Evidence map›Paper›PMID 32131789›Full record

ArticleBMC public health2020

Adolescent multiple risk behaviours cluster by number of risks rather than distinct risk profiles in the ALSPAC cohort.

Caroline Wright, Jon Heron, Rona Campbell, Matthew Hickman, Ruth R Kipping

Abstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

5 authors.

Caroline WrightPopulation Health Sciences, Bristol Medical School, Barley House, University of Bristol, Oakfield Grove, Clifton, Bristol, BS8 2BN, UK. caroline.wright@bristol.ac.uk.ORCID http://orcid.org/0000-0002-4321-4872
Jon HeronPopulation Health Sciences, Bristol Medical School, Barley House, University of Bristol, Oakfield Grove, Clifton, Bristol, BS8 2BN, UK.
Rona CampbellPopulation Health Sciences, Bristol Medical School, Barley House, University of Bristol, Oakfield Grove, Clifton, Bristol, BS8 2BN, UK.
Matthew HickmanPopulation Health Sciences, Bristol Medical School, Barley House, University of Bristol, Oakfield Grove, Clifton, Bristol, BS8 2BN, UK.
Ruth R KippingPopulation Health Sciences, Bristol Medical School, Barley House, University of Bristol, Oakfield Grove, Clifton, Bristol, BS8 2BN, UK.

Funding

Cancer Research UK 23895Medical Research Council G0802736Medical Research Council MC_PC_15018Medical Research Council MC_PC_19009Medical Research Council MR/K023233/1Medical Research Council MR/L022206/1Wellcome Trust
6 · The paper itself

Abstract

backgroundExperimentation with new behaviours during adolescence is normal. However, engagement in two or more risk behaviours, termed multiple risk behaviours is associated with socioeconomic disadvantage and poor health and social outcomes. Evidence of how adolescents cluster based on their risk behaviours is mixed.

methodsLatent Class Analysis was used to study patterns of engagement in 10 self-reported risk behaviours (including substance use, self-harm and sexual health) from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort at ages 15-16 years. Data was available for 6556 adolescents. Associations between risk profile and sex were explored.

resultsA 3-class model for both females and males was deemed to have acceptable fit. Whilst we found evidence of a sex difference in the risk behaviours reported within each class, the sex-specific results were very similar in many respects. For instance, the prevalence of membership of the high-risk class was 8.5% for males and 8.7% for females and both groups had an average of 5.9 behaviours. However, the classes were both statistically dubious, with class separation (entropy) being poor as well as conceptually problematic, because the resulting classes did not provide distinct profiles and varied only by quantity of risk-behaviours.

conclusionClusters of adolescents were not characterised by distinct risk behaviour profiles, and provide no additional insight for intervention strategies. Given this is a more complicated, software-specific method, we conclude that an equally effective, but more readily replicable approach is to use a count of the number of risk behaviours.

Indexed as

Risk-TakingAdolescentAdolescent BehaviorCluster AnalysisCohort StudiesFemaleHumansMaleSelf-Injurious BehaviorSexual HealthSubstance-Related DisordersALSPACClusteringLatent class analysisMultiple risk behavioursPublic health intervention

Identifiers

PMID32131789
PMCPMC7057689

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Registered trials

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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.