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Record W7033674430

Risk factors for emotional- behavioral problems in residential-care and late-adopted adolescents: a pilot study with narrative interviews for attachment and alexithymia

2018· article· en· W7033674430 on OpenAlexaboutno aff

Bibliographic record

VenueCINECA IRIS Institutial Research Information System (University of Genoa) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Leadership and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaVulnerability (computing)NarrativeStepwise regressionAttachment measuresEmotional securityInsecure attachmentMultilevel model
DOInot available

Abstract

fetched live from OpenAlex

Adolescents in residential-care and late-adopted ones resulted high-risk to 
\nemotional-behavioural problems, showing vulnerability to risk-factors as 
\ninsecure/disorganized attachments and difficulties in emotional regulation, such 
\nalexithymia. Moreover, findings suggested higher risk for residential adolescents. 
\nHowever, there are no studies that investigated jointly the role of attachment and 
\nalexithymia with respect to emotional-behavioural problems displayed by adolescents in
\nthose high-risk groups, as we aim to do in a larger pilot study with a multi-method 
\napproach. In this preliminary report, we subsampled 20 adolescents (aged 13-17, M = 
\n14.95, SD = 1.4; 80% boys) with traumatic past experiences, dividing 10 late-adoptees 
\nand 10 residential-care, equalling for age and gender. We used the Child Behavior 
\nChecklist (CBCL 6-18) to assess emotional-behavioral problems; the Friends & Family 
\nInterview (FFI) to assess attachment representations, in terms of classifications and 
\nscales; the Toronto Structured Interview for Alexithymia (TSIA) to detect the levels of 
\nalexithymia. U-Mann Whitney confirmed that residential showed higher levels of 
\nemotional-behavioral problems - especially externalizing ones (p = .03) - less security 
\n(p = .003) and more avoidance (p = .03) in attachment and higher levels of alexithymia 
\n(p = .009) than adoptees. In the total group, correlations were found between 
\npsychopathology, less security in attachment and higher alexithymia, which also 
\nshowed associations each other (p =.029). However, a stepwise regression only 
\naccounted the poor attachment’ security as predictor of 29.9% of the variance in 
\nexternalizing problems (adjusted-R2 = .255, p = .019). Larger samples are needed, but 
\nboth variables seem correlated to high-risk adolescent’s adjustment: in particular, 
\nattachment security resulted a key-feature to promote especially in residential-care 
\ncontexts, where the adolescents seem more vulnerable than in adoptive families.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.002
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 head0.180
GPT teacher head0.404
Teacher spread0.224 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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