Evidence map›Paper›PMID 33108540›Full record

ArticleJournal of patient-reported outcomes2020

Capturing patient experience: does quality-of-life appraisal entail a new class of measurement?

Carolyn E Schwartz, Roland B Stark, Bruce D Rapkin

Abstract read
In one paragraph

Article in Journal of patient-reported outcomes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  3. Individual differences in the long-term impact of the pandemic: moderators of COVID-related hardship, worry, and social support.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
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  4. Article
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  6. Observational
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  12. What should progress in response-shift research look like?Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021
    Article
  13. Article
  14. 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

3 authors.

Carolyn E SchwartzDeltaQuest Foundation, Inc., 31 Mitchell Road, Concord, MA, 01742, USA. carolyn.schwartz@deltaquest.org.ORCID http://orcid.org/0000-0002-9173-7774
Roland B StarkDeltaQuest Foundation, Inc., 31 Mitchell Road, Concord, MA, 01742, USA.
Bruce D RapkinDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTwo decades of research on quality-of-life (QOL) appraisal have demonstrated links between patient experience and health outcomes and have accounted for both intra-individual change and inter-individual differences in a wide range of research contexts. The present work investigates patterns across diagnostic and demographic groupings to demonstrate how population-specific circumstances drive the structure of QOL appraisal.

methodsThis secondary analysis (N = 6448) utilized data from six patient groups: spine surgery, multiple sclerosis, heterogeneous chronically ill, heterogeneous cancer, bladder cancer, and human immunodeficiency virus (HIV). We explored patterns of inter-item correlation across patient samples, using items from the Standards of Comparison and Sampling of Experience subsections of the QOL Appraisal Profile v1 and v2. Similar matrices were compared by demographic characteristics.

resultsPatterns of inter-item correlations for Standards of Comparison items varied sharply across disease groups and racial groups while being similar across age, gender, and education levels. Inter-item correlation matrices for Sampling of Experience items revealed marked differences among disease groups and educational and racial categories but were similar across age and gender groups.

conclusionsAppraisal parameters showed evidence of shared and unique aspects across samples and circumstances, findings which make sense in light of sample differences in health status and demographic influences. Tools to assess patient experience and meaning may be best understood as idiometric instruments. We discuss their distinctions from psychometric and clinimetric tools at theoretical, statistical, and applied levels.

Indexed as

AppraisalCausal indicatorClinimetricEffect indicatorFormative versus reflective measurement modelIdiometricMeasurement theoryPsychometricResponse shift

Identifiers

PMID33108540
PMCPMC7591682

What OpenQuestion holds

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LicenceCC BY
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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.