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Record W2031299491 · doi:10.5664/jcsm.2996

Development and Validation of the Nonrestorative Sleep Scale (NRSS)

2013· article· en· W2031299491 on OpenAlexaff
Kate Wilkinson, Colin M. Shapiro

Bibliographic record

VenueJournal of Clinical Sleep Medicine · 2013
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsAlertnessConstruct validityPsychologyReliability (semiconductor)PsychometricsClinical psychologyMedicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

STUDY OBJECTIVES: Nonrestorative sleep (NRS) is defined as the subjective feeling that sleep has been insufficiently refreshing, often despite the appearance of physiologically normal sleep. While NRS has been shown to be associated with a variety of cognitive, affective, and medical complaints, there is currently no valid, reliable instrument available in the public domain for its assessment. The purpose of this study was to develop and validate the nonrestorative sleep scale (NRSS). PARTICIPANTS: The scale was administered to a sample of 226 (age: 46.7 ± 14.9 years; gender: 48% female) consecutive sleep clinic patients and to 30 control participants (age: 36.9 ± 12.5; gender: 53% female). RESULTS: Data screening led to a final instrument of 12 items, and factor analysis resulted in 4 factors accounting for 73.2% of total variance. The scale demonstrated excellent internal reliability (α = 0.88) and good test-retest reliability (r = 0.72). Preliminary evaluations of construct validity found that certain subscales correlated reasonably well with previously validated sleep, alertness, and affective scales. Comparisons between global NRSS scores and objective polysomnographic variables revealed a few very small but significant correlations. CONCLUSIONS: Based on these findings, the NRSS was confirmed to be a valid and reliable tool for the assessment of nonrestorative sleep.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.387
Teacher spread0.334 · 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

Citations56
Published2013
Admission routes1
Has abstractyes

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