Evidence map›Paper›PMID 34866346›Full record

ArticleCancer medicine2022

The underlying structure of the English Cancer Patient Experience Survey: Factor analysis to support survey reporting and design.

Mayam Gomez-Cano, Georgios Lyratzopoulos, John L Campbell, Marc N Elliott, Gary A Abel

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 17% of its field
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. 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

5 authors at 3 institutions in 2 countries.

Mayam Gomez-CanoUniversity of Exeter Medical School (Primary Care), University of Exeter, Exeter, UK.ORCID 0000-0002-8298-1898
Georgios LyratzopoulosEpidemiology of Cancer Healthcare and Outcomes (ECHO) Group, Department of Behavioural Science and Health, University College London, London, UK.
John L CampbellUniversity of Exeter Medical School (Primary Care), University of Exeter, Exeter, UK.
Marc N ElliottRAND Corporation, Santa Monica, California, USA.
Gary A AbelUniversity of Exeter Medical School (Primary Care), University of Exeter, Exeter, UK.ORCID 0000-0003-2231-5161
University of Exeter · GBLondon Cancer · GBRAND Corporation · US

Funding

Cancer Research UK 18180Cancer Research UK C18081/A18180
6 · The paper itself

Abstract

backgroundThe English Cancer Patient Experience Survey (CPES) is a regularly conducted survey measuring the experience of cancer patients. We studied the survey's underlying structure using factor analysis to identify potential for improvements in reporting or questionnaire design.

methodsCancer Patient Experience Survey 2015 respondents (n = 71,186, response rate 66%) were split into two random subgroups. Using exploratory factor analysis (EFA) on the first subgroup, we identified the survey's latent structure. EFA was then applied to 12 sets of items. A first ("core") set was formed by questions that applied to all participants. The subsequent sets contained the "core set" plus questions corresponding to specific care pathways/patient groups. We used confirmatory factor analysis (CFA) on the second data subgroup for cross-validation.

resultsThe EFA suggested that five latent factors underlie the survey's core questions. Analysis on the remaining 11 care pathway/patient group items also indicated the same five latent factors, although additional factors were present for questions applicable to patients with an overnight stay or those accessing specialist nursing. The five factors models had an excellent fit (comparative fit index = 0.95, root mean square error of approximation = 0.045 for core set of questions). Items loading on each factor generally corresponded to a specific section or subsection of the questionnaire. CFA findings were concordant with the EFA patterns.

conclusionThe findings suggest five coherent underlying sub-constructs relating to different aspects of cancer health care. The findings support the construction of evidence-based composite indicators for different domains of experience and provide options for survey re-design.

Indexed as

Patient Outcome AssessmentFactor Analysis, StatisticalHumansNeoplasmscancerfactor analysishealth services administrationindicatorsoncologypatient experiencepsycho-oncologysurveysurveys and questionnaires

Identifiers

PMID34866346
PMCPMC8704178
OpenAlexW4200365564

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.