Evidence map›Paper›PMID 40785155›Full record

ArticleInternational journal of mental health nursing2025

An Exploration of Online Positive Feedback in Relation to Mental Health Nursing Practice.

Mark Pearson, Stefan Rennick-Egglestone

Abstract read
In one paragraph

Article in International journal of mental health nursing, 2025. 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

2 authors.

Mark PearsonUniversity of Nottingham, Nottingham, UK.ORCID https://orcid.org/0000-0001-6749-3565
Stefan Rennick-EgglestoneSchool of Health Sciences, Institute of Mental Health, University of Nottingham, Nottingham, UK.ORCID https://orcid.org/0000-0003-4187-011X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Web-based databases of service user feedback have become an important resource for the task of understanding the quality of healthcare provision, both in the UK and internationally. This research explores positive feedback submitted to the Care Opinion website (https://www.careopinion.org.uk/), some of which can provide insights into effective mental health nurse practices. An iterative search was undertaken using the Care Opinion website on 7 March 2025. A set of tags which frequently identified effective mental health nursing practices was identified, and then 51 items of feedback were taken forward for full analysis. The data was then analysed in relation to the deductively selected domains of tone, form, and intent. These were identified in a typology produced by a previous study of 200 positive feedback items across multiple sources. In relation to tone, most pieces of feedback were entirely positive with a small number being mixed. The intent of the feedback was often to express gratitude but also functioned to emphasise change and contrast the helpfulness of certain staff or organisations against others which were experienced as less helpful. A typology of form was established, comprised of (1) Narratives of being there; (2) Narratives of listening and being heard; Narratives of therapeutic relationships; and Narratives of recovery. Positive feedback can provide a valuable insight into the experiences of service users. This research provides proof of concept evidence that knowledge can be gained about the impact of mental health nursing through the analysis of online feedback gathered through websites such as Care Opinion.

Indexed as

FeedbackInternetPsychiatric NursingHumansmental healthnurse educationnursing

Identifiers

PMID40785155
PMCPMC12336429

What OpenQuestion holds

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Registered trials

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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.