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Record W3030768425 · doi:10.1186/s12887-020-02161-2

A concept analysis of children with complex health conditions: implications for research and practice

2020· article· en· W3030768425 on OpenAlexafffund
Rima Azar, Shelley Doucet, Amanda Rose Horsman, Patricia Charlton, Alison Luke, Daniel A. Nagel, Nicky Hyndman, William Montelpare

Bibliographic record

VenueBMC Pediatrics · 2020
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsVeterans Affairs CanadaUniversity of New BrunswickRoyal Canadian NavyUniversity of Prince Edward IslandMount Allison University
FundersPioneers in Health Care Innovation Fund, University of TwenteNew Brunswick Children's FoundationCanadian Institutes of Health ResearchNational Breast Cancer Foundation
KeywordsMeaning (existential)Context (archaeology)MedicineChronic conditionQuality (philosophy)Mental healthQuality of life (healthcare)Applied psychologyDevelopmental psychologyPsychologyPsychiatryNursingEpistemologyPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: This concept analysis aimed to clarify the meaning of "children with complex health conditions" and endorse a definition to inform future research, policy, and practice. METHODS: Using Walker and Avant's (2011)'s approach, we refined the search strategy with input from our team, including family representatives. We reviewed the published and grey literature. We also interviewed 84 health, social, and educational stakeholders involved in the care of children with complex health conditions about their use/understanding of the concept. RESULTS: We provided model, borderline, related, and contrary cases for clarification purposes. We identified defining attributes that nuance the concept: (1) conditions and needs' breadth; (2) uniqueness of each child/condition; (3) varying extent of severity over time; 4) developmental age; and (5) uniqueness of each family/context. Antecedents were chronic physical, mental, developmental, and/or behavioural condition(s). There were individual, family, and system consequences, including fragmented services. CONCLUSIONS: Building on previous definitions, we proposed an iteration that acknowledges the conditions' changing trajectories as involving one or more chronic condition(s), regardless of type(s), whose trajectories can change over time, requiring services across sectors/settings, oftentimes resulting in a lower quality of life. A strength of this paper is the integration of the stakeholders'/family's voices into the development of the definition.

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)0.002
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 score0.520
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
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 head0.454
GPT teacher head0.578
Teacher spread0.124 · 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

Citations16
Published2020
Admission routes2
Has abstractyes

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