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Record W4393442298 · doi:10.3389/fpsyt.2024.1345844

On the complex relationship between resilience and hair cortisol levels in adolescence despite parental physical abuse: a fourth wave of resilience research

2024· article· en· W4393442298 on OpenAlexaff
Wassilis Kassis, Dilan Aksoy, Céline A. Favre, Julia Arnold, Stefan Gaugler, Katharina Elisabeth Grafinger, Sibylle Artz, Doug Magnuson

Bibliographic record

VenueFrontiers in Psychiatry · 2024
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of Victoria
FundersNorthwestern UniversitySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsPsychologyResilience (materials science)Developmental psychologyPsychological resiliencePhysical abusePsychological abuseClinical psychologyChild abuseMedicineHuman factors and ergonomicsPoison controlSocial psychologyMedical emergency

Abstract

fetched live from OpenAlex

Introduction To understand the family’s role in adolescents’ mental health development and the connection to neurodevelopmental disorders related to experienced parental physical abuse, we first explored resilience pathways longitudinally and secondly, connected the identified patterns to adolescents’ hair cortisol levels that are rooted in the hypothalamic–pituitary–adrenal axis as the main stress response system and connected brain structure alterations. Methods We analyzed longitudinal online questionnaire data for three consecutive high school years (from seventh to ninth grade) and four survey waves from a representative sample of n = 1609 high school students in Switzerland on violence–resilience pathways. Furthermore, we collected students’ hair samples from a subsample of n = 229 at survey wave 4. About 30% of the participating adolescents had been physically abused by their parents. Out of the overall sample, we drew a subsample of adolescents with parental abuse experiences (survey wave 1 n = 509; survey wave 2 n = 506; survey wave 3 n = 561; survey wave 4 n = 560). Results Despite the odds, about 20–30% of adolescents who have experienced parental physical abuse escaped the family violence cycle and can be called resilient. By applying a person-oriented analytical approach via latent class and transition analysis, we longitudinally identified and compared four distinct violence–resilience patterns. We identified violence resilience as a multidimensional latent construct, which includes hedonic and eudaimonic protective and risk indicators. Because resilience should not solely be operationalized based on the lack of psychopathology, our latent construct included both feeling good (hedonic indicators such as high levels of self-esteem and low levels of depression/anxiety and dissociation) and doing well (eudaimonic indicators such as high levels of self-determination and self-efficacy as well as low levels of aggression toward peers). Discussion The present study confirmed that higher cortisol levels significantly relate to the comorbid pattern (internalizing and externalizing symptoms), and further confirmed the presence of lasting alterations in brain structures. In this way, we corroborated the insight that when studying the resilience pathways and trajectories of abused adolescents, biological markers such as hair cortisol significantly enhance and deepen the understanding of the longitudinal mechanisms of psychological markers (e.g., self-determination, self-esteem, self-efficacy) that are commonly applied in questionnaires.

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)0.005
metaresearch head score (Gemma)0.005
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.106
GPT teacher head0.429
Teacher spread0.323 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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