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Record W2795269941 · doi:10.1093/schbul/sby017.615

F84. ASSOCIATIONS BETWEEN INTELLIGENCE, VERBAL WORKING MEMORY AND PROCESSING SPEED IN PARENTS WITH SCHIZOPHRENIA OR BIPOLAR DISORDER AND THEIR 7-YEAR OLD OFFSPRING

2018· article· en· W2795269941 on OpenAlexaff
Aja Neergaard Greve, Jens Richardt Møllegaard Jepsen, Erik Lykke Mortensen, Rudolf Uher, Lynn E. MacKenzie, Leslie Foldager, Ditte Lou Gantriis, Birgitte Klee Burton, Ditte Ellersgaard, Camilla Jerlang Christiani, Katrine Søborg Spang, Nicoline Hemager, Maria Toft Henriksen, Kate Kold Zahle, Henriette Stadsgaard, Anne Amalie Elgaard Thorup, Merete Nordentoft, Kerstin Jessica Plessen, Ole Mors, Vibeke Bliksted

Bibliographic record

VenueSchizophrenia Bulletin · 2018
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBipolar disorderNeurocognitivePsychologySchizophrenia (object-oriented programming)Working memoryPopulationIntelligence quotientPsychiatryPsychopathologyVerbal memoryClinical psychologyCognitionMedicine

Abstract

fetched live from OpenAlex

Neurocognitive phenotypes may contribute to understanding the pathway leading from genes to psychopathology. We aimed to investigate associations of intelligence, processing speed and verbal working memory between parents and offspring in families with schizophrenia, bipolar disorder and controls. Data are from The Danish High Risk and Resilience Study – VIA7, a population-based nationwide cohort identified through Danish Registries. Participants are 522 children aged 7 with no, one, or two parents with schizophrenia or bipolar disorder and biological parents. Control children were matched to children from the schizophrenia group (age, gender, and municipality). Children at familial risk of bipolar disorder were comparison group. Child assessors were blinded to risk status. Main Outcomes were intelligence measured with Reynolds Intellectual Screening Test (RIST), verbal working memory assessed with letter number sequencing (LNS) and processing speed assessed with Coding (WISC-IV/WAIS-IV). We examined 434 index parents (151 schizophrenia, 100 bipolar disorder and 183 controls, mean (SD) age 39.7 (5.7), 264 (61%) females), 443 co-parents (mean (SD) age 40.1 (5.4), 210 (47%) females) and 489 children (mean (SD) age 7.8 (0.2), 231 (47%) females). Children′s intelligence was associated with index parents’ intelligence (B = 0.40, 95% CI: 0.28;0.52, p < 0.001) and co-parents’ intelligence (B = 0.16, 95% CI: 0.03;0.28, p = 0.012). Children’s processing speed was associated with index parents’ processing speed (B = 0.07, 95% CI: 0.02;0.12, p = 0.007), co-parents’ processing speed (B = 0.09, 95% CI: 0.04;0.15, p < 0.001), group (schizophrenia: B = -1.92, 95% CI: -3.63;-0.21, p = 0.028) and gender of child (male: B = -4.55, 95% CI: -4.98; -2.12, p < 0.001). Children’s working memory was associated with index parents’ LNS score (B=0.25, 95% CI: 0.13;0.37, p < 0.001), co-parents’ working memory (B = 0.23, 95% CI: 0.09;0.37, p = 0.001), group (schizophrenia: B = -1.02, 95% CI: -0.89;-0.16, p = 0.020) and gender of child (male: B = -0.85, 95% CI: -1.60;-0.11, p = 0.025). Findings showed associations of neurocognitive phenotypes between parents and offspring. These associations do not differ markedly between schizophrenia, bipolar disorder and controls.

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 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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.263
Teacher spread0.241 · 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 teacher head, 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

Citations2
Published2018
Admission routes1
Has abstractyes

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