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Record W1506795858 · doi:10.1111/1471-3802.12074

Reduce, manage or cope: a review of strategies for training school staff to address challenging behaviours displayed by students with intellectual/developmental disabilities

2014· review· en· W1506795858 on OpenAlexafffund
Brenda M. Stoesz, Shahin Shooshtari, Janine M. Montgomery, Toby L. Martin, Dustin J. Heinrichs, Joyce Douglas

Bibliographic record

VenueJournal of Research in Special Educational Needs · 2014
Typereview
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of ManitobaSt.Amant
FundersCanadian Institutes of Health Research
KeywordsPsychologyPsychological interventionMedical educationIntellectual disabilityCoping (psychology)Challenging behaviourTraining (meteorology)Applied psychologyMedicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Members of a knowledge translation and exchange ( KTE ) research team assessed the training needs of the teaching staff at a school for individuals with intellectual/developmental disabilities ( IDD ). In response to this need, KTE researchers retrieved peer‐reviewed articles for training staff working with individuals with IDD who exhibit challenging behaviours. These articles were categorised according to the following training content: (1) interventions designed to reduce the frequency of challenging behaviours; (2) appropriate ways to manage challenging behaviours in the moment to promote safety for all parties and/or to terminate the ongoing behaviour; and/or (3) procedures or perspectives relevant to coping with or ameliorating the negative impacts of challenging behaviours on staff. We then examined the training methods (teaching strategies, training duration) involved in teaching the content and assessed the effectiveness of these programmes. Overall, we found that effective training programmes consisted of workshops, practica and feedback on specific skill performance. Some forms of brief training were effective for increasing staffs' knowledge/skills and reducing the frequency of challenging behaviour.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.619
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.517
GPT teacher head0.564
Teacher spread0.047 · 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.

Study designNot applicable
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

Citations27
Published2014
Admission routes2
Has abstractyes

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