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Record W4366816473 · doi:10.1080/20473869.2023.2202010

Assessment of home environment for autistic individuals: a literature review of the existing tools

2023· review· en· W4366816473 on OpenAlexafffund
Alicia Ruiz-Rodrigo, Miranda Lemay, Ariane Savaria, Cindy Louis-Delsoin, Ernesto Morales

Bibliographic record

VenueInternational Journal of Developmental Disabilities · 2023
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalUniversité LavalUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
FundersUniversité de Montréal
KeywordsPsychologyAutismDevelopmental psychology

Abstract

fetched live from OpenAlex

Background: Autism Spectrum Disorder is a neurodevelopmental disorder, and its prevalence is estimated at 1% worldwide. The home environment can influence activities and roles for autistic individuals, however there are limited assessments that focus on the home environment for this population. Purpose: To identify existing assessment tools of home environment for autistic individuals in the literature. Methods: We explored five databases. Initial search on databases was made in 2019 and updated in 2022. Documents selection was made in two phases: 1) title and abstract screening, 2) full-text reading of selected publications. The included studies were analyzed. Results: We identified seven home environment-related assessment tools that can be used with the autistic population. Most of the tools included few items related to the non-human environment and do not include specific elements of the environment (e.g.: details about sensory stimuli or assessment of the layout). Six of them are design for children or youths and only one out seven is specific to autistic people. Conclusions: The identified tools do not allow for a detailed assessment of the non-human environment of autistic individuals only the identification of environment-related difficulties. More research and the development of new tools are needed to improve it.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.549
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.165
GPT teacher head0.430
Teacher spread0.265 · 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 designSystematic review
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

Citations0
Published2023
Admission routes2
Has abstractyes

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