Evidence map›Paper›PMID 30638956›Full record

ReviewBrazilian journal of physical therapy

Understanding and interpreting confidence and credible intervals around effect estimates.

Luiz Hespanhol, Caio Sain Vallio, Lucíola Menezes Costa, Bruno T Saragiotto

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Brazilian journal of physical therapy. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 169 papers, 16 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
169citing papers in PubMed, 16 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

169 citing papers in PubMed, 16 syntheses or guidelines pooled it.

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  6. Comparison of Luteal Support Protocols in Frozen IVF/ICSI Cycles: A Network Meta-Analysis.BJOG : an international journal of obstetrics and gynaecology · 2025
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  9. Second-Line Treatment for Patients With Primary Biliary Cholangitis: A Systematic Review With Network Meta-Analysis.Liver international : official journal of the International Association for the Study of the Liver · 2025
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109 more citing papers are in PubMed but not listed here.

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.

Luiz HespanholMasters and Doctoral Programs in Physical Therapy, Universidade Cidade de São Paulo (UNICID), São Paulo, SP, Brazil; Department of Public and Occupational Health (DPOH), Amsterdam Public Health Research Institute (APH), VU University Medical Center (VUmc), Amsterdam, The Netherlands; Amsterdam Collaboration on Health and Safety in Sports (ACHSS), Academic Medical Center/VU University Medical Center IOC Research Center, Amsterdam, The Netherlands. Electronic address: l.hespanhol@outlook.com.
Caio Sain VallioMasters and Doctoral Programs in Physical Therapy, Universidade Cidade de São Paulo (UNICID), São Paulo, SP, Brazil.
Lucíola Menezes CostaMasters and Doctoral Programs in Physical Therapy, Universidade Cidade de São Paulo (UNICID), São Paulo, SP, Brazil.
Bruno T SaragiottoMasters and Doctoral Programs in Physical Therapy, Universidade Cidade de São Paulo (UNICID), São Paulo, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionReporting confidence intervals in scientific articles is important and relevant for evidence-based practice. Clinicians should understand confidence intervals in order to determine if they can realistically expect results similar to those presented in research studies when they implement the scientific evidence in clinical practice. The aims of this masterclass are: (1) to discuss confidence intervals around effect estimates; (2) to understand confidence intervals estimation (frequentist and Bayesian approaches); and (3) to interpret such uncertainty measures. CONTENT: Confidence intervals are measures of uncertainty around effect estimates. Interpretation of the frequentist 95% confidence interval: we can be 95% confident that the true (unknown) estimate would lie within the lower and upper limits of the interval, based on hypothesized repeats of the experiment. Many researchers and health professionals oversimplify the interpretation of the frequentist 95% confidence interval by dichotomizing it in statistically significant or non-statistically significant, hampering a proper discussion on the values, the width (precision) and the practical implications of such interval. Interpretation of the Bayesian 95% confidence interval (which is known as credible interval): there is a 95% probability that the true (unknown) estimate would lie within the interval, given the evidence provided by the observed data.

conclusionsThe use and reporting of confidence intervals should be encouraged in all scientific articles. Clinicians should consider using the interpretation, relevance and applicability of confidence intervals in real-world decision-making. Training and education may enhance knowledge and skills related to estimating, understanding and interpreting uncertainty measures, reducing the barriers for their use under either frequentist or Bayesian approaches.

Indexed as

Bayes TheoremHumansUncertaintyBiostatisticsConfidence intervalsEvidence-based practicePhysical therapy specialtyStatistical data analysis

Identifiers

PMID30638956
PMCPMC6630113

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.