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Record W4375861342 · doi:10.32920/22779719.v1

School reintegration following hospitalisation for children with medical complexity and chronic disease diagnoses: a scoping review protocol

2023· review· en· W4375861342 on OpenAlexaff
Samantha Burns, Katie Doering, Donna Koller, Catherine Stratton

Bibliographic record

Venuenot available
Typereview
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsPsycINFOCINAHLMEDLINEPsychologyMedical diagnosisMedicineClinical psychologyFamily medicinePsychiatryPsychological intervention

Abstract

fetched live from OpenAlex

Introduction Schools play a significant role in children’s social, emotional and intellectual well- being. For children with medical complexity (CMC) and chronic disease diagnoses (CDD), an absence from school due to prolonged hospitalisation places them at risk for greater social exclusion and poorer academic outcomes than their healthy counterparts. Processes that support the school reintegration of children with complex and chronic medical conditions currently lack consistency and identified evidence- based practices. This scoping review aims to integrate the relevant literature on current reintegration procedures as well as assess stakeholders’ perceived challenges related to children with CMC and CDD’s return to school following hospitalisation. Finally, information will be synthesised regarding parental and child involvement in reintegration strategies. Methods and analysis The current scoping review follows the five- stage framework proposed by Arksey and O’Malley (2005). The search syntax will be applied in Medline, Web of Science, PsycInfo, Education Resource, ERIC, CINAHL and SocIndex. Peer- reviewed journal articles will be included without the restriction of publication year or language. However, only children and adolescents aged 4–18 with CMC and CDD, who have been out of school for 2 weeks or more and reintegrated into a non- hospital school setting will be included. Articles will be screened by two authors based on the outlined eligibility criteria. Data will be summarised qualitatively and where applicable, visualisation techniques such as tables, graphs and figures will be implemented to address approaches, strategies and outcomes related to reintegration to school following hospitalisation. Ethics and dissemination The current study comprises available publications and does not collect primary data. For this reason, ethics approval is not necessary. The results of this scoping review will be prepared and submitted for publication in a peer- reviewed journal and presented at future conferences to key stakeholders focusing on educational accessibility and inclusion.

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)0.089
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.089
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0890.062
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0150.015
Bibliometrics0.0220.015
Science and technology studies0.0050.005
Scholarly communication0.0090.010
Open science0.0070.007
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0660.012

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 head0.171
GPT teacher head0.537
Teacher spread0.367 · 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 designNot applicable
Domainnot available
GenreProtocol

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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