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Record W2581571045 · doi:10.1177/0008417416652909

Psychometric properties of the NOMO 1.0 tested among adult powered-mobility users

2016· article· en· W2581571045 on OpenAlexvenueno aff
Terje Sund, Åse Brandt, Heidi Anttila, Susanne Iwarsson

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2016
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyGerontologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Nordic Mobility Related Outcome Evaluation of Assistive Device Intervention (NOMO 1.0) instrument evaluates the effectiveness of mobility devices in assessing mobility-related participation, captured by three scales (Need for Assistance, Frequency, and Ease/Difficulty) and one index (Participation Repertoire). PURPOSE: This study aimed to investigate a range of psychometric properties of the NOMO 1.0 in a sample of adult powered mobility device (PMD) users. METHOD: Data collected from PMD users ( N = 248) in Denmark, Finland, and Norway as part of a larger study were analyzed using state-of-the-art statistical methods. FINDINGS: The acceptability and applicability of the NOMO 1.0 items were generally within recommended values. Some floor/ceiling effects were found and the reliability was acceptable for only the Frequency scale. The factor analysis identified one component for the Need for Assistance scale and six components of the Frequency scale. IMPLICATIONS: The NOMO 1.0 should be used for research purposes and not for clinical practice. Better reliability should be established for the Need for Assistance and Ease/Difficulty scales prior to further psychometric testing to establish the validity of the NOMO 1.0.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.211
GPT teacher head0.431
Teacher spread0.220 · 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.

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

Citations2
Published2016
Admission routes1
Has abstractyes

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