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Karas M, Olsen J, Straczkiewicz M, Johnson SA, Burke KM, Iwasaki S, Lahav A, Scheier ZA, Clark AP, Iyer AS, Huang E, Berry JD, Onnela J. Tracking amyotrophic lateral sclerosis disease progression using passively collected smartphone sensor data. Ann Clin Transl Neurol 2024; 11:1380-1392. [PMID: 38816946 PMCID: PMC11187949 DOI: 10.1002/acn3.52050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/03/2024] [Accepted: 03/05/2024] [Indexed: 06/01/2024] Open
Abstract
BACKGROUND Passively collected smartphone sensor data provide an opportunity to study physical activity and mobility unobtrusively over long periods of time and may enable disease monitoring in people with amyotrophic lateral sclerosis (PALS). METHODS We enrolled 63 PALS who used Beiwe mobile application that collected their smartphone accelerometer and GPS data and administered the self-entry ALS Functional Rating Scale-Revised (ALSFRS-RSE) survey. We identified individual steps from accelerometer data and used the Activity Index to summarize activity at the minute level. Walking, Activity Index, and GPS outcomes were then aggregated into day-level measures. We used linear mixed effect models (LMMs) to estimate baseline and monthly change for ALSFRS-RSE scores (total score, subscores Q1-3, Q4-6, Q7-9, Q10-12) and smartphone sensor data measures, as well as the associations between them. FINDINGS The analytic sample (N = 45) was 64.4% male with a mean age of 60.1 years. The mean observation period was 292.3 days. The ALSFRS-RSE total score baseline mean was 35.8 and had a monthly rate of decline of -0.48 (p-value <0.001). We observed statistically significant change over time and association with ALSFRS-RSE total score for four smartphone sensor data-derived measures: walking cadence from top 1 min and log-transformed step count, step count from top 1 min, and Activity Index from top 1 min. INTERPRETATION Smartphone sensors can unobtrusively track physical changes in PALS, potentially aiding disease monitoring and future research.
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Affiliation(s)
- Marta Karas
- Department of Biostatistics, Harvard T.H. Chan School of Public HealthHarvard University677 Huntington Ave.BostonMassachusetts02115USA
| | - Julia Olsen
- Department of Biostatistics, Harvard T.H. Chan School of Public HealthHarvard University677 Huntington Ave.BostonMassachusetts02115USA
| | - Marcin Straczkiewicz
- Department of Biostatistics, Harvard T.H. Chan School of Public HealthHarvard University677 Huntington Ave.BostonMassachusetts02115USA
| | - Stephen A. Johnson
- Department of NeurologyMayo Clinic13400 E. Shea Blvd.ScottsdaleArizona85259USA
| | - Katherine M. Burke
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Satoshi Iwasaki
- Mitsubishi Tanabe Pharma Holdings America, Inc.525 Washington Blvd.Jersey CityNew Jersey07310USA
| | - Amir Lahav
- Mitsubishi Tanabe Pharma Holdings America, Inc.525 Washington Blvd.Jersey CityNew Jersey07310USA
| | - Zoe A. Scheier
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Alison P. Clark
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Amrita S. Iyer
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Emily Huang
- Department of Statistical SciencesWake Forest UniversityWinston‐SalemNorth Carolina27106USA
| | - James D. Berry
- Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital15 Parkman St #835BostonMassachusetts02114USA
| | - Jukka‐Pekka Onnela
- Department of Biostatistics, Harvard T.H. Chan School of Public HealthHarvard University677 Huntington Ave.BostonMassachusetts02115USA
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Bingham IN, Norel R, Roitberg EG, Peller J, Trevisan MA, Agurto C, Shalom DE, Aguirre F, Embon I, Taitz A, Harris D, Wright A, Seaver K, Sullivan S, Green JR, Ostrow LW, Fraenkel E, Berry JD. Listener effort quantifies clinically meaningful progression of dysarthria in people living with amyotrophic lateral sclerosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.31.24308140. [PMID: 38853969 PMCID: PMC11160879 DOI: 10.1101/2024.05.31.24308140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative motor neuron disease that causes progressive muscle weakness. Progressive bulbar dysfunction causes dysarthria and thus social isolation, reducing quality of life. The Everything ALS Speech Study obtained longitudinal clinical information and speech recordings from 292 participants. In a subset of 120 participants, we measured speaking rate (SR) and listener effort (LE), a measure of dysarthria severity rated by speech pathologists from recordings. LE intra- and inter-rater reliability was very high (ICC 0.88 to 0.92). LE correlated with other measures of dysarthria at baseline. LE changed over time in participants with ALS (slope 0.77 pts/month; p<0.001) but not controls (slope 0.005 pts/month; p=0.807). The slope of LE progression was similar in all participants with ALS who had bulbar dysfunction at baseline, regardless of ALS site of onset. LE could be a remotely collected clinically meaningful clinical outcome assessment for ALS clinical trials.
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Affiliation(s)
- Indu Navar Bingham
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
| | | | - Esteban G. Roitberg
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
- Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Buenos Aires, Argentina
| | - Julián Peller
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
- Laboratorio de Neurociencias Cognitivas Computacionales, Humai, Buenos Aires, Argentina
| | - Marcos A Trevisan
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física - CONICET – Universidad de Buenos Aires, Instituto de Física Interdisciplinaria y Aplicada (INFINA). Buenos Aires, Argentina
| | | | - Diego E. Shalom
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física - CONICET – Universidad de Buenos Aires, Instituto de Física Interdisciplinaria y Aplicada (INFINA). Buenos Aires, Argentina
| | - Felipe Aguirre
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
| | - Iair Embon
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
| | - Alan Taitz
- SRI International, Menlo Park, CA, USA. This work was performed working at
| | - Donna Harris
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
- Lewis Katz School of Medicine at Temple University, Department of Neurology, Philadelphia, PA, USA
| | - Amy Wright
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
| | - Katie Seaver
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
- MGH Institute of Health Professions, Charlestown Massachusetts, MA, USA
| | - Stacey Sullivan
- Peter Cohen Foundation dba Everything ALS, Seattle, Washington and Los Altos, California, USA
- Sean M. Healey and AMG Center for ALS, Massachusetts General Hospital & Harvard Medical School, Boston, MA, USA
| | - Jordan R. Green
- MGH Institute of Health Professions, Charlestown Massachusetts, MA, USA
| | - Lyle W. Ostrow
- Lewis Katz School of Medicine at Temple University, Department of Neurology, Philadelphia, PA, USA
| | - Ernest Fraenkel
- Massachusetts Institute of Technology, Department of Biological Engineering, Cambridge, MA, USA
| | - James D. Berry
- Sean M. Healey and AMG Center for ALS, Massachusetts General Hospital & Harvard Medical School, Boston, MA, USA
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Gong R, Zhang L, Su X, Lei C, Yu H, Huang Y, Zhang J, Xu W, Pu Y, Wei X, Yu Q, Shi Q. Remote research burden of follow-up in longitudinal patient-reported outcomes (PROs) data collection: An exploratory sequential mixed-methods study (Preprint).. [DOI: 10.2196/preprints.51290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
BACKGROUND
Longitudinal patient-reported outcomes studies require questionnaire assessments to be administered remotely multiple times, burdening research staff.
OBJECTIVE
To define and quantify the burden that researcher may experience during patient follow-up.
METHODS
Data were collected via interviews and a questionnaire. This study is an exploratory sequential mixed-methods study. Traditional content analysis was used for the qualitative data. Quantitative data were analyzed using Spearman’s correlation, and significance was tested using the chi-square test. Learning curves of healthcare staff regarding follow-up calls were generated using cumulative summation analysis.
RESULTS
We constructed a three-dimension conceptual framework for staff burden: (a) time-related burden, (b) technical-related burden, and (c) emotional-related burden. The quantitative analysis found that follow-up time was significantly correlated with staff experience, workload, and learning curve periods. There was a significant difference between the lost-to-follow-up rate of staff with and without follow-up experience with this program. Staff working on a daily assessment schedule had a higher lost-to-follow-up rate than those on a twice-a-week schedule. Additionally, inexperienced follow-up staff needed 113 calls to achieve stable follow-up time and quality, while experienced staff needed only 55 calls.
CONCLUSIONS
Researchers in longitudinal PROs projects suffer from a multidimensional burden during remote follow-up. Our results may help establish a proper PROs follow-up protocol to reduce the burden on research staff without sacrificing data quality.
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Taylor JC, Heuer HW, Clark AL, Wise AB, Manoochehri M, Forsberg L, Mester C, Rao M, Brushaber D, Kramer J, Welch AE, Kornak J, Kremers W, Appleby B, Dickerson BC, Domoto‐Reilly K, Fields JA, Ghoshal N, Graff‐Radford N, Grossman M, Hall MGH, Huey ED, Irwin D, Lapid MI, Litvan I, Mackenzie IR, Masdeu JC, Mendez MF, Nevler N, Onyike CU, Pascual B, Pressman P, Rankin KP, Ratnasiri B, Rojas JC, Tartaglia MC, Wong B, Gorno‐Tempini ML, Boeve BF, Rosen HJ, Boxer AL, Staffaroni AM. Feasibility and acceptability of remote smartphone cognitive testing in frontotemporal dementia research. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12423. [PMID: 37180971 PMCID: PMC10170087 DOI: 10.1002/dad2.12423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 12/27/2022] [Accepted: 03/01/2023] [Indexed: 05/16/2023]
Abstract
Introduction Remote smartphone assessments of cognition, speech/language, and motor functioning in frontotemporal dementia (FTD) could enable decentralized clinical trials and improve access to research. We studied the feasibility and acceptability of remote smartphone data collection in FTD research using the ALLFTD Mobile App (ALLFTD-mApp). Methods A diagnostically mixed sample of 214 participants with FTD or from familial FTD kindreds (asymptomatic: CDR®+NACC-FTLD = 0 [N = 101]; prodromal: 0.5 [N = 49]; symptomatic ≥1 [N = 51]; not measured [N = 13]) were asked to complete ALLFTD-mApp tests on their smartphone three times within 12 days. They completed smartphone familiarity and participation experience surveys. Results It was feasible for participants to complete the ALLFTD-mApp on their own smartphones. Participants reported high smartphone familiarity, completed ∼ 70% of tasks, and considered the time commitment acceptable (98% of respondents). Greater disease severity was associated with poorer performance across several tests. Discussion These findings suggest that the ALLFTD-mApp study protocol is feasible and acceptable for remote FTD research. HIGHLIGHTS The ALLFTD Mobile App is a smartphone-based platform for remote, self-administered data collection.The ALLFTD Mobile App consists of a comprehensive battery of surveys and tests of executive functioning, memory, speech and language, and motor abilities.Remote digital data collection using the ALLFTD Mobile App was feasible in a multicenter research consortium that studies FTD. Data was collected in healthy controls and participants with a range of diagnoses, particularly FTD spectrum disorders.Remote digital data collection was well accepted by participants with a variety of diagnoses.
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Affiliation(s)
- Jack Carson Taylor
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Hilary W. Heuer
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Annie L. Clark
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Amy B. Wise
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | | | - Leah Forsberg
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
| | - Carly Mester
- Department of Quantitative Health SciencesDivision of Biomedical Statistics and InformaticsMayo ClinicRochesterMinnesotaUSA
| | - Meghana Rao
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
| | - Daniell Brushaber
- Department of Quantitative Health SciencesDivision of Biomedical Statistics and InformaticsMayo ClinicRochesterMinnesotaUSA
| | - Joel Kramer
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Ariane E. Welch
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - John Kornak
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Walter Kremers
- Department of Quantitative Health SciencesDivision of Biomedical Statistics and InformaticsMayo ClinicRochesterMinnesotaUSA
| | - Brian Appleby
- Department of NeurologyCase Western Reserve UniversityClevelandOhioUSA
| | - Bradford C. Dickerson
- Department of NeurologyMassachusetts General Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | | | - Julie A. Fields
- Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | - Nupur Ghoshal
- Center for Advanced Medicine Memory Diagnostic CenterWashington UniversitySaint LouisMissouriUSA
| | | | - Murray Grossman
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Matthew GH Hall
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Edward D. Huey
- Department of NeurologyColumbia UniversityNew YorkNew YorkUSA
| | - David Irwin
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Maria I. Lapid
- Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | - Irene Litvan
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Ian R. Mackenzie
- Department of PathologyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | | | - Mario F. Mendez
- Department of NeurologyUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Naomi Nevler
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral SciencesJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Belen Pascual
- Department of NeurologyHouston MethodistHoustonTexasUSA
| | - Peter Pressman
- Department of NeurologyUniversity of ColoradoAuroraColoradoUSA
| | - Katherine P. Rankin
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Buddhika Ratnasiri
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Julio C. Rojas
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, Division of NeurologyUniversity of TorontoTorontoOntarioCanada
| | - Bonnie Wong
- Department of NeurologyMassachusetts General Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Maria Luisa Gorno‐Tempini
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | | | - Howard J. Rosen
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Adam L. Boxer
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
| | - Adam M. Staffaroni
- Department of Neurology, Memory and Aging Center, University of California, San FranciscoWeill Institute for NeurosciencesSan FranciscoCaliforniaUSA
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Wearable device and smartphone data quantify ALS progression and may provide novel outcome measures. NPJ Digit Med 2023; 6:34. [PMID: 36879025 PMCID: PMC9987377 DOI: 10.1038/s41746-023-00778-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 02/14/2023] [Indexed: 03/08/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) therapeutic development has largely relied on staff-administered functional rating scales to determine treatment efficacy. We sought to determine if mobile applications (apps) and wearable devices can be used to quantify ALS disease progression through active (surveys) and passive (sensors) data collection. Forty ambulatory adults with ALS were followed for 6-months. The Beiwe app was used to administer the self-entry ALS functional rating scale-revised (ALSFRS-RSE) and the Rasch Overall ALS Disability Scale (ROADS) surveys every 2-4 weeks. Each participant used a wrist-worn activity monitor (ActiGraph Insight Watch) or an ankle-worn activity monitor (Modus StepWatch) continuously. Wearable device wear and app survey compliance were adequate. ALSFRS-R highly correlated with ALSFRS-RSE. Several wearable data daily physical activity measures demonstrated statistically significant change over time and associations with ALSFRS-RSE and ROADS. Active and passive digital data collection hold promise for novel ALS trial outcome measure development.
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Walk D, Nicholson K, Locatelli E, Chan J, Macklin EA, Ferment V, Manousakis G, Chase M, Connolly M, Dagostino D, Hall M, Ostrow J, Pothier L, Lieberman C, Gelevski D, Randall R, Sherman AV, Steinhart E, Walker DG, Walker J, Yu H, Wills AM, Schwarzschild MA, Beukenhorst AL, Onnela JP, Berry JD, Cudkowicz ME, Paganoni S. Randomized trial of inosine for urate elevation in amyotrophic lateral sclerosis. Muscle Nerve 2023; 67:378-386. [PMID: 36840949 DOI: 10.1002/mus.27807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 02/17/2023] [Accepted: 02/17/2023] [Indexed: 02/26/2023]
Abstract
INTRODUCTION/AIMS Higher urate levels are associated with improved ALS survival in retrospective studies, however whether raising urate levels confers a survival advantage is unknown. In the Safety of Urate Elevation in Amyotrophic Lateral Sclerosis (SURE-ALS) trial, inosine raised serum urate and was safe and well-tolerated. The SURE-ALS2 trial was designed to assess longer term safety. Functional outcomes and a smartphone application were also explored. METHODS Participants were randomized 2:1 to inosine (n = 14) or placebo (n = 9) for 20 weeks, titrated to serum urate of 7-8 mg/dL. Primary outcomes were safety and tolerability. Functional outcomes were measured with the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R). Mobility and ALSFRS-R were also assessed by a smartphone application. RESULTS During inosine treatment, mean urate ranged 5.68-6.82 mg/dL. Treatment-emergent adverse event (TEAE) incidence was similar between groups (p > .10). Renal TEAEs occurred in three (21%) and hypertension in one (7%) of participants randomized to inosine. Inosine was tolerated in 71% of participants versus placebo 67%. Two participants (14%) in the inosine group experienced TEAEs deemed related to treatment (nephrolithiasis); one was a severe adverse event. Mean ALSFRS-R decline did not differ between groups (p = .69). Change in measured home time was similar between groups. Digital and in-clinic ALSFRS-R correlated well. DISCUSSION Inosine met pre-specified criteria for safety and tolerability. A functional benefit was not demonstrated in this trial designed for safety and tolerability. Findings suggested potential utility for a smartphone application in ALS clinical and research settings.
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Affiliation(s)
- David Walk
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Katharine Nicholson
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Eduardo Locatelli
- Department of Neurology, Holy Cross Hospital, Fort Lauderdale, Florida, USA
| | - James Chan
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Eric A Macklin
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Valerie Ferment
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Georgios Manousakis
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Marianne Chase
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Mariah Connolly
- Clinical Research Organization, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Derek Dagostino
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Meghan Hall
- Clinical Research Organization, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Joseph Ostrow
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Lindsay Pothier
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Cassandra Lieberman
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Dario Gelevski
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Rebecca Randall
- Clinical Research Organization, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Alexander V Sherman
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Erin Steinhart
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Daniela Grasso Walker
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jason Walker
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Hong Yu
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Anne-Marie Wills
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Michael A Schwarzschild
- Department of Neurology, Massachusetts General Hospital, MassGeneral Institute for Neurodegenerative Disease, Boston, Massachusetts, USA
| | - Anna L Beukenhorst
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Jukka-Pekka Onnela
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - James D Berry
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Merit E Cudkowicz
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sabrina Paganoni
- Neurological Clinical Research Institute and Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, Massachusetts, USA
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7
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French MA, Keatley E, Li J, Balasubramanian A, Hansel NN, Wise R, Searson P, Singh A, Raghavan P, Wegener S, Roemmich RT, Celnik P. The feasibility of remotely monitoring physical, cognitive, and psychosocial function in individuals with stroke or chronic obstructive pulmonary disease. Digit Health 2023; 9:20552076231176160. [PMID: 37214659 PMCID: PMC10192672 DOI: 10.1177/20552076231176160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 04/28/2023] [Indexed: 05/24/2023] Open
Abstract
Objective Clinical implementation of remote monitoring of human function requires an understanding of its feasibility. We evaluated adherence and the resources required to monitor physical, cognitive, and psychosocial function in individuals with either chronic obstructive pulmonary disease or stroke during a three-month period. Methods Seventy-three individuals agreed to wear a Fitbit to monitor physical function and to complete monthly online assessments of cognitive and psychosocial function. During a three-month period, we measured adherence to monitoring (1) physical function using average daily wear time, and (2) cognition and psychosocial function using the percentage of assessments completed. We measured the resources needed to promote adherence as (1) the number of participants requiring at least one reminder to synchronize their Fitbit, and (2) the number of reminders needed for each completed cognitive and psychosocial assessment. Results After accounting for withdrawals, the average daily wear time was 77.5 ± 19.9% of the day and did not differ significantly between months 1, 2, and 3 (p = 0.30). To achieve this level of adherence, 64.9% of participants required at least one reminder to synchronize their device. Participants completed 61.0% of the cognitive and psychosocial assessments; the portion of assessments completed each month didnot significantly differ (p = 0.44). Participants required 1.13 ± 0.57 reminders for each completed assessment. Results did not differ by disease diagnosis. Conclusions Remote monitoring of human function in individuals with either chronic obstructive pulmonary disease or stroke is feasible as demonstrated by high adherence. However, the number of reminders required indicates that careful consideration must be given to the resources available to obtain high adherence.
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Affiliation(s)
- Margaret A French
- Department of Physical Medicine and
Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD,
USA
| | - Eva Keatley
- Department of Physical Medicine and
Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD,
USA
| | - Junyao Li
- Department of Physical Medicine and
Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD,
USA
| | - Aparna Balasubramanian
- Division of Pulmonary and Critical Care
Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care
Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Robert Wise
- Division of Pulmonary and Critical Care
Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Peter Searson
- Department of Physical Medicine and
Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD,
USA
- Department of Materials Science and
Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Anil Singh
- Department of Pulmonary and Critical
Care Medicine, Allegheny Health Network, Pittsburg, PA, USA
| | - Preeti Raghavan
- Department of Physical Medicine and
Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD,
USA
| | - Stephen Wegener
- Department of Physical Medicine and
Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD,
USA
| | - Ryan T Roemmich
- Department of Physical Medicine and
Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD,
USA
- Kennedy Krieger Institute, Center for Movement Studies, Baltimore, MD, USA
| | - Pablo Celnik
- Department of Physical Medicine and
Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD,
USA
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8
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Meyer T, Spittel S, Grehl T, Weyen U, Steinbach R, Kettemann D, Petri S, Weydt P, Günther R, Baum P, Schlapakow E, Koch JC, Boentert M, Wolf J, Grosskreutz J, Rödiger A, Ilse B, Metelmann M, Norden J, Koc RY, Körtvélyessy P, Riitano A, Walter B, Hildebrandt B, Schaudinn F, Münch C, Maier A. Remote digital assessment of amyotrophic lateral sclerosis functional rating scale - a multicenter observational study. Amyotroph Lateral Scler Frontotemporal Degener 2022; 24:175-184. [PMID: 35912984 DOI: 10.1080/21678421.2022.2104649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
Objective: Remote self-assessment of the revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R) using digital data capture was investigated for its feasibility as an add-on to ALSFRS-R assessments during multidisciplinary clinic visits. Methods: From August 2017 to December 2021, at 12 ALS centers in Germany, an observational study on remote assessment of the ALSFRS-R was performed. In addition to the assessment of ALSFRS-R during clinic visits, patients were offered a digital self-assessment of the ALSFRS-R - either on a computer or on a mobile application ("ALS-App"). Results: An estimated multicenter cohort of 4,670 ALS patients received care at participating ALS centers. Of these patients, 971 remotely submitted the ALSFRS-R, representing 21% of the multicenter cohort. Of those who opted for remote assessment, 53.7% (n = 521) completed a minimum of 4 ALSFRS-R per year with a mean number of 10.9 assessments per year. Different assessment frequencies were found for patients using a computer (7.9 per year, n = 857) and mobile app (14.6 per year, n = 234). Patients doing remote assessments were more likely to be male and less functionally impaired but many patients with severe disability managed to complete it themselves or with a caregiver (35% of remote ALSFRS-R cohort in King's Stage 4). Conclusions: In a dedicated ALS center setting remote digital self-assessment of ALSFRS-R can provide substantial data which is complementary and potentially an alternative to clinic assessments and could be used for research purposes and person-level patient management. Addressing barriers relating to patient uptake and adherence are key to its success.
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Affiliation(s)
- Thomas Meyer
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Ambulanzpartner Soziotechnologie APST GmbH, Berlin, Germany
| | - Susanne Spittel
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Ambulanzpartner Soziotechnologie APST GmbH, Berlin, Germany
| | - Torsten Grehl
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Alfried Krupp Krankenhaus, Essen, Germany
| | - Ute Weyen
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Berufsgenossenschaftliches Universitätsklinikum Bergmannsheil, Bochum, Germany
| | - Robert Steinbach
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany
| | - Dagmar Kettemann
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Susanne Petri
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Patrick Weydt
- Department for Neurodegenerative Disorders and Gerontopsychiatry, Bonn University, Bonn, Germany
| | - René Günther
- Department of Neurology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,DZNE, German Center for Neurodegenerative Diseases, Research Site Dresden, Dresden, Germany
| | - Petra Baum
- Department of Neurology, Universitätsklinikum Leipzig, Leipzig, Germany
| | - Elena Schlapakow
- Department of Neurology, Universitätsklinikum Halle, Halle (Saale), Germany
| | - Jan Christoph Koch
- Department of Neurology, Universitätsmedizin Göttingen, Göttingen, Germany
| | - Matthias Boentert
- Department of Sleep Medicine and Neuromuscular Disorders, Universitätsklinikum Münster, Münster, Germany
| | - Joachim Wolf
- Department of Neurology, Diako Mannheim, Mannheim, Germany
| | - Julian Grosskreutz
- Precision Neurology, Universitätsklinikum Schleswig-Holstein, Lübeck, Germany
| | - Annekathrin Rödiger
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany
| | - Benjamin Ilse
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany
| | - Moritz Metelmann
- Department of Neurology, Universitätsklinikum Leipzig, Leipzig, Germany
| | - Jenny Norden
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Ruhan Yasemin Koc
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Péter Körtvélyessy
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Alessio Riitano
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Bertram Walter
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | | | | | - Christoph Münch
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Ambulanzpartner Soziotechnologie APST GmbH, Berlin, Germany
| | - André Maier
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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Geronimo A. Remote patient monitoring in neuromuscular disease. Muscle Nerve 2022; 66:233-235. [PMID: 35674416 DOI: 10.1002/mus.27658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 05/31/2022] [Accepted: 06/03/2022] [Indexed: 11/11/2022]
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10
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Beukenhorst AL, Druce KL, De Cock D. Smartphones for musculoskeletal research - hype or hope? Lessons from a decennium of mHealth studies. BMC Musculoskelet Disord 2022; 23:487. [PMID: 35606783 PMCID: PMC9124742 DOI: 10.1186/s12891-022-05420-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 05/10/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Smartphones provide opportunities for musculoskeletal research: they are integrated in participants' daily lives and can be used to collect patient-reported outcomes as well as sensor data from large groups of people. As the field of research with smartphones and smartwatches matures, it has transpired that some of the advantages of this modern technology are in fact double-edged swords. BODY: In this narrative review, we illustrate the advantages of using smartphones for data collection with 18 studies from various musculoskeletal domains. We critically appraised existing literature, debunking some myths around the advantages of smartphones: the myth that smartphone studies automatically enable high engagement, that they reach more representative samples, that they cost little, and that sensor data is objective. We provide a nuanced view of evidence in these areas and discuss strategies to increase engagement, to reach representative samples, to reduce costs and to avoid potential sources of subjectivity in analysing sensor data. CONCLUSION If smartphone studies are designed without awareness of the challenges inherent to smartphone use, they may fail or may provide biased results. Keeping participants of smartphone studies engaged longitudinally is a major challenge. Based on prior research, we provide 6 actions by researchers to increase engagement. Smartphone studies often have participants that are younger, have higher incomes and high digital literacy. We provide advice for reaching more representative participant groups, and for ensuring that study conclusions are not plagued by bias resulting from unrepresentative sampling. Costs associated with app development and testing, data storage and analysis, and tech support are substantial, even if studies use a 'bring your own device'-policy. Exchange of information on costs, collective app development and usage of open-source tools would help the musculoskeletal community reduce costs of smartphone studies. In general, transparency and wider adoption of best practices would help bringing smartphone studies to the next level. Then, the community can focus on specific challenges of smartphones in musculoskeletal contexts, such as symptom-related barriers to using smartphones for research, validating algorithms in patient populations with reduced functional ability, digitising validated questionnaires, and methods to reliably quantify pain, quality of life and fatigue.
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Affiliation(s)
- Anna L Beukenhorst
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA. .,Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
| | - Katie L Druce
- Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Diederik De Cock
- Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven, Leuven, Belgium
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