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Record W2797347853 · doi:10.22215/etd/2017-11770

Somatic Marker Functioning During Recovery From a Romantic Relationship with a Psychopathic Abuser: An Examination of Mental Health, Resilience and Post-Traumatic Growth in Social Decision Making

2017· dissertation· en· W2797347853 on OpenAlexaff
Courtney Humeny

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsCarleton University
Fundersnot available
KeywordsIowa gambling taskPsychologyMental healthClinical psychologyNeuropsychologyDistressPsychological resilienceAffect (linguistics)Developmental psychologyPsychiatryCognitionPsychotherapist

Abstract

fetched live from OpenAlex

Damasio’s (1994) Somatic Marker Hypothesis (SMH) proposes a system in the brain that creates somatic markers, a mechanism which assists in integrating emotional information to aid in everyday functioning, including social decision making. Survivors of domestic abuse commonly experience mental health impairments that are associated with abnormalities in the somatic marker circuitry. These abnormalities are made apparent in deficits in facial affect processing and social impairments that contribute to the maintenance of these disorders. Whiffen and MacIntosh (2005) propose that the strategies survivors use to cope with distress can perpetuate and extend impairments to mental health by diminishing their ability to maintain supportive relationships. However, some survivors demonstrate growth or resilience despite their experiences, and utilize social support relatively well. The purpose of my research is to provide a conceptual investigation of the neuropsychological underpinnings of Whiffen and MacIntosh’s pathway by utilizing Damasio’s SMH. I examine survivors of a romantic relationship with a psychopathic abuser. Survivors of psychopathic abusers have received limited attention from researchers, but suggestions have been made regarding profound emotional and interpersonal outcomes (Pagliaro, 2009). Two studies were conducted to examine the extent that abusers’ level of psychopathic traits influenced survivors’ abuse experiences and recovery outcomes (e.g., mental health impairments, resilience). Participants (N = 105 and N = 392) were recruited from domestic abuse support websites and completed a series of close and open-ended questionnaires, the Iowa Gambling Task (IGT), and a facial affect recognition task. A series of correlation and regression analyses revealed that abusers’ ascribed level of psychopathic traits were predicted by survivors’ experiences of abuse that was frequent, physically harmful, and versatile (i.e., physical, financial, sexual, and property abuse), and survivors’ diminished intensity of positive emotional experiences and elevated post-traumatic stress symptoms (Study 1a and 2). While both Factor 1 and Factor 2 psychopathy were predictive of frequent and physically harmful abuse, Factor 1 psychopathy was also predictive of survivors’ levels of anxiety (Study 1a).

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.020
GPT teacher head0.317
Teacher spread0.297 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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