Evidence map›Paper›PMID 31674676›Full record

Observational studyResearch in nursing & health2019

Using propensity score matching with doses in observational studies: An example from a child physical abuse and sleep quality study.

Xiaopeng Ji, Naixue Cui, Jianghong Liu

Abstract readObservational Study
In one paragraph

Observational study in Research in nursing & health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed.

  1. Article
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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Xiaopeng JiSchool of Nursing, College of Health Sciences, University of Delaware, Newark.ORCID 0000-0002-6977-3883
Naixue CuiSchool of Nursing, Shandong University, Jinan, China.ORCID 0000-0003-4684-5482
Jianghong LiuFamily and Community Health, School of Nursing, University of Pennsylvania, Philadelphia.ORCID 0000-0002-8405-6153

Funding

Lead exposure, externalizing behavior, and neurobiological mediating factorsR01ES018858 · NIEHS · UNIVERSITY OF PENNSYLVANIA · PI LIU, JIANGHONG · 2010 to 2014
$1.7M
Mechanisms that mediate the link between lead exposure and child behavior problemK02ES019878 · NIEHS · UNIVERSITY OF PENNSYLVANIA · PI LIU, JIANGHONG · 2011 to 2015
$656k
Environmental Toxicity, Malnutrition, and Children's Externalizing BehaviorK01ES015877 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI LIU, JIANGHONG · 2007 to 2010
$605k
NIEHS NIH HHS K01 ES015877NIEHS NIH HHS K02 ES019878NIEHS NIH HHS R01 ES018858
6 · The paper itself

Abstract

Both physical abuse and poor sleep quality are public health concerns among adolescents, particularly in mainland China, but examining any causal effect of physical abuse on adolescents' sleep quality using a randomized controlled trial is not possible for obvious ethical reasons. Researchers have proposed the use of propensity score matching with doses to minimize overt bias and estimate the effect of multidose treatments or varying degrees of risk exposure in observational studies. In this paper, we demonstrate the propensity score methods with a focus on matching with doses in an examination of the relationship between physical abuse levels (frequency and number of perpetrators) and self-reported sleep quality among adolescents. Secondary analyses were conducted using data from the China Jintan Child Cohort. The sample comprised 707 adolescents (13.16 ± 0.90 years old) who had complete data on physical abuse, sleep, and covariates. Propensity scores were computed from eight covariates and used to carry out pair matching, matching with the frequency of abusive experience, and matching with the number of perpetrators. The standardized differences of covariates suggested an acceptable balance between groups after matching. The results derived from matching sets consistently indicated that adolescents being physically abused by parent(s) have worse sleep quality. Despite its inherent limitations, propensity score matching with doses provides a useful tool for nurse researchers analyzing observational data.

Indexed as

Propensity ScoreAdolescentChild AbuseChinaCohort StudiesFemaleHumansMaleNursing ResearchSleep HygieneSurveys and Questionnairesadolescentschild abusematching with dosespropensity scoresleep

Identifiers

PMID31674676
PMCPMC6858510

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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.