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Record W2413339855 · doi:10.1111/hex.12173

Editorial

2014· editorial· es· W2413339855 on OpenAlexaboutno aff
Jonathan Tritter

Bibliographic record

VenueHealth Expectations · 2014
Typeeditorial
Languagees
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Welcome to the first online regular edition of Health Expectations. The change from publishing a print edition allows us to produce six issues a year instead of the current four. The first set of articles relates to decision making and the use of decision aids targeted at particular patient populations. Adopting a telephone survey approach Singer and colleagues spoke with more than 2500 adults in the United States about how they made decisions relating to nine specific medical issues.1 Exploring decision making from a cost-benefit perspective, it is clear that such calculation informed respondent decision making but varied both between respondents and between different medical issues. By contrast, Robertson and her team from Canada and Australia describe how, for the Australian respondents to a survey of regular medicine users, physician recommendation is the most important factor in decision to take a medicine whatever the health insurance status of respondents.2 Promoting shared decision making about serious and terminal conditions is particularly difficult. Schroy, Mylvaganam, S. and Davidson from Boston explored the perceived impact of a decision-aid on colorectal cancer screening from the perspective of primary care providers in Boston, USA.3 The majority of respondent providers thought the tool was useful as a way to prepare patients for a consultation as it would save time and might lead to a better decision. Going beyond the results of an Italian randomized control trial of a decision aid (personal interview with a physician using a navigable CD and take-home booklet) for people with multiple sclerosis, Solari and colleagues collected interviews and focus group data from trial participants, participating physicians and the patient's neurologists.4 The results confirm the value of the decision aid from multiple perspectives. A group based at the University of Colorado in the United States report the results of a pilot clinical trial of a palliative care decision aid (dvd and booklet) with 51 patients.5 Using both interview and survey data, they found that participants exhibited no increased knowledge or less decision conflict, but, despite this, reported greater empowerment. The challenges of researching the experience of end-of-life care is very apparent in this article in terms of recruitment rates and high attrition and also the potential differences between the reports of patients and carers. The growing relevance of supporting shared decision making and decision aids is clearly demonstrated in these articles and, particularly, their relevance for conditions that will significantly change people's lives and for which the decision will have significant ramifications. The next set of articles considers how people make choices about particular tests or treatments. The expansion of self-testing has important implications for self-management, shared decision making and medicalization of society. The decision to self-test for cardiovascular risk factors and the experience is explored by Ickenroth and colleagues.6 Drawing on interviews with Dutch self-testers, they report that most felt healthy but wanted to do a self-test in order to have a valid reason to see a physician, suggesting that this practice is part of an active approach to the self-management of wellbeing but also potentially a behaviour by the ‘worried well’. The strength of preference for bariatric surgery using a willingness-to-pay approach in obese patients in Brazil is discussed by Ferreira and colleagues.7 Using survey and clinical data, they identify the presence of sleep apnoea as a key influence on decisions and that respondents were willing to pay to undergo the surgery sooner rather than later. The issue of rationing is considered more explicitly in Broqvist and Garpenby's article.8 Drawing on interviews with 14 Swedish citizens, they explore the different factors affecting the acceptability of rationing and that despite awareness of resource limitations, some still felt that rationing, particularly by not offering the best possible treatments was unacceptable. More importantly, the research confirms a lack of transparency in Sweden about how rationing decisions were justified and operationalized at county council level. The next two articles consider people's experience of care explicitly engage with theory in discussing two different involvement systems. The approach to social participation in primary care in Guatemala is described by Ruano, Sebastián and Hurtig.9 As part of decentralizing government power, a formal system of participation based on social development councils at community, municipal, provincial and national levels has been implemented across the 22 provinces in Guatemala. Applying a framework based on how, who, where and why, people participate to understand a specific municipal-level health commission. The only community members involved are from two pilot health promotion projects and have far less social and educational capital than the professional members of the commission; this undermines their capacity to ensure that decisions link social participation and social development rather than the resource sharing that is the primary intent of the other stakeholders involved. Some of the issues raised by Ruano and colleagues are also addressed in Gibson, Lewando-Hundt and Blaxter's study of neonatal networks in the UK.10 Applying Fraser's framework of weak and strong publics, they describe three distinct modes of parent involvement across the 23 networks nationally: information sources, consultants and representatives. They conclude that ‘participatory parity’ can only be achieved where parents had structures in place to link groups of parents systematically to representation on a board and may be one way to create a ‘strong public’. The application of Fraser's framework of weak and strong publics may also help to consider how involvement relates to both power hierarchies and political context and, as importantly, may provide a basis for cross-national and intersectoral approaches to involvement. The next two articles in this issue explore ways in which patient involvement can be used to develop health-care services to be more patient-centred. Using patient involvement to improve health promotion has a long history and Yen and colleagues discuss an example of this activity in relation to a Malaysian six month, work-based cardiovascular risk programme based on individual counselling and group seminars.11 In-depth interviews were conducted with the 17 participants from the Engineering campus of a premier public university revealing a positive response to the personalized advice that was part of the programme, but there was limited evidence of behavioural change. Understanding the views of patients and dentists on organizational aspects of general dental practice in the Netherlands was the focus of the questionnaire-based study reported by Sonneveld and colleagues from Radboud University Nijmegen.12 The results illustrate significant differences in preferred organizational characteristics between the two groups although they all consider extended opening hours in the evening and, on weekends, a low priority. The final article, by Tambuyzer, Pieters and Van Audenhove draws on a literature review and data synthesis to set out a comprehensive value-based model of patient involvement.13 The model highlights the areas where little evidence exists, such as the particular approaches needed in relation to specific groups such as children. The articles in this issue continue to emphasize the international nature of Health Expectations and patient involvement in practice. More than in most issues, these articles are engaging with and developing theory providing the conceptual tools that will permit greater comparative studies within and across different health-care sectors, systems and national contexts.

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)0.001
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0010.010

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 head0.122
GPT teacher head0.448
Teacher spread0.326 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2014
Admission routes1
Has abstractyes

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