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Record W1525305872 · doi:10.1016/j.eurpsy.2010.09.010

Parental bonding and alexithymia: A meta-analysis

2011· article· en· W1525305872 on OpenAlexaboutno aff
Fred Arne Thorberg, Ross McD. Young, Karen A. Sullivan, Michael Lyvers

Bibliographic record

VenueEuropean Psychiatry · 2011
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
FundersQueensland University of Technology
KeywordsAlexithymiaPsycINFOFeelingPsychologyToronto Alexithymia ScaleMeta-analysisDevelopmental psychologyClinical psychologyParenting stylesMEDLINESocial psychologyMedicine

Abstract

fetched live from OpenAlex

AIM: The primary purpose of this meta-analysis was to explore, clarify and report the strength of the relationship between alexithymia, as measured by the Toronto Alexithymia Scale (TAS-20), and parenting style as measured by the Parental Bonding Instrument (PBI). METHODS: Web of Science, PsycInfo, PubMed and ProQuest: Dissertations and Theses searches were undertaken, yielding nine samples with sufficient data to be included in the meta-analysis. RESULTS: Evidence indicated moderate to strong relationships between maternal care and alexithymia, and between maternal care and two of the three TAS-20 alexithymia facets (Difficulties Describing Feelings and Difficulties Identifying Feelings, but not Externally Oriented Thinking). Moderate relationships were observed for both maternal- and paternal-overprotection and alexithymia respectively, and for overprotection (both maternal and paternal) and Difficulties Describing Feelings. CONCLUSION: This study is the first meta-analysis of the relationship between parenting styles and alexithymia, and findings confirm an especially strong association between maternal care and key elements of alexithymia. This review highlights the issues that still remain to be addressed in exploring the link between parenting style and alexithymia.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.000

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 head0.068
GPT teacher head0.281
Teacher spread0.213 · 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 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

Citations6
Published2011
Admission routes1
Has abstractyes

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