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Record W7111915384

What is the impact of childhood asthma on the educational attainment of children

2022· other· W7111915384 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2022
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAsthmaEducational attainmentPopulationEpidemiologyInclusion (mineral)Selection biasDanishEarly childhood
DOInot available

Abstract

fetched live from OpenAlex

Searches The search will be performed by NTW, NDW and RJ and differences will be resolved by discussion with a fourth reviewer (SJS) . We will conduct searches in Pubmed, Science Direct, Web of Science, The Cochrane Library and Scopus. In addition to the electronic search, the studies cited by the included studies and the studies included in the previous meta-analyses related to the subject will be searched. Inclusion criteria: - Studies published from anytime to present - Studies that document history of childhood asthma (less than 18 years of old) and educational attainment of children less than 18 years old - Studies with any sample size - Studies covering any regions and countries Exclusion criteria: - Non -English studies - Grey Literature, congress, conference and symposium etc. abstracts, reports published in meeting booklets without the full article Types of studies to be included Any type of research study Condition or domain being studied Asthma in childhood: Asthma is a common childhood respiratory illness affecting both developed and developing countries. Though the prevalence is varied between countries, increasing urbanization and indoor/ outdoor air pollution triggers asthma among susceptible children. Uncontrolled and exaggerated attacks can cause mortality, sleep disturbance, mobility limitation, reduced exercise capacity and psychological issues among children which can adversely affect their educational outcomes. The potential impact on the educational performance is still not widely analysed and documented. Inclusion criteria Population Individuals aged 18 and under Exposure Diagnosed/ self reported asthma when aged 18 and under Comparator Individuals aged 18 and under without Asthma Outcome Education outcomes related to school attendance, school completion, exam scores and pass rates* Study design Any type of research study that document asthma and educational outcomes Data extraction (selection and coding) The titles and abstract of studies identified from the developed search strategy will be screened with the assistance of Rayyan literature review software. Title abstract and screening will be completed by NTW, NDW, RJ and any conflicts between reviewers regarding which studies will progress to full text screening will first attempt to be resolved through discussion, with a fourth reviewer (SJS) available to arbitrate any unresolved disagreement. Full-text screening will then be conducted again with three reviewers independently, with any disagreements to be resolved through discussion initially and fourth (SJS) and fifith (FS) reviewer available to arbitrate any unresolved disagreement. Included studies will then progress to data extraction. A flowchart of the selection process that meets the guidelines of the ‘Preferred Reporting Items for Systematic Reviews and Meta-Analyses’ (PRISMA) will be prepared. In addition to the factors that influence selection, information to describe relevant characteristics of included studies will also be extracted including description of the study design and context (including country and participating sample) as well as a summary of methods and procedures used. For the data extraction a spreadsheet in Microsoft Excel 2019 will be prepared. The spreadsheet will initially be piloted with a small selection of included articles. Final amendments to the structure of the excel spreadsheet will be made prior to then completing data extraction for all articles. Extraction of data will be performed by one reviewer (NTW) and checked="checked" value="1" by a second reviewer(NDW). Any conflicts will be resolved through discussion until there is consensus (with additional reviewers available to arbitrate any unresolved disagreement if necessary). Risk of bias assessment Different types of risk of bias assessment tools will utilize according to the type of research study. For Randomised Intervention Studies- Cochrane RoB tool For Non Randomised Intervention studies – ROBINS I tool (Risk Of Bias In Non-randomised Studies) For interrupterd time series studies- Efective Practice and Organization of Care group (EPOC) Risk of Bias tool For case control and cohort and descriptive studies- New Castle-Ottawa scale These are widely used critical appraisal tools that are relevant for both qualitative and quantitative study designs to assess the methodological quality of a study and to determine the extent to which a study has addressed the possibility of bias in its design, conduct and analysis. The bias assessment will be conducted independently by two reviewers. Any disagreement will be resolved through discussion, and if necessary a third reviewer will be consulted. Strategy for data synthesis The included studies will be described and summarized in tables. It is expected that the studies to be included will likely have used varying methods, outcome typologies and study designs, and thereby it may not be possible to perform a quantitative synthesis to address the primary aim of this review. If there are studies that are sufficiently homogeneous in nature, a quantitative synthesis will be performed or we will try to develop a standardised method. A narrative synthesis of the results of will be conducted for the non-homogenous articles. Analysis of subgroups or subsets. Following subgroups analysis will be performed provided that sufficient information is available in the results. Compare the outcomes of children with and without other co-morbidities additionally to asthma Compare the outcomes of children based on the description of severity of Asthma

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)0.016
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.053
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0160.010
Bibliometrics0.0220.023
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0030.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0270.002

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 head0.010
GPT teacher head0.272
Teacher spread0.262 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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