Evidence map›Paper›PMID 38053732›Full record

ArticleDigital health

Long-term effects of deep-learning digital therapeutics on pain, movement control, and preliminary cost-effectiveness in low back pain: A randomized controlled trial.

Chanhee Park, Chunghwi Yi, Woochol Joseph Choi, Hyo-Sang Lim, Han Ul Yoon, Sung Joshua Hyun You

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
3.9field-weighted citation impact, top 6% of its field
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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 16 citations in OpenAlex.

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  15. Adoption of Digital Therapeutics in Europe.Therapeutics and clinical risk management · 2024
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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

6 authors at 1 institution in 1 country.

Chanhee ParkSports(Movement Artificial-Intelligence Robotics Technology (SMART) Institute, Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea.ORCID https://orcid.org/0000-0003-2262-8555
Chunghwi YiDepartment of Physical Therapy, Yonsei University, Wonju, Republic of Korea.
Woochol Joseph ChoiDepartment of Physical Therapy, Yonsei University, Wonju, Republic of Korea.
Hyo-Sang LimDivision of Software, Yonsei University, Wonju, Republic of Korea.
Han Ul YoonDivision of Computer and Telecommunication Engineering, Yonsei University, Wonju, Republic of Korea.
Sung Joshua Hyun YouSports(Movement Artificial-Intelligence Robotics Technology (SMART) Institute, Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea.
Yonsei University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The present study aimed to compare the effects of a deep learning-based digital application with digital application physical therapy (DPT) and those of conventional physical therapy (CPT) on back pain intensity, limited functional ability, lower extremity weakness, radicular symptoms, limited range of motion (ROM), functional movement, quality of life, cost-effectiveness, and postintervention questionnaires for perceived transmission risk of COVID-19 and satisfaction results in 100 participants with low back pain (LBP). Methods: One hundred participants with LBP were randomized into either DPT or CPT groups, three times per week over four weeks. Outcome measures included the (1) Oswestry Disability Index, (2) Quebec Back Pain Disability Scale, (3) Roland-Morris Disability Questionnaire (RMDQ), (4) Numeric Pain Rating Scale, (5) functional movement screen (FMS), (6) short form-12, (7) lower extremity strength, (8) ROM of trunk flexion, extension, and bilateral side bending, (9) questionnaires for perceived transmission risk of COVID-19, (10) preliminary cost-effectiveness, and (11) postintervention satisfaction questionnaire results. The analysis of variance was conducted at Results: Analysis of variance showed that DPT showed superior effects, compared to CPT on RMDQ, hip extensor strength, transmission risk of COVID-19, as well as satisfaction. Both groups showed significant improvement pre- and postintervention, suggesting that DPT is as effective as CPT, and was superior in preliminary cost-effectiveness and transmission risk of COVID-19. Conclusions: Our results provide novel, promising clinical evidence that DPT was as effective as CPT in improving structural and functional impairment, activity limitation, and participation restriction. Our results highlight the successful incorporation of DPT intervention for clinical outcome measures, lower extremity strength, trunk mobility, ADL improvement, QOL improvement, and FMS in LBP.

Indexed as

artificial intelligencedigital therapylow back painsmartphone

Identifiers

PMID38053732
PMCPMC10695084
OpenAlexW4389292670

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.