Evidence map›Paper›PMID 32208358›Full record

ArticleJournal of medical Internet research2020

Digital Care for Chronic Musculoskeletal Pain: 10,000 Participant Longitudinal Cohort Study.

Jeannie F Bailey, Vibhu Agarwal, Patricia Zheng, Matthew Smuck, Michael Fredericson, David J Kennedy, Jeffrey Krauss

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

69 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jeannie F Bailey *Department of Orthopaedic Surgery, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0003-4618-7512
Vibhu Agarwal *Hinge Health, Inc, San Francisco, CA, United States.ORCID 0000-0002-6392-3924
Patricia ZhengDepartment of Orthopaedic Surgery, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0002-5855-5303
Matthew SmuckDivision of Physical Medicine & Rehabilitation, Stanford University, Palo Alto, CA, United States.ORCID 0000-0002-2990-069X
Michael FredericsonDivision of Physical Medicine & Rehabilitation, Stanford University, Palo Alto, CA, United States.ORCID 0000-0001-9826-2348
David J KennedyVanderbilt University Medical Center, Nashville, CA, United States.ORCID 0000-0001-8061-0287
Jeffrey KraussHinge Health, Inc, San Francisco, CA, United States.ORCID 0000-0001-6794-3052

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic musculoskeletal pain has a vast global prevalence and economic burden. Conservative therapies are universally recommended but require patient engagement and self-management to be effective.

objectiveThis study aimed to evaluate the efficacy of a 12-week digital care program (DCP) in a large population of patients with chronic knee and back pain.

methodsA longitudinal observational study was conducted using a remote DCP available through a mobile app. Subjects participated in a 12-week multimodal DCP incorporating education, sensor-guided exercise therapy (ET), and behavioral health support with 1-on-1 remote health coaching. The primary outcome was pain measured by the visual analog scale (VAS). Secondary measures included engagement levels, program completion, program satisfaction, condition-specific pain measures, depression, anxiety, and work productivity.

resultsA total of 10,264 adults with either knee (n=3796) or low back (n=6468) pain for at least three months were included in the study. Participants experienced a 68.45% average improvement in VAS pain between baseline intake and 12 weeks. In all, 73.04% (7497/10,264) participants completed the DCP into the final month. In total, 78.60% (5893/7497) of program completers (7144/10,264, 69.60% of all participants) achieved minimally important change in pain. Furthermore, the number of ET sessions and coaching interactions were both positively associated with improvement in pain, suggesting that the amount of engagement influenced outcomes. Secondary outcomes included a 57.9% and 58.3% decrease in depression and anxiety scores, respectively, and 61.5% improvement in work productivity. Finally, 3 distinct clusters of pain response trajectories were identified, which could be predicted with a mean 76% accuracy using baseline measures.

conclusionsThese results support the efficacy and scalability of a DCP for chronic low back and knee pain in a large, diverse, real-world population. Participants demonstrated high completion and engagement rates and a significant positive relationship between engagement and pain reduction was identified, a finding that has not been previously demonstrated in a DCP. Furthermore, the large sample size allowed for the identification of distinct pain response subgroups, which may prove beneficial in predicting recovery and tailoring future interventions. This is the first longitudinal digital health study to analyze pain outcomes in a sample of this magnitude, and it supports the prospect for DCPs to serve the overwhelming number of musculoskeletal pain sufferers worldwide.

Indexed as

AdultChronic DiseaseCohort StudiesFemaleHumansLongitudinal StudiesMaleMusculoskeletal Painexercise therapylow back painmobile phonemusculoskeletal painpatient engagementtelemedicinetelerehabilitation

Identifiers

PMID32208358
PMCPMC7248800

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.