Evidence map›Paper›PMID 33788054›Full record

ArticleChild psychiatry and human development2022

Predicting Child Maltreatment over the Early Life Course: A Prospective Study.

Jake M Najman, James G Scott, Gail M Williams, Alexandra M Clavarino, Steve Kisely, Tara R McGee

Abstract read
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In one paragraph

Article in Child psychiatry and human development, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jake M NajmanSchool of Public Health, University of Queensland, Public Health Building, Herston Campus, 288 Herston Road, Herston, QLD, 4006, Australia. j.najman@uq.edu.au.ORCID 0000-0001-7079-2080
James G ScottMental Health Research Programme, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD, 4006, Australia.
Gail M WilliamsSchool of Public Health, University of Queensland, Public Health Building, Herston Campus, 288 Herston Road, Herston, QLD, 4006, Australia.
Alexandra M ClavarinoSchool of Public Health, University of Queensland, Public Health Building, Herston Campus, 288 Herston Road, Herston, QLD, 4006, Australia.
Steve KiselySchool of Medicine, Princess Alexandra Hospital, University of Queensland, Woolloongabba, QLD, 4102, Australia.
Tara R McGeeSchool of Criminology and Criminal Justice, Griffith University, 176 Messines Ridge Road, Mount Gravatt, QLD, 4122, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A large number of early life exposures predict child maltreatment. Using data from a 30-year birth cohort study we examine 12 early life course risk factors of four types of self-reported childhood maltreatment recalled at the 30-year follow-up. Of the 7223 children in the sample at birth, 2425 responded to the Child Trauma Questionnaire at the 30-year follow-up. On adjusted analysis being a teenage mother predicts childhood physical and sexual abuse, as well as child neglect. More numerous maternal marital partner changes in the 5 years after the birth predict offspring experiences of emotional abuse, sexual abuse and childhood neglect. Policy responses should focus on the broad social context in which children are reared as the most effective approach to reducing the high level of childhood abuse and neglect.

Indexed as

Adult Survivors of Child AbuseChild AbuseAdolescentChildCohort StudiesHumansInfant, NewbornProspective StudiesSurveys and QuestionnairesChild abuseEarly lifeNeglectPredictors

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.