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Record W4403471659 · doi:10.1016/j.jaac.2024.08.503

Maternal Depressive Symptoms and Risk for Childhood Depression: Role of Executive Functions

2024· article· en· W4403471659 on OpenAlexaff
Meredith Han, Ranjani Nadarajan, Nixi Wang, Michelle Z. L. Kee, Shuping Lim, Yashna K Sagar, Benjamin Chow, Ai Peng Tan, Bobby K. Cheon, Yuen‐Siang Ang, Juan Zhou, Helen Chen, Yap Seng Chong, Peter D. Gluckman, Michael J. Meaney, Evelyn Law

Bibliographic record

VenueJournal of the American Academy of Child & Adolescent Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersMinistry of Education - SingaporeNational Research Foundation SingaporeAgency for Science, Technology and ResearchNational Research Foundation
KeywordsDepressive symptomsDepression (economics)Executive functionsPsychologyClinical psychologyPsychiatryDevelopmental psychologyCognitionEconomics

Abstract

fetched live from OpenAlex

OBJECTIVE: Offspring of mothers with depression are at increased risk for executive function (EF) deficits and later depressive symptoms, but limited studies have examined EF as an intermediary pathway. This study examined the role of EF in mediating the association between maternal and child depressive symptoms. METHOD: Data were from a longitudinal birth cohort comprising 739 participants followed from the antenatal period for 12 years. Mothers completed the Edinburgh Perinatal Depression Scale at 26 to 28 weeks' gestation and at 3 and 24 months postpartum. At ages 8.5 to 10 years, children self-reported using the Children's Depression Inventory, Second Edition. Task-based and parent-reported EF measures were collected at 4 time points between 3.5 and 8.5 years. Latent growth curve models examined antenatal depressive symptoms and their trajectory in contributing to cold (ie, cognitive) and hot (ie, affective) EFs. The extent to which EF mediated this association was then assessed. RESULTS: Maternal depressive symptoms did not directly predict depressive symptoms in late childhood. Antenatal depressive symptoms predicted lower cold EF (β = -.13, 95% CI [-0.25, -0.004]) and hot EF (β = -.26, 95% CI [-0.38, -0.15]). Deficits in cold EF (β = -.26, 95% CI [-0.41, -0.11]) acted as an intermediary path to depressive symptoms, whereas hot EF mediated the association between maternal and child depressive symptoms, forming an indirect path that accounted for 37.5% of the association. CONCLUSION: Deficits in hot EF may be a pathway in explaining the intergenerational transmission of depression. This finding suggests fostering EF skills as a potential strategy for at-risk children. CLINICAL TRIAL REGISTRATION INFORMATION: Growing Up in Singapore Towards Healthy Outcomes (GUSTO); https://clinicaltrials.gov/study/NCT01174875?cond=NCT01174875 PLAIN LANGUAGE SUMMARY: This study using data from the Growing Up in Singapore Towards Healthy Outcomes cohort (n=739) examines the role of cognitive and affective executive functions (EF) in mediating the association between maternal and child depressive symptoms. Results show that "hot" EF (regulating emotions and motivation) accounted for 37.5% of the association between maternal prenatal depression and childhood depressive symptoms. Findings suggest that fostering hot EF skills may be a preventative strategy for children from families at risk of intergenerational transmission of depression. DIVERSITY & INCLUSION STATEMENT: We worked to ensure that the study questionnaires were prepared in an inclusive way. We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as living with a disability.

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)0.003
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0010.000

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 head0.006
GPT teacher head0.280
Teacher spread0.274 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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Same venueJournal of the American Academy of Child & Adolescent PsychiatrySame topicMaternal Mental Health During Pregnancy and PostpartumFrench-language works237,207