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Record W4365514020 · doi:10.1186/s12891-023-06400-2

Psychometric properties of a standardized protocol of muscle strength assessment by hand-held dynamometry in healthy adults: a reliability study

2023· article· en· W4365514020 on OpenAlexafffundabout
Marika Morin, Luc J. Hébert, Marc Perron, Émilie Petitclerc, Shanna-Rose Lake, Élise Duchesne

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2023
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsCentre for Interdisciplinary Research in RehabilitationCégep de JonquièreUniversité LavalHôpital Charles-Le MoyneCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité du Québec à Chicoutimi
FundersFonds de Recherche du Québec - SantéRéseau Provincial de Recherche en Adaptation-RéadaptationMitacsMuscular Dystrophy Canada
KeywordsSports medicineMedicineReliability (semiconductor)Protocol (science)Physical therapyRehabilitationPhysical medicine and rehabilitationMuscle strengthAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Maximal isometric muscle strength (MIMS) assessment is a key component of physiotherapists' work. Hand-held dynamometry (HHD) is a simple and quick method to obtain quantified MIMS values that have been shown to be valid, reliable, and more responsive than manual muscle testing. However, the lack of MIMS reference values for several muscle groups in healthy adults with well-known psychometric properties limits the use and the interpretation of these measures obtained with HHD in clinic. OBJECTIVE: To determine the intra- and inter-rater reliability, standard error of measurement (SEM) and minimal detectable change (MDC) of MIMS torque values obtained with HHD. METHODS: Intra and Inter-rater Reliability Study. The MIMS torque of 17 muscle groups was assessed by two independent raters at three different times in 30 healthy adults using a standardized HHD protocol using the MEDup™ (Atlas Medic, Québec, Canada). Participants were excluded if they presented any of the following criteria: 1) participation in sport at a competitive level; 2) degenerative or neuromusculoskeletal disease that could affect torque measurements; 3) traumatic experience or disease in the previous years that could affect their muscle function; and 4) use of medication that could impact muscle strength (e.g., muscle relaxants, analgesics, opioids) at the time of the evaluation. Intra- and inter-rater reliability were determined using two-way mixed (intra) and random effects (inter) absolute agreement intraclass correlation coefficients (ICC: 95% confidence interval) models. SEM and MDC were calculated from these data. RESULTS: Intra- and inter-rater reliability were excellent with ICC (95% confidence interval) varying from 0.90 to 0.99 (0.85-0.99) and 0.89 to 0.99 (0.55-0.995), respectively. Absolute SEM and MDC for intra-rater reliability ranged from 0.14 to 3.20 Nm and 0.38 to 8.87 Nm, respectively, and from 0.17 to 5.80 Nm and 0.47 to 16.06 Nm for inter-rater reliability, respectively. CONCLUSIONS: The excellent reliability obtained in this study suggest that the use of such a standardized HHD protocol is a method of choice for MIMS torque measurements in both clinical and research settings. And the identification of the now known metrological qualities of such a protocol should encourage and promote the optimal use of manual dynamometry.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.376
Teacher spread0.347 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2023
Admission routes3
Has abstractyes

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