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Record W7162132664 · doi:10.82308/27460

The relationship between child maltreatment subtypes and components of emotional competence in emerging adults

2023· dissertation· en· W7162132664 on OpenAlexaboutno aff
Polly Cheng

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsEmotion workEmotion recognitionMental healthEmotional regulationPoison controlEmotional competenceHuman factors and ergonomicsCompetence (human resources)Psychological abuse

Abstract

fetched live from OpenAlex

Child maltreatment is a pervasive public health issue that affects one in four children each year on a global scale. While not everyone who experiences child maltreatment has poor mental or physical health outcomes, many do suffer from emotional difficulties such as difficulty with emotion regulation and emotion recognition. Though child maltreatment is often studied as a single cumulative category, it comprises of different subtypes including physical and sexual abuse, emotional maltreatment, physical neglect, and exposure to domestic violence. Each of these subtypes have been linked with emotion regulation and emotion recognition problems, however, maltreatment subtypes frequently co-occur. Due to this overlap, when different maltreatment subtypes are not taken into consideration, effects may be overestimated or misattributed. There is currently a dearth of literature that examines the differential effects of childhood maltreatment subtypes on emotion regulation dimensions and the recognition of specific emotions. Additionally, while both emotion regulation and emotion recognition are core components of emotional competence, they are conceptualized to be distinct domains. Despite this, child maltreatment has been robustly associated with both emotion regulation and emotion recognition deficits suggesting that they may be related processes. Currently, without a theoretical basis on the relationship between different components of emotional competence, the relationship between emotion regulation and emotion recognition is unclear. As such, this dissertation aims to take a fine-grained approach to better understand the differential effects of child maltreatment subtypes on emotion regulation dimensions and the recognition of specific emotions in Study 1. Study 2 aims to empirically assess the relationship between emotion regulation and emotion recognition by examining the moderating role of emotion regulation in the relationship between child maltreatment and emotion recognition. Considering how emerging adulthood (18 – 25 years) is a developmental period where psychopathology often emerges, there is an impetus to better understand how child maltreatment impacts emotional functioning in this understudied population within child maltreatment research. A sample of 573 emerging adults were recruited across Canada to complete an online survey that asked about child maltreatment history, difficulty with emotion regulation, and involved an emotion recognition task. Path analyses in Study 1 indicated that emotional maltreatment had a global effect on emotion regulation difficulties and the recognition of negatively valanced emotions (anger, fear, and sadness). Neglect predicted difficulties with managing impulsive behaviour; sexual abuse predicted difficulties engaging in goal-directed behaviour. Physical abuse was associated with poorer recognition of fear. Multigroup analysis revealed that patterns did not differ between clinically distressed and non-distressed participants. In Study 2, moderation analysis revealed that child maltreatment was associated with poorer recognition of negatively valanced emotions, but only in the context of poor emotion regulation, however, exploratory analyses examining differential patterns revealed more nuanced relationships. While most maltreatment subtypes significantly interacted with emotion regulation (impulse control difficulties and limited access to emotion regulation strategies), the moderation was only significant for the recognition of disgust. Together, the results from both studies provide insight into the significant impact of emotional maltreatment on both emotion regulation and emotion recognition and how these patterns change when emotion regulation is examined as a moderator. These findings highlight the presence of common and disparate elements between child maltreatment subtypes which provide a basis for more targeted approaches to intervention for survivors of child maltreatment

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.320
Teacher spread0.279 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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