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Record W2344493422 · doi:10.1111/hex.12470

Positive reporting? Is there a bias is reporting of patient and public involvement and engagement?

2016· editorial· en· W2344493422 on OpenAlexaboutno aff
Carolyn Chew‐Graham

Bibliographic record

VenueHealth Expectations · 2016
Typeeditorial
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
Fundersnot available
KeywordsPublic relationsPublic involvementPublic engagementService (business)Public serviceMedicinePsychologyMedical educationPolitical scienceBusinessMarketing

Abstract

fetched live from OpenAlex

Welcome to this edition of Health Expectations. As we have stated in earlier editorial briefings (e.g. 18.6), we are paying much more attention to the role played by patients and the public in selecting and agreeing the research question, study design and methods, interpretation and discussion of study findings, and in dissemination of results. So this edition of HEX particularly reflects this. In the UK, the National Institute for Health Research suggests that patients or service users can be involved in research in three ways, which are not mutually exclusive1: In Going the Extra Mile,2 a series of key recommendations are made, with plans for implementation, to further develop patient and public involvement in research. The report draws on the ‘strengths of the models of public involvement developed in Canada and the USA include their focus on communities and their assiduous attention to maintaining a clear line of sight from research design and delivery to patient outcomes and experience’. A key phrase in the report is on page 2: ‘Public Involvement should be so embedded in the culture (of NIHR) that new staff or new researchers coming into the field, would naturally take on the values and practices of effective public involvement’. Shippee et al.3 describe a model for the stages of patient and service user involvement and engagement: preparatory, execution and translational, and propose a framework which provides a standard structure and language for reporting and indexing to support comparative effectiveness and optimize patient and service user involvement. Tierney et al., in this edition of HEX, report their review of service user involvement in research and service development highlight that most studies only reported positive outcomes, raising questions about the balance or completeness of the published appraisals. They conclude that ‘to improve normalization of meaningful involvement in primary care, it is necessary to encourage explicit reporting of definitions, methodological innovation to enhance cogovernance and dissemination of research processes and findings’. Tierney et al. remind us of the PIRICOM Review4 which reported negative impacts on patients involved in research, in terms of personal impact, skill levels and knowledge levels, and users feeling overburdened, not listened to and marginalized. Fairbrother et al., in this edition of HEX, describe involving patients in a feasibility study using a ‘patient panel’ approach, but refer to their consideration of the word ‘scrutiny’ to describe the function of their panel. They report that involvement in the panel was considered a positive experience by participants, although ‘challenges were identified in terms of the time and cost implications of undertaking patient involvement’. Jinks et al.5 describe an on-going project which aims to describe and understand what the costs and consequences of patient and public involvement (PPI) in primary care research. This study has yet to report its findings, but a conference abstract indicates challenges in data collection.6 Boaz et al., in this edition of HEX, report a qualitative study exploring researchers’ attitudes to PPI and patient involvement in science (PES). They state that ‘while participants demonstrated a range of attitudes to these practices, they shared a resistance to sharing power and control of the research process with the public and patients’. This resonates with the difficulty Jinks et al.5 report in asking researchers to identify patient/service users and inviting them to complete questionnaires to generate data for their study. In a very recent article, Jinks et al.7 describe about how to sustain genuine PPIE involvement, beyond time-limited commitment to a single research project. They stress the need for institutional support and suggest that the following are needed: In conclusion, patient involvement and engagement is advocated, and indeed, most funding bodies demand it.1, 2 Attempts have been made to describe frameworks or models to conceptualize PPI; and while there is an increasing awareness of the challenges of PPI in high-quality research, as Tierney reports, there remains a positive bias in that most studies report positive outcomes for their PPI activities. We would like to encourage authors to report impact of PPI on studies in their submissions to HEX – and tell it how it is.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.212
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.257
GPT teacher head0.466
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2016
Admission routes1
Has abstractyes

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