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Shi JLH, Sit RWS. Impact of 25 Years of Mobile Health Tools for Pain Management in Patients With Chronic Musculoskeletal Pain: Systematic Review. J Med Internet Res 2024; 26:e59358. [PMID: 39150748 PMCID: PMC11364951 DOI: 10.2196/59358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 06/18/2024] [Accepted: 07/16/2024] [Indexed: 08/17/2024] Open
Abstract
BACKGROUND Mobile technologies are increasingly being used in health care and public health practice for patient communication, monitoring, and education. Mobile health (mHealth) tools have also been used to facilitate adherence to chronic musculoskeletal pain (CMP) management, which is critical to achieving improved pain outcomes, quality of life, and cost-effective health care. OBJECTIVE The aim of this systematic review was to evaluate the 25-year trend of the literature on the adherence, usability, feasibility, and acceptability of mHealth interventions in CMP management among patients and health care providers. METHODS We searched the PubMed, Cochrane CENTRAL, MEDLINE, EMBASE, and Web of Science databases for studies assessing the role of mHealth in CMP management from January 1999 to December 2023. Outcomes of interest included the effect of mHealth interventions on patient adherence; pain-specific clinical outcomes after the intervention; and the usability, feasibility, and acceptability of mHealth tools and platforms in chronic pain management among target end users. RESULTS A total of 89 articles (26,429 participants) were included in the systematic review. Mobile apps were the most commonly used mHealth tools (78/89, 88%) among the included studies, followed by mobile app plus monitor (5/89, 6%), mobile app plus wearable sensor (4/89, 4%), and web-based mobile app plus monitor (1/89, 1%). Usability, feasibility, and acceptability or patient preferences for mHealth interventions were assessed in 26% (23/89) of the studies and observed to be generally high. Overall, 30% (27/89) of the studies used a randomized controlled trial (RCT), cohort, or pilot design to assess the impact of the mHealth intervention on patients' adherence, with significant improvements (all P<.05) observed in 93% (25/27) of these studies. Significant (judged at P<.05) between-group differences were reported in 27 of the 29 (93%) RCTs that measured the effect of mHealth on CMP-specific clinical outcomes. CONCLUSIONS There is great potential for mHealth tools to better facilitate adherence to CMP management, and the current evidence supporting their effectiveness is generally high. Further research should focus on the cost-effectiveness of mHealth interventions for better incorporating these tools into health care practices. TRIAL REGISTRATION International Prospective Register of Systematic Reviews (PROSPERO) CRD42024524634; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=524634.
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Affiliation(s)
- Jenny Lin-Hong Shi
- Department of Medicine, Jockey Club School of Public Health and Primary Care, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Regina Wing-Shan Sit
- Department of Medicine, Jockey Club School of Public Health and Primary Care, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
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Armfield N, Elphinston R, Liimatainen J, Scotti Requena S, Eather CE, Edirippulige S, Ritchie C, Robins S, Sterling M. Development and Use of Mobile Messaging for Individuals With Musculoskeletal Pain Conditions: Scoping Review. JMIR Mhealth Uhealth 2024; 12:e55625. [PMID: 39141913 PMCID: PMC11358670 DOI: 10.2196/55625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/29/2024] [Accepted: 06/12/2024] [Indexed: 08/16/2024] Open
Abstract
BACKGROUND Population studies show that musculoskeletal conditions are a leading contributor to the total burden of healthy life lost, second only to cancer and with a similar burden to cardiovascular disease. Prioritizing the delivery of effective treatments is necessary, and with the ubiquity of consumer smart devices, the use of digital health interventions is increasing. Messaging is popular and easy to use and has been studied for a range of health-related uses, including health promotion, encouragement of behavior change, and monitoring of disease progression. It may have a useful role to play in the management and self-management of musculoskeletal conditions. OBJECTIVE Previous reviews on the use of messaging for people with musculoskeletal conditions have focused on synthesizing evidence of effectiveness from randomized controlled trials. In this review, our objective was to map the musculoskeletal messaging literature more broadly to identify information that may inform the design of future messaging interventions and summarize the current evidence of efficacy, effectiveness, and economics. METHODS Following a prepublished protocol developed using the Joanna Briggs Institute Manual for Evidence Synthesis, we conducted a comprehensive scoping review of the literature (2010-2022; sources: PubMed, CINAHL, Embase, and PsycINFO) related to SMS text messaging and app-based messaging for people with musculoskeletal conditions. We described our findings using tables, plots, and a narrative summary. RESULTS We identified a total of 8328 papers for screening, of which 50 (0.6%) were included in this review (3/50, 6% previous reviews and 47/50, 94% papers describing 40 primary studies). Rheumatic diseases accounted for the largest proportion of the included primary studies (19/40, 48%), followed by studies on multiple musculoskeletal conditions or pain sites (10/40, 25%), back pain (9/40, 23%), neck pain (1/40, 3%), and "other" (1/40, 3%). Most studies (33/40, 83%) described interventions intended to promote positive behavior change, typically by encouraging increased physical activity and exercise. The studies evaluated a range of outcomes, including pain, function, quality of life, and medication adherence. Overall, the results either favored messaging interventions or had equivocal outcomes. While the theoretical underpinnings of the interventions were generally well described, only 4% (2/47) of the papers provided comprehensive descriptions of the messaging intervention design and development process. We found no relevant economic evaluations. CONCLUSIONS Messaging has been used for the care and self-management of a range of musculoskeletal conditions with generally favorable outcomes reported. However, with few exceptions, design considerations are poorly described in the literature. Further work is needed to understand and disseminate information about messaging content and message delivery characteristics, such as timing and frequency specifically for people with musculoskeletal conditions. Similarly, further work is needed to understand the economic effects of messaging and practical considerations related to implementation and sustainability. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.1136/bmjopen-2021-048964.
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Affiliation(s)
- Nigel Armfield
- RECOVER Injury Research Centre, The University of Queensland, Brisbane, Australia
- National Health and Medical Research Council (NHMRC) Centre for Research Excellence in Better Outcomes for Compensable Injury, Brisbane, Australia
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia
- STARS Education and Research Alliance, Surgical Treatment and Rehabilitation Service, The University of Queensland and Metro North Health, Brisbane, Australia
| | - Rachel Elphinston
- RECOVER Injury Research Centre, The University of Queensland, Brisbane, Australia
- National Health and Medical Research Council (NHMRC) Centre for Research Excellence in Better Outcomes for Compensable Injury, Brisbane, Australia
- STARS Education and Research Alliance, Surgical Treatment and Rehabilitation Service, The University of Queensland and Metro North Health, Brisbane, Australia
- School of Psychology, The University of Queensland, St Lucia, Australia
| | - Jenna Liimatainen
- RECOVER Injury Research Centre, The University of Queensland, Brisbane, Australia
- National Health and Medical Research Council (NHMRC) Centre for Research Excellence in Better Outcomes for Compensable Injury, Brisbane, Australia
- STARS Education and Research Alliance, Surgical Treatment and Rehabilitation Service, The University of Queensland and Metro North Health, Brisbane, Australia
| | - Simone Scotti Requena
- Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Chloe-Emily Eather
- RECOVER Injury Research Centre, The University of Queensland, Brisbane, Australia
- National Health and Medical Research Council (NHMRC) Centre for Research Excellence in Better Outcomes for Compensable Injury, Brisbane, Australia
- STARS Education and Research Alliance, Surgical Treatment and Rehabilitation Service, The University of Queensland and Metro North Health, Brisbane, Australia
- School of Health and Rehabilitation Sciences, The University of Queensland, St Lucia, Australia
| | - Sisira Edirippulige
- Centre for Online Health, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Carrie Ritchie
- RECOVER Injury Research Centre, The University of Queensland, Brisbane, Australia
| | - Sarah Robins
- RECOVER Injury Research Centre, The University of Queensland, Brisbane, Australia
| | - Michele Sterling
- RECOVER Injury Research Centre, The University of Queensland, Brisbane, Australia
- National Health and Medical Research Council (NHMRC) Centre for Research Excellence in Better Outcomes for Compensable Injury, Brisbane, Australia
- STARS Education and Research Alliance, Surgical Treatment and Rehabilitation Service, The University of Queensland and Metro North Health, Brisbane, Australia
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Marcuzzi A, Klevanger NE, Aasdahl L, Gismervik S, Bach K, Mork PJ, Nordstoga AL. An Artificial Intelligence-Based App for Self-Management of Low Back and Neck Pain in Specialist Care: Process Evaluation From a Randomized Clinical Trial. JMIR Hum Factors 2024; 11:e55716. [PMID: 38980710 PMCID: PMC11267091 DOI: 10.2196/55716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 04/25/2024] [Accepted: 04/26/2024] [Indexed: 07/10/2024] Open
Abstract
BACKGROUND Self-management is endorsed in clinical practice guidelines for the care of musculoskeletal pain. In a randomized clinical trial, we tested the effectiveness of an artificial intelligence-based self-management app (selfBACK) as an adjunct to usual care for patients with low back and neck pain referred to specialist care. OBJECTIVE This study is a process evaluation aiming to explore patients' engagement and experiences with the selfBACK app and specialist health care practitioners' views on adopting digital self-management tools in their clinical practice. METHODS App usage analytics in the first 12 weeks were used to explore patients' engagement with the SELFBACK app. Among the 99 patients allocated to the SELFBACK interventions, a purposive sample of 11 patients (aged 27-75 years, 8 female) was selected for semistructured individual interviews based on app usage. Two focus group interviews were conducted with specialist health care practitioners (n=9). Interviews were analyzed using thematic analysis. RESULTS Nearly one-third of patients never accessed the app, and one-third were low users. Three themes were identified from interviews with patients and health care practitioners: (1) overall impression of the app, where patients discussed the interface and content of the app, reported on usability issues, and described their app usage; (2) perceived value of the app, where patients and health care practitioners described the primary value of the app and its potential to supplement usual care; and (3) suggestions for future use, where patients and health care practitioners addressed aspects they believed would determine acceptance. CONCLUSIONS Although the app's uptake was relatively low, both patients and health care practitioners had a positive opinion about adopting an app-based self-management intervention for low back and neck pain as an add-on to usual care. Both described that the app could reassure patients by providing trustworthy information, thus empowering them to take actions on their own. Factors influencing app acceptance and engagement, such as content relevance, tailoring, trust, and usability properties, were identified. TRIAL REGISTRATION ClinicalTrials.gov NCT04463043; https://clinicaltrials.gov/study/NCT04463043.
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Affiliation(s)
- Anna Marcuzzi
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Nina Elisabeth Klevanger
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Lene Aasdahl
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Unicare Helsefort Rehabilitation Center, Rissa, Norway
| | - Sigmund Gismervik
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kerstin Bach
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anne Lovise Nordstoga
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
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Dobija L, Lechauve JB, Mbony-Irankunda D, Plan-Paquet A, Dupeyron A, Coudeyre E. Smartphone applications are used for self-management, telerehabilitation, evaluation and data collection in low back pain healthcare: a scoping review. F1000Res 2024; 11:1001. [PMID: 38846061 PMCID: PMC11153999 DOI: 10.12688/f1000research.123331.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/03/2024] [Indexed: 06/09/2024] Open
Abstract
Background Smartphone use has grown in providing healthcare for patients with low back pain (LBP), but the literature lacks an analysis of the use of smartphone apps. This scoping review aimed to identify current areas of smartphone apps use for managing LBP. We also aimed to evaluate the current status of the effectiveness or scientific validity of such use and determine perspectives for their potential development. Methods We searched PubMed, PEDro and Embase for articles published in English up to May 3 rd, 2021 that investigated smartphone use for LBP healthcare and their purpose. All types of study design were accepted. Studies concerning telemedicine or telerehabilitation but without use of a smartphone were not included. The same search strategy was performed by two researchers independently and a third researcher validated the synthesis of the included studies. Results We included 43 articles: randomised controlled trials (RCTs) (n=12), study protocols (n=6), reliability/validity studies (n=6), systematic reviews (n=7), cohort studies (n=4), qualitative studies (n=6), and case series (n=1). The purposes of the smartphone app were for 1) evaluation, 2) telerehabilitation, 3) self-management, and 4) data collection. Self-management was the most-studied use, showing promising results derived from moderate- to good-quality RCTs for patients with chronic LBP and patients after spinal surgery. Promising results exist regarding evaluation and data collection use and contradictory results regarding measurement use. Conclusions This scoping review revealed a notable interest in the scientific literatures regarding the use of smartphone apps for LBP patients. The identified purposes point to current scientific status and perspectives for further studies including RCTs and systematic reviews targeting specific usage.
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Affiliation(s)
- Lech Dobija
- UNH, INRAE, Université Clermont-Auvergne, Clermont-Ferrand, Puy de Dôme, 63000, France
- Service de Médecine Physique et de Réadaptation, Centre Hospitalo-Universitaire (CHU) de Clermont Ferrand, Cébazat, Puy de Dôme, 63118, France
| | - Jean-Baptiste Lechauve
- Service de Médecine Physique et de Réadaptation, Centre Hospitalo-Universitaire (CHU) de Clermont Ferrand, Cébazat, Puy de Dôme, 63118, France
| | - Didier Mbony-Irankunda
- Service de Médecine Physique et de Réadaptation, Centre Hospitalo-Universitaire (CHU) de Clermont Ferrand, Cébazat, Puy de Dôme, 63118, France
| | - Anne Plan-Paquet
- Service de Médecine Physique et de Réadaptation, Centre Hospitalo-Universitaire (CHU) de Clermont Ferrand, Cébazat, Puy de Dôme, 63118, France
| | - Arnaud Dupeyron
- Université Montpellier, Nimes, 30900, France
- Service de Médecine Physique et de Réadaptation, Centre Hospitalo-Universitaire (CHU) de Nimes, Nimes, 30900, France
| | - Emmanuel Coudeyre
- UNH, INRAE, Université Clermont-Auvergne, Clermont-Ferrand, Puy de Dôme, 63000, France
- Service de Médecine Physique et de Réadaptation, Centre Hospitalo-Universitaire (CHU) de Clermont Ferrand, Cébazat, Puy de Dôme, 63118, France
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Zhou T, Salman D, McGregor A. mHealth Apps for the Self-Management of Low Back Pain: Systematic Search in App Stores and Content Analysis. JMIR Mhealth Uhealth 2024; 12:e53262. [PMID: 38300700 PMCID: PMC10870204 DOI: 10.2196/53262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/06/2023] [Accepted: 12/21/2023] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND With the rapid development of mobile health (mHealth) technology, many health apps have been introduced to the commercial market for people with back pain conditions. However, little is known about their content, quality, approaches to care for low back pain (LBP), and associated risks of use. OBJECTIVE The aims of this research were to (1) identify apps for the self-management of LBP currently on the market and (2) assess their quality, intervention content, theoretical approaches, and risk-related approaches. METHODS The UK iTunes and Google Play stores were initially searched for apps related to the self-management of LBP in May 2022. A repeat search in June 2023 was conducted to ensure that any relevant new apps developed in the last year were incorporated into the review. A total of 3 keywords recommended by the Cochrane Back and Neck Group were used to search apps "low back pain," "back pain," and "lumbago." The quality of the apps was assessed by using the 5-point Mobile App Rating Scale (MARS). RESULTS A total of 69 apps (25 iOS and 44 Android) met the inclusion criteria. These LBP self-management apps mainly provide recommendations on muscle stretching (n=51, 73.9%), muscle strengthening (n=42, 60.9%), core stability exercises (n=32, 46.4%), yoga (n=19, 27.5%), and information about LBP mechanisms (n=17, 24.6%). Most interventions (n=14, 78%) are consistent with the recommendations in the National Institute for Health and Care Excellence (NICE) guidelines. The mean (SD) MARS overall score of included apps was 2.4 (0.44) out of a possible 5 points. The functionality dimension was associated with the highest score (3.0), whereas the engagement and information dimension resulted in the lowest score (2.1). Regarding theoretical and risk-related approaches, 18 (26.1%) of the 69 apps reported the rate of intervention progression, 11 (15.9%) reported safety checks, only 1 (1.4%) reported personalization of care, and none reported the theoretical care model or the age group targeted. CONCLUSIONS mHealth apps are potentially promising alternatives to help people manage their LBP; however, most of the LBP self-management apps were of poor quality and did not report the theoretical approaches to care and their associated risks. Although nearly all apps reviewed included a component of care listed in the NICE guidelines, the model of care delivery or embracement of care principles such as the application of a biopsychosocial model was unclear.
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Affiliation(s)
- Tianyu Zhou
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - David Salman
- Department of Primary Care and Public Health, Imperial College London, London, United Kingdom
| | - Alison McGregor
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
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Rivera-Romero O, Gabarron E, Ropero J, Denecke K. Designing personalised mHealth solutions: An overview. J Biomed Inform 2023; 146:104500. [PMID: 37722446 DOI: 10.1016/j.jbi.2023.104500] [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: 02/28/2023] [Revised: 09/14/2023] [Accepted: 09/16/2023] [Indexed: 09/20/2023]
Abstract
INTRODUCTION Mobile health, or mHealth, is based on mobile information and communication technologies and provides solutions for empowering individuals to participate in healthcare. Personalisation techniques have been used to increase user engagement and adherence to interventions delivered as mHealth solutions. This study aims to explore the current state of personalisation in mHealth, including its current trends and implementation. MATERIALS AND METHODS We conducted a review following PRISMA guidelines. Four databases (PubMed, ACM Digital Library, IEEE Xplore, and APA PsycInfo) were searched for studies on mHealth solutions that integrate personalisation. The retrieved papers were assessed for eligibility and useful information regarding integrated personalisation techniques. RESULTS Out of the 1,139 retrieved studies, 62 were included in the narrative synthesis. Research interest in the personalisation of mHealth solutions has increased since 2020. mHealth solutions were mainly applied to endocrine, nutritional, and metabolic diseases; mental, behavioural, or neurodevelopmental diseases; or the promotion of healthy lifestyle behaviours. Its main purposes are to support disease self-management and promote healthy lifestyle behaviours. Mobile applications are the most prevalent technological solution. Although several design models, such as user-centred and patient-centred designs, were used, no specific frameworks or models for personalisation were followed. These solutions rely on behaviour change theories, use gamification or motivational messages, and personalise the content rather than functionality. A broad range of data is used for personalisation purposes. There is a lack of studies assessing the efficacy of these solutions; therefore, further evidence is needed. DISCUSSION Personalisation in mHealth has not been well researched. Although several techniques have been integrated, the effects of using a combination of personalisation techniques remain unclear. Although personalisation is considered a persuasive strategy, many mHealth solutions do not employ it. CONCLUSIONS Open research questions concern guidelines for successful personalisation techniques in mHealth, design frameworks, and comprehensive studies on the effects and interactions among multiple personalisation techniques.
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Affiliation(s)
- Octavio Rivera-Romero
- Electronic Technology Department, Universidad de Sevilla, Spain; Instituto de Investigación en Informática de la Universidad de Sevilla, Spain.
| | - Elia Gabarron
- Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway; Department of Education, ICT and Learning, Østfold University College, Halden, Norway
| | - Jorge Ropero
- Electronic Technology Department, Universidad de Sevilla, Spain
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Bardal EM, Sandal LF, Nilsen TIL, Nicholl BI, Mork PJ, Søgaard K. Do age, gender, and education modify the effectiveness of app-delivered and tailored self-management support among adults with low back pain?-Secondary analysis of the selfBACK randomised controlled trial. PLOS DIGITAL HEALTH 2023; 2:e0000302. [PMID: 37738237 PMCID: PMC10516425 DOI: 10.1371/journal.pdig.0000302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 06/19/2023] [Indexed: 09/24/2023]
Abstract
selfBACK is an artificial intelligence based self-management app for low back pain (LBP) recently reported to reduce LBP-related disability. The aim of this study was to examine if age, gender, or education modify the effectiveness of the selfBACK intervention using secondary analysis of the selfBACK randomized controlled trial. Persons seeking care for LBP were recruited from primary care in Denmark and Norway and an outpatient clinic (Denmark). The intervention group (n = 232) received the selfBACK app adjunct to usual care. The control group (n = 229) received usual care only. Analyses were stratified by age (18-34, 35-64, ≥65 years), gender (male, female), and education (≤12, >12 years) to investigate differences in effect at three and nine months follow-up on LBP-related disability (Roland-Morris Disability Questionnaire [RMDQ]), LBP intensity and pain self-efficacy. Overall, there was no effect modification for any of the sociodemographic factors. However, data on LBP-related disability suggest that the effect of the intervention was somewhat more beneficial in older than in younger participants. The difference between the intervention and control group due to interaction was 2.6 (95% CI: 0.4 to 4.9) RMDQ points for those aged ≥65 years as compared to those aged 35-64 years. In conclusion, age, gender, or education did not influence the effect of the selfBACK intervention on LBP-related disability. However, older participants may have an additional long-term positive effect compared to younger participants. Trial registration: ClinicalTrials.gov Identifier: NCT03798288.
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Affiliation(s)
- Ellen Marie Bardal
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Clinic of Rehabilitation, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Louise Fleng Sandal
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark (UoSD), Odense M, Denmark
| | - Tom Ivar Lund Nilsen
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Clinic of Anaesthesia and Intensive Care, St Olavs Hospital, Trondheim University Hospital,Trondheim, Norway
| | - Barbara I. Nicholl
- Institute of Health and Wellbeing, University of Glasgow (GLA), Glasgow, United Kingdom
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Karen Søgaard
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark (UoSD), Odense M, Denmark
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Nordstoga AL, Aasdahl L, Sandal LF, Dalager T, Kongsvold A, Mork PJ, Nilsen TIL. The Role of Pain Duration and Pain Intensity on the Effectiveness of App-Delivered Self-Management for Low Back Pain (selfBACK): Secondary Analysis of a Randomized Controlled Trial. JMIR Mhealth Uhealth 2023; 11:e40422. [PMID: 37656023 PMCID: PMC10501500 DOI: 10.2196/40422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 12/20/2022] [Accepted: 06/09/2023] [Indexed: 09/02/2023] Open
Abstract
Background Clinical guidelines for nonspecific low back pain (LBP) recommend self-management tailored to individual needs and capabilities as a first-line treatment. Mobile health solutions are a promising method for delivering tailored self-management interventions to patients with nonspecific LBP. However, it is not clear if the effectiveness of such self-management interventions depends on patients' initial pain characteristics. High pain intensity and long-term symptoms of LBP have been associated with an unfavorable prognosis, and current best evidence indicates that long-term LBP (lasting more than 3 months) requires a more extensive treatment approach compared to more acute LBP. The artificial intelligence-based selfBACK app supports tailored and evidence-based self-management of nonspecific LBP. In a recent randomized controlled trial, we showed that individuals who received the selfBACK app in addition to usual care had lower LBP-related disability at the 3-month follow-up compared to those who received usual care only. This effect was sustained at 6 and 9 months. Objective This study aims to explore if the baseline duration and intensity of LBP influence the effectiveness of the selfBACK intervention in a secondary analysis of the selfBACK randomized controlled trial. Methods In the selfBACK trial, 461 adults (18 years or older) who sought care for nonspecific LBP in primary care or at an outpatient spine clinic were randomized to receive the selfBACK intervention adjunct to usual care (n=232) or usual care alone (n=229). In this secondary analysis, the participants were stratified according to the duration of the current LBP episode at baseline (≤12 weeks vs >12 weeks) or baseline LBP intensity (≤5 points vs >5 points) measured by a 0-10 numeric rating scale. The outcomes were LBP-related disability measured by the Roland-Morris Disability Questionnaire (0- to 24-point scale), average LBP intensity, pain self-efficacy, and global perceived effect. To assess whether the duration and intensity of LBP influenced the effect of selfBACK, we estimated the difference in treatment effect between the strata at the 3- and 9-month follow-ups with a 95% CI. Results Overall, there was no difference in effect for patients with different durations or intensities of LBP at either the 3- or 9-month follow-ups. However, there was suggestive evidence that the effect of the selfBACK intervention on LBP-related disability at the 3-month follow-up was largely confined to people with the highest versus the lowest LBP intensity (mean difference between the intervention and control group -1.8, 95% CI -3.0 to -0.7 vs 0.2, 95% CI -1.1 to 0.7), but this was not sustained at the 9-month follow-up. Conclusions The results suggest that the intensity and duration of LBP have negligible influence on the effectiveness of the selfBACK intervention on LBP-related disability, average LBP intensity, pain self-efficacy, and global perceived effect.
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Affiliation(s)
- Anne Lovise Nordstoga
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, Trondheim University Hospital, Trondheim, Norway
| | - Lene Aasdahl
- Unicare Helsefort Rehabilitation Center, Rissa, Norway
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Louise Fleng Sandal
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Tina Dalager
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Atle Kongsvold
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tom Ivar Lund Nilsen
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Anaesthesia and Intensive Care, Trondheim University Hospital, Trondheim, Norway
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Lewkowicz D, Bottinger E, Siegel M. Economic Evaluation of Digital Therapeutic Care Apps for Unsupervised Treatment of Low Back Pain: Monte Carlo Simulation. JMIR Mhealth Uhealth 2023; 11:e44585. [PMID: 37384379 PMCID: PMC10365619 DOI: 10.2196/44585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/26/2023] [Accepted: 05/23/2023] [Indexed: 06/30/2023] Open
Abstract
BACKGROUND Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany. OBJECTIVE The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results. METHODS The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany. RESULTS The Monte Carlo simulation yielded on average a €135.97 (a currency exchange rate of EUR €1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional €34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently €239.96 to €164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%. CONCLUSIONS Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps.
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Affiliation(s)
- Daniel Lewkowicz
- Digital Health Center, Hasso Plattner Insitute, University of Potsdam, Potsdam, Germany
| | - Erwin Bottinger
- Digital Health Center, Hasso Plattner Insitute, University of Potsdam, Potsdam, Germany
| | - Martin Siegel
- Department of Empirical Health Economics, Technische Universität Berlin, Berlin, Germany
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10
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Marcuzzi A, Nordstoga AL, Bach K, Aasdahl L, Nilsen TIL, Bardal EM, Boldermo NØ, Falkener Bertheussen G, Marchand GH, Gismervik S, Mork PJ. Effect of an Artificial Intelligence-Based Self-Management App on Musculoskeletal Health in Patients With Neck and/or Low Back Pain Referred to Specialist Care: A Randomized Clinical Trial. JAMA Netw Open 2023; 6:e2320400. [PMID: 37368401 DOI: 10.1001/jamanetworkopen.2023.20400] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/28/2023] Open
Abstract
Importance Self-management is a key element in the care of persistent neck and low back pain. Individually tailored self-management support delivered via a smartphone app in a specialist care setting has not been tested. Objective To determine the effect of individually tailored self-management support delivered via an artificial intelligence-based app (SELFBACK) adjunct to usual care vs usual care alone or nontailored web-based self-management support (e-Help) on musculoskeletal health. Design, Setting, and Participants This randomized clinical trial recruited adults 18 years or older with neck and/or low back pain who had been referred to and accepted on a waiting list for specialist care at a multidisciplinary hospital outpatient clinic for back, neck, and shoulder rehabilitation. Participants were enrolled from July 9, 2020, to April 29, 2021. Of 377 patients assessed for eligibility, 76 did not complete the baseline questionnaire, and 7 did not meet the eligibility criteria (ie, did not own a smartphone, were unable to take part in exercise, or had language barriers); the remaining 294 patients were included in the study and randomized to 3 parallel groups, with follow-up of 6 months. Interventions Participants were randomly assigned to receive app-based individually tailored self-management support in addition to usual care (app group), web-based nontailored self-management support in addition to usual care (e-Help group), or usual care alone (usual care group). Main Outcomes and Measures The primary outcome was change in musculoskeletal health measured by the Musculoskeletal Health Questionnaire (MSK-HQ) at 3 months. Secondary outcomes included change in musculoskeletal health measured by the MSK-HQ at 6 weeks and 6 months and pain-related disability, pain intensity, pain-related cognition, and health-related quality of life at 6 weeks, 3 months, and 6 months. Results Among 294 participants (mean [SD] age, 50.6 [14.9] years; 173 women [58.8%]), 99 were randomized to the app group, 98 to the e-Help group, and 97 to the usual care group. At 3 months, 243 participants (82.7%) had complete data on the primary outcome. In the intention-to-treat analysis at 3 months, the adjusted mean difference in MSK-HQ score between the app and usual care groups was 0.62 points (95% CI, -1.66 to 2.90 points; P = .60). The adjusted mean difference between the app and e-Help groups was 1.08 points (95% CI, -1.24 to 3.41 points; P = .36). Conclusions and Relevance In this randomized clinical trial, individually tailored self-management support delivered via an artificial intelligence-based app adjunct to usual care was not significantly more effective in improving musculoskeletal health than usual care alone or web-based nontailored self-management support in patients with neck and/or low back pain referred to specialist care. Further research is needed to investigate the utility of implementing digitally supported self-management interventions in the specialist care setting and to identify instruments that capture changes in self-management behavior. Trial Registration ClinicalTrials.gov Identifier: NCT04463043.
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Affiliation(s)
- Anna Marcuzzi
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway
| | - Anne Lovise Nordstoga
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kerstin Bach
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Lene Aasdahl
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Unicare Helsefort Rehabilitation Center, Rissa, Norway
| | - Tom Ivar Lund Nilsen
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Anesthesia and Intensive Care, St Olavs Hospital, Trondheim, Norway
| | - Ellen Marie Bardal
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Nora Østbø Boldermo
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway
| | - Gro Falkener Bertheussen
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Gunn Hege Marchand
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Sigmund Gismervik
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
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11
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Kermani F, Zarkesh MR, Vaziri M, Sheikhtaheri A. A case-based reasoning system for neonatal survival and LOS prediction in neonatal intensive care units: a development and validation study. Sci Rep 2023; 13:8421. [PMID: 37225782 DOI: 10.1038/s41598-023-35333-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 05/16/2023] [Indexed: 05/26/2023] Open
Abstract
Early prediction of neonates' survival and Length of Stay (LOS) in Neonatal Intensive Care Units (NICU) is effective in decision-making. We developed an intelligent system to predict neonatal survival and LOS using the "Case-Based Reasoning" (CBR) method. We developed a web-based CBR system based on K-Nearest Neighborhood (KNN) on 1682 neonates and 17 variables for mortality and 13 variables for LOS and evaluated the system with 336 retrospectively collected data. We implemented the system in a NICU to externally validate the system and evaluate the system prediction acceptability and usability. Our internal validation on the balanced case base showed high accuracy (97.02%), and F-score (0.984) for survival prediction. The root Mean Square Error (RMSE) for LOS was 4.78 days. External validation on the balanced case base indicated high accuracy (98.91%), and F-score (0.993) to predict survival. RMSE for LOS was 3.27 days. Usability evaluation showed that more than half of the issues identified were related to appearance and rated as a low priority to be fixed. Acceptability assessment showed a high acceptance and confidence in responses. The usability score (80.71) indicated high system usability for neonatologists. This system is available at http://neonatalcdss.ir/ . Positive results of our system in terms of performance, acceptability, and usability indicated this system can be used to improve neonatal care.
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Affiliation(s)
- Farzaneh Kermani
- Health Information Technology Department, School of Allied Medical Sciences, Semnan University of Medical Sciences, Semnan, Iran
| | - Mohammad Reza Zarkesh
- Maternal, Fetal and Neonatal Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Department of Neonatology, Yas Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Abbas Sheikhtaheri
- Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
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12
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Tousignant-Laflamme Y, Longtin C, Coutu MF, Gaudreault N, Kairy D, Nastasiag I, Léonard G. Self-management programs to ensure sustainable return to work following long-term sick leave due to low back pain: A sequential qualitative study. Work 2023:WOR220202. [PMID: 36641727 DOI: 10.3233/wor-220202] [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: 01/12/2023] Open
Abstract
BACKGROUND Low back pain (LBP) is a prevalent condition frequently leading to disability. Research suggests that self-management (SM) programs for chronic LBP should include strategies to promote sustainable return to work. OBJECTIVES This study aimed to 1) validate and prioritize the essential content elements of a SM program in light of the needs of workplace representatives, and 2) identify the main facilitators and barriers to be considered when developing and implementing a SM program delivered via information and communication technologies (ICT). METHODS A sequential qualitative design was used. We recruited workplace representatives and potential future users of SM programs (union representatives and employers) and collected data through focus groups and nominal group techniques to validate the relevance of the different elements included into 3 broad categories (Understand, Learn, Apply), as well as to highlight potential barriers and facilitators. RESULTS Eleven participants took part in this study. The content elements proposed in the literature for SM programs were found to align with potential future users' needs, with participants ranking the same elements as those proposed in the scientific literature as the most important across all categories. Although some barriers were identified, workplace representatives believed that ICT offer an appropriate strategy for delivering individualized SM programs to injured workers who have returned to work. CONCLUSION Our study suggests that the elements identified in the literature as essential components of SM programs designed to ensure a sustainable return to work for people with LBP are in line with the needs of future users.
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Affiliation(s)
- Yannick Tousignant-Laflamme
- School of Rehabilitation, Université de Sherbrooke, Sherbrooke, QC,Canada.,Clinical Research Centre of the CHUS, CIUSSS de l'Estrie-CHUS, Sherbrooke, QC,Canada
| | - Christian Longtin
- School of Rehabilitation, Université de Sherbrooke, Sherbrooke, QC,Canada
| | - Marie-France Coutu
- CAPRIT, Université de Sherbrooke, Longueuil, QC,Canada.,School of Rehabilitation, Université de Sherbrooke, Longueuil, QC,Canada
| | - Nathaly Gaudreault
- School of Rehabilitation, Université de Sherbrooke, Sherbrooke, QC,Canada.,Clinical Research Centre of the CHUS, CIUSSS de l'Estrie-CHUS, Sherbrooke, QC,Canada
| | - Dahlia Kairy
- School of Rehabilitation, Université de Montréal, Montréal, QC,Canada.,Centre de Recherche Interdisciplinaire en Réadaptation, Montréal, QC,Canada
| | | | - Guillaume Léonard
- School of Rehabilitation, Université de Sherbrooke, Sherbrooke, QC,Canada.,Research Centre on Aging, CIUSSS de l'Estrie-CHUS, Sherbrooke, QC,Canada
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13
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Carvalho C, Prando BC, Dantas LO, Serrão PRMDS. Mobile health technologies for the management of spine disorders: A systematic review of mHealth applications in Brazil. Musculoskelet Sci Pract 2022; 60:102562. [PMID: 35413592 DOI: 10.1016/j.msksp.2022.102562] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 03/17/2022] [Accepted: 04/04/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Spine disorders are conditions that affect a growing number of individuals, and mobile health (mHealth) applications (apps) offer potential to assist the self-management of these conditions. OBJECTIVES To perform a systematic review of the availability of mHealth apps for patients with spine disorders at Brazilian online stores and evaluate the apps in terms of engagement, user interface, experience, and quality of the information. DESIGN Systematic review. METHOD A search for spine disorders mHealth apps from the Google Play Store and AppStore in Brazil was performed by two independent reviewers on June 2021. Only smartphone apps in Brazilian Portuguese directed at spine disorders that provided information about education, counseling, exercise, or monitoring of patient health were included. The quality of eligible mHealth apps was assessed using the Mobile App Rating Scale (MARS). RESULTS Of the 2775 mHealth apps found, 10 were eligible for inclusion. All apps offered exercise programs. Three apps also offered tools to track patient-reported symptoms, nutritional orientation, or educational content in addition to the exercise program. Using MARS, the apps scored poorly in terms of quality, with an overall mean score ±standard deviation of 2.75 ± 0.63 on a scale of 1-5 points. Most apps scored poorly for credibility, user interface, and engagement. CONCLUSIONS The mHealth apps for spine disorders currently available in Brazil are of poor quality and limited functionality. Effective collaboration between industry and researchers is needed to develop better user-centered mHealth apps that can empower patients with these conditions.
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Affiliation(s)
- Cristiano Carvalho
- Physical Therapy Department, Federal University of São Carlos, São Carlos, SP, Brazil; Physical Therapy Post-Graduate Program, Federal University of São Carlos, São Carlos, SP, Brazil.
| | | | - Lucas Ogura Dantas
- Physical Therapy Department, Federal University of São Carlos, São Carlos, SP, Brazil; Physical Therapy Post-Graduate Program, Federal University of São Carlos, São Carlos, SP, Brazil
| | - Paula Regina Mendes da Silva Serrão
- Physical Therapy Department, Federal University of São Carlos, São Carlos, SP, Brazil; Physical Therapy Post-Graduate Program, Federal University of São Carlos, São Carlos, SP, Brazil
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14
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Lewkowicz D, Wohlbrandt AM, Bottinger E. Digital Therapeutic Care Apps With Decision-Support Interventions for People With Low Back Pain in Germany: Cost-Effectiveness Analysis. JMIR Mhealth Uhealth 2022; 10:e35042. [PMID: 35129454 PMCID: PMC8861873 DOI: 10.2196/35042] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 12/17/2021] [Accepted: 12/29/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Digital therapeutic care apps provide a new effective and scalable approach for people with nonspecific low back pain (LBP). Digital therapeutic care apps are also driven by personalized decision-support interventions that support the user in self-managing LBP, and may induce prolonged behavior change to reduce the frequency and intensity of pain episodes. However, these therapeutic apps are associated with high attrition rates, and the initial prescription cost is higher than that of face-to-face physiotherapy. In Germany, digital therapeutic care apps are now being reimbursed by statutory health insurance; however, price targets and cost-driving factors for the formation of the reimbursement rate remain unexplored. OBJECTIVE The aim of this study was to evaluate the cost-effectiveness of a digital therapeutic care app compared to treatment as usual (TAU) in Germany. We further aimed to explore under which circumstances the reimbursement rate could be modified to consider value-based pricing. METHODS We developed a state-transition Markov model based on a best-practice analysis of prior LBP-related decision-analytic models, and evaluated the cost utility of a digital therapeutic care app compared to TAU in Germany. Based on a 3-year time horizon, we simulated the incremental cost and quality-adjusted life years (QALYs) for people with nonacute LBP from the societal perspective. In the deterministic sensitivity and scenario analyses, we focused on diverging attrition rates and app cost to assess our model's robustness and conditions for changing the reimbursement rate. All costs are reported in Euro (€1=US $1.12). RESULTS Our base case results indicated that the digital therapeutic care strategy led to an incremental cost of €121.59, but also generated 0.0221 additional QALYs compared to the TAU strategy, with an estimated incremental cost-effectiveness ratio (ICER) of €5486 per QALY. The sensitivity analysis revealed that the reimbursement rate and the capability of digital therapeutic care to prevent reoccurring LBP episodes have a significant impact on the ICER. At the same time, the other parameters remained unaffected and thus supported the robustness of our model. In the scenario analysis, the different model time horizons and attrition rates strongly influenced the economic outcome. Reducing the cost of the app to €99 per 3 months or decreasing the app's attrition rate resulted in digital therapeutic care being significantly less costly with more generated QALYs, and is thus considered to be the dominant strategy over TAU. CONCLUSIONS The current reimbursement rate for a digital therapeutic care app in the statutory health insurance can be considered a cost-effective measure compared to TAU. The app's attrition rate and effect on the patient's prolonged behavior change essentially influence the settlement of an appropriate reimbursement rate. Future value-based pricing targets should focus on additional outcome parameters besides pain intensity and functional disability by including attrition rates and the app's long-term effect on quality of life.
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Affiliation(s)
- Daniel Lewkowicz
- Digital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany
| | - Attila M Wohlbrandt
- Digital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany
| | - Erwin Bottinger
- Digital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.,Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
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15
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Svendsen MJ, Sandal LF, Kjær P, Nicholl BI, Cooper K, Mair F, Hartvigsen J, Stochkendahl MJ, Søgaard K, Mork PJ, Rasmussen C. Using Intervention Mapping to Develop a Decision Support System–Based Smartphone App (selfBACK) to Support Self-management of Nonspecific Low Back Pain: Development and Usability Study. J Med Internet Res 2022; 24:e26555. [PMID: 35072645 PMCID: PMC8822424 DOI: 10.2196/26555] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 03/07/2021] [Accepted: 11/04/2021] [Indexed: 12/29/2022] Open
Abstract
Background
International guidelines consistently endorse the promotion of self-management for people with low back pain (LBP); however, implementation of these guidelines remains a challenge. Digital health interventions, such as those that can be provided by smartphone apps, have been proposed as a promising mode of supporting self-management in people with chronic conditions, including LBP. However, the evidence base for digital health interventions to support self-management of LBP is weak, and detailed descriptions and documentation of the interventions are lacking. Structured intervention mapping (IM) constitutes a 6-step process that can be used to guide the development of complex interventions.
Objective
The aim of this paper is to describe the IM process for designing and creating an app-based intervention designed to support self-management of nonspecific LBP to reduce pain-related disability.
Methods
The first 5 steps of the IM process were systematically applied. The core processes included literature reviews, brainstorming and group discussions, and the inclusion of stakeholders and representatives from the target population. Over a period of >2 years, the intervention content and the technical features of delivery were created, tested, and revised through user tests, feasibility studies, and a pilot study.
Results
A behavioral outcome was identified as a proxy for reaching the overall program goal, that is, increased use of evidence-based self-management strategies. Physical exercises, education, and physical activity were the main components of the self-management intervention and were designed and produced to be delivered via a smartphone app. All intervention content was theoretically underpinned by the behavior change theory and the normalization process theory.
Conclusions
We describe a detailed example of the application of the IM approach for the development of a theory-driven, complex, and digital intervention designed to support self-management of LBP. This description provides transparency in the developmental process of the intervention and can be a possible blueprint for designing and creating future digital health interventions for self-management.
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Affiliation(s)
- Malene Jagd Svendsen
- The National Research Centre for the Working Environment, Copenhagen, Denmark
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Louise Fleng Sandal
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Per Kjær
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
- Health Sciences Research Centre, UCL University College, Odense, Denmark
| | - Barbara I Nicholl
- Institute of Health and Wellbeing, General Practice & Primary Care, University of Glasgow, Glasgow, United Kingdom
| | - Kay Cooper
- School of Health Sciences, Robert Gordon University, Aberdeen, United Kingdom
| | - Frances Mair
- Institute of Health and Wellbeing, General Practice & Primary Care, University of Glasgow, Glasgow, United Kingdom
| | - Jan Hartvigsen
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
- Chiropractic Knowledge Hub, Odense, Denmark
| | - Mette Jensen Stochkendahl
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
- Chiropractic Knowledge Hub, Odense, Denmark
| | - Karen Søgaard
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Charlotte Rasmussen
- The National Research Centre for the Working Environment, Copenhagen, Denmark
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16
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Sandal LF, Bach K, Øverås CK, Svendsen MJ, Dalager T, Stejnicher Drongstrup Jensen J, Kongsvold A, Nordstoga AL, Bardal EM, Ashikhmin I, Wood K, Rasmussen CDN, Stochkendahl MJ, Nicholl BI, Wiratunga N, Cooper K, Hartvigsen J, Kjær P, Sjøgaard G, Nilsen TIL, Mair FS, Søgaard K, Mork PJ. Effectiveness of App-Delivered, Tailored Self-management Support for Adults With Lower Back Pain-Related Disability: A selfBACK Randomized Clinical Trial. JAMA Intern Med 2021; 181:1288-1296. [PMID: 34338710 PMCID: PMC8329791 DOI: 10.1001/jamainternmed.2021.4097] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
IMPORTANCE Lower back pain (LBP) is a prevalent and challenging condition in primary care. The effectiveness of an individually tailored self-management support tool delivered via a smartphone app has not been rigorously tested. OBJECTIVE To investigate the effectiveness of selfBACK, an evidence-based, individually tailored self-management support system delivered through an app as an adjunct to usual care for adults with LBP-related disability. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial with an intention-to-treat data analysis enrolled eligible individuals who sought care for LBP in a primary care or an outpatient spine clinic in Denmark and Norway from March 8 to December 14, 2019. Participants were 18 years or older, had nonspecific LBP, scored 6 points or higher on the Roland-Morris Disability Questionnaire (RMDQ), and had a smartphone and access to email. INTERVENTIONS The selfBACK app provided weekly recommendations for physical activity, strength and flexibility exercises, and daily educational messages. Self-management recommendations were tailored to participant characteristics and symptoms. Usual care included advice or treatment offered to participants by their clinician. MAIN OUTCOMES AND MEASURES Primary outcome was the mean difference in RMDQ scores between the intervention group and control group at 3 months. Secondary outcomes included average and worst LBP intensity levels in the preceding week as measured on the numerical rating scale, ability to cope as assessed with the Pain Self-Efficacy Questionnaire, fear-avoidance belief as assessed by the Fear-Avoidance Beliefs Questionnaire, cognitive and emotional representations of illness as assessed by the Brief Illness Perception Questionnaire, health-related quality of life as assessed by the EuroQol-5 Dimension questionnaire, physical activity level as assessed by the Saltin-Grimby Physical Activity Level Scale, and overall improvement as assessed by the Global Perceived Effect scale. Outcomes were measured at baseline, 6 weeks, 3 months, 6 months, and 9 months. RESULTS A total of 461 participants were included in the analysis; the population had a mean [SD] age of 47.5 [14.7] years and included 255 women (55%). Of these participants, 232 were randomized to the intervention group and 229 to the control group. By the 3-month follow-up, 399 participants (87%) had completed the trial. The adjusted mean difference in RMDQ score between the 2 groups at 3 months was 0.79 (95% CI, 0.06-1.51; P = .03), favoring the selfBACK intervention. The percentage of participants who reported a score improvement of at least 4 points on the RMDQ was 52% in the intervention group vs 39% in the control group (adjusted odds ratio, 1.76; 95% CI, 1.15-2.70; P = .01). CONCLUSIONS AND RELEVANCE Among adults who sought care for LBP in a primary care or an outpatient spine clinic, those who used the selfBACK system as an adjunct to usual care had reduced pain-related disability at 3 months. The improvement in pain-related disability was small and of uncertain clinical significance. Process evaluation may provide insights into refining the selfBACK app to increase its effectiveness. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03798288.
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Affiliation(s)
- Louise Fleng Sandal
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Kerstin Bach
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Cecilie K Øverås
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.,Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Malene Jagd Svendsen
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.,Musculoskeletal Disorders and Physical Workload, National Research Centre for the Working Environment, Copenhagen, Denmark
| | - Tina Dalager
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | | | - Atle Kongsvold
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anne Lovise Nordstoga
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ellen Marie Bardal
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ilya Ashikhmin
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Karen Wood
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | | | - Mette Jensen Stochkendahl
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.,Nordic Institute of Chiropractic and Clinical Biomechanics, Odense, Denmark
| | - Barbara I Nicholl
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | | | - Kay Cooper
- Robert Gordon University School of Health Sciences, Aberdeen, United Kingdom
| | - Jan Hartvigsen
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.,Nordic Institute of Chiropractic and Clinical Biomechanics, Odense, Denmark
| | - Per Kjær
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Gisela Sjøgaard
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Tom I L Nilsen
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Frances S Mair
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Karen Søgaard
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
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17
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Kongsted A, Jensen TS, Doktor K, Hestbæk L. Effects of weekly pain monitoring on back pain outcomes: a non-randomised controlled study. Chiropr Man Therap 2021; 29:37. [PMID: 34530882 PMCID: PMC8444569 DOI: 10.1186/s12998-021-00393-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 09/06/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Disease monitoring is an important element of self-management of several chronic diseases. Pain monitoring has become very easily available, but the role in musculoskeletal pain conditions is not clear. Awareness of pain might be helpful for people to understand pain, but focusing on pain may on the contrary negatively affect pain experience and behaviours. The objective of this study was to investigate the potential impact of pain monitoring on low back pain (LBP), specifically to determine if pain intensity, activity limitation and pain control, differed between patients with weekly pain monitoring over 12 months and patients with follow-ups at 2 weeks, 3 months and 12 months. METHODS This was a non-randomised controlled study embedded in a cohort study with data collection November 1st 2016 to December 21st 2018. Adults seeking care for LBP were enrolled at the first visit to a chiropractor and followed with surveys after 2 weeks, 3 months and 12 months. Those enrolled first, n = 1,623, furthermore received weekly SMS-questions about pain frequency and pain intensity, whereas those enrolled next was the control group, n = 1,269 followed only by surveys. Outcomes at 12-months were compared, adjusting for group differences on baseline parameters. RESULTS LBP intensity (0-10) was slightly lower at 12-months follow-up in the SMS group than the control group (adjusted beta - 0.40 (95% CI: - 0.62; - 0.19)). No relevant between-group differences were observed for activity limitation (0-100) (1.51 (95% CI: - 0.83; 3.85)) or ability to control pain (0-10) (- 0.08 (95% CI - 0.31; 0.15)). CONCLUSIONS Frequent pain monitoring did not demonstrate any negative effects of weekly pain monitoring, and it was perhaps even helpful. The role of self-monitoring as part of self-managing LBP should be explored further including optimal frequencies, formats, and methods for feedback. TRIAL REGISTRATION The study was not registered as a clinical trial.
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Affiliation(s)
- Alice Kongsted
- Chiropractic Knowledge Hub, Campusvej 55, 5230, Odense M, Denmark. .,Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark.
| | - Tue Secher Jensen
- Chiropractic Knowledge Hub, Campusvej 55, 5230, Odense M, Denmark.,Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark.,Diagnostic Center, Silkeborg Regional Hospital, Falkevej 1, 8600, Silkeborg, Denmark
| | - Klaus Doktor
- Chiropractic Knowledge Hub, Campusvej 55, 5230, Odense M, Denmark.,Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark
| | - Lise Hestbæk
- Chiropractic Knowledge Hub, Campusvej 55, 5230, Odense M, Denmark.,Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark.,Diagnostic Center, Silkeborg Regional Hospital, Falkevej 1, 8600, Silkeborg, Denmark
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18
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Marcuzzi A, Bach K, Nordstoga AL, Bertheussen GF, Ashikhmin I, Boldermo NØ, Kvarner EN, Nilsen TIL, Marchand GH, Ose SO, Aasdahl L, Kaspersen SL, Bardal EM, Børke JB, Mork PJ, Gismervik S. Individually tailored self-management app-based intervention (selfBACK) versus a self-management web-based intervention (e-Help) or usual care in people with low back and neck pain referred to secondary care: protocol for a multiarm randomised clinical trial. BMJ Open 2021; 11:e047921. [PMID: 34518253 PMCID: PMC8438956 DOI: 10.1136/bmjopen-2020-047921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
INTRODUCTION Low back pain (LBP) and neck pain (NP) are common and costly conditions. Self-management is a key element in the care of persistent LBP and NP. Artificial intelligence can be used to support and tailor self-management interventions, but their effectiveness needs to be ascertained. The aims of this trial are (1) to evaluate the effectiveness of an individually tailored app-based self-management intervention (selfBACK) adjunct to usual care in people with LBP and/or NP in secondary care compared with usual care only, and (2) to compare the effectiveness of selfBACK with a web-based self-management intervention without individual tailoring (e-Help). METHODS AND ANALYSIS This is a randomised, assessor-blind clinical trial with three parallel arms: (1) selfBACK app adjunct to usual care; (2) e-Help website adjunct to usual care and (3) usual care only. Patients referred to St Olavs Hospital, Trondheim (Norway) with LBP and/or NP and accepted for assessment/treatment at the multidisciplinary outpatient clinic for back or neck rehabilitation are invited to the study. Eligible and consenting participants are randomised to one of the three arms with equal allocation ratio. We aim to include 279 participants (93 in each arm). Outcome variables are assessed at baseline (before randomisation) and at 6-week, 3-month and 6-month follow-up. The primary outcome is musculoskeletal health measured by the Musculoskeletal Health Questionnaire at 3 months. A mixed-methods process evaluation will document patients' and clinicians' experiences with the interventions. A health economic evaluation will estimate the cost-effectiveness of both interventions' adjunct to usual care. ETHICS AND DISSEMINATION The trial is approved by the Regional Committee for Medical and Health Research Ethics in Central Norway (Ref. 2019/64084). The results of the trial will be published in peer-review journals and presentations at national and international conferences relevant to this topic. TRIAL REGISTRATION NUMBER NCT04463043.
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Affiliation(s)
- Anna Marcuzzi
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Kerstin Bach
- Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Anne Lovise Nordstoga
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
| | - Gro Falkener Bertheussen
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Ilya Ashikhmin
- Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Nora Østbø Boldermo
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
| | - Else-Norun Kvarner
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
| | - Tom Ivar Lund Nilsen
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Clinic of Anesthesia and Intensive Care, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
| | - Gunn Hege Marchand
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Solveig Osborg Ose
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
- Health Services Research, SINTEF Digital, Trondheim, Norway
| | - Lene Aasdahl
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Unicare Helsefort Rehabilitation Center, Rissa, Norway
| | - Silje Lill Kaspersen
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Health Services Research, SINTEF Digital, Trondheim, Norway
| | - Ellen Marie Bardal
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Janne-Birgitte Børke
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Sigmund Gismervik
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital,Trondheim University Hospital, Trondheim, Norway
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19
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Taboada A, Ly E, Ramo D, Dillon F, Chang YJ, Hooper C, Yost E, Haritatos J. Implementing Goal Mama: Barriers and Facilitators to Introducing Mobile Health Technology in a Public Health Nurse Home-Visiting Program. Glob Qual Nurs Res 2021; 8:23333936211014497. [PMID: 34017901 PMCID: PMC8114238 DOI: 10.1177/23333936211014497] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 04/13/2021] [Accepted: 04/14/2021] [Indexed: 11/22/2022] Open
Abstract
The present study explores barriers and facilitators experienced by public health nurses introducing a mobile health technology platform (Goal Mama) to the Nurse-Family Partnership home-visiting program. Goal Mama is a HIPAA-compliant goal-coaching and visit preparation platform that clients and nurses use together to set and track goals. Forty-two nurses across five sites, including urban, suburban, and rural communities, piloted the platform with clients for 6 months. The mixed method, QUAL+quan pilot evaluation focused on deeply understanding the implementation process. Data were analyzed via iterative content analysis and multivariate regression analysis, and triangulated to identify salient findings. Over 6 months of use participants identified critical areas for product and implementation improvement, but still viewed the platform favorably. Key opportunities for improving sustained use revolved around supporting the technological and programmatic integration needed to lower key barriers and further facilitate implementation.
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Affiliation(s)
| | | | - Danielle Ramo
- Hopelab, San Francisco, CA, USA.,Weill Institute for Neurosciences, San Francisco, CA, USA
| | | | | | | | - Elly Yost
- Nurse Family Partnership National Service Office, Denver, CO, USA
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