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Record W4296019167 · doi:10.1111/1467-9604.12419

Routine‐based interview in early intervention: professionals' perspectives

2022· article· en· W4296019167 on OpenAlexfundno aff
Ana Paula da Silva Pereira, Andréa Perosa Saigh Jurdi, Helena Reis, Andreia S. P. Sousa

Bibliographic record

VenueSupport for Learning · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaUniversidade do MinhoInternational Council for Canadian Studies
KeywordsIntervention (counseling)PortuguesePsychologySemi-structured interviewMedical educationQualitative researchInterviewPlan (archaeology)Applied psychologyNursingMedicinePsychiatrySociology

Abstract

fetched live from OpenAlex

The Routine‐Based Interview is a promising method to collect information in Early Intervention, since it focuses on all members of the family and their routines, while seeking to highlight what parents consider a priority in the intervention. For that reason, in this paper, we aim to analyse the kind of benefits and difficulties that may be found in the Routine‐Based Interview's implementation process. The present research comprises the qualitative interview method, according to which semi‐structured interviews were carried out by eight Portuguese professionals enrolled in the Portuguese System for Early Intervention. The professionals highlight the benefits of the Routine‐Based Interview as a way to clearly and objectively evaluate and identify the concerns and priorities of the family, as well as the child's competencies and the functional goals that will be included in the intervention plan. All participants stress the need for more training in the Routine‐Based Interview process.

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)0.059
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.013
Scholarly communication0.0090.005
Open science0.0020.007
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.062
GPT teacher head0.411
Teacher spread0.349 · 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 designQualitative
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

Citations4
Published2022
Admission routes1
Has abstractyes

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