Evidence map›Paper›PMID 37786916›Full record

ReviewJournal of dental research2023

Quantitative Assessment of Systematic Bias: A Guide for Researchers.

J C Bond, M P Fox, L A Wise, B Heaton

Abstract readReview
In one paragraph

Review in Journal of dental research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Observational
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
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

4 authors.

J C BondDepartment of Health Policy and Health Services Research, Boston University Henry M. Goldman School of Dental Medicine, Boston, MA, USA.ORCID 0000-0002-2988-7755
M P FoxDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
L A WiseDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
B HeatonDepartment of Health Policy and Health Services Research, Boston University Henry M. Goldman School of Dental Medicine, Boston, MA, USA.ORCID 0000-0002-3097-4717

Funding

An internet-based preconception cohort study in North America and DenmarkR01HD086742 · NICHD · BOSTON UNIVERSITY MEDICAL CAMPUS · PI LAUREN A WISE · 2016 to 2026
$6.7M
Feasibility of an internet-based study of time-to-pregnancy in the United StatesR21HD072326 · NICHD · BOSTON UNIVERSITY MEDICAL CAMPUS · PI WISE, LAUREN A · 2013 to 2014
$337k
Women's oral health in the preconception period: correlates and consequencesF31DE031969 · NIDCR · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BOND, JULIA CRAIG · 2022 to 2023
$74k
NICHD NIH HHS R01 HD086742NICHD NIH HHS R21 HD072326NIDCR NIH HHS F31 DE031969
6 · The paper itself

Abstract

Observational research provides valuable opportunities to advance oral health science but is limited by vulnerabilities to systematic bias, including unmeasured confounding, errors in variable measurement, or bias in the creation of study populations and/or analytic samples. The potential influence of systematic biases on observed results is often only briefly mentioned among the discussion of limitations of a given study, despite existing methods that support detailed assessments of their potential effects. Quantitative bias analysis is a set of methodological techniques that, when applied to observational data, can provide important context to aid in the interpretation and integration of observational research findings into the broader body of oral health research. Specifically, these methods were developed to provide quantitative estimates of the potential magnitude and direction of the influence of systematic biases on observed results. We aim to encourage and facilitate the broad adoption of quantitative bias analyses into observational oral health research. To this end, we provide an overview of quantitative bias analysis techniques, including a step-by-step implementation guide. We also provide a detailed appendix that guides readers through an applied example using real data obtained from a prospective observational cohort study of preconception periodontitis in relation to time to pregnancy. Quantitative bias analysis methods are available to all investigators. When appropriately applied to observational studies, findings from such studies can have a greater impact in the broader research context.

Indexed as

Research DesignBiasFemaleHumansPregnancyProspective Studiescomputer simulationepidemiologic methods, observational studies as a topicepidemiologymethodspublic health

Identifiers

PMID37786916
PMCPMC10714380

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.