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Record W2804585708 · doi:10.1002/jclp.22646

A case study illustrating the use of an attachment video‐feedback intervention strategy

2018· article· en· W2804585708 on OpenAlexaff
George M. Tarabulsy, Karine Dubois‐Comtois, Claire Baudry, Ellen Moss, Annie Roberge, Laura-Émilie Savage, Chantal Cyr, Diane St‐Laurent, Annie Bernier

Bibliographic record

VenueJournal of Clinical Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalUniversité du Québec à Trois-RivièresUniversité LavalOntario Centre of Excellence for Child and Youth Mental Health
Fundersnot available
KeywordsPsychologyIntervention (counseling)Context (archaeology)AutonomyVideo feedbackDevelopmental psychologyAffect (linguistics)Maternal sensitivityGovernment (linguistics)Affect regulationAttachment theoryCommunicationPsychiatry

Abstract

fetched live from OpenAlex

Children from high-risk environments are more likely to experience problems in development. Many difficulties are linked to early experiences in the context of the emerging attachment relationship. Over the past 20 years, our group has collaborated with government agencies to develop and implement an attachment-based video-feedback intervention strategy (AVI) that targets parental sensitivity and attachment. This case study presents the manner in which a young mother and her 6-month-old son experienced AVI. The study shows how the absence of maternal sensitivity and responsiveness to infant signals, difficulties in helping the child regulate affect, and problems in autonomy support are addressed via eight semi-structured mentoring visits. Discussion focuses on how AVI may be a helpful addition to primary prevention programs.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.400
GPT teacher head0.538
Teacher spread0.138 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

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