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Record W2559914827 · doi:10.1177/1559827616681725

Sleep Disruption in Pediatric Cancer Survivors

2016· review· en· W2559914827 on OpenAlexaff
Erin L. Merz, Lianne Tomfohr‐Madsen

Bibliographic record

VenueAmerican Journal of Lifestyle Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicinePsychological interventionPediatric cancerIntervention (counseling)Extant taxonPopulationSleep (system call)Childhood cancerSleep deprivationClinical psychologyCancerPsychiatryCognition

Abstract

fetched live from OpenAlex

Sleep disruption is a commonly reported consequence of cancer and its treatment in pediatric patients and survivors. This review summarizes common sleep concerns in this population and introduces a multidimensional framework of risk factors specific to childhood cancer that may interact to develop and maintain disrupted sleep. Based on the extant literature, parameters of the cancer and its treatment, physical and social environmental conditions both during and after treatment, changes to family behavior and norms, psychological factors and traumatic stress, and reduced physical activity are hypothesized to be the most pertinent risk factors for disrupted sleep in this population. Potential clinical assessment strategies and behavioral interventions relevant to these considerations are discussed, with reference to the behavioral model of insomnia. The review concludes by offering directions for research and clinical practice, including developing and testing comprehensive assessment tools, intervention effectiveness studies in both oncology and primary care clinics, and efforts to increase patient-provider communication about sleep in pediatric oncology.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.037
GPT teacher head0.388
Teacher spread0.351 · 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 designOther design
Domainnot available
GenreReview

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

Citations25
Published2016
Admission routes1
Has abstractyes

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