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Record W3210846235 · doi:10.3389/fpain.2021.755877

Devices Used to Measure Force-Time Characteristics of Spinal Manipulations and Mobilizations: A Mixed-Methods Scoping Review on Metrologic Properties and Factors Influencing Use

2021· article· en· W3210846235 on OpenAlexafffund
Marie-Andrée Mercier, Philippe Rousseau, Martha Funabashi, Martin Descarreaux, Isabelle Pagé

Bibliographic record

VenueFrontiers in Pain Research · 2021
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsCentre for Interdisciplinary Research in RehabilitationCanadian Memorial Chiropractic CollegeUniversité du Québec à Trois-Rivières
FundersFondation Chiropratique du Québec
KeywordsContext (archaeology)LimitingPsychological interventionReliability (semiconductor)ModalitiesHealth careMeasure (data warehouse)Computer scienceMedicinePsychologyEngineeringData miningNursingMechanical engineering

Abstract

fetched live from OpenAlex

Background: Spinal manipulations (SMT) and mobilizations (MOB) are interventions commonly performed by many health care providers to manage musculoskeletal conditions. The clinical effects of these interventions are believed to be, at least in part, associated with their force-time characteristics. Numerous devices have been developed to measure the force-time characteristics of these modalities. The use of a device may be facilitated or limited by different factors such as its metrologic properties. Objectives: This mixed-method scoping review aimed to characterize the metrologic properties of devices used to measure SMT/MOB force-time characteristics and to determine which factors may facilitate or limit the use of such devices within the context of research, education and clinical practice. Methods: This study followed the Joanna Briggs Institute's framework. The literature search strategy included four concepts: (1) devices, (2) measurement of SMT or MOB force-time characteristics on humans, (3) factors facilitating or limiting the use of devices, and (4) metrologic properties. Two reviewers independently reviewed titles, abstracts and full articles to determine inclusion. To be included, studies had to report on a device metrologic property (e.g., reliability, accuracy) and/or discuss factors that may facilitate or limit the use of the device within the context of research, education or clinical practice. Metrologic properties were extracted per device. Limiting and facilitating factors were extracted and themes were identified. Results: From the 8,998 studies initially retrieved, 46 studies were finally included. Ten devices measuring SMT/MOB force-time characteristics at the clinician-patient interface and six measuring them at patient-table interfaces were identified. Between zero and eight metrologic properties were reported per device: measurement error (defined as validity, accuracy, fidelity, or calibration), reliability/repeatability, coupling/crosstalk effect, linearity/correlation, sensitivity, variability, drift, and calibration. From the results, five themes related to the facilitating and limiting factors were developed: user-friendliness and versatility, metrologic/intrinsic properties, cost and durability, technique application, and feedback. Conclusion: Various devices are available to measure SMT/MOB force-time characteristics. Metrologic properties were reported for most devices, but terminology standardization is lacking. The usefulness of a device in a particular context should be determined considering the metrologic properties as well as other potential facilitating and limiting factors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.163
GPT teacher head0.421
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2021
Admission routes2
Has abstractyes

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