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Record W2124280560 · doi:10.4236/psych.2013.43a047

Assessment for Intervention of Children with Fetal Alcohol Spectrum Disorders: Perspectives of Classroom Teachers, Administrators, Caregivers, and Allied Professionals

2013· article· en· W2124280560 on OpenAlexaff
Jacqueline Pei, Jenelle Job, Cheryl Poth, Erin Atkinson

Bibliographic record

VenuePsychology · 2013
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsThematic analysisIntervention (counseling)PsychologyFetal Alcohol Spectrum DisorderMedical educationFetal alcoholFocus groupBest practiceQualitative researchProcess (computing)Applied psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The present study begins to address the need for evidence-based approaches for guiding the psychological assessment of children with Fetal Alcohol Spectrum Disorders (FASD). This project represents an important step toward increasing links between research and practice in the communication and use of assessment results for informing intervention decisions. Using a qualitative research approach, the current study contributes to knowledge about concerns with current psychological assessment practices and offers suggestions for optimization based on conversations with teachers, administrators, caregivers and allied professionals. Thematic analysis of 11 focus groups and 3 interviews (N = 60) yielded 3 major findings: the need to focus on the whole child, the necessity of an assessment process that is responsive, and building capacity in the school. This study increases the links between research and practice as we move toward a model of assessment for intervention. Such a model has a strong potential for optimizing assessment practices to better meet the needs of children with FASDs as it promotes a shift that focuses on successful child outcomes regardless of diagnosis.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.025
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.334
Teacher spread0.323 · 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

Citations25
Published2013
Admission routes1
Has abstractyes

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