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Record W2801932715 · doi:10.1093/sleep/zsy061.1041

1042 Sleep Problems are Associated with Depression, Pain and Fatigue in Adults with Spinal Cord Injury

2018· article· en· W2801932715 on OpenAlexaff
Donald Fogelberg, Susan Forwell, Kyle Jean Diab, Michael V. Vitiello, Dagmar Amtmann

Bibliographic record

VenueSLEEP · 2018
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDepression (economics)Sleep disorderPhysical therapyMedicineSpinal cord injuryPopulationGeriatric Depression ScaleInsomniaPsychologyPsychiatryCognitionSpinal cord

Abstract

fetched live from OpenAlex

People with Spinal Cord Injury (SCI) report significantly more sleep disturbance than the general population, which has significant implications for function, rehabilitation outcomes and quality of life. This study examined the relationship between sleep problems, depression, pain and fatigue in adults with SCI. Six hundred and twenty adults with SCI in a longitudinal survey of self-reported health completed the Medical Outcomes Study Sleep Scale (MOS-SS); Patient Health Questionnaire-9 (PHQ-9 (depression)); Brief Pain Inventory-7 (BPI-7); and Fatigue Severity Scale (FSS). The majority of participants were community dwelling, with 1.5% institutionalized. Pearson’s correlations between the MOS-SS summary measure (Sleep Problems Index II), MOS-SS subscales (sleep disturbance, snoring, shortness of breath, sleep quantity, sleep adequacy, and daytime somnolence) and depression, pain and fatigue were examined. Hierarchical multiple regression analysis examined the relationship between sleep problems (dependent variable) and depression, pain and fatigue (independent variables) controlling for age, sex, level of injury, and completeness of injury. Most correlations were statistically significant (p ≤ 0.05); the exceptions were snoring in relation to sleep adequacy, sleep quantity, depression and pain. The overall model explained 46.2% of the variance in sleep problems (P < 0.001). Additionally, depression (β=.393), pain (β=.269), and fatigue (β=.098) all made unique statistically significant contributions (P < 0.05). This study found that depression, pain and fatigue, are significantly related to sleep problems in people with SCI. Although the cross-sectional nature of this analysis does not permit conclusions about causality, these findings are consistent with results of studies in the general population that found poor sleep is associated with more depression, pain, and fatigue. The strong association of each of these symptoms with poor sleep following SCI highlights the critical importance of routinely screening people with SCI for sleep problems in order to inform treatment decisions and better manage conditions co-morbid with SCI. DOE (NIDRR H133B031129, H133B080025); NIH (NIAMS 5U01AR05217, NICHD K01HD076183).

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)0.001
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 score0.054
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.031
GPT teacher head0.332
Teacher spread0.301 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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