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Record W75226995 · doi:10.1155/2012/635967

The Pain and Sleep Questionnaire Three‐Item Index (PSQ‐3): A Reliable and Valid Measure of The Impact of Pain on Sleep in Chronic Nonmalignant Pain of Various Etiologies

2012· review· en· W75226995 on OpenAlexaff
Lindsay E. Ayearst, Zoltan Harsanyi, Kenneth J. Michalko

Bibliographic record

VenuePain Research and Management · 2012
Typereview
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsPurdue Pharma (Canada)The Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsPhysical therapyCronbach's alphaChronic painSleep disorderMedicineConstruct validityConfirmatory factor analysisPsychometricsPhysical medicine and rehabilitationClinical psychologyInsomniaPsychiatryStructural equation modelingStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Sleep disturbance is among the more common complaints reported by chronic pain patients. Because pain-related sleep disturbance may serve as a marker for the assessment of responses to treatment for chronic pain, inclusion of a measure designed to assess the impact of pain on sleep in clinical trial protocols is important, if not necessary. Measures typically used for this purpose lack scales specifically designed for the assessment of the impact of pain on sleep or are based on a single item. Single-item scales lack reliability and, therefore, validity. OBJECTIVES: To investigate the psychometric properties of the five-item Pain and Sleep Questionnaire (PSQ) Index, which is embedded in the eight-item inventory, by applying an accepted methodology using retrospective analyses in controlled clinical trials in which the measure had been administered among patients with chronic nonmalignant pain. METHODS: Data were pooled from nine independent, single-site, double-blind, randomized placebo-controlled clinical trials conducted over a period of approximately 10 years, the majority of which were cross-over designs. A cross-validation approach was adopted with exploratory and confirmatory factor analyses conducted to evaluate the underlying structure and dimensionality of the measure. Internal consistency reliability was evaluated using Cronbach's alpha coefficient. Mean score differences were used to assess the ability of the index to detect important treatment changes. Correlation coefficients were calculated between index scores and scores from other health-related outcome measures to evaluate the criterion validity of the index. Finally, predictive validity was assessed using multiple regression analyses. RESULTS: Pooling the data resulted in a sample of 605 patients (65.5% female; mean age 55.7 years). Findings suggested a revised three-item PSQ Index (PSQ-3). The PSQ-3 demonstrated high internal consistency across samples (ranging from 0.82 to 0.93) and was sensitive to detecting meaningful treatment effects within different chronic pain categories. Moderate to strong correlations (r>0.40) between the PSQ-3 and other health-related outcome measures provided preliminary evidence for criterion-related validity. Results of multiple regression analyses demonstrated that the PSQ-3 accounted for between 29% and 40% of the variance in scores from other health-related outcome measures. CONCLUSIONS: Results support the scoring of a revised three-item index for the assessment of the impact of pain on sleep. The revised index demonstrated acceptable levels of internal consistency and preliminary support for the structural, criterion-related and predictive validity of the index was achieved.

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)0.006
metaresearch head score (Gemma)0.007
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 score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.067
GPT teacher head0.383
Teacher spread0.316 · 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

Citations59
Published2012
Admission routes1
Has abstractyes

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