Evidence map›Paper›PMID 29920877›Full record

ArticleHealth expectations : an international journal of public participation in health care and health policy2018

Public and patient involvement in quantitative health research: A statistical perspective.

Ailish Hannigan

Abstract read
In one paragraph

Article in Health expectations : an international journal of public participation in health care and health policy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. A public and patient consultation process as an aid to design a person-centred randomized clinical trial.Health expectations : an international journal of public participation in health care and health policy · 2021
    Trial
  2. Article
  3. Article
  4. Evaluation of a 'Research Methods' Training Course for Novice Lived Experience Researchers.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
  5. Article
  6. Article
  7. Involving People With Lived Experience in Electronic Health Record Database Studies Reflections and Learning From the CHOOSE Study.Health expectations : an international journal of public participation in health care and health policy · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Stakeholder involvement in the development of trial material for a clinical trial.Health expectations : an international journal of public participation in health care and health policy · 2021
    Article
  18. Article
  19. Article
  20. PPI in research: a reflection from early stage researchers.Research involvement and engagement · 2019
    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

1 author.

Ailish HanniganPublic and Patient Involvement Research Unit, Graduate Entry Medical School, University of Limerick, Limerick, Ireland.ORCID 0000-0003-0554-2741

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe majority of studies included in recent reviews of impact for public and patient involvement (PPI) in health research had a qualitative design. PPI in solely quantitative designs is underexplored, particularly its impact on statistical analysis. Statisticians in practice have a long history of working in both consultative (indirect) and collaborative (direct) roles in health research, yet their perspective on PPI in quantitative health research has never been explicitly examined.

objectiveTo explore the potential and challenges of PPI from a statistical perspective at distinct stages of quantitative research, that is sampling, measurement and statistical analysis, distinguishing between indirect and direct PPI.

conclusionsStatistical analysis is underpinned by having a representative sample, and a collaborative or direct approach to PPI may help achieve that by supporting access to and increasing participation of under-represented groups in the population. Acknowledging and valuing the role of lay knowledge of the context in statistical analysis and in deciding what variables to measure may support collective learning and advance scientific understanding, as evidenced by the use of participatory modelling in other disciplines. A recurring issue for quantitative researchers, which reflects quantitative sampling methods, is the selection and required number of PPI contributors, and this requires further methodological development. Direct approaches to PPI in quantitative health research may potentially increase its impact, but the facilitation and partnership skills required may require further training for all stakeholders, including statisticians.

Indexed as

Data Interpretation, StatisticalHealth Services ResearchPatient ParticipationResearch DesignHumansclinical trialcohort studiesparticipatorypublic and patient involvementquantitativestatistics

Identifiers

PMID29920877
PMCPMC6250860

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.