Dataset Information

Sensory-Discriminative Three-Dimensional Body Pain Mobile App Measures Versus Traditional Pain Measurement With a Visual Analog Scale: Validation Study.

ABSTRACT: BACKGROUND:To quantify pain severity in patients and the efficacy treatments, researchers and clinicians apply tools such as the traditional visual analog scale (VAS) that leads to inaccurate interpretation of the main sensory pain. OBJECTIVE:This study aimed to validate the pain measurements of a neuroscience-based 3D body pain mobile app called GeoPain. METHODS:Patients with temporomandibular disorder (TMD) were assessed using GeoPain measures in comparison to VAS and positive and negative affect schedule (PANAS), pain and mood scales, respectively. Principal component analysis (PCA), scatter score analysis, Pearson methods, and effect size were used to determine the correlation between GeoPain and VAS measures. RESULTS:The PCA resulted in two main orthogonal components: first principal component (PC1) and second principal component (PC2). PC1 comprises a combination score of all GeoPain measures, which had a high internal consistency and clustered together in TMD pain. PC2 included VAS and PANAS. All loading coefficients for GeoPain measures in PC1 were above 0.70, with low loadings for VAS and PANAS. Meanwhile, PC2 was dominated by a VAS and PANAS coefficient >0.4. Repeated measure analysis revealed a strong correlation between the VAS and mood scores from PANAS over time, which might be related to the subjectivity of the VAS measure, whereas sensory-discriminative GeoPain measures, not VAS, demonstrated an association between chronicity and TMD pain in locations spread away from the most commonly reported area or pain epicenter (P=.01). Analysis using VAS did not detect an association at baseline between TMD and chronic pain. The long-term reliability (lag >1 day) was consistently high for the pain area and intensity number summation (PAINS) with lag autocorrelations averaging between 0.7 and 0.8, and greater than the autocorrelations for VAS averaging between 0.3 and 0.6. The combination of higher reliability for PAINS and its objectivity, displayed by the lack of association with PANAS as compared with VAS, indicated that PAINS has better sensitivity and reliability for measuring treatment effect over time for sensory-discriminative pain. The effect sizes for PAINS were larger than those for VAS, consequently requiring smaller sample sizes to assess the analgesic efficacy of treatment if PAINS was used versus VAS. The PAINS effect size was 0.51 SD for both facial sides and 0.60 SD for the right side versus 0.35 SD for VAS. Therefore, the sample size required to detect such effect sizes with 80% power would be n=125 per group for VAS, but as low as n=44 per group for PAINS, which is almost a third of the sample size needed by VAS. CONCLUSIONS:GeoPain demonstrates precision and reliability as a 3D mobile interface for measuring and analyzing sensory-discriminative aspects of subregional pain in terms of its severity and response to treatment, without being influenced by mood variations from patients.

SUBMITTER: Kaciroti N

PROVIDER: S-EPMC7468641 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sensory-Discriminative Three-Dimensional Body Pain Mobile App Measures Versus Traditional Pain Measurement With a Visual Analog Scale: Validation Study.

Kaciroti Niko N DosSantos Marcos Fabio MF Moura Brenda B Bellile Emily Light EL Nascimento Thiago Dias TD Maslowski Eric E Danciu Theodora E TE Donnell Adam A DaSilva Alexandre F AF

JMIR mHealth and uHealth 20200819 8

<h4>Background</h4>To quantify pain severity in patients and the efficacy treatments, researchers and clinicians apply tools such as the traditional visual analog scale (VAS) that leads to inaccurate interpretation of the main sensory pain.<h4>Objective</h4>This study aimed to validate the pain measurements of a neuroscience-based 3D body pain mobile app called GeoPain.<h4>Methods</h4>Patients with temporomandibular disorder (TMD) were assessed using GeoPain measures in comparison to VAS and pos ...[more]

PMID: 32124732

Similar Datasets

Project description:BackgroundeCohort studies offer an efficient approach for data collection. However, eCohort studies are challenged by volunteer bias and low adherence. We designed an eCohort embedded in the Framingham Heart Study (eFHS) to address these challenges and to compare the digital data to traditional data collection.ObjectiveThe aim of this study was to evaluate adherence of the eFHS app-based surveys deployed at baseline (time of enrollment in the eCohort) and every 3 months up to 1 year, and to compare baseline digital surveys with surveys collected at the research center.MethodsWe defined adherence rates as the proportion of participants who completed at least one survey at a given 3-month period and computed adherence rates for each 3-month period. To evaluate agreement, we compared several baseline measures obtained in the eFHS app survey to those obtained at the in-person research center exam using the concordance correlation coefficient (CCC).ResultsAmong the 1948 eFHS participants (mean age 53, SD 9 years; 57% women), we found high adherence to baseline surveys (89%) and a decrease in adherence over time (58% at 3 months, 52% at 6 months, 41% at 9 months, and 40% at 12 months). eFHS participants who returned surveys were more likely to be women (adjusted odds ratio [aOR] 1.58, 95% CI 1.18-2.11) and less likely to be smokers (aOR 0.53, 95% CI 0.32-0.90). Compared to in-person exam data, we observed moderate agreement for baseline app-based surveys of the Physical Activity Index (mean difference 2.27, CCC=0.56), and high agreement for average drinks per week (mean difference 0.54, CCC=0.82) and depressive symptoms scores (mean difference 0.03, CCC=0.77).ConclusionsWe observed that eFHS participants had a high survey return at baseline and each 3-month survey period over the 12 months of follow up. We observed moderate to high agreement between digital and research center measures for several types of surveys, including physical activity, depressive symptoms, and alcohol use. Thus, this digital data collection mechanism is a promising tool to collect data related to cardiovascular disease and its risk factors.

Project description:BackgroundPain 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.MethodsThe 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.ResultsA 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.ConclusionsMost 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.

Project description:Nonspecific low back pain (NLBP) is the diagnosis for individuals with back pain that has no underlying medical cause (eg, tumor, infection, fracture, herniated disc, spinal stenosis). The American College of Physicians (ACP) and American Pain Society (APS) recommend multidisciplinary treatments for NLBP that lasts more than 4 weeks. This approach, however, is impractical for many physicians to implement, and relatively few providers offer NLBP treatment that meets the joint ACP-APS guidelines.This study evaluated the efficacy of a mobile-Web intervention called "FitBack" to help users implement self-tailored strategies to manage and prevent NLBP occurrences.A total of 597 adults were recruited, screened, consented, and assessed online at baseline, at 2 months (T2), and at 4 months (T3). After baseline assessments, participants were randomized into three groups: FitBack intervention, alternative care group that received 8 emails urging participants to link to six Internet resources for NLBP, and control group. The FitBack group also received weekly email reminder prompts for 8 weeks plus emails to do assessments. The control group was only contacted to do assessments.Users of the FitBack program showed greater improvement compared to the control group in every comparison of the critical physical, behavioral, and worksite outcome measures at 4-month follow-up. In addition, users of the FitBack program performed better than the alternative care group on current back pain, behavioral, and worksite outcomes at 4-month follow-up. For example, subjects in the control group were 1.7 times more likely to report current back pain than subjects in the FitBack group; subjects in the alternative care group were 1.6 times more likely to report current back pain at 4-month follow-up. Further, the users of the FitBack program showed greater improvement compared to both the control and alternative care groups at 4-month follow-up on patient activation, constructs of the Theory of Planned Behavior, and attitudes toward pain.This research demonstrated that a theoretically based stand-alone mobile-Web intervention that tailors content to users' preferences and interests can be an effective tool in self-management of low back pain. When viewed from the RE-AIM perspective (ie, reach, efficacy/effectiveness, adoption, implementation fidelity, and maintenance), this study supports the notion that there is considerable value in this type of intervention as a potentially cost-effective tool that can reach large numbers of people. The results are promising considering that the FitBack intervention was neither supported by professional caregivers nor integrated within a health promotion campaign, which might have provided additional support for participants. Still, more research is needed on how self-guided mobile-Web interventions will be used over time and to understand factors associated with continuing user engagement.Clinicaltrials.gov NCT01950091; http://clinicaltrials.gov/ct2/show/NCT01950091 (Archived by WebCite at http://www.webcitation.org/6TwZucX77).

Project description:Background:Patient-reported outcome measures (PROMs) are being increasingly used in orthopedic surgery; however, there is significant variability and burden associated with their administration. The visual analog scale (VAS) for function, strength, and pain may represent a simple and efficient way to measure outcomes, specifically after rotator cuff repair (RCR) surgery. Purpose:To define the efficiency and longitudinal psychometric properties of VAS instruments assessing function, strength, and pain after RCR. Methods:Single-question VAS measures assessing function, strength, and pain as a percentage of normal were administered alongside legacy PROMs in patients undergoing RCR. VAS and PROMs were administered at preoperative, 6- and 12-month time points between June 2017 and April 2018. An electronic registry was used to examine time-to-completion data. PROM performance was assessed using Spearman correlation coefficients. Both absolute and relative floor and ceiling effects were examined. Effect size was measured at 6 and 12 months through the calculation of Cohen's d coefficient. Receiver-operating curves with area under the curve calculations were used to determine the ability of preoperative VAS scores in predicting minimally clinically important difference achievement on American Shoulder and Elbow Surgeons score (ASES). Results:A total of 190 patients (55.6 ± 10.9 years, 66.9% male) met criteria. The 3 VAS PROMs required less time to complete than ASES (1.36 ± 1.12 vs. 5.17 ± 2.39) and Patient-Reported Outcome Measurement Information System (PROMIS) Upper Extremity v2.0 (UE) Computer Adaptive Test (1.72 ± 1.48). Compared with ASES, VAS function, strength, and pain demonstrated fair correlations preoperatively (r = 0.44-0.46) that improved to good at 6 months (r = 0.61-0.67) and further improved at 1 year (r = 0.62-0.78). The performance of VAS measures with other function PROMs was comparable with performance relative to ASES, with poor to very good correlations preoperatively (r = 0.21-0.62) that improved to good to excellent by 1 year (r = 0.62-0.94). A significant relative ceiling effect was demonstrated by PROMIS UE at 12 months (16.9%). Large effect sizes were demonstrated by the ASES, Single Assessment Numeric Evaluation, Constant, PROMIS UE, and VAS function and strength instruments (Cohen d ? 0.8). Conclusion:Single-question VAS assessments for function, strength, and pain are an efficient means for assessing outcome in RCR surgery and may be particularly useful in the postoperative setting. VAS instruments collectively trended toward floor effects preoperatively, suggesting that legacy instruments may more appropriately establish preoperative baselines. However, in the postoperative setting, VAS instruments demonstrate good-to-excellent correlation, minimized time-to-completion, and no appreciable floor or ceiling effects.

Project description:Pain is one of the most prevalent health-related concerns and is among the top 3 most common reasons for seeking medical help. Scientific publications of data collected from pain tracking and monitoring apps are important to help consumers and healthcare professionals select the right app for their use.The main objectives of this paper were to (1) discover user engagement patterns of the pain management app, Manage My Pain, using data mining methods; and (2) identify the association between several attributes characterizing individual users and their levels of engagement.User engagement was defined by 2 key features of the app: longevity (number of days between the first and last pain record) and number of records. Users were divided into 5 user engagement clusters employing the k-means clustering algorithm. Each cluster was characterized by 6 attributes: gender, age, number of pain conditions, number of medications, pain severity, and opioid use. Z tests and chi-square tests were used for analyzing categorical attributes. Effects of gender and cluster on numerical attributes were analyzed using 2-way analysis of variances (ANOVAs) followed up by pairwise comparisons using Tukey honest significant difference (HSD).The clustering process produced 5 clusters representing different levels of user engagement. The proportion of males and females was significantly different in 4 of the 5 clusters (all P ≤.03). The proportion of males was higher than females in users with relatively high longevity. Mean ages of users in 2 clusters with high longevity were higher than users from other 3 clusters (all P <.001). Overall, males were significantly older than females (P <.001). Across clusters, females reported more pain conditions than males (all P <.001). Users from highly engaged clusters reported taking more medication than less engaged users (all P <.001). Females reported taking a greater number of medications than males (P =.04). In 4 of 5 clusters, the percentage of males taking an opioid was significantly greater (all P ≤.05) than that of females. The proportion of males with mild pain was significantly higher than that of females in 3 clusters (all P ≤.008).Although most users of the app reported being female, male users were more likely to be highly engaged in the app. Users in the most engaged clusters self-reported a higher number of pain conditions, a higher number of current medications, and a higher incidence of opioid usage. The high engagement by males in these clusters does not appear to be driven by pain severity which may, in part, be the case for females. Use of a mobile pain app may be relatively more attractive to highly-engaged males than highly-engaged females, and to those with relatively more complex chronic pain problems.

Project description:BACKGROUND:Despite the availability of effective medications and clinical guidelines for pain management, pain control is suboptimal in a sizeable proportion of patients with cancer pain. The National Comprehensive Cancer Network guidelines recommend a comprehensive and multimodal approach for management of cancer pain. We developed a mobile phone application, ePAL, based on clinical guidelines to empower patients for cancer pain management by prompting regular pain assessments and coaching for self-management. OBJECTIVE:The objective of this study is to evaluate the effect of a multidimensional mobile phone-based pain management application, ePAL, on controlling cancer pain and improving quality of life in patients with cancer pain being treated at an academic palliative care clinic. METHODS:The study will be implemented as a 2-arm randomized controlled trial with 110 adult patients with CP who own a mobile phone over a follow-up period of two months. Participants will be randomized to either the intervention group receiving ePAL and usual care or to a control group receiving only usual care. The brief pain inventory will be used to assess our primary outcome which is pain intensity. We will also evaluate the effect of the intervention on secondary outcomes which include the effect of the intervention on hospital utilization for pain crisis, quality of life, adherence to analgesic medications, barriers to pain control, anxiety and patient engagement. Instruments that will be used in evaluating secondary outcomes include the Brief Pain Inventory, Morisky Medication Adherence Scale, Barriers Questionnaire-II, Functional Assessment of Cancer Therapy-General, Edmonton Symptom Assessment System, Generalized Anxiety Disorder 7-item scale, and the Functional Assessment of Chronic Illness Therapy-Fatigue. The intention-to-treat approach will be used to evaluate outcomes. Our primary outcome, pain intensity, measured longitudinally over eight weeks, will be assessed by mixed model repeated analysis. Effect sizes will be calculated as mean group differences with standard deviations. RESULTS:The study is still in progress. We hope to have results by the end of 2015. CONCLUSIONS:The multidimensional approach to pain management implemented on a mobile phone application could lead to significant improvements in patient outcomes. TRIAL REGISTRATION:ClinicalTrials.gov NCT02069743; https://clinicaltrials.gov/ct2/show/NCT02069743 (Archived by WebCite at http://www.webcitation.org/6Qb65XGGA).

Dataset Information

Sensory-Discriminative Three-Dimensional Body Pain Mobile App Measures Versus Traditional Pain Measurement With a Visual Analog Scale: Validation Study.

Publications

Sensory-Discriminative Three-Dimensional Body Pain Mobile App Measures Versus Traditional Pain Measurement With a Visual Analog Scale: Validation Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets