Evidence map›Paper›PMID 39753210›Full record

Observational studyJournal of medical Internet research2024

Advanced Technology in a Real-World Rehabilitation Setting: Longitudinal Observational Study on Clinician Adoption and Implementation.

Louise Michelle Nettleton Pearce, Julie Pryor, Jason Redhead, Catherine Sherrington, Leanne Hassett

Abstract readObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
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

5 authors.

Louise Michelle Nettleton PearceRoyal Rehab Group, Sydney, Australia.ORCID 0000-0002-1622-8814
Julie PryorRoyal Rehab Group, Sydney, Australia.ORCID 0000-0003-4907-8530
Jason RedheadRoyal Rehab Group, Sydney, Australia.ORCID 0009-0001-3068-9350
Catherine SherringtonInstitute for Musculoskeletal Health, Sydney Local Health District, Sydney, Australia.ORCID 0000-0001-8934-4368
Leanne HassettInstitute for Musculoskeletal Health, Sydney Local Health District, Sydney, Australia.ORCID 0000-0002-3546-1822

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdvanced technologies are becoming increasingly accessible in rehabilitation. Current research suggests technology can increase therapy dosage, provide multisensory feedback, and reduce manual handling for clinicians. While more high-quality evidence regarding the effectiveness of rehabilitation technologies is needed, understanding of how to effectively integrate technology into clinical practice is also limited. Current implementation of rehabilitation technology is inconsistent, with low uptake among clinicians and frequent reports of technology abandonment. An Australian rehabilitation provider opened a new technology therapy center in 2022, offering a unique opportunity to generate practice-based evidence to inform future technology implementation and research.

objectiveThis study aimed to investigate the implementation and adoption of advanced technology within a real-world rehabilitation setting.

methodsThis study was a longitudinal observational study in a rehabilitation organization with inpatient, outpatient, and community settings. Allied health clinicians (n=119) within the organization had access to advanced technologies, with patients receiving neurological, spinal cord injury, brain injury, or general rehabilitation. Interventions included 21 advanced technologies, including robotic, virtual reality (VR), sensor-based, and functional electrical stimulation devices. Clinicians received training for devices in a staged approach by external and internal trainers. Data were collected from patient electronic medical records from July 1, 2022, to June 30, 2023. Outcomes included frequency of advanced technology use, patient demographics (age, gender, and primary health condition), clinician discipline, rehabilitation service (inpatient, outpatient, or community), goals of technology therapy sessions, and therapy dosage achieved (minutes active, number of repetitions, and meters walked).

resultsClinicians used advanced technology 4208 times with 269 patients over 12 months; specifically, physiotherapists (2716/4208, 65%), occupational therapists (1396/4208, 33%), and allied health assistants (96/4208, 2%). The majority of patients had stroke, spinal cord injury, or brain injury diagnoses (188/269, 70%). Devices were typically used to target impairment and activity limitation-related goals. Frequently used devices included gait training body-weight support (VR treadmill and overground), overground robotic exoskeletons, and upper limb robotic VR devices. Outpatient services were the dominant users of advanced technology (3940/4208, 94%). Clinicians most commonly used devices for patients with stroke (1973/4208, 47%) and the greatest variety of devices for patients with stroke and spinal cord injury. The relative use of lower limb robotic devices was greater in inpatient services (91/178, 51%, vs outpatient services, 963/2335, 41%) (χ

conclusionsThe type and amount of advanced technology use differed between patient populations and rehabilitation settings. To support clinician use of advanced technology, devices should match the rehabilitation context. Tailored strategies are important, such as clinician training. Further practice-based research is required to provide guidance on implementation and to establish the effectiveness of advanced technology use.

Indexed as

RoboticsAdultAustraliaFemaleHumansLongitudinal StudiesMaleMiddle Ageddigital healthexoskeleton deviceimplementation sciencemobile phoneoccupational therapyphysical therapyphysiotherapyrehabilitationroboticstechnologyvirtual reality

Identifiers

PMID39753210
PMCPMC11729780

What OpenQuestion holds

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LicenceCC BY
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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.