Development and validation of a pain monitoring app for patients with musculoskeletal conditions (The Keele pain recorder feasibility study)

The Effect of Everyday-Life Social Contact on Pain

Pain is a biopsychosocial phenomenon, resulting from the interplay between physiological and psychological processes and social factors. Given that humans constantly interact with others, the effect of social factors is particularly relevant. Documenting the significance of the social modulation of pain, an increasing number of studies have investigated the effect of social contact on subjective pain intensity and pain-related physiological changes. While evidence suggests that social contact can alleviate pain, contradictory findings indicate an increase in pain intensity and a deterioration of pain coping strategies. This evidence primarily stems from studies examining the effect of social contact on pain within highly controlled laboratory conditions. Moreover, pain assessments often rely on one-time subjective reports of average pain intensity across a predefined period. Ecological momentary assessments (EMAs) can circumvent these problems, as they can capture diverse aspects of behavior and experiences multiple times a day, in real time, with high resolution, and within naturalistic and ecologically valid settings. These multiple measures allow for the examination of fluctuations of pain symptoms throughout the day in relation to affective, cognitive, behavioral, and social factors. In this opinion paper, we review the current state and future relevance of EMA-based social pain research in daily life. Specifically, we examine whether everyday-life social support reduces or enhances pain. The first part of the paper provides a comprehensive overview of the use of EMA in pain research and summarizes the main findings. The review of the relatively limited number of existing EMA studies shows that the association between pain and social contact in everyday life depends on numerous factors, including pain syndromes, temporal dynamics, the nature of social interactions, and characteristics of the interaction partners. In line with laboratory research, there is evidence that everyday-life social contact can alleviate, but also intensify pain, depending on the type of social support. Everyday-life emotional support seems to reduce pain, while extensive solicitous support was found to have opposite effects. Moreover, positive short-term effects of social support can be overshadowed by other symptoms such as fatigue. Overall, gathering and integrating experiences from a patient's social environment can offer valuable insights. These insights can help interpret dynamics in pain intensity and accompanying symptoms such as depression or fatigue. We conclude that factors determining the reducing versus enhancing effects of social contact on pain need to be investigated more thoroughly. We advocate EMA as the assessment method of the future and highlight open questions that should be addressed in future EMA studies on pain and the potential of ecological momentary interventions for pain treatment.

Self-guided digital acceptance and commitment therapy for fibromyalgia management: results of a randomized, active-controlled, phase II pilot clinical trial

Although empirically validated for fibromyalgia (FM), cognitive and behavioral therapies, including Acceptance and Commitment Therapy (ACT), are inaccessible to many patients. A self-guided, smartphone-based ACT program would significantly improve accessibility. The SMART-FM study assessed the feasibility of conducting a predominantly virtual clinical trial in an FM population in addition to evaluating preliminary evidence for the safety and efficacy of a digital ACT program for FM (FM-ACT). Sixty-seven patients with FM were randomized to 12 weeks of FM-ACT (n = 39) or digital symptom tracking (FM-ST; n = 28). The study population was 98.5% female, with an average age of 53 years and an average baseline FM symptom severity score of 8 out of 11. Endpoints included the Fibromyalgia Impact Questionnaire-Revised (FIQ-R) and the Patient Global Impression of Change (PGIC). The between-arm effect size for the change from baseline to Week 12 in FIQ-R total scores was d = 0.44 (least-squares mean difference, - 5.7; SE, 3.16; 95% CI, - 11.9 to 0.6; P = .074). At Week 12, 73.0% of FM-ACT participants reported improvement on the PGIC versus 22.2% of FM-ST participants (P < .001). FM-ACT demonstrated improved outcomes compared to FM-ST, with high engagement and low attrition in both arms. Retrospectively registered at ClinicalTrials.gov (NCT05005351) on August 13, 2021.

The Added Value of Face-to-Face Supervision to a Therapeutic Exercise-Based App in the Management of Patients with Chronic Low Back Pain: A Randomized Clinical Trial

Low back pain (LBP) is a significant global health challenge due to its high prevalence, and chronicity and recurrence rates, with projections suggesting an increase in the next years due to population growth and aging. The chronic and recurrent nature of LBP, responsible for a significant percentage of years lived with disability, underscores the need for effective management strategies, including self-management strategies advocated by current guidelines, to empower patients and potentially improve healthcare efficiency and clinical outcomes. Therefore, the aim of this study was to analyze the added value of face-to-face visits in patients with chronic LBP undergoing a self-management program based on therapeutic exercises on pain intensity, disability, quality of life and treatment adherence and satisfaction. A randomized clinical trial was conducted, allocating 49 patients into a experimental group with a mobile health (mHealth) app usage and face-to-face sessions and 49 patients into an active control group without face-to-face sessions. Pain intensity, disability and quality of life were assessed at baseline, 4 weeks postintervention and 12 weeks postintervention. Patients' satisfaction and adherence were assessed at the end of the study. The multivariate general model revealed no statistically significant time × group interaction for any outcome (p > 0.0068) but mental quality of life (p = 0.006). Within-group differences revealed significant improvements for all the clinical indicators (all, p < 0.001). Patients allocated to the experimental group reported greater satisfaction and adherence (both, p < 0.001) compared to the control group. The use of mHealth apps such as Healthy Back® as part of digital health initiatives may serve as a beneficial approach to enhance the management of LBP.

Assessing Pain in Older Adults: Caregivers play a key role in recognizing and documenting pain at home

This article is part of a series, Supporting Family Caregivers: No Longer Home Alone, published in collaboration with the AARP Public Policy Institute. Results of focus groups, conducted as part of the AARP Public Policy Institute's No Longer Home Alone video project, supported evidence that family caregivers aren't given the information they need to manage the complex care regimens of family members. This series of articles and accompanying videos aims to help nurses provide caregivers with the tools they need to manage their family member's health care at home. This new group of articles provides practical information nurses can share with family caregivers of persons living with pain. To use this series, nurses should read the articles first, so they understand how best to help family caregivers. Then they can refer caregivers to the informational tear sheet-Information for Family Caregivers-and instructional videos, encouraging them to ask questions. For additional information, see Resources for Nurses. Cite this article as: Horgas, A.L., et al. Assessing Pain in Older Adults. Am J Nurs 2022; 122 (12): 42-48.

Assessing Pain in Older Adults

This article is part of a series, Supporting Family Caregivers: No Longer Home Alone, published in collaboration with the AARP Public Policy Institute. Results of focus groups, conducted as part of the AARP Public Policy Institute's No Longer Home Alone video project, supported evidence that family caregivers aren't given the information they need to manage the complex care regimens of family members. This series of articles and accompanying videos aims to help nurses provide caregivers with the tools they need to manage their family member's health care at home. This new group of articles provides practical information nurses can share with family caregivers of persons living with pain. To use this series, nurses should read the articles first, so they understand how best to help family caregivers. Then they can refer caregivers to the informational tear sheet-Information for Family Caregivers-and instructional videos, encouraging them to ask questions. For additional information, see Resources for Nurses.

Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain

Smartphone-based ecological momentary assessment (EMA) methods are widely used for data collection and monitoring in healthcare but their uptake clinically has been limited. Low back pain, a condition with limited effective treatments, has the potential to benefit from EMA. This study aimed to (i) determine the feasibility of collecting pain and function data using smartphone-based EMA, (ii) examine pain data collected using EMA compared to traditional methods, (iii) characterize individuals' progress in relation to pain and function, and (iv) investigate the appropriation of the method. Our results showed that an individual's 'pain intensity index' provided a measure of the burden of their low back pain, which differed from but complemented traditional 'change in pain intensity' measures. We found significant variations in the pain and function over the course of an individual's back pain that was not captured by the cohort's mean scores, the approach currently used as the gold standard in clinical trials. The EMA method was highly acceptable to the participants, and the Model of Technology Appropriation provided information on technology adoption. This study highlights the potential of the smartphone-based EMA method for enhancing the collection of outcome data and providing a personalized approach to the management of low back pain.

Applying Healthcare Failure Mode and Effect Analysis and the Development of a Real-Time Mobile Application for Modified Early Warning Score Notification to Improve Patient Safety During Hemodialysis

OBJECTIVE

Patients undergoing hemodialysis are a high-risk population. This study identified possible errors by using a healthcare failure mode and effect analysis system to improve patient safety during hemodialysis.

METHODS

A multidisciplinary collaborative team, including physicians, nurses, information technicians, and medical staff members, was assembled. A flow diagram was used to indicate each process of the hemodialysis procedure from evaluating patient condition to transporting the patient back to the ward from the hemodialysis center. We scored all possible failure modes using the hazard scoring method as a combination of the occurrence frequency and severity. These potential failure modes were used to identify and evaluate possible risks by using a risk scoring matrix.

RESULTS

Thirty failure modes were identified across 6 processes, and their potential causes were explored. Four major strategies for addressing most of the failure modes were implemented: establishment of a mobile application that sends real-time automated alerts to the medical team based on the Modified Early Warning Score, design of a modified dialysis Identify-Situation-Background-Assessment-Recommendation checklist for dialysis, technician education and training, and internal auditing and monitoring of the implementation of the entire process. After the implementation of the strategies, the hazard scores of patients during dialysis dropped by 71.2% from 170 points to 49 points.

CONCLUSIONS

The healthcare failure mode and effect analysis system was useful for evaluating potential risk during dialysis. Using the mobile application reduced the occurrence of emergency resuscitation during hemodialysis and significantly improved the communication between medical personnel.

Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis

Background

Osteoporosis is the fourth most common chronic disease worldwide. The adoption of preventative measures and effective self-management interventions can help improve bone health. Mobile health (mHealth) technologies can play a key role in the care and self-management of patients with osteoporosis.

Objective

This study presents a systematic review and meta-analysis of the currently available mHealth apps targeting osteoporosis self-management, aiming to determine the current status, gaps, and challenges that future research could address, as well as propose appropriate recommendations.

Methods

A systematic review of all English articles was conducted, in addition to a survey of all apps available in iOS and Android app stores as of May 2021. A comprehensive literature search (2010 to May 2021) of PubMed, Scopus, EBSCO, Web of Science, and IEEE Xplore was conducted. Articles were included if they described apps dedicated to or useful for osteoporosis (targeting self-management, nutrition, physical activity, and risk assessment) delivered on smartphone devices for adults aged ≥18 years. Of the 32 articles, a random effects meta-analysis was performed on 13 (41%) studies of randomized controlled trials, whereas the 19 (59%) remaining studies were only included in the narrative synthesis as they did not provide enough data.

Results

In total, 3906 unique articles were identified. Of these 3906 articles, 32 (0.81%) articles met the inclusion criteria and were reviewed in depth. The 32 studies comprised 14,235 participants, of whom, on average, 69.5% (n=9893) were female, with a mean age of 49.8 (SD 17.8) years. The app search identified 23 relevant apps for osteoporosis self-management. The meta-analysis revealed that mHealth-supported interventions resulted in a significant reduction in pain (Hedges g −1.09, 95% CI −1.68 to −0.45) and disability (Hedges g −0.77, 95% CI −1.59 to 0.05). The posttreatment effect of the digital intervention was significant for physical function (Hedges g 2.54, 95% CI −4.08 to 4.08) but nonsignificant for well-being (Hedges g 0.17, 95% CI −1.84 to 2.17), physical activity (Hedges g 0.09, 95% CI −0.59 to 0.50), anxiety (Hedges g −0.29, 95% CI −6.11 to 5.53), fatigue (Hedges g −0.34, 95% CI −5.84 to 5.16), calcium (Hedges g −0.05, 95% CI −0.59 to 0.50), vitamin D intake (Hedges g 0.10, 95% CI −4.05 to 4.26), and trabecular score (Hedges g 0.06, 95% CI −1.00 to 1.12).

Conclusions

Osteoporosis apps have the potential to support and improve the management of the disease and its symptoms; they also appear to be valuable tools for patients and health professionals. However, most of the apps that are currently available lack clinically validated evidence of their efficacy and focus on a limited number of symptoms. A more holistic and personalized approach within a cocreation design ecosystem is needed.

Trial Registration

PROSPERO 2021 CRD42021269399; https://tinyurl.com/2sw454a9

Machine learning approaches applied in spinal pain research

The purpose of this narrative review is to provide a critical reflection of how analytical machine learning approaches could provide the platform to harness variability of patient presentation to enhance clinical prediction. The review includes a summary of current knowledge on the physiological adaptations present in people with spinal pain. We discuss how contemporary evidence highlights the importance of not relying on single features when characterizing patients given the variability of physiological adaptations present in people with spinal pain. The advantages and disadvantages of current analytical strategies in contemporary basic science and epidemiological research are reviewed and we consider how analytical machine learning approaches could provide the platform to harness the variability of patient presentations to enhance clinical prediction of pain persistence or recurrence. We propose that machine learning techniques can be leveraged to translate a potentially heterogeneous set of variables into clinically useful information with the potential to enhance patient management.

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.

Smartphone Applications Designed to Improve Older People's Chronic Pain Management: An Integrated Systematic Review

(1) Background: Older people’s chronic pain is often not well managed because of fears of side-effects and under-reporting. Telehealth interventions, in the form of smartphone applications, are attracting much interest in the management of chronic diseases, with new and evolving approaches in response to current population demographics. However, the extent to which telehealth interventions may be used to promote and effect the self-management of chronic pain is not established. (2) Aim: To provide an objective review of the existing quantitative and qualitative evidence pertaining to the benefits of smartphone applications for the management of chronic pain in older people. (3) Methods: A literature search was undertaken using PubMed, Medline, CINAHL, Embase, PsychINFO, the Cochrane database, Science Direct and references of retrieved articles. The data were independently extracted by two reviewers from the original reports. (4) Results: This integrative systematic review identified 10 articles considering smartphone applications related to self-management of chronic pain among older adults. (5) Conclusions: It is important for future research to not only examine the effects of smartphone initiatives, but also to compare their safety, acceptability, efficacy and cost–benefit ratio in relation to existing treatment modalities.

User Engagement and Clinical Impact of the Manage My Pain App in Patients With Chronic Pain: A Real-World, Multi-site Trial

Background

Chronic pain imposes a large burden on individuals and society. A patient-centric digital chronic pain management app called Manage My Pain (MMP) can be used to enhance communication between providers and patients and promote self-management.

Objective

The purpose of this study was to evaluate the real-world engagement of patients in urban and rural settings in Ontario, Canada with the MMP app alongside their standard of care and assess the impact of its usage on clinical outcomes of pain and related mental health.

Methods

A total of 246 participants with chronic pain at a rural and 2 urban pain clinics were recruited into this prospective, open-label, exploratory study that compared the use of MMP, a digital health app for pain that incorporates validated questionnaires and provides patients with summarized reports of their progress in combination with standard care (app group), against data entered on paper-based questionnaires (nonapp group). Participants completed validated questionnaires on anxiety, depression, pain catastrophizing, satisfaction, and daily opioid consumption up to 4.5 months after the initial visit (short-term follow-up) and between 4.5 and 7 months after the initial visit (long-term follow-up). Engagement and clinical outcomes were compared between participants in the two groups.

Results

A total of 73.6% (181/246) of the participants agreed to use the app, with 63.4% (111/175) of them using it for at least one month. Individuals who used the app rated lower anxiety (reduction in Generalized Anxiety Disorder 7-item questionnaire score by 2.10 points, 95% CI –3.96 to –0.24) at short-term follow-up and had a greater reduction in pain catastrophizing (reduction in Pain Catastrophizing Scale score by 5.23 points, 95% CI –9.55 to –0.91) at long-term follow-up relative to patients with pain who did not engage with the MMP app.

Conclusions

The use of MMP by patients with chronic pain is associated with engagement and improvements in self-reported anxiety and pain catastrophizing. Further research is required to understand factors that impact continued engagement and clinical outcomes in patients with chronic pain.

Trial Registration

ClinicalTrials.gov NCT04762329; https://clinicaltrials.gov/ct2/show/NCT04762329

Usability of a self-administered geriatric assessment mHealth: Cross-sectional study in a geriatric clinic

AIM

mHealth can facilitate comprehensive geriatric assessment (CGA) in countries with limited geriatric healthcare facilities. It can compensate for the lack of trained geriatricians and integrate CGA in different healthcare disciplines leading to better clinical outcomes. This study assessed the usability of a self-administered geriatric assessment smartphone application.

METHODS

A cross-sectional study included participants from the geriatric clinic at Ain Shams University Hospital, Cairo, Egypt. This study was performed in three phases: development and validation of an abbreviated geriatric assessment tool, and validation of the application prototype. Twenty subjects were recruited for pretesting the abbreviated assessment tool, then another 50 patients to validate this tool in a face-to-face interview. Afterwards, another 12 patients completed the prototype followed by a standardized office visit interview. Each assessment domain was evaluated in agreement with a valid reference test during the clinical interview.

RESULTS

The application was simple and user friendly. The scores of each domain correlated to the reference test scores (rho = 0.59-0.93). Most of the domains exhibited good agreement with the reference tests (kappa = 0.68-1.00) (except for frailty and nutritional assessment).

CONCLUSIONS

The mHealth geriatric assessment is possible and highly desirable during physical distancing and beyond. Obviously, this approach cannot substitute for clinical examination and multidisciplinary standard CGA. However, it may overcome some barriers facing the geriatrization of medicine. It would help general practitioners to provide pre-CGA evaluation, particularly in areas with limited access to formal geriatric healthcare services. Geriatr Gerontol Int 2021; 21: 222-228.

App-Based Pain Management and Opioid Education Program for Patients in Clinic Waiting Rooms

BACKGROUND

Best approaches to delivering patient education related to pain management and opioid safety are understudied.

AIMS

This study assessed the feasibility, acceptability, and preliminary patient-reported impact of an app-based patient pain education program.

DESIGN

Pilot study with data collection occurring on 43 weekdays between August 2019-February 2020.

SETTING

Waiting rooms at the pain clinic and a primary care medical home within two military treatment facilities.

PARTICIPANTS

Military health system beneficiaries seeking general care at the primary care medical home or pain-specific care at the pain clinic.

METHODS

The Joint Pain Education and Project curriculum includes patient-focused videos describing the biopsychosocial aspects of pain and pain management, medication take-back and safe disposal, and multidimensional pain assessments. The app-based videos were available on tablets in the waiting rooms for patients to view and complete surveys on after.

RESULTS

Overall, 152 patients viewed the videos and completed surveys. Most viewers were interested in receiving other tablet-based health education while in the waiting room (62%). Most viewers found videos to be moderately or very helpful (73%) and were satisfied or very satisfied with the information provided (85%). Participants at the primary care medical home were more likely to find videos helpful compared to participants at the pain clinic (OR = 2.11; 95% CI: 1.07, 4.20; p = .03).

CONCLUSION

Implementing app-based pain management education is feasible across clinic settings and is well received by patients. Clinics should consider providing pain education across care setting, rather than just pain specialty clinics, to help foster discussions between clinicians and patients regarding pain management and opioid safety.

Electronic Data Capture Versus Conventional Data Collection Methods in Clinical Pain Studies: Systematic Review and Meta-Analysis

BACKGROUND

The most commonly used means to assess pain is by patient self-reported questionnaires. These questionnaires have traditionally been completed using paper-and-pencil, telephone, or in-person methods, which may limit the validity of the collected data. Electronic data capture methods represent a potential way to validly, reliably, and feasibly collect pain-related data from patients in both clinical and research settings.

OBJECTIVE

The aim of this study was to conduct a systematic review and meta-analysis to compare electronic and conventional pain-related data collection methods with respect to pain score equivalence, data completeness, ease of use, efficiency, and acceptability between methods.

METHODS

We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica Database (EMBASE), and Cochrane Central Register of Controlled Trials (CENTRAL) from database inception until November 2019. We included all peer-reviewed studies that compared electronic (any modality) and conventional (paper-, telephone-, or in-person-based) data capture methods for patient-reported pain data on one of the following outcomes: pain score equivalence, data completeness, ease of use, efficiency, and acceptability. We used random effects models to combine score equivalence data across studies that reported correlations or measures of agreement between electronic and conventional pain assessment methods.

RESULTS

A total of 53 unique studies were included in this systematic review, of which 21 were included in the meta-analysis. Overall, the pain scores reported electronically were congruent with those reported using conventional modalities, with the majority of studies (36/44, 82%) that reported on pain scores demonstrating this relationship. The weighted summary correlation coefficient of pain score equivalence from our meta-analysis was 0.92 (95% CI 0.88-0.95). Studies on data completeness, patient- or provider-reported ease of use, and efficiency generally indicated that electronic data capture methods were equivalent or superior to conventional methods. Most (19/23, 83%) studies that directly surveyed patients reported that the electronic format was the preferred data collection method.

CONCLUSIONS

Electronic pain-related data capture methods are comparable with conventional methods in terms of score equivalence, data completeness, ease, efficiency, and acceptability and, if the appropriate psychometric evaluations are in place, are a feasible means to collect pain data in clinical and research settings.

Methodological Quality of Manuscripts Reporting on the Usability of Mobile Applications for Pain Assessment and Management: A Systematic Review

BACKGROUND

There has been increasing use of mobile mHealth applications, including pain assessment and pain self-management apps. The usability of mHealth applications has vital importance as it affects the quality of apps. Thus, usability assessment with methodological rigor is essential to minimize errors and undesirable consequences, as well as to increase user acceptance.

OBJECTIVE

this study aimed to synthesize and evaluate existing studies on the assessment of the usability of pain-related apps using a newly developed scale.

METHODS

an electronic search was conducted in several databases, combining relevant keywords. Then titles and abstracts were screened against inclusion and exclusion criteria. The eligible studies were retrieved and independently screened for inclusion by two authors. Disagreements were resolved by discussion until consensus was reached.

RESULTS

a total of 31 articles were eligible for inclusion. Quality assessment revealed that most manuscripts did not assess usability using valid instruments or triangulation of methods of usability assessment. Most manuscripts also failed to assess the three domains of usability (effectiveness, efficiency and satisfaction).

CONCLUSIONS

future studies should consider existing guidelines on usability assessment design, development and assessment of pain-related apps.