Dataset Information

Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study.

ABSTRACT: BACKGROUND:Current clinical assessments of people with multiple sclerosis are episodic and may miss critical features of functional fluctuations between visits. OBJECTIVE:The goal of the research was to assess the feasibility of remote active testing and passive monitoring using smartphones and smartwatch technology in people with multiple sclerosis with respect to adherence and satisfaction with the FLOODLIGHT test battery. METHODS:People with multiple sclerosis (aged 20 to 57 years; Expanded Disability Status Scale 0-5.5; n=76) and healthy controls (n=25) performed the FLOODLIGHT test battery, comprising active tests (daily, weekly, every two weeks, or on demand) and passive monitoring (sensor-based gait and mobility) for 24 weeks using a smartphone and smartwatch. The primary analysis assessed adherence (proportion of weeks with at least 3 days of completed testing and 4 hours per day passive monitoring) and questionnaire-based satisfaction. In-clinic assessments (clinical and magnetic resonance imaging) were performed. RESULTS:People with multiple sclerosis showed 70% (16.68/24 weeks) adherence to active tests and 79% (18.89/24 weeks) to passive monitoring; satisfaction score was on average 73.7 out of 100. Neither adherence nor satisfaction was associated with specific population characteristics. Test-battery assessments had an at least acceptable impact on daily activities in over 80% (61/72) of people with multiple sclerosis. CONCLUSIONS:People with multiple sclerosis were engaged and satisfied with the FLOODLIGHT test battery. FLOODLIGHT sensor-based measures may enable continuous assessment of multiple sclerosis disease in clinical trials and real-world settings. TRIAL REGISTRATION:ClinicalTrials.gov: NCT02952911; https://clinicaltrials.gov/ct2/show/NCT02952911.

SUBMITTER: Midaglia L

PROVIDER: S-EPMC6743265 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study.

Midaglia Luciana L Mulero Patricia P Montalban Xavier X Graves Jennifer J Hauser Stephen L SL Julian Laura L Baker Michael M Schadrack Jan J Gossens Christian C Scotland Alf A Lipsmeier Florian F van Beek Johan J Bernasconi Corrado C Belachew Shibeshih S Lindemann Michael M

Journal of medical Internet research 20190830 8

<h4>Background</h4>Current clinical assessments of people with multiple sclerosis are episodic and may miss critical features of functional fluctuations between visits.<h4>Objective</h4>The goal of the research was to assess the feasibility of remote active testing and passive monitoring using smartphones and smartwatch technology in people with multiple sclerosis with respect to adherence and satisfaction with the FLOODLIGHT test battery.<h4>Methods</h4>People with multiple sclerosis (aged 20 t ...[more]

PMID: 31471961

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Project description:BACKGROUND:Advances in mobile health (mHealth) have enabled systematic and continuous management of patients with chronic diseases. OBJECTIVE:We developed a smartphone-based mHealth system and aimed to evaluate its effects on health behavior management and risk factor control in stroke patients. METHODS:With a multifaceted stroke aftercare management system that included exercise, medication, and educational materials, we performed a 12-week single-arm intervention among eligible poststroke patients in the stroke clinic from September to December 2016. The intervention consisted of (1) regular blood pressure (BP), blood glucose, and physical activity measurements; (2) stroke education; (3) an exercise program; (4) a medication program; and (5) feedback on reviewing of records by clinicians. Clinical assessments consisted of the stroke awareness score, Beck Depression Inventory-II (BDI), EuroQol-5 Dimensions (EQ-5D), and BP at visit 1 (baseline), visit 2 (4 weeks), and visit 3 (12 weeks). Temporal differences in the parameters over 12 weeks were investigated with repeated-measures analysis of variance. Changes in medication adherence at visit 1-2 (from visit 1 to visit 2) and visit 2-3 (from visit 2 to visit 3) were compared. System satisfaction was evaluated with a self-questionnaire using a 5-point Likert scale at visit 3. RESULTS:The study was approved by the Institutional Review Board in September 2016, and participants were enrolled from September to December 2016. Among the 110 patients enrolled for the study, 99 were included in our analyses. The mean stroke awareness score (baseline: 59.6 [SD 18.1]; 4 weeks: 67.6 [SD 16.0], P<.001; 12 weeks: 74.7 [SD 14.0], P<.001) and BDI score (baseline: 12.7 [SD 10.1]; 4 weeks: 11.2 [SD 10.2], P=.01; 12 weeks: 10.7 [SD 10.2], P<.001) showed gradual improvement; however, no significant differences were found in the mean EQ-5D score (baseline: 0.66 [SD 0.33]; 4 weeks: 0.69 [SD 0.34], P=.01; 12 weeks: 0.69 [SD 0.34], P<.001). Twenty-six patients who had uncontrolled BP at baseline had -13.92 mmHg (P=.001) and -6.19 mmHg (P<.001) reductions on average in systolic and diastolic BP, respectively, without any antihypertensive medication change. Medication compliance was better at visit 2-3 (60.9% [SD 37.2%]) than at visit 1-2 (47.8% [SD 38.7%], P<.001). CONCLUSIONS:Awareness of stroke, depression, and BP was enhanced when using the smartphone-based mHealth system. Emerging mHealth techniques have potential as new nonpharmacological secondary prevention methods because of their ubiquitous access, near real-time responsiveness, and comparatively lower cost.

Project description:BackgroundMonitoring of patient outcomes in multiple sclerosis (MS) is fundamental for individualized treatment decisions. So far, these decisions have been motivated by conventional outcomes, i.e., relapses or clinical disability supported by radiological disease activity. Complementing this concept, patient reported outcomes (PROs) assess individual health-related quality of life, among other constructs. Their inclusion in clinical routine, however, has been challenging as assessing them requires resources of time and personnel.ObjectiveThis interventional feasibility study investigated the haMSter app, a mobile health solution for remote and longitudinal monitoring of PROs in a sample of people with MS (pwMS).MethodsThe core feature of haMSter is the provision of three PRO questionnaires relevant to MS (anxiety/depression, MS-related quality of life, and fatigue) that patients can fill out once a month. For this feasibility trial, we offered 50 volunteers to use the haMSter app over six months and to take part in a haMSter study visit. This consultation concluded the study and participants had the opportunity to discuss their graphically plotted PRO results with their treating physician.ResultsThe main outcome was overall patient adherence to monthly completion of the PRO questionnaires, which remained high up to 4 months (98%) and dropped over time (months 5: 83% and 6: 66%). Exploratory outcomes included patient satisfaction as estimated on the Telemedicine Perception Questionnaire (TMPQ, 17-85 points). The mean TMPQ score was 64 (95%CI: 62-66) points, indicating a high degree of approval. Ancillary tests included subgroup analyses of participants with particularly high or low satisfaction and upper extremity disability as a potential obstacle to utility or acceptance. We found no distinct characteristics separating participants with high or low satisfaction.ConclusionsIn this first feasibility trial, the haMSter app for longitudinal PRO monitoring was well received in terms of adherence and satisfaction. ClinicalTrials.gov identifier: NCT04555863.

Project description:Importance:Atrial fibrillation (AF) affects 34 million people worldwide and is a leading cause of stroke. A readily accessible means to continuously monitor for AF could prevent large numbers of strokes and death. Objective:To develop and validate a deep neural network to detect AF using smartwatch data. Design, Setting, and Participants:In this multinational cardiovascular remote cohort study coordinated at the University of California, San Francisco, smartwatches were used to obtain heart rate and step count data for algorithm development. A total of 9750 participants enrolled in the Health eHeart Study and 51 patients undergoing cardioversion at the University of California, San Francisco, were enrolled between February 2016 and March 2017. A deep neural network was trained using a method called heuristic pretraining in which the network approximated representations of the R-R interval (ie, time between heartbeats) without manual labeling of training data. Validation was performed against the reference standard 12-lead electrocardiography (ECG) in a separate cohort of patients undergoing cardioversion. A second exploratory validation was performed using smartwatch data from ambulatory individuals against the reference standard of self-reported history of persistent AF. Data were analyzed from March 2017 to September 2017. Main Outcomes and Measures:The sensitivity, specificity, and receiver operating characteristic C statistic for the algorithm to detect AF were generated based on the reference standard of 12-lead ECG-diagnosed AF. Results:Of the 9750 participants enrolled in the remote cohort, including 347 participants with AF, 6143 (63.0%) were male, and the mean (SD) age was 42 (12) years. There were more than 139 million heart rate measurements on which the deep neural network was trained. The deep neural network exhibited a C statistic of 0.97 (95% CI, 0.94-1.00; P < .001) to detect AF against the reference standard 12-lead ECG-diagnosed AF in the external validation cohort of 51 patients undergoing cardioversion; sensitivity was 98.0% and specificity was 90.2%. In an exploratory analysis relying on self-report of persistent AF in ambulatory participants, the C statistic was 0.72 (95% CI, 0.64-0.78); sensitivity was 67.7% and specificity was 67.6%. Conclusions and Relevance:This proof-of-concept study found that smartwatch photoplethysmography coupled with a deep neural network can passively detect AF but with some loss of sensitivity and specificity against a criterion-standard ECG. Further studies will help identify the optimal role for smartwatch-guided rhythm assessment.

Project description:BackgroundA study was undertaken to evaluate remote monitoring via smartphone sensor-based tests in people with multiple sclerosis (PwMS). This analysis aimed to explore regional neural correlates of digital measures derived from these tests.MethodsIn a 24-week, non-randomized, interventional, feasibility study (NCT02952911), sensor-based tests on the Floodlight Proof-of-Concept app were used to assess cognition (smartphone-based electronic Symbol Digit Modalities Test), upper extremity function (Draw a Shape Test, Pinching Test), and gait and balance (Static Balance Test, Two-Minute Walk Test, U-Turn Test). In this post-hoc analysis, digital measures and standard clinical measures (e.g., Nine-Hole Peg Test [9HPT]) were correlated against regional structural magnetic resonance imaging outcomes. Seventy-six PwMS aged 18-55 years with an Expanded Disability Status Scale score of 0.0-5.5 were enrolled from two different sites (USA and Spain). Sixty-two PwMS were included in this analysis.ResultsWorse performance on digital and clinical measures was associated with smaller regional brain volumes and larger ventricular volumes. Whereas digital and clinical measures had many neural correlates in common (e.g., putamen, globus pallidus, caudate nucleus, lateral occipital cortex), some were observed only for digital measures. For example, Draw a Shape Test and Pinching Test measures, but not 9HPT score, correlated with volume of the hippocampus (r = 0.37 [drawing accuracy over time on the Draw a Shape Test]/ - 0.45 [touching asynchrony on the Pinching Test]), thalamus (r = 0.38/ - 0.41), and pons (r = 0.35/ - 0.35).ConclusionsMultiple neural correlates were identified for the digital measures in a cohort of people with early MS. Digital measures showed associations with brain regions that clinical measures were unable to demonstrate, thus providing potential novel information on functional ability compared with standard clinical assessments.

Project description:BACKGROUND:A lifesaving treatment for myocardial infarction is the placement of a stent in a closed or obstructed coronary artery. The largest modifiable risk factor after receiving a stent is medication adherence to Dual AntiPlatelet Therapy, a combination of P2Y12 inhibitors and aspirin. OBJECTIVE:This study aimed to determine the acceptability of a protocol and an intervention using the My Interventional Drug-Eluting Stent Educational App (MyIDEA) and to evaluate medication adherence using the proportion of days covered (PDC) and platelet activation tests in a multisite randomized controlled trial. METHODS:Potential participants who received a post percutaneous coronary intervention (PCI) procedure with a drug-eluting stent were approached. All patients older than 50 years and who spoke English were recruited. Participants were recruited, baseline demographics were collected, and the Hospital Anxiety and Depression Scale (HADS), Rapid Estimate of Adult Literacy in Medicine-Short Form, Burden-Benefit questionnaire, 36-Item Short Form Health Survey, and PCI knowledge questionnaire were administered. Block randomization was used to randomize participants to either usual care or MyIDEA supplementation. MyIDEA is a personalized educational intervention based on the Kolb experiential learning theory using patient narratives for education. During the visits, participants' blood was collected to measure platelet suppression from medication. During the second and third encounters, the Morisky medication adherence score and cardiology outcomes were measured. The study was conducted at the University of Illinois Hospital and John H Stroger Jr Cook County Hospital with appropriate ethical approvals. Platelet suppression was measured through aspirin reactive units and P2Y12 reactive units. Medication adherence was measured using the PDC. The analysis team was blinded to the participants' group membership. The primary outcome was a feasibility analysis of recruitment and retention. RESULTS:The mean age of participants was 60.4 years (SD 7.1); the majority of patients were black and non-Hispanic. The majority of patients' reading levels were seventh grade or above, and they were not very familiar with other electronic devices for information and communication. The number of control subjects was 21, and the number of participants in the interventional arm was 24. The interventional group was able to use MyIDEA in both the hospital and outpatient setting. However, there was no significant difference in platelet suppression or medication adherence between groups. There were also differences between the groups in terms of depression and anxiety, initially, as measured by HADS. No documented adverse event associated with the intervention was found. CONCLUSIONS:Elderly patients are willing to use tablet devices to be educated about health conditions. Additional studies are required to measure the effectiveness and determine the most suitable timing and location for patient education. TRIAL REGISTRATION:ClinicalTrials.gov NCT04439864; https://clinicaltrials.gov/ct2/show/NCT04439864.

Project description:BACKGROUND:Improved clinical effectiveness and therefore positive modification of multiple sclerosis (MS) with basic therapy can be achieved by long-term regular intake of drugs as prescribed but investigations have shown that a high percentage of patients do not take their medications as prescribed. OBJECTIVES:We assessed the satisfaction and adherence of patients with MS with their current disease-modifying treatment under clinical practice conditions. We compared different facets of satisfaction as well as their internal relationship and identified predictors in an exploratory manner. METHODS:Therapy satisfaction in patients with relapsing-remitting multiple sclerosis (THEPA-MS) was a noninterventional, prospective cross-sectional study performed throughout Germany in 2013 and 2014, and included patients with clinically isolated syndrome or relapsing-remitting MS. We applied a standardized approach to document satisfaction and adherence by patient-reported outcomes (Treatment Satisfaction Questionnaire for Medication) as well as by physician ratings. RESULTS:Of 3312 patients with a mean age of 43.7 years, 73.3% were women and the mean level of disability according to the Expanded Disability Status Scale was 2.29; 13.3% did not receive any medication at the time of documentation, 21.3% received interferon ?1a intramuscularly, 20.7% had interferon ?1a subcutaneously, 17.0% had interferon ?1b subcutaneously and 23.7% had glatiramer acetate. Adherence rates varied between 60% (lifetime) and 96.5% (current medication). Differences between current medications were found for side effects and convenience scores but not for effectiveness, satisfaction and adherence. Higher global satisfaction and effectiveness were associated with fewer relapses, longer duration of medication, lower disability score and the absence of several side effects. CONCLUSION:In a connected model of patient satisfaction, effectiveness, side effects, convenience and adherence, patients' individual needs and concerns have to be addressed. Most differences were found with respect to side effects and convenience of treatment. Therefore, an improvement in these two domains seems to be the most promising proximate approach to elevate adherence levels.

Dataset Information

Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study.

Publications

Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study.

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