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Record W2079771528 · doi:10.1111/jcpp.12306

Practitioner Review: Diagnosing childhood resilience – a systemic approach to the diagnosis of adaptation in adverse social and physical ecologies

2014· review· en· W2079771528 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2014
Typereview
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyMental healthCoping (psychology)Developmental psychologyPsychological resilienceTemperamentClinical psychologyAttributionPoison controlPersonalitySocial psychologyPsychiatryMedicineMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: With growing interest in resilience among mental health care providers globally, there is a need for a simple way to consider the complex interactions that predict adaptive coping when there is exposure to high levels of adversity such as family violence, mental illness of a child or caregiver, natural disasters, social marginalization, or political conflict. METHODS: This article presents diagnostic criteria for assessing childhood resilience in a way that is sensitive to the systemic factors that influence a child's wellbeing. The most important characteristics of children who cope well under adversity and avoid problems like depression, PTSD, and delinquency are highlighted. RESULTS: A multidimensional assessment of resilience is presented that examines, first, the severity, chronicity, ecological level, children's attributions of causality, and cultural and contextual relevance of experiences of adversity. Second, promotive and protective factors related to resilience are assessed with sensitivity to the differential impact these have on outcomes depending on a child's level of exposure to adversity. These factors include individual qualities like temperament, personality, and cognitions, as well as contextual dimensions of positive functioning related to the available and accessibility of resources, their strategic use, positive reinforcement by a child's significant others, and the adaptive capacity of the environment itself. Third, an assessment of resilience includes temporal and cultural factors that increase or decrease the influence of protective factors. A decision tree for the diagnosis of resilience is presented, followed by a case study and diagnosis of a 15-year-old boy who required treatment for a number of mental health challenges. CONCLUSIONS: The diagnostic criteria for assessing resilience and its application to clinical practice demonstrate the potential usefulness of a systemic approach to understanding resilience among child populations.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.419
Teacher spread0.379 · 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