Integration of Mobile Health Technology in the Treatment of Chronic Pain: A Critical Review

Could the use of web-based applications assist in neuropsychiatric treatment? An umbrella review

BACKGROUND

The aim of this study was to evaluate the use of applications accessed through internet browsers as tools for neuropsychiatric treatment, as well as to verify the benefits and efficacy of virtual support as a therapeutic approach.

METHODS

A broad review of the MEDLINE (PubMed), SciELE and Cochrane databases for review articles was conducted. Articles involving the use of browser-based applications as a support for neurological and psychiatric treatment, with available texts on the selected platforms with no language or year restrictions, were included.

RESULTS

A total of 83 reviews were included in this study. Due to the homogeneity of the information between some articles, the research was grouped according to the following revised themes: mindfulness, tinnitus, electronic health (eHealth), youth and students' mental health, mobile health applications (mHealth), depression, anxiety and stress, psychoactive substances, sleep quality, chronic diseases and mental disorders.

CONCLUSION

The findings suggest that the use of virtual support through applications helps neuropsychiatric treatment, improving the well-being and quality of life of these patients.

Mobile Health App and Web Platform (eDOL) for Medical Follow-Up of Patients With Chronic Pain: Cohort Study Involving the French eDOL National Cohort After 1 Year

BACKGROUND

Chronic pain affects approximately 30% of the general population, severely degrades quality of life and professional life, and leads to additional health care costs. Moreover, the medical follow-up of patients with chronic pain remains complex and provides only fragmentary data on painful daily experiences. This situation makes the management of patients with chronic pain less than optimal and may partly explain the lack of effectiveness of current therapies. Real-life monitoring of subjective and objective markers of chronic pain using mobile health (mHealth) programs could better characterize patients, chronic pain, pain medications, and daily impact to help medical management.

OBJECTIVE

This cohort study aimed to assess the ability of our mHealth tool (eDOL) to collect extensive real-life medical data from chronic pain patients after 1 year of use. The data collected in this way would provide new epidemiological and pathophysiological data on chronic pain.

METHODS

A French national cohort of patients with chronic pain treated at 18 pain clinics has been established and followed up using mHealth tools. This cohort makes it possible to collect the determinants and repercussions of chronic pain and their evolutions in a real-life context, taking into account all environmental events likely to influence chronic pain. The patients were asked to complete several questionnaires, body schemes, and weekly meters, and were able to interact with a chatbot and use educational modules on chronic pain. Physicians could monitor their patients' progress in real time via an online platform.

RESULTS

The cohort study included 1427 patients and analyzed 1178 patients. The eDOL tool was able to collect various sociodemographic data; specific data for characterizing pain disorders, including body scheme; data on comorbidities related to chronic pain and its psychological and overall impact on patients' quality of life; data on drug and nondrug therapeutics and their benefit-to-risk ratio; and medical or treatment history. Among the patients completing weekly meters, 49.4% (497/1007) continued to complete them after 3 months of follow-up, and the proportion stabilized at 39.3% (108/275) after 12 months of follow-up. Overall, despite a fairly high attrition rate over the follow-up period, the eDOL tool collected extensive data. This amount of data will increase over time and provide a significant volume of health data of interest for future research involving the epidemiology, care pathways, trajectories, medical management, sociodemographic characteristics, and other aspects of patients with chronic pain.

CONCLUSIONS

This work demonstrates that the mHealth tool eDOL is able to generate a considerable volume of data concerning the determinants and repercussions of chronic pain and their evolutions in a real-life context. The eDOL tool can incorporate numerous parameters to ensure the detailed characterization of patients with chronic pain for future research and pain management.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04880096; https://clinicaltrials.gov/ct2/show/NCT04880096.

Retention, adherence, and acceptability testing of a digital health intervention in a 3-group randomized controlled trial for chronic musculoskeletal pain

OBJECTIVES

Evaluate a digital health intervention using Auricular Point Acupressure (APA) for chronic musculoskeletal pain in terms of participant retention, adherence, acceptability, and satisfaction. Chronic musculoskeletal pain is a global concern and there are persistent challenges in pain management. Despite the value of digital health interventions, these interventions need to be fully evaluated for feasibility.

METHODS

We conducted a 3-group, longitudinal, randomized controlled trial (RCT). After Institutional Review Board approval, we posted recruitment flyers in a university, healthcare clinics, and community settings. Participants were randomized into an in-person + app group (n = 8), virtual + app group (n = 7), and a wait-list, education-enhanced control group (n = 8), evaluating our outcomes using standard feasibility measures. The 4-week intervention consisted of virtual sessions, telecommunications, and our APA app, followed by a 3-month follow-up.

RESULTS

Data from 22 participants were subsequently analyzed (95.7%). All app participants adhered to the study protocol and used APA at the minimum recommended frequency and duration. The virtual + app group used APA more during the intervention and follow-up periods. All app participants found the intervention to be acceptable and at least 80% overall were satisfied with APA at the 3-month follow-up. There were no adverse events reported.

CONCLUSIONS

Our digital health intervention was found to be acceptable and sustainable; participants adhered to and were satisfied with the intervention providing support for a larger RCT.

CLINICAL TRIAL

#: NCT05020470.

Mobile apps to self-manage chronic low back pain: A realist synthesis exploring what works, for whom and in what circumstances

Objective

Chronic low back pain places a significant burden on healthcare services and sufferers. Clinical guidelines state that it is a condition that requires self-management. This realist synthesis explores how a mobile app could help people to self-manage chronic low back pain.

Method

Six databases and several non-academic sources were searched. In addition, nineteen realist interviews were conducted with stakeholders. Sources were selected and appraised for relevancy, richness, and rigour. Data was coded with analytical memos making retroductive inferences. Causal explanations were presented in context-mechanism-outcome configurations to form three programme theories.

Results

Data from 57 sources was synthesised to create 16 context-mechanism-outcome configurations and presented as three refined programme theories. The findings suggest people need to feel believed before they will engage with a self-management app. For those who feel abandoned by the healthcare service, a self-management app for chronic low back pain can be a valuable source of ongoing support and reduce feelings of social isolation.

Conclusion

A self-management app, if introduced appropriately and as adjunct to care, can be an empowering tool to self-manage chronic low back pain.

Innovation

Using input from key stakeholders enhances our understanding of the hidden generative mechanisms underpinning a programme's success or failure.

Risk Factors for Self-Harm Ideation Among Persons Treated With Opioids for Chronic Low Back Pain

OBJECTIVES

Chronic pain is a significant health concern that adversely affects all aspects of life, including emotional well-being. Opioids are prescribed for the management of refractory, severe chronic pain, although they have been associated with adverse effects, including addiction and overdose. The aim of this study was to examine factors that predict thoughts of self-harm among adults with chronic pain who are prescribed opioids.

MATERIALS AND METHODS

Seven hundred sixty-five (N=765) persons with opioid-treated chronic lower back pain completed the Current Opioid Misuse Measure (COMM) and other validated questionnaires as part of a larger study. Response to 1 question from the COMM ("How often have you seriously thought about hurting yourself?") was used to assess suicide risk on a 5-point scale (0=never; 4=very often).

RESULTS

Participants were categorized into 3 groups according to their responses to the self-harm question: never (N=628; 82.1%), seldom or sometimes (N=74; 9.7%), and often or very often (N=63; 8.2%). Multivariate adjusted odds ratio (aOR) analyses indicated that reports of alcohol or drug overuse within the past month (aOR=1.41,[95% CI 1.11-1.78]), posttraumatic stress (PTSD; aOR=1.24,[1.07 to 1.44]), pain catastrophizing (aOR=1.03,[1.01 to 1.05]), not loving oneself (aOR=0.99,[.98-1.00]) and poor perceived mental health (aOR=0.94,[.92 to 97]) were most associated with thoughts of self-harm. Importantly, the ideation frequency of self-harm was highest among individuals treated with higher daily doses of opioids.

DISCUSSION

These results support the need for continued monitoring of adults treated with opioids for chronic pain, particularly among those on high-dose opioids who present with increased negative affect and concerns of substance misuse.

Mobile Phone-Based Telemonitoring for Improving Adherence to Analgesic Treatment in Trauma Patients After Emergency Department Discharge: A Randomized Controlled Trial

OBJECTIVE

To determine the impact of mobile-phone telemonitoring on patients' adherence and satisfaction with posttrauma pain treatment.

MATERIALS AND METHODS

We conducted a prospective randomized clinical trial including patients with minor trauma discharged from the emergency department (ED) with analgesic treatment. Patients were randomized to one of 3 groups, the control group, where patients received a phone call on day-7, the short message service (SMS) group, where patients received a daily text message to remind them to take their treatment during 7 days, and the mobile-phone based telemonitoring (TLM) group. Patients' adherence to analgesic treatments using the Morisky Medication Adherence Scale, current pain by using a visual analogue scale, and patients' satisfaction were assessed. For the TLM group, the assessment was performed at day-2, 4 and 7.

RESULTS

Good adherence was observed in 418 patients (92.9%) in the TLM group versus 398 patients (88.6%) in the SMS group and 380 patients (84.8%) in the control group ( P <0.001). The factor mostly associated with adherence was telemonitoring (OR 2.40 95% CI 1.55-3.71). The decrease in pain visual analogue scale was highest in the TLM group compared with SMS and control groups ( P <0.001). The percentage of patients' satisfaction at 7 days post-ED discharge was 93% in the TLM group versus 88% in the SMS group and 84% in the standard group ( P =0.02).

DISCUSSION

Our findings suggest that mobile-phone-based telemonitoring is beneficial in the treatment of pain in trauma patients after ED discharge. This approach improved patients' adherence and satisfaction.

Mapping the Design Space of Technology-Based Solutions for Better Chronic Pain Care: Introducing the Pain Tech Landscape

OBJECTIVES

Technology has substantial potential to transform and extend care for persons with chronic pain, a burdensome and costly condition. To catalyze the development of impactful applications of technology in this space, we developed the Pain Tech Landscape (PTL) model, which integrates pain care needs with characteristics of technological solutions.

METHODS

Our interdisciplinary group representing experts in pain and human factors research developed PTL through iterative discussions. To demonstrate one potential use of the model, we apply data generated from a narrative review of selected pain and technology journals (2000-2020) in the form of heat map overlays, to reveal where pain tech research attention has focused to date.

RESULTS

The PTL comprises three two-dimensional planes, with pain care needs on each x axis (measurement to management) and technology applications on the y axes according to a) user agency (user- to system-driven), b) usage time frame (temporary to lifelong), and c) collaboration (single-user to collaborative). Heat maps show that existing applications reside primarily in the "user-driven/management" quadrant (e.g., self-care apps). Examples of less developed areas include artificial intelligence and Internet of Things (i.e., Internet-linked household objects), and collaborative/social tools for pain management.

CONCLUSIONS

Collaborative development between the pain and tech fields in early developmental stages using the PTL as a common language could yield impactful solutions for chronic pain management. The PTL could also be used to track developments in the field over time. We encourage periodic reassessment and refinement of the PTL model, which can also be adapted to other chronic conditions.

Development of a patient-centered text message-based platform for the self-management of interstitial cystitis/bladder pain syndrome symptoms

OBJECTIVE

To develop a patient-centered text message-based platform that promotes self-management of symptoms of interstitial cystitis/bladder pain syndrome (IC/BPS).

METHODS

Adult women with IC/BPS interested in initiating a first- or second-line treatments per American Urological Association guidelines (recategorized as "behavioral/non-pharmacologic treatments" and "oral medicines" in the 2022 version) participated in rapid cycle innovation consisting of iterative cycles of contextual inquiry, prototype design and development. We delivered treatment modules and supportive messages using an algorithm-driven interactive messaging prototype through a HIPAA-compliant texting platform. Patients provided feedback through narrative text messages and an exit interview. Feedback was analyzed qualitatively and used to iteratively revise the platform until engagement ≥ 85% and accuracy ≥ 80% were achieved. The final version consisted of four treatment module categories (patient education and behavioral modification, cognitive behavioral therapy, pelvic floor physical therapy, and guided mindfulness practices) and supportive messages delivered through an automated algorithm over 6 weeks.

RESULTS

Thirty IC/BPS patients with moderate symptom bother (median IC Problem Index score 9, range 6-12) participated in five cycles of contextual inquiry. Qualitative analysis identified three overarching concepts that informed the development of the platform: preference for patient centered terms, desire to gain self-efficacy in managing symptoms, and need for provider support. Patients preferred the term "interstitial cystitis" to "bladder pain syndrome" which carried the stigma of chronic pain. Patients reported greater self-efficacy in managing symptoms through improved access to mind-body and behavioral treatment modules that helped them to gain insight into their motivations and behaviors. The concept of provider support was informed by shared decision making (patients could choose preferred treatment modules) and reduced sense of isolation (weekly check in messages to check on symptom bother).

CONCLUSION

A patient centered text message-based platform may be clinically useful in the self-management of IC/BPS symptoms.

Multidisciplinary approach, continuous care and opioid management in cancer pain: case series and review of the literature

Underlying cancer pain has heterogenous aetiologies and mechanisms. It requires detailed and comprehensive pain assessment, combined with personalized treatment. A multidisciplinary team is essential to providing the best management of cancer pain at every disease stage, improving the quality of life and outcomes in patients with cancer. This narrative literature review emphasizes the value of providing all patients with multidisciplinary pain management in their preferred care setting. Real-life experiences are also reported to witness the efforts of physicians to properly manage cancer pain. This article is part of the Management of breakthrough cancer pain Special Issue: https://www.drugsincontext.com/special_issues/management-of-breakthrough-cancer-pain.

Determining the Influencing Factors on Acceptance of eHealth Pain Management Interventions Among Patients With Chronic Pain Using the Unified Theory of Acceptance and Use of Technology: Cross-sectional Study

Background

Chronic pain is a complex disease with high prevalence rates, and many individuals who are affected do not receive adequate treatment. As a complement to conventional therapies, eHealth interventions could provide many benefits to a multimodal treatment approach for patients with chronic pain, whereby future use is associated with the acceptance of these interventions.

Objective

This study aims to assess the acceptance of eHealth pain management interventions among patients with chronic pain and identify the influencing factors on acceptance. A further objective of the study is to evaluate the viability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and compare it with its extended version in terms of explained variance of acceptance.

Methods

We performed a cross-sectional web-based study. In total, 307 participants with chronic pain, as defined according to the International Association for the Study of Pain criteria, were recruited through flyers, posters, and web-based inquiries between December 2020 and July 2021. In addition to sociodemographic and medical data, the assessment included validated psychometric instruments and an extended version of the well-established UTAUT model. For statistical analyses, group comparisons and multiple hierarchical regression analyses were performed.

Results

The acceptance of eHealth pain management interventions among patients with chronic pain was overall moderate to high (mean 3.67, SD 0.89). There was significant difference in acceptance among age groups (W=9674.0; r=0.156; P=.04). Effort expectancy (β=.37; P<.001), performance expectancy (β=.33; P<.001), and social influence (β=.34; P<.001) proved to be the most important predictors of acceptance. The extended UTAUT (including the original UTAUT factors as well as sociodemographic, medical, and eHealth-related factors) model explained 66.4% of the variance in acceptance, thus supporting the viability of the model. Compared with the original UTAUT model (performance expectancy, effort expectancy, and social influence), the extended model explained significantly more variance (F_25,278=1.74; P=.02).

Conclusions

Given the association between acceptance and future use, the knowledge of the influencing factors on acceptance should be used in the development and promotion of eHealth pain management interventions. Overall, the acceptance of eHealth pain management interventions was moderate to high. In total, 8 predictors proved to be significant predictors of acceptance. The UTAUT model is a valuable instrument for determining acceptance as well as the factors that influence acceptance of eHealth pain management interventions among patients with chronic pain. The extended UTAUT model provided the greatest predictive value for acceptance.

Development of the Emoji faces pain scale and its validation on mobile device in adult surgery patients: A longitudinal observational study (Preprint)

BACKGROUND

Measuring pain on digital devices using classic unidimensional pain scales such as the visual analog scale (VAS), numerical rating scale (NRS), and faces pain scale (FPS) has been proven to be reliable and valid. Emoji are pictographs designed in colorful form following the Unicode standard. It could be more beneficial to use emoji as faces of FPS on digital devices because emoji can easily fit on most devices and emoji are open-source so no approval would be needed before use. With a concise and user-friendly design, the emoji faces pain scale (Emoji-FPS) might be more generalizable to a wider population and more preferred by digital device users.

OBJECTIVE

This study was designed to develop an Emoji-FPS as well as to evaluate its reliability, validity, and preference on mobile devices in adult patients who underwent surgery.

METHODS

A modified Delphi technique with 2 rounds of web-based surveys was applied to obtain panelists' consensus on the sequence of emoji that can best represent 6 levels of pain. The initial candidate sequences of emoji for the Delphi process were constructed referring to 2 well-validated FPSs (Wong-Baker FACES pain rating scale [Wong-Baker FACES] and faces pain scale-revised [FPS-R]). Then, a prospective cohort of patients scheduled to receive perianal surgery was recruited and asked to complete a web-based questionnaire on a mobile device at 5 time points (before surgery [T1], wake up after surgery [T2], 4 hours after surgery [T3], the second day after surgery [T4], and 15 minutes after T4 [T5]). The 4 well-validated pain scales (NRS, VAS, Wong-Baker FACES, and FPS-R) were used as reference scales.

RESULTS

After 2 rounds of surveys on 40 Delphi panelists, an Emoji-FPS was finally determined to represent 6 pain levels (0, 2, 4, 6, 8, and 10) from "no hurt" to "hurts worst." For validation, 300 patients were recruited and 299 were analyzed, the mean age of whom was 38.5 (SD 10.5) years, and 106 (35.5%) were women. For concurrent validity, the Emoji-FPS was highly correlated with 4 reference scales with Spearman correlation coefficient ρ ranging from 0.91 to 0.95. Excellent agreements were observed between 4 versions of Emoji-FPS (iOS, Android, Microsoft, and OpenMoji), with weighted κ coefficients ranging from 0.96 to 0.97. For discriminant validity, patients' mean preoperative Emoji-FPS score (T1) was significantly higher than their postoperative Emoji-FPS score (T4) with a difference of 1.4 (95% CI 1.3-1.6; P<.001). For test-retest reliability, Emoji-FPS scores measured at T4 and T5 were highly correlated with a ρ of 0.91. The Emoji-FPS was mostly preferred, followed by the Wong-Baker FACES, FPS-R, NRS, and VAS.

CONCLUSIONS

The Emoji-FPS is reliable and valid compared with traditional pain scales in adult surgery patients.

Do pain management apps use evidence-based psychological components? A systematic review of app content and quality

Background

With hundreds of pain management apps on the Canadian marketplace, it can be challenging for patients and clinicians to select effective and evidence-based mobile health (mHealth) apps that address pain from a biopsychosocial perspective.

Aims

The aim of this study is to identify pain management apps within the Canadian app marketplaces to aid clinicians in recommending apps.

Methods

The iOS and Android marketplaces were systematically searched to identify pain management apps that included at least one core component of cognitive behavioral therapy (CBT) or mindfulness- and acceptance-based therapies. Selected apps were assessed using a researcher developed psychological components checklist, and the Mobile App Rating Scale (MARS). These two measures provided a robust assessment of the apps' technical abilities and psychological principles being implemented.

Results

Five hundred eight pain management apps were identified, yet only 12 included a psychological component and were available for evaluation. On average, apps contained 8.10 out of 18 psychological components (SD = 2.77) with a MARS quality rating of 4.02 out of 5 (SD = 0.32). The most common psychological components were grounded in CBT, including psychoeducation, sleep hygiene, behavioral activation, coping skills training, and social support. Among the least commonly included components were goal setting, values, and culture/diversity. Two-thirds of the apps involved health care practitioners in their development, but independent scientific review of apps was scarce.

Conclusion

The highest scoring apps (Curable, Pathways, Vivify) are highlighted for health care practitioners who may wish to recommend mHealth technologies to their patients for pain management. Future directions for research and app development are discussed.

A systematic evaluation of primary headache management apps leveraging behavior change techniques

BACKGROUND

Mobile health apps have the potential to promote adherence to headache management through the use of evidence-based behavior change techniques (e.g., self-monitoring). While many headache management apps exist, the extent to which these apps include behavior change techniques remains unknown. Thus, the present study systematically evaluated the content and quality of commercially available headache management apps.

METHODS

Headache apps were identified using a systematic search in the Apple App and Google Play stores. A total of 55 apps were evaluated using the taxonomy of behavior change techniques and app quality using the Mobile App Rating Scale.

RESULTS

Headache management apps included 0-14 behavior change techniques (Mean [M] = 5.89) and 0-8 headache management behavior change techniques (M = 4.29). App quality ranged from 2.84-4.67 (M = 3.73) out of 5.00. Three apps, Migraine Trainer, Easeday: Headache & Migraine, and PainScale, included the highest number of overall and headache management behavior change techniques along with good quality scores.

CONCLUSIONS

While randomized controlled trials are necessary to determine the efficacy of individual headache apps, most existing apps include evidence-based headache management behavior change techniques. Headache apps often focus on either self-monitoring or stress management via relaxation training, suggesting that patients' needs should be used to inform app selection.

eDOL mHealth App and Web Platform for Self-monitoring and Medical Follow-up of Patients With Chronic Pain: Observational Feasibility Study

BACKGROUND

Chronic pain affects approximately 30% of the general population, severely degrades quality of life (especially in older adults) and professional life (inability or reduction in the ability to work and loss of employment), and leads to billions in additional health care costs. Moreover, available painkillers are old, with limited efficacy and can cause significant adverse effects. Thus, there is a need for innovation in the management of chronic pain. Better characterization of patients could help to identify the predictors of successful treatments, and thus, guide physicians in the initial choice of treatment and in the follow-up of their patients. Nevertheless, current assessments of patients with chronic pain provide only fragmentary data on painful daily experiences. Real-life monitoring of subjective and objective markers of chronic pain using mobile health (mHealth) programs can address this issue.

OBJECTIVE

We hypothesized that regular patient self-monitoring using an mHealth app would lead physicians to obtain deeper understanding and new insight into patients with chronic pain and that, for patients, regular self-monitoring using an mHealth app would play a positive therapeutic role and improve adherence to treatment. We aimed to evaluate the feasibility and acceptability of a new mHealth app called eDOL.

METHODS

We conducted an observational study to assess the feasibility and acceptability of the eDOL tool. Patients completed several questionnaires using the tool over a period of 2 weeks and repeated assessments weekly over a period of 3 months. Physicians saw their patients at a follow-up visit that took place at least 3 months after the inclusion visit. A composite criterion of the acceptability and feasibility of the eDOL tool was calculated after the completion of study using satisfaction surveys from both patients and physicians.

RESULTS

Data from 105 patients (of 133 who were included) were analyzed. The rate of adherence was 61.9% (65/105) after 3 months. The median acceptability score was 7 (out of 10) for both patients and physicians. There was a high rate of completion of the baseline questionnaires and assessments (mean 89.3%), and a low rate of completion of the follow-up questionnaires and assessments (63.8% (67/105) and 61.9% (65/105) respectively). We were also able to characterize subgroups of patients and determine a profile of those who adhered to eDOL. We obtained 4 clusters that differ from each other in their biopsychosocial characteristics. Cluster 4 corresponds to patients with more disabling chronic pain (daily impact and comorbidities) and vice versa for cluster 1.

CONCLUSIONS

This work demonstrates that eDOL is highly feasible and acceptable for both patients with chronic pain and their physicians. It also shows that such a tool can integrate many parameters to ensure the detailed characterization of patients for future research works and pain management.

TRIAL REGISTRATION

ClinicalTrial.gov NCT03931694; http://clinicaltrials.gov/ct2/show/NCT03931694.

Research approaches for evaluating opioid sparing in clinical trials of acute and chronic pain treatments: Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials recommendations

ABSTRACT

Randomized clinical trials have demonstrated the efficacy of opioid analgesics for the treatment of acute and chronic pain conditions, and for some patients, these medications may be the only effective treatment available. Unfortunately, opioid analgesics are also associated with major risks (eg, opioid use disorder) and adverse outcomes (eg, respiratory depression and falls). The risks and adverse outcomes associated with opioid analgesics have prompted efforts to reduce their use in the treatment of both acute and chronic pain. This article presents Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) consensus recommendations for the design of opioid-sparing clinical trials. The recommendations presented in this article are based on the following definition of an opioid-sparing intervention: any intervention that (1) prevents the initiation of treatment with opioid analgesics, (2) decreases the duration of such treatment, (3) reduces the total dosages of opioids that are prescribed for or used by patients, or (4) reduces opioid-related adverse outcomes (without increasing opioid dosages), all without causing an unacceptable increase in pain. These recommendations are based on the results of a background review, presentations and discussions at an IMMPACT consensus meeting, and iterative drafts of this article modified to accommodate input from the co-authors. We discuss opioid sparing definitions, study objectives, outcome measures, the assessment of opioid-related adverse events, incorporation of adequate pain control in trial design, interpretation of research findings, and future research priorities to inform opioid-sparing trial methods. The considerations and recommendations presented in this article are meant to help guide the design, conduct, analysis, and interpretation of future trials.

Development and Feasibility Testing of an Animated Cartoon-Based Self-Care Application for Low-Back Pain – a Pilot Study

Objectives: Use of animated cartoon for pain management is an emerging area, however, no study have explored it as a digital platform for rehabilitation of low-back pain (LBP). This study was aimed to develop and evaluate the feasibility of an animated cartoon-based self-care (ACBSC) app for LBP, and to examine the correlation between the app rating parameters and patients’ pain. Methods: This two-phase study comprised a development and feasibility testing components. Development of the ACBSC app was based on Mckenzie’s Mechanical Diagnosis and Therapy (MDT) extension protocolplus back hygiene following standard iteration and prototyping process. Twenty-eight consecutive patients with chronic non-specific LBP with 'direction Preference’ for extension based on the MDT screening algorithm participated in the feasibility phase. The participants utilized the cartoon-based app thrice weekly for two weeks. Outcomes were assessed in terms of usability, satisfaction and user’s experience using the system usability scale and mobile application rating scale. Quadruple visual analogue scale was used to assess pain intensity of the participants. Results: On a unified scale of 20, functionality (15.4 ± 2.41) and aesthetics 14 ± 2.00 had highest and least objective quality rating on the app parameters. Total objective and subjective quality rating of the app was 16.9 ± 1.97 and 15.6 ± 2.42 respectively. Total impact and usability score was 24.1 ± 3.39 (out of 30) and 27.8 ± 3.09 (out of 50). Participants reported that back care cartoon app mostly affect mindfulness/meditation/relaxation (42.9%), increases happiness/well-being (46.4%), leads to behavioural change (60.7%) and targets physical health (100%). There was no significant correlation between participants’ pain characteristics and app rating parameters (p>0.05). Conclusion: The animated cartoon-based self-care LBP app has moderate to high usability, functionality, aesthetics and quality rating, and may serve as an effective mobile-app for self-management of long-term LBP.

A Brief Psychological Intervention for Chronic Pain in Primary Care: A Pilot Randomized Controlled Trial

OBJECTIVE

Although evidence-based psychological interventions improve chronic pain, many patients do not engage in behavioral health services. Offering a brief intervention in a medical setting may provide benefits to patients with chronic pain. The purpose of this study was to examine preliminary outcomes of a brief psychological intervention for chronic pain delivered in primary care.

DESIGN

Pilot randomized controlled trial.

SETTING

Primary care clinic.

SUBJECTS

Sixty participants with chronic pain were randomized to a 5-session psychological intervention or treatment-as-usual control group.

METHODS

Participants completed pre- and post-intervention measures assessing pain severity, pain interference, pain catastrophizing, depression, and anxiety.

RESULTS

Most participants (76.7%) randomized to the intervention completed all sessions. Compared to the control group, those in the intervention had decreases in pain severity (P = .048), pain catastrophizing (P = .04), and depression (P = .01) from pre- to post-intervention. Within the intervention group, there was a significant improvement in pain interference scores (P = 0.02). Within the intervention group, effect sizes were medium to large for changes in pain severity, pain interference, pain catastrophizing, and depression scores. There were no significant changes in anxiety scores.

CONCLUSION

Results suggest that delivery of a brief psychological intervention for chronic pain in primary care appears to offer improvements in pain severity, pain interference, pain catastrophizing, and depression. Findings suggest that shorter-term psychological interventions may offer similar benefits as longer-term ones. Furthermore, offering a brief intervention in primary care may increase access and engagement in behavioral pain management services. Future research should examine this through a fully-powered trial with longer-term outcomes.

User-Centered Development of a Mobile App for Biopsychosocial Pain Assessment in Adults: Usability, Reliability, and Validity Study

Background

Pain-related mobile apps targeting pain assessment commonly limit pain assessment to pain behaviors and physiological aspects. However, current guidelines state that pain assessment should follow the biopsychosocial model, clearly addressing biological, psychological, and social aspects of the pain experience. Existing reviews also highlight that pain specialists and end users are not commonly involved in the development process of mobile apps for pain assessment, negatively affecting the quality of the available apps.

Objective

This study aimed to develop a mobile app for pain assessment (AvaliaDor) and assess its usability, validity, reliability, and measurement error in a sample of real patients with chronic pain recruited from a physiotherapy clinic.

Methods

This study was divided into 2 phases: phase 1—development of the AvaliaDor app; and phase 2—assessment of the apps’ usability, reliability, measurement error, and validity. AvaliaDor was developed (phase 1) based on the literature and the recommendations of physiotherapists and patients with pain in cycles of evaluation, inclusion of recommendations, and reevaluation until no further changes were required. The final version of the app was then tested in patients with musculoskeletal pain attending a private physiotherapy practice (phase 2) who were asked to use the app twice on 2 consecutive days for reliability purposes. In addition, participants had to complete a set of paper-based scales (Brief Pain Inventory, painDETECT, Pain Catastrophizing Scale, and Tampa Scale for Kinesiophobia), which were used to assess the validity (criterion validity and hypothesis testing) of the app, and the Post-Study System Usability Questionnaire was used to assess its usability.

Results

The development process (phase 1) included 5 physiotherapists external to the research team and 5 patients with musculoskeletal pain, and it resulted in the creation of an app named AvaliaDor, which includes an assessment of pain intensity, location, and phenotype; associated disability; and the issues of pain catastrophizing and fear of movement. A total of 52 patients with pain (mean age 50.12 years, SD 11.71 years; 39 females) participated in phase 2 and used the app twice. The Pearson correlation coefficient between the scores on the paper-based scales and the app ranged between 0.81 and 0.93 for criterion validity and between 0.41 and 0.59 for hypothesis testing. Test-retest reliability was moderate to good (intraclass correlation coefficient between 0.67 and 0.90) and the score for usability was 1.16 (SD 0.27), indicating good usability.

Conclusions

A mobile app named AvaliaDor was developed to assess the intensity, location, and phenotype of pain; associated disability; and the issues of pain catastrophizing and fear of movement in a user-centered design process. The app was shown to be usable, valid, and reliable for assessing pain from a biopsychosocial perspective in a heterogeneous group of patients with pain. Future work can explore the long-term use of AvaliaDor in clinical contexts and its advantages for the assessment and management of patients with pain.

Health care providers' experiences of pain management and attitudes towards digitally supported self-management interventions for chronic pain: a qualitative study

BACKGROUND

Chronic pain constitutes a significant burden for the individuals affected, and is a frequent reason why patients seek health care services. While in-person psychosocial interventions can be of support to people living with chronic pain, such interventions are not always accessible. eHealth interventions may provide greater accessibility, but the evidence and use of digital self-management solutions for chronic pain are still limited and the lack of health care provider input in the development process of such solutions a concern. Therefore, the aim of the current study was to investigate health care providers' experiences of treating patients with chronic pain, their attitudes towards, and use of, digital solutions in pain management, and their suggestions for content and design elements for a potential digital pain self-management intervention.

METHODS

Twelve health care providers representing a variety of health care disciplines participated in semi-structured interviews. The interviews were analyzed using thematic analysis.

RESULTS

The material was analyzed into three main themes: [1] Patients with chronic pain and their current use of the health care services, [2] Health care providers' own motivation and impression of patient prerequisites for use of digital self-management interventions, and [3] Suggestions for content and design elements in a digital self-management intervention for people living with chronic pain. The challenges faced by patients living with chronic pain were described as numerous. Despite interest and positive attitudes, few of the health care providers had used or recommended eHealth solutions to their patients. A range of potential content and functionality elements were identified, including aspects of motivation and engagement and providers also emphasized the importance of easy access and positive, personal content to support existing treatment.

CONCLUSIONS

This study offers insights into health care providers' considerations for the potential of digital self-management interventions supporting patients living with chronic pain. Findings indicate the need for change and a more comprehensive treatment approach to pain management. eHealth solutions may contribute to such change, and providers pointed to a need for health care provider involvement, timely support and follow-up as important factors for integrating digital pain self-management interventions into clinical care.

TRIAL REGISTRATION

ClinicalTrials.gov : NCT03705104.

Systematic evaluation of commercially available pain management apps examining behavior change techniques

ABSTRACT

Mobile health (mHealth) apps have the potential to enhance pain management through the use of daily diaries, medication and appointment reminders, education, and facilitating communication between patients and providers. Although many pain management apps exist, the extent to which these apps use evidence-based behavior change techniques (BCTs) remains largely unknown, making it nearly impossible for providers to recommend apps with evidence-based strategies. This study systematically evaluated commercially available pain management apps for evidence-based BCTs and app quality. Pain management apps were identified using the search terms "pain" and "pain management" in the App and Google Play stores. Reviewed apps were specific to pain management, in English, for patients, and free. A total of 28 apps were coded using the taxonomy of BCTs. App quality was assessed using the Mobile App Rating Scale. Apps included 2 to 15 BCTs (M = 7.36) and 1 to 8 (M = 4.21) pain management-specific BCTs. Prompt intention formation, instruction, behavioral-health link, consequences, feedback, and self-monitoring were the most common BCTs used in the reviewed apps. App quality from the Mobile App Rating Scale ranged from 2.27 to 4.54 (M = 3.65) out of a possible 5, with higher scores indicating better quality. PainScale followed by Migraine Buddy demonstrated the highest number of overall and pain management BCTs as well as good quality scores. Although existing apps should be assessed through randomized controlled trials and future apps should include capabilities for electronic medical record integration, current pain management apps often use evidence-based pain management BCTs.

Mobile Health-Collected Biophysical Markers in Children with Serious Illness-Related Pain

Context: There is an ongoing established need to develop engaging pain assessment strategies to provide more effective individualized care to pediatric patients with serious illnesses. This study explores the acceptability of wireless devices as one option. Objective: To evaluate the ability of wrist-wearable technology to collect physiological data from children with serious illnesses. Methods: Single-site prospective observational study conducted between September 2017 and September 2018 at Rady Children's Hospital, San Diego, California, inpatient wards. Pediatric patients with diagnoses of cancer and sickle cell disease admitted to the hospital for acute-on-chronic pain and taking opioid pain medications were asked to complete two 24-hour continuous monitoring periods with the Empatica E4 wristband. Results: Data collected from the device correlated with manually obtained vital signs. Children responded favorably to wearing the device. Participants with reported subjective pain versus no pain had average heart rate increased by 16.4 bpm, skin temperature decreased by 3.5°C, and electrodermal activity decreased by 0.27. Conclusions: This study shows the possibility of collecting continuous biophysical data in a nonobtrusive manner in seriously ill children experiencing acute-on-chronic pain using wearable devices. It provides the framework for larger studies to explore the utility of such data in relation to metrics of pain and suffering in this patient population.

mHealth for pediatric chronic pain: state of the art and future directions

INTRODUCTION

Chronic pain conditions are common among children and engender cascading effects across social, emotional, and behavioral domains for the child and family. Mobile health (mHealth) describes the practice of delivering healthcare via mobile devices and may be an ideal solution to increase access and reach of evidence-based behavioral health interventions.

AREAS COVERED

The aim of this narrative review is to present a state-of-the-art overview of evidence-based mHealth efforts within the field of pediatric chronic pain and consider new and promising directions for study. Given the nascent nature of the field, published mHealth interventions in all stages of development are discussed. Literature was identified through a non-systematic search in PubMed and Google Scholar, and a review of reference lists of papers that were identified as particularly relevant or foundational (within and outside of the chronic pain literature).

EXPERT OPINION

mHealth is a promising interventional modality with early evidence suggesting it is primed to enhance behavioral health delivery and patient outcomes. There are many exciting future directions to be explored including drawing inspiration from digital health technology to generate new ways of thinking about the optimal treatment of pediatric chronic pain.

Telemonitoring in Chronic Pain Management Using Smartphone Apps: A Randomized Controlled Trial Comparing Usual Assessment against App-Based Monitoring with and without Clinical Alarms

BACKGROUND

The usefulness of mHealth in helping to target face-to-face interventions for chronic pain more effectively remains unclear. In the present study, we aim to test whether the Pain Monitor mobile phone application (app) is well accepted by clinicians, and can help improve existent medical treatments for patients with chronic musculoskeletal pain. Regarding this last goal, we compared three treatment conditions, namely usual treatment, usual treatment with an app without alarms and usual treatment with an app with alarms. All treatments lasted one month. The three treatments were compared for all outcomes, i.e., pain severity and interference, fatigue, depressed mood, anxiety and anger.

METHODS

In this randomized controlled trial, the usual monitoring method (i.e., onsite; n = 44) was compared with daily ecological momentary assessment using the Pain Monitor app-both with (n = 43) and without alarms (n = 45). Alarms were sent to the clinicians in the presence of pre-established undesired clinical events and could be used to make treatment adjustments throughout the one-month study.

RESULTS

With the exception of anger, clinically significant changes (CSC; 30% improvement) were greater in the app + alarm condition across outcomes (e.g., 43.6% of patients experienced a CSC in depressed mood in the app + alarm condition, which occurred in less than 29% of patients in the other groups). The clinicians were willing to use the app, especially the version with alarms.

CONCLUSIONS

The use of apps may have some benefits in individual health care, especially when using alarms to tailor treatments.

Pain Management Best Practices from Multispecialty Organizations During the COVID-19 Pandemic and Public Health Crises

BACKGROUND

It is nearly impossible to overestimate the burden of chronic pain, which is associated with enormous personal and socioeconomic costs. Chronic pain is the leading cause of disability in the world, is associated with multiple psychiatric comorbidities, and has been causally linked to the opioid crisis. Access to pain treatment has been called a fundamental human right by numerous organizations. The current COVID-19 pandemic has strained medical resources, creating a dilemma for physicians charged with the responsibility to limit spread of the contagion and to treat the patients they are entrusted to care for.

METHODS

To address these issues, an expert panel was convened that included pain management experts from the military, Veterans Health Administration, and academia. Endorsement from stakeholder societies was sought upon completion of the document within a one-week period.

RESULTS

In these guidelines, we provide a framework for pain practitioners and institutions to balance the often-conflicting goals of risk mitigation for health care providers, risk mitigation for patients, conservation of resources, and access to pain management services. Specific issues discussed include general and intervention-specific risk mitigation, patient flow issues and staffing plans, telemedicine options, triaging recommendations, strategies to reduce psychological sequelae in health care providers, and resource utilization.

CONCLUSIONS

The COVID-19 public health crisis has strained health care systems, creating a conundrum for patients, pain medicine practitioners, hospital leaders, and regulatory officials. Although this document provides a framework for pain management services, systems-wide and individual decisions must take into account clinical considerations, regional health conditions, government and hospital directives, resource availability, and the welfare of health care providers.

Telemedicine for chronic pain management during COVID-19 pandemic

Treatment of chronic pain is an essential service. Due to lockdown, travel restrictions, social and physical distancing requirements or fear that health care facilities may be infected; patients may avoid visiting health care facilities in person. It is also imperative to decrease the risk of exposure of the health care workers (HCWs) to severe acute respiratory syndrome corona virus 2 (SARS CoV2) and to ease the overtly burdened health care system. But any disruption in pain practice will have alarming consequences for individuals, society, and whole of health care system and providers. In the current scenario of COVID-19 pandemic, telemedicine is emerging as a key technology for efficient communication and sustainable solution to provide essential health care services and should be considered for chronic pain patients (CPPs). Recently, Board of Governors in supersession of Medical Council of India along with National Institution for Transforming India (NITI Aayog) released “Telemedicine Practice Guidelines” enabling registered medical practitioners to provide healthcare using telemedicine. This article describes the challenges in CPPs during COVID-19 pandemic and the use of telemedicine as the rescue management vehicle for CPPs in current scenario.

Enablers and barriers of people with chronic musculoskeletal pain for engaging in telehealth interventions: protocol for a qualitative systematic review and meta-synthesis

BACKGROUND

Chronic musculoskeletal pain represents an enormous burden in society. Best-practice care for chronic musculoskeletal pain suggests adoption of self-management strategies. Telehealth interventions (e.g., videoconferencing) are a promising approach to promote self-management and have the potential to overcome geographical barriers between patient and care providers. Understanding patient perspectives will inform and identify practical challenges towards applying the self-management strategies delivered via telehealth to everyday lives. The aim of this study is to synthesize the perceptions of individuals with musculoskeletal pain with regards to enablers and barriers to engaging in telehealth interventions for chronic musculoskeletal pain self-management.

METHODS

A systematic review of qualitative studies will be performed based on searches of MEDLINE, EMBASE, CINAHL, LILACS, and PsycINFO databases. Screening of identified titles will be conducted by two independent investigators. Data extraction will retrieve detailed qualitative information from selected articles. The critical appraisal skills program (CASP) checklist will be used for critical appraisal of included studies, and the level of confidence in the findings will be assessed using the confidence in the evidence from reviews of qualitative research (GRADE-CERQual). A thematic synthesis approach will be used to derive analytical themes.

DISCUSSION

This review will systematically identify, synthesize, and present enablers and barriers reported by people with musculoskeletal pain to engage in telehealth interventions. The review will provide information required to support the design and improvement of telehealth services.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42019136148.

Digital Care for Chronic Musculoskeletal Pain: 10,000 Participant Longitudinal Cohort Study

BACKGROUND

Chronic musculoskeletal pain has a vast global prevalence and economic burden. Conservative therapies are universally recommended but require patient engagement and self-management to be effective.

OBJECTIVE

This study aimed to evaluate the efficacy of a 12-week digital care program (DCP) in a large population of patients with chronic knee and back pain.

METHODS

A longitudinal observational study was conducted using a remote DCP available through a mobile app. Subjects participated in a 12-week multimodal DCP incorporating education, sensor-guided exercise therapy (ET), and behavioral health support with 1-on-1 remote health coaching. The primary outcome was pain measured by the visual analog scale (VAS). Secondary measures included engagement levels, program completion, program satisfaction, condition-specific pain measures, depression, anxiety, and work productivity.

RESULTS

A total of 10,264 adults with either knee (n=3796) or low back (n=6468) pain for at least three months were included in the study. Participants experienced a 68.45% average improvement in VAS pain between baseline intake and 12 weeks. In all, 73.04% (7497/10,264) participants completed the DCP into the final month. In total, 78.60% (5893/7497) of program completers (7144/10,264, 69.60% of all participants) achieved minimally important change in pain. Furthermore, the number of ET sessions and coaching interactions were both positively associated with improvement in pain, suggesting that the amount of engagement influenced outcomes. Secondary outcomes included a 57.9% and 58.3% decrease in depression and anxiety scores, respectively, and 61.5% improvement in work productivity. Finally, 3 distinct clusters of pain response trajectories were identified, which could be predicted with a mean 76% accuracy using baseline measures.

CONCLUSIONS

These results support the efficacy and scalability of a DCP for chronic low back and knee pain in a large, diverse, real-world population. Participants demonstrated high completion and engagement rates and a significant positive relationship between engagement and pain reduction was identified, a finding that has not been previously demonstrated in a DCP. Furthermore, the large sample size allowed for the identification of distinct pain response subgroups, which may prove beneficial in predicting recovery and tailoring future interventions. This is the first longitudinal digital health study to analyze pain outcomes in a sample of this magnitude, and it supports the prospect for DCPs to serve the overwhelming number of musculoskeletal pain sufferers worldwide.

Clinical Integration of a Smartphone App for Patients With Chronic Pain: Retrospective Analysis of Predictors of Benefits and Patient Engagement Between Clinic Visits

Background

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.

Objective

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.

Methods

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.

Results

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 (P<.05) compared with patients showing lower engagement. Patients completing a small number of daily assessments reported less pain intensity, less daily activity interference, and less pain-related disability on average and were less likely to use the two-way messaging than those who were more engaged with the pain app (P<.05).

Conclusions

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.

Benefits of Mobile Apps for Cancer Pain Management: Systematic Review

Background

Pain ratings reported by patients with cancer continue to increase, and numerous computer and phone apps for managing cancer-related pain have been developed recently; however, whether these apps effectively alleviate patients’ pain remains unknown.

Objective

This study aimed to comprehensively evaluate the role of mobile apps in the management of cancer pain.

Methods

Literature on the use of apps for cancer pain management and interventions, published before August 2019, was retrieved from the following databases: MEDLINE, Embase, Cochrane, CINAHL, Scopus, and PsycINFO. The effects of apps on cancer pain were evaluated using RevMan5.3 software, and the rates of adverse drug reactions were analyzed using the R Statistical Software Package 3.5.3.

Results

A total of 13 studies were selected for the analysis: 5 randomized controlled trials (RCTs), 4 before-after studies, 2 single-arm trials, 1 prospective cohort study, and 1 prospective descriptive study. The 5 RCTs reported data for 487 patients (240 patients in the intervention group and 247 patients in the control group), and the remaining studies reported data for 428 patients. We conducted a meta-analysis of the RCTs. According to the meta-analysis, apps can significantly reduce pain scores (mean difference [MD]=–0.50, 95% CI –0.94 to –0.07, I²=62%, P=.02). We then used apps that have an instant messaging module for subgroup analysis; these apps significantly reduced patients’ pain scores (MD=–0.67, 95% CI –1.06 to –0.28, I²=57%, P<.01). Patients using apps without an instant messaging module did not see a reduction in the pain score (MD=0.30, 95% CI –1.31 to 1.92, I²=70%, P=.71). Overall, patients were highly satisfied with using apps. Other outcomes, such as pain catastrophizing or quality of life, demonstrated greater improvement in patients using apps with instant messaging modules compared with patients not using an app.

Conclusions

The use of apps with instant messaging modules is associated with reduced pain scores in patients with cancer-related pain, and patient acceptance of these apps is high. Apps without instant messaging modules are associated with relatively higher pain scores. The presence of an instant messaging module may be a key factor affecting the effect of an app on cancer pain.

Use of Mobile Health Apps and Wearable Technology to Assess Changes and Predict Pain During Treatment of Acute Pain in Sickle Cell Disease: Feasibility Study

BACKGROUND

Sickle cell disease (SCD) is an inherited red blood cell disorder affecting millions worldwide, and it results in many potential medical complications throughout the life course. The hallmark of SCD is pain. Many patients experience daily chronic pain as well as intermittent, unpredictable acute vaso-occlusive painful episodes called pain crises. These pain crises often require acute medical care through the day hospital or emergency department. Following presentation, a number of these patients are subsequently admitted with continued efforts of treatment focused on palliative pain control and hydration for management. Mitigating pain crises is challenging for both the patients and their providers, given the perceived unpredictability and subjective nature of pain.

OBJECTIVE

The objective of this study was to show the feasibility of using objective, physiologic measurements obtained from a wearable device during an acute pain crisis to predict patient-reported pain scores (in an app and to nursing staff) using machine learning techniques.

METHODS

For this feasibility study, we enrolled 27 adult patients presenting to the day hospital with acute pain. At the beginning of pain treatment, each participant was given a wearable device (Microsoft Band 2) that collected physiologic measurements. Pain scores from our mobile app, Technology Resources to Understand Pain Assessment in Patients with Pain, and those obtained by nursing staff were both used with wearable signals to complete time stamp matching and feature extraction and selection. Following this, we constructed regression and classification machine learning algorithms to build between-subject pain prediction models.

RESULTS

Patients were monitored for an average of 3.79 (SD 2.23) hours, with an average of 5826 (SD 2667) objective data values per patient. As expected, we found that pain scores and heart rate decreased for most patients during the course of their stay. Using the wearable sensor data and pain scores, we were able to create a regression model to predict subjective pain scores with a root mean square error of 1.430 and correlation between observations and predictions of 0.706. Furthermore, we verified the hypothesis that the regression model outperformed the classification model by comparing the performances of the support vector machines (SVM) and the SVM for regression.

CONCLUSIONS

The Microsoft Band 2 allowed easy collection of objective, physiologic markers during an acute pain crisis in adults with SCD. Features can be extracted from these data signals and matched with pain scores. Machine learning models can then use these features to feasibly predict patient pain scores.

Validity, Reliability, Feasibility, and Usefulness of Pain Monitor: A Multidimensional Smartphone App for Daily Monitoring of Adults With Heterogenous Chronic Pain

OBJECTIVES

Ecological momentary assessment has been recommended in the management of chronic pain. Smartphone apps might be a useful tool for that purpose. This goal of this study was to develop and test a multidimensional smartphone app for adults with chronic pain. A multidisciplinary team developed the app content after a series of meetings, considering clinical guidelines for pain measurement. The content included pain intensity and interference, fatigue, mood, perceived health status, activity level, side effects of the medication, use of rescue medication, and pain-related sychological constructs (catastrophizing, acceptance, fear, and coping).

METHODS

Thirty-eight participants (21 to 59 y) used the app, called Pain Monitor, twice a day during 30 consecutive days. Patients completed a set of well-established measures at the beginning and end of the study via paper-and-pencil. Weekly phone assessments were also made for pain intensity, pain interference, fatigue, and mood.

RESULTS

Construct validity was revealed by moderate-to-strong correlations between app content and traditional measures. Feasibility was supported by high compliance (between 70% and 82%) and high acceptability and ease of use. Both side effects of the medication and use of rescue medication were found to be useful tools to guide treatment.

DISCUSSION

The new assessment protocol in the app allows for an easy and rapid multidimensional assessment of chronic pain patients.

Online teletherapy for chronic pain: A systematic review

OBJECTIVE

A systematic review designed to evaluate the benefits of remote group pain management for persons with chronic pain was performed.

METHODS

PubMed, EMBASE and PsychINFO databases were searched in April 2019. Eligible studies evaluated teletherapy for chronic pain based on set inclusion and exclusion criteria. Two reviewers independently screened eligible studies, assessed risk of bias and extracted data. Each study design was rated and study quality was assessed using an 11-point scale of methodological quality.

RESULTS

Comprehensive searches identified 12 studies that met all inclusion/exclusion criteria and each study was assessed for type of technology, study design, outcome measures, study findings and limitations. No published studies investigated synchronous teletherapy for groups of chronic pain patients. Methods of assessment varied considerably across studies. Strength of evidence was moderate and many of the selected studies had issues with treatment compliance/adherence and selection bias. Teletherapy strategies for persons with chronic pain were shown to improve pain, mood, disability and catastrophising, however half of the studies selected did not meet the criteria for acceptable standards for internal validity. Those trials with limited therapist involvement appeared to be less beneficial and tended to report lower adherence than those which had higher levels of therapist guidance or peer support.

CONCLUSIONS

Preliminary findings suggest that teletherapy and remote online cognitive behavioural therapy strategies can be effective in improving quality of life among persons with chronic pain, although the overall quality of evidence is moderate. Controlled trials are needed to assess live remote teletherapy for chronic pain.

Internet of Things Applied in Healthcare Based on Open Hardware with Low-Energy Consumption

Objectives

The Internet of Things (IoT) and its applications are growing simultaneously. These applications need new intelligent devices along heterogeneous networking. Which makes them costly to implement indeed. Platforms and open devices designed for open-source hardware are possible solutions. This research was conducted under an IoT design, implementation, and assessment model for the remote monitoring of pulse oximetry via oxygen partial saturation (SpO₂) and heart rate (HR) with low-energy consumption.

Methods

This study focused on the development of SpO₂ and HR measurements that will allow the monitoring and estimation in real time of the user's state and health related to the established parameters. Measurements were acquired and recorded using a remote web server that recorded the acquired variables for further processing. The statistical analysis data allows comparison of the registered data measured with theoretical models.

Results

The IoT model was developed use Bluetooth low-energy devices, which comply with low-cost and open-hardware solutions operated via ‘HTTP requests’ for data transmission and reception from a cloud server to an edge device. Network performance assessment was conducted to guarantee the availability and integrity of the acquired values and signals. The system measured SpO₂ and HR variables. The most significant result was to achieve energy consumption 20% lower than that of devices in the market.

Conclusions

In summary, the acquired data validation based on the IoT model had a transmission error of 0.001% which proves its applicability in healthcare.

Treating chronic pain and opioid misuse disorder among underserved populations in Colorado

The increased use of prescription opioids has resulted in widespread misuse. As a result, more than 40,000 Americans lost their lives to opiate overdose in 2016 alone. These data have led to a national movement focused on appropriate opioid prescribing practices. The Centers for Disease Control and Prevention (CDC) developed its Guidelines for Prescribing Opioids for Chronic Pain (2017), a template for pain management and substance assessment in primary care. These CDC guidelines aim to prevent misuse/deaths and early identification of substance use disorders. Although the guidelines are appropriate for initiation of opioid therapy, they are not sufficient to manage patients who have already developed misuse disorders. Other modalities such as medication-assisted treatment (MAT) have been described as beneficial for patients with high risk for or who have an opioid misuse disorder. This article builds on the CDC's 2017 advisory document by applying it in praxis: first, non-opioid medication therapy options and nonmedication therapy options are explored; next, a case study is presented of an integrated primary care-managed patient who presented with both chronic pain and established opioid use disorder. Although the CDC guidelines were not followed in the patient's initial prescription opioid treatment regimen, those guidelines were used as a starting point for follow-up treatment, helping both to assess the patient's risk for opioid misuse disorder and to determine that MAT was an appropriate method of treatment.

Mobile applications for pain management: an app analysis for clinical usage

BACKGROUND

Pain is the most common and distressing symptom for patients in all clinical settings. The dearth of health informatics tools to support acute and chronic pain management may be contributing to the chronic pain and opioid abuse crises. The purpose of this study is to qualitatively evaluate the content and functionality of mobile pain management apps.

METHODS

The Apple App Store and the Google Play Store were searched to identify pain management apps. The inclusion criteria were as follows: (1) that apps include a pain diary function allowing users to record pain episodes, (2) are available in either Apple App Store or Google Play Store, and (3) are available in the English language. We excluded apps if they were limited to only specific forms of pain or specific diseases.

RESULTS

A total of 36 apps met the inclusion criteria. Most of the apps served as pain diary tools to record the key characteristics of pain. The pain diary features of the apps were grouped into nine categories: the recordings of pain intensity, pain location, pain quality, pain's impacts on daily life, other features of pain, other related symptoms, medication, patients' habits and basic information, and other miscellaneous functions. The apps displayed various problems in use. The problem of not involving healthcare professionals in app development has not been resolved. Approximately 31% of apps including a pain diary function engaged clinicians in app development. Only 19% involved end-users in development and then only in an ad-hoc way. Only one third of the apps supported the cross-platforms, none of the apps supported clinician access to graphical pain data visualization, none secured HIPAA compliance, and none endorsed the PEG tool for primary care physicians' chronic pain management.

CONCLUSIONS

Most of the 36 pain management apps demonstrated various problems including user interface and security. Many apps lacked clinician and end-user involvement in app development impacting the clinical utility of these apps. We could not find any pain apps suitable for clinical usage despite high demand from clinicians due to the US opioid crisis.

A Systematic Literature Review of the Design Approach and Usability Evaluation of the Pain Management Mobile Applications

The increasing popularity of mHealth is a promising opportunity for pain self-management. Mobile apps can be easily developed, but understanding the design and usability will result in apps that can retain more users. This research aims at identifying, analyzing, and synthesizing the current state-of-the-art of: (a) the design approach and (b) usability assessment of pain management mobile applications. A systematic literature review was conducted on 27 studies retrieved from Medline, PubMed, EMBASE, Web of Science, and Scopus. The review revealed that most of the apps were for chronic pain. No app was specifically for men or for the elderly. None of the studies involved expert-based system inspection methods. Only one study used two different approaches of automated and empirical evaluation. We mapped the identified usability issues to ISO 9241-11 and ISO/IEC 25010, and aggregated the recommendations for improvement. Moreover, we also identified certain issues that are solely concerned with the patient’s behavior. We organized the issues into taxonomies of design considerations for building usable pain self-management mobile applications. As pain is prevalent among the elderly, pain management will be much needed while moving toward an aging society. However, we found that the involvement of the elderly in the development of pain management mobile apps is very minimal, which may affect the utility and usability of the apps.

Apps and Mobile Health Technology in Rehabilitation: The Good, the Bad, and the Unknown

Although there is disparity in access to mobile health (mHealth) services among people with disabilities, several smartphone and tablet-based mHealth applications are available that may affect the care of patients in rehabilitation medicine. This article reviews the current evidence for and breadth of application-based mHealth interventions in rehabilitation medicine, including comprehensive self-management mHealth services; weight management mHealth services; diagnosis-specific mHealth services for individuals with brain, spinal cord, musculoskeletal, or other injury types; and nonmedical services to improve community and social integration.

Update and future perspective of behavioral medicine in the treatment for chronic pain

Chronic pain is a biopsychosocial condition, and behavioral medicine has made significant contributions to the understanding of the phenomenon and optimization of therapeutic outcomes. The objective of this article is to provide future perspectives of behavioral medicine in pain management based upon recent development in the field. We will briefly review the mainstream approach of cognitive-behavioral therapy, its variations and new and innovative approaches that are on the horizon. We also review strategies that address potential barriers to pain management. Behavioral medicine is a promising field in pain medicine. The future growth is likely to come from addressing how we incorporate the patient heterogeneity into our treatment approaches and a better understanding of its role in a multimodal treatment.

Evaluation of Self-Management Support Functions in Apps for People With Persistent Pain: Systematic Review

Background

Smartphone apps are a potential mechanism for development of self-management skills in people with persistent pain. However, the inclusion of best-practice content items in available pain management apps fostering core self-management skills for self-management support is not known.

Objective

The aim of the study was to evaluate the contents of smartphone apps providing information on pain management strategies for people with persistent pain facilitating self-management support and to appraise the app quality.

Methods

A systematic search was performed in the New Zealand App Store and Google Play Store. Apps were included if they were designed for people with persistent pain, provided information on pain self-management strategies, and were available in English. App contents were evaluated using an a priori 14-item self-management support (SMS-14) checklist. App quality was assessed using the 23-item Mobile Apps Rating Scale.

Results

Of the 939 apps screened, 19 apps met the inclusion criteria. Meditation and guided relaxation were the most frequently included self-management strategies. Overall, the included apps met a median of 4 (range 1-8) of the SMS-14 checklist. A total of 3 apps (Curable, PainScale-Pain Diary and Coach, and SuperBetter) met the largest number of items (8 out of 14) to foster self-management of pain. Self-monitoring of symptoms (n=11) and self-tailoring of strategies (n=9) were frequently featured functions, whereas a few apps had features facilitating social support and enabling communicating with clinicians. No apps provided information tailored to the cultural needs of the user. The app quality mean scores using Mobile Apps Rating Scale ranged from 2.7 to 4.5 (out of 5.0). Although use of 2 apps (Headspace and SuperBetter) has been shown to improve health outcomes, none of the included apps have been evaluated in people with persistent pain.

Conclusions

Of the 3 apps (Curable, PainScale-Pain Diary and Coach, and SuperBetter) that met the largest number of items to support skills in self-management of pain, 2 apps (PainScale-Pain Diary and Coach and SuperBetter) were free, suggesting the potential for using apps as a scalable, wide-reaching intervention to complement face-to-face care. However, none provided culturally tailored information. Although 2 apps (Headspace and SuperBetter) were validated to show improved health outcomes, none were tested in people with persistent pain. Both users and clinicians should be aware of such limitations and make informed choices in using or recommending apps as a self-management tool. For better integration of apps in clinical practice, concerted efforts are required among app developers, clinicians, and people with persistent pain in developing apps and evaluating for clinical efficacy.

Determining Pain Catastrophizing From Daily Pain App Assessment Data: Role of Computer-Based Classification

This study compared persons with chronic pain who consistently reported that their pain was worsening with those who reported that their pain was improving or remaining the same per daily assessment data from a smartphone pain app. All participants completed baseline measures and were asked to record their progress every day by answering whether their overall condition had improved, remained the same, or gotten worse (perceived change) on a visual analogue scale. One hundred forty-four individuals with chronic pain who successfully entered daily assessments were included. Those persons who were classified as worse showed significantly higher pain intensity scores, greater activity interference, higher disability and mood disturbance scores, and higher scores on the Pain Catastrophizing Scale both at baseline and after 3 months (P < .001). Repeated measures analyses and multilevel modeling of perceived change data over different time intervals of 20 assessments over 40 days, 10 assessments over 20 days, and 5 assessments over 10 days were examined. These analyses demonstrated that group classification of better, same, and worse could be reliably determined, even with as few as 5 assessments. These results support the use of innovative mobile health technology to identify individuals who are prone to catastrophize about their pain. Perspective: This study demonstrated that daily assessment of overall perceived change with a smartphone pain app was positively correlated with the Pain Catastrophizing Scale and capturing short-term daily assessment trends data using computer-based classification methods might be a future way to help to identify individuals who tend to catastrophize about their pain.