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Record W245798691

Waiting for an operation: parents' perspectives.

2004· article· en· W245798691 on OpenAlexaff
Grant G. Miller

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsMedicineIntervention (counseling)Sick childHumanitiesFamily medicinePediatricsNursing
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine parents' attitudes toward and acceptance of waiting times for their child's operation. DESIGN: Waiting times were measured by a cross-sectional method. A descriptive survey was conducted of families with a child waiting for a non-urgent operation. SETTING: A university teaching hospital. SUBJECTS: Parents of children (age < 20 yr) waiting for non-urgent pediatric general-surgery operations. MAIN OUTCOME MEASURES: Parents' concerns and attitudes about waiting for their child's operation, how it was affecting the child and family, how urgent they felt the need for surgery was, and what they thought was a reasonable maximum waiting period. RESULTS: Of 89 patients waiting for non-urgent pediatric general-surgery operations at the time of the survey, 61% had been waiting > 6 months and 30% > 12 months. Of the 57 families (64%) who returned completed surveys, 94% reported the wait to be emotionally stressful for the family; 81.5% expected their child's quality of life would improve after the operation. As for length of wait, 83% felt that > 3 months was unacceptable, and 98% > 6 months. CONCLUSIONS: Parents of children waiting for pediatric general surgery operations thought that the need for the operation was significantly more urgent then their classification of elective. They felt that waiting periods should not exceed 3 months. Long waiting periods are stressful for both family and child. Parental perceptions are important when considering strategies for wait-list management.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.040
GPT teacher head0.273
Teacher spread0.233 · 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

Citations35
Published2004
Admission routes1
Has abstractyes

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