Evidence map›Paper›PMID 39289005›Full record

SynthesisBMJ health & care informatics2024

Characteristics of positive feedback provided by UK health service users: content analysis of examples from two databases.

Rebecca Lloyd, Mike Slade, Richard Byng, Alex Russell, Fiona Ng, Alex Stirzaker, Stefan Rennick-Egglestone

Abstract readSystematic Review
In one paragraph

Synthesis in BMJ health & care informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Rebecca LloydSchool of Health Sciences, Institute of Mental Health, University of Nottingham, Nottingham, UK.
Mike SladeSchool of Health Sciences, Institute of Mental Health, University of Nottingham, Nottingham, UK.
Richard ByngPeninsula Schools of Medicine and Dentistry, University of Plymouth, Plymouth, UK.
Alex RussellHarvard Medical School, Harvard University, Cambridge, Massachusetts, USA.
Fiona NgSchool of Health Sciences, Institute of Mental Health, University of Nottingham, Nottingham, UK.
Alex StirzakerPeninsula Schools of Medicine and Dentistry, University of Plymouth, Plymouth, UK.
Stefan Rennick-EgglestoneSchool of Health Sciences, Institute of Mental Health, University of Nottingham, Nottingham, UK stefan.egglestone@nottingham.ac.uk.ORCID http://orcid.org/0000-0003-4187-011X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost feedback received by health services is positive. Our systematic scoping review mapped all available empirical evidence for how positive patient feedback creates healthcare change. Most included papers did not provide specific details on positive feedback characteristics.

objectivesDescribe positive feedback characteristics by (1) developing heuristics for identifying positive feedback; (2) sharing annotated feedback examples; (3) describing their positive content.

methods200 items were selected from two contrasting databases: (1) https://careopinion.org.uk/; (2) National Health Service (NHS) Friends and Family Test data collected by an NHS trust. Preliminary heuristics and positive feedback categories were developed from a small convenience sample, and iteratively refined.

resultsCategories were identified: positive-only; mixed; narrative; factual; grateful. We propose a typology describing tone (positive-only, mixed), form (factual, narrative) and intent (grateful). Separating positive and negative elements in mixed feedback was sometimes impossible due to ambiguity. Narrative feedback often described the cumulative impact of interactions with healthcare providers, healthcare professionals, influential individuals and community organisations. Grateful feedback was targeted at individual staff or entire units, but the target was sometimes ambiguous.

conclusionPeople commissioning feedback collection systems should consider mechanisms to maximise utility by limiting ambiguity. Since being enabled to provide narrative feedback can allow contributors to make contextualised statements about what worked for them and why, then there may be trade-offs to negotiate between limiting ambiguity, and encouraging rich narratives. Groups tasked with using feedback should plan the human resources needed for careful inspection, and consider providing narrative analysis training.

Indexed as

Health Care SurveysPatient SatisfactionState MedicineDatabases, FactualHumansUnited KingdomHealth Services Research

Identifiers

PMID39289005
PMCPMC11429259

What OpenQuestion holds

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LicenceCC BY-NC
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.