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Record W1998281970 · doi:10.1111/1467-8624.00343

Children and Mothers in War: An Outcome Study of a Psychosocial Intervention Program

2001· article· en· W1998281970 on OpenAlexfundno aff
Ragnhild Dybdahl

Bibliographic record

VenueChild Development · 2001
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersMcMaster UniversityUNICEF
KeywordsPsychosocialMental healthIntervention (counseling)PsychologyDistressClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

The present study was designed to evaluate the effects on children (age: M = 5.5 years) in war-torn Bosnia and Herzegovina of a psychosocial intervention program consisting of weekly group meetings for mothers for 5 months. An additional aim was to investigate the children's psychosocial functioning and the mental health of their mothers. Internally displaced mother-child dyads were randomly assigned to an intervention group receiving psychosocial support and basic medical care (n = 42) or to a control group receiving medical care only (n = 45). Participants took part in interviews and tests to provide information about war exposure, mental health, psychosocial functioning, intellectual abilities, and physical health. Results showed that although all participants were exposed to severe trauma, their manifestations of distress varied considerably. The intervention program had a positive effect on mothers' mental health, children's weight gain, and several measures of children's psychosocial functioning and mental health, whereas there was no difference between the two groups on other measures. The findings have implications for policy.

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)0.002
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.029
GPT teacher head0.378
Teacher spread0.348 · 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

Citations258
Published2001
Admission routes1
Has abstractyes

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