, mean (SD) | 2.6 (2.1) | 0-10 | |
Sleep hours, mean (SD) | 6.3 (1.8) | 1-12 | |
Pain interference (total)e, mean (SD) | 4.9 (2.7) | 0-10 | |
Pain Disability Index, mean (SD) | 31.5 (17.7) | 0-70 | |
Hospital Anxiety and Depression Scale total, mean (SD) | 14.9 (7.7) | 0-36 | |
Pain Catastrophizing Scale, mean (SD) | 17.3 (12.2)) | 0-50 | |
Number of symptomsf (present or absent), mean (SD) | 1.6 (2.4) | 0-13 | |
Number of pain descriptorsg (present or absent), mean (SD) | 4.1 (1.9) | 1-9 | |
Number of daily assessments, mean (SD) | 62.0 (49.9) | 1-426 |
aN/A: not applicable.
bN=212.
c0=no pain; 10=pain as bad as you can imagine.
dN=243.
eDuring the past 24 hours, how much has your pain interfered with (1) general activity, (2) mood, (3) walking ability, (4) normal work, (5) relations with others, (6) sleep, and (7) enjoyment of life? 0=has not interfered; 10=completely interfered.
fSide effect symptoms: constipation, dizziness, dry mouth, headache, itching, memory lapse, confusion, nausea, nightmares, sneezing, sweating, visual problems, weakness, and other.
gPain descriptors: throbbing, stabbing, aching, burning, pricking, pulling, shooting, numbing, and other.
Of the 253 subjects considered for the analysis, 43 (18.1%) reported some type of technical problem with the app during the study period that briefly restricted their daily assessments. This did not significantly affect their engagement with the pain app. The total number of daily assessments from the pain app averaged 62.0 (SD 49.9). Comparisons between baseline measures and repeat measures at 3 months showed an overall decrease in average pain intensity on the BPI (5.3, SD 1.8 vs 4.9, SD 2.3; t185=4.0;
A total of 72.3% (183/253) users completed the satisfaction questionnaire after approximately 3 months. No significant differences in demographic characteristics were found between those who completed the satisfaction questionnaire and those who did not complete this questionnaire. Most users found the app easy to use (mean 8.7, SD 2.2) and easy to navigate (mean 8.5, SD 2.4; 0=not at all easy; 10=very easy). The majority of users also found the daily reminders to be useful (mean 6.7, SD 3.9; 0=not at all useful, 10=very useful). Some of the users, primarily the Android users, reported that the push notification reminders did not consistently work on their phone, and they were more likely to rate lower perceived usefulness of the daily reminders because they did not work. The users felt that the app offered some help in coping with their pain (mean 4.5, SD 3.7; 0=not at all helpful, 10=very helpful), whereas the majority of the users felt that they would be willing to use the app in the future (mean 7.1, SD 3.3; 0=not at all willing, 10=very willing).
No significant differences were found on demographic variables of age, gender, ethnicity, or pain duration on all outcome variables. Those who reported liking the pain app were more likely to use it often to submit more daily reports and reported greater pain intensity and more disability. Pearson product-moment correlations between the 5 satisfaction questions ranged between 0.21 and 0.58.
Factor analysis of the satisfaction questionnaire responses using principal component analysis with Varimax rotation found two factors above an eigenvalue of greater than 1.0: (1) easy to use, easy to navigate, useful reminders (correlation
Pearson product-moment correlations were run between the combined satisfaction ratings of
Discriminant function analyses were run using those variables, which revealed significant differences between those with generally higher ratings on
Differences were examined on the baseline and outcome variables between those selected patients with pain who felt that the pain app both helped them cope with their pain and were willing to use the app in the future (n=84; >7/10) and those who reported that the pain app both did not help them cope and were less inclined to use it in the future (n=81; <7/10) based on the 3-month satisfaction questions (
Most of those who responded to the follow-up question
Pearson product-moment correlations among patient satisfaction questionnaire responses between those who found the pain app easy to use, and those who felt that the app helped them to cope and would be willing to use the pain app in the future (0=very satisfied; 10=very unsatisfied).
Variable | Pearson product-moment correlations for |
Pearson product-moment correlations for |
|
Age (years) | 0.20a | −0.08 | |
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Worse pain | −0.06 | 0.18a |
|
Least pain | 0.15 | 0.22b |
|
Average pain | 0.10 | 0.24b |
BMI (kg/m2) | 0.11 | 0.26b | |
Brief Pain Inventory activity interference (0-10) | −0.03 | 0.24b | |
Pain Disability Inventory total (0-70) | 0.00 | 0.19a | |
Side effect list total (0-14)a,c | −0.18a | 0.19a | |
Pain description total (0-9)b,d | −0.23a | 0.15 | |
Number of daily assessments entered | 0.09 | 0.15 | |
Total number of messages sent and received | −0.01 | 0.18a | |
Opioids (yes/no) | 0.11 | 0.19a |
a
b
cSide effect symptoms: constipation, dizziness, dry mouth, headache, itching, memory lapse, confusion, nausea, nightmares, sneezing, sweating, visual problems, weakness, and other.
dPain descriptors: throbbing, stabbing, aching, burning, pricking, pulling, shooting, numbing, and other.
Differences between patients with pain who felt that the pain app helped them cope with their pain and were willing to use the app in the future (n=84) and those who reported that the pain app did not help them cope and were less inclined to use it in the future (n=81).
Variablea | Yes (n=84) | No (n=81) | Chi-square ( |
|
BPIb pain (baseline, range 0-10), mean (SD) | 5.7 (1.9) | 5.1 (1.8) | 2.3 (157)c | N/Ad |
BPI pain (3-month follow-up, range 0-10), mean (SD) | 5.2 (2.4) | 4.4 (2.0) | 2.3 (155)c | N/A |
BPI activity interference (range 0-10), mean (SD) | 5.0 (2.4) | 3.9 (2.6) | 2.7 (157)c | N/A |
BPI activity interference (3-month follow-up, range 0-10), mean (SD) | 4.7 (2.8) | 3.8 (2.8) | Not significant | N/A |
PDIe total (baseline), mean (SD) | 34.6 (16.9) | 27.2 (17.0) | 2.7 (145)f | N/A |
PDI total (3-month follow-up), mean (SD) | 31.8 (18.3) | 25.0 (17.0) | 2.4 (150)c | N/A |
Pain description (range 0-9)g, mean (SD) | 4.5 (2.1) | 3.9 (1.6) | 2.1 (160)c | N/A |
Side effects total (yes, range 0-14)h, mean (SD) | 7.8 (15.6) | 4.1 (8.6) | Not significant | N/A |
BMI (kg/m2), mean (SD) | 31.6 (7.8) | 28.1 (6.5) | 3.2 (160)f | N/A |
Opioids (% yes of total) | 22.6 | 16.4 | N/A | 4.3 (1)c |
Number of daily assessments entered, mean (SD) | 83.6 (62.3) | 65.9 (37.9) | 2.2 (162)c | N/A |
Total messages, mean (SD) | 13.1 (12.3) | 8.9 (7.9) | 2.6 (162)c | N/A |
aNo differences were found between groups on age, gender, pain site, ethnicity, or pain duration.
bBPI: Brief Pain Inventory.
c
dN/A: not applicable.
ePDI: Pain Disability Inventory.
f
gPain descriptors: throbbing, stabbing, aching, burning, pricking, pulling, shooting, numbing, and other.
hSide effect symptoms: constipation, dizziness, dry mouth, headache, itching, memory lapse, confusion, nausea, nightmares, sneezing, sweating, visual problems, weakness, and other.
Although many pain-related apps exist, attention has been given recently to understanding how these apps are used over time and what factors contribute to greater compliance and patient engagement [
The challenge with mobile health (mHealth) technology is to encourage and motivate participants to continue to use an app to track behavior, maintain contact with their provider, and make improvements in their condition. This is particularly important among individuals with chronic illnesses. The goal of innovative mHealth technology is to offer medical and psychological assistance remotely to reduce health care utilization by reducing clinic and emergency room visits and unnecessary expensive tests. This is a future direction for health care technology, but engaging individuals in ways that increase use of this technology continues to represent a challenge among app developers. It may be no surprise that those patients with pain who used the app more were more satisfied with the pain-related software program. It is interesting to speculate why those with more pain, greater self-reported disability, greater weight, more use of opioids, and more pain descriptors were more satisfied with the smartphone pain app. Quite possibly, those who were busy throughout the day found the app to be more bothersome. Subjective feedback suggests that some preferred not to focus on their pain and found the frequent monitoring to be more of a bother than helpful. Those who reported more limitations owing to their pain might have been more focused on their pain and welcomed the opportunity to share their experience with their providers. Some may have also wanted to verify their disability and document their limitations for others.
There are many challenges with pain apps going forward. Few physicians recommend pain apps because of lack of time, lack of information about which apps are reliable, concerns of liability, and insufficient evidence that the use of an app will improve outcomes [
There are a number of limitations of this analysis that should be highlighted. As with any new technology, we encountered some software and hardware difficulties that may have adversely affected the use of the app and consequently affected the outcome data. Some subjects did not receive reminders or push notifications to complete their daily assessments, which seemed to be reported mostly by Android smartphone owners. In addition, some encountered difficulties when they upgraded their smartphones, including problems downloading the program to their new device. They also reported minor problems with the app when software updates were made to either the iPhone or Android devices. Corresponding changes were needed in the software code of the pain app every time these changes were made to the iOS and Android platforms. The BWH-PMC staff also needed to make periodic changes to the administrative portal and server, which caused delays in capturing patient data. Thus, factors other than patient noncompliance, including technical difficulties with the software and the devices, may have accounted for the perceived benefit from the pain app. Not all users were able to participate owing to the limitations of their phone capabilities or them not owning a smartphone. Thus, these results may have been affected by selection bias. Patients were encouraged to use the app as part of a study, which may have influenced the use of the app more than what might have been done if patients were not involved in a study. We also could not determine how the availability of RA support was an influencing factor in engagement. It should also be pointed out that the results are correlational in nature, and no causal relationships can be assumed.
This retrospective analysis demonstrates that a smartphone pain app for persons with chronic pain can be perceived to be easy to use, but certain factors, including greater pain and disability, might have an increased influence in motivating individuals to use the app. It also highlights potential challenges in using mHealth technology. Future improvements are needed to make pain apps more adaptive and engaging and directly tailored to the individual user. This would likely have a positive impact on adherence and may lead to increased improvements among persons with chronic pain.
Comments regarding use of the pain app after a 3 month trial "Is there anything about the pain app that you would change.".
American Medical Informatics Association
Brief Pain Inventory
Brigham and Women’s Hospital Pain Management Center
electronic medical record
Hospital Anxiety and Depression Scale
mobile health
Pain Catastrophizing Scale
Pain Disability Inventory
research assistant
A portion of the results of this analysis was presented at the American Medical Informatics Association’s (AMIA) annual symposium, San Francisco, California, November 6, 2018. The AMIA poster and this manuscript were funded by Pfizer to understand the importance of utilizing a pain app to communicate between patients and providers between clinic visits. The authors gratefully recognize Joseph C Cappelleri, Walter J McClain, Elizabeth Scanlan, Margarita Udall, Limeng Wan, and the patients and staff of BWH-PMC for their assistance and participation related to the development of this manuscript. Special thanks are also extended to the staff of Technogrounds Inc for helping to develop the different versions of the app.
This manuscript development was funded by Pfizer Inc. ER and RJ are employees of BWH-PMC, which received financial support from Pfizer for participation in this manuscript. LN, BP, and KN are Medical Affairs employees of Pfizer Inc.
ER and RJ conducted the retrospective analysis without any support or input from Pfizer Inc. RJ developed the initial draft of this manuscript. All other authors and contributors provided edits, suggestions, and revisions to the final manuscript.
LN, BP, and KN are employees of Pfizer Inc. ER and RJ declare no conflicts of interest.