Tourism gender research: A critical accounting

This paper seeks to rouse debate about the workings of tourism enquiry as a knowledge-generating system through its critical accounting of the sub-field of tourism gender research. This accounting includes a gender-aware bibliometric analysis of 466 journal papers published during 1985–2012, which categorises the sub-field’s prevailing themes and methodologies and identifies its most prolific authors and popular journals. It contends that, despite three decades of study and a recent increase in papers, tourism gender research remains marginal to tourism enquiry, disarticulated from wider feminist and gender-aware initiatives and lacks the critical mass of research leaders, publications, citations and multi-institutional networks, which characterise other tourism sub-fields. The paper identifies two possible futures for gender-aware tourism research: stagnation or ignition

Stakeholder involvement in systematic reviews: a protocol for a systematic review of methods, outcomes and effects

Background There is an expectation for stakeholders (including patients, the public, health professionals, and others) to be involved in research. Researchers are increasingly recognising that it is good practice to involve stakeholders in systematic reviews. There is currently a lack of evidence about (A) how to do this and (B) the effects, or impact, of such involvement. We aim to create a map of the evidence relating to stakeholder involvement in systematic reviews, and use this evidence to address the two points above. Methods We will complete a mixed-method synthesis of the evidence, first completing a scoping review to create a broad map of evidence relating to stakeholder involvement in systematic reviews, and secondly completing two contingent syntheses. We will use a stepwise approach to searching; the initial step will include comprehensive searches of electronic databases, including CENTRAL, AMED, Embase, Medline, Cinahl and other databases, supplemented with pre-defined hand-searching and contacting authors. Two reviewers will undertake each review task (i.e., screening, data extraction) using standard systematic review processes. For the scoping review, we will include any paper, regardless of publication status or study design, which investigates, reports or discusses involvement in a systematic review. Included papers will be summarised within structured tables. Criteria for judging the focus and comprehensiveness of the description of methods of involvement will be applied, informing which papers are included within the two contingent syntheses. Synthesis A will detail the methods that have been used to involve stakeholders in systematic reviews. Papers from the scoping review that are judged to provide an adequate description of methods or approaches will be included. Details of the methods of involvement will be extracted from included papers using pre-defined headings, presented in tables and described narratively. Synthesis B will include studies that explore the effect of stakeholder involvement on the quality, relevance or impact of a systematic review, as identified from the scoping review. Study quality will be appraised, data extracted and synthesised within tables. Discussion This review should help researchers select, improve and evaluate methods of involving stakeholders in systematic reviews. Review findings will contribute to Cochrane training resources

Social Enterprise Evaluation : Implications for Tourism Development

The evaluation of social enterprise projects has focused mainly on devising effective performance measurement methods and processes to justify the investment of resources and time committed to such activities. With increasing demands for accountability, effectiveness, evidence of return on investment and value-added results, evaluation activities have been driven by imperatives of objectivity in assessments and the development of tools that monetize the social outcomes and impacts of social enterprise projects. These traditional approaches to evaluation have also been widely adapted in tourism based social enterprises that seek to attain goals of poverty alleviation, empowerment of local communities, and improved livelihoods for those marginalized from mainstream tourism economic activities. This chapter argues that traditional approaches to evaluation may be limited in supporting social entrepreneurship projects with development objectives of empowerment and societal change. It is proposed that social enterprise projects involving community participation may be better positioned to achieve their developmental objectives by incorporating more of the principles of Participatory Evaluation (PE) and Empowerment Evaluation (EE) in the quest to harness the economic prowess of tourism for human development

Power to the people: To what extent has public involvement in applied health research achieved this?

Public involvement in applied health research is a pre-requisite for funding from many funding bodies. In particular the National Institute of Health Research (NIHR) in the UK, clearly states that it values lay knowledge and there is an expectation that members of the public will participate as research partners in research. As a result a large public involvement infrastructure has emerged to facilitate this. However, there is concern that despite the flurry of activity in promoting public involvement, lay knowledge is marginalised and has limited impact on research decision-making. This article asks to what extent has power shifted from the scientific research community to the public? It discusses the meaning of power and models of public involvement and examines the development of public involvement in applied health research. It identifies public involvement in a range of decision-making: identifying priority areas for commissioning research; making decisions about which projects are funded; decisions about details of research design. Whilst there is evidence that the public voice is present in the composition of research proposals submitted to NIHR and in the decision-making about which projects are funded and how they are carried out, there is less evidence of a change in the power dynamic manifest in social relations between the scientific research community and the public. As a result the biomedical model remains dominant and largely unchallenged in research decision-making

Stakeholder involvement in systematic reviews:a scoping review

Abstract Background There is increasing recognition that it is good practice to involve stakeholders (meaning patients, the public, health professionals and others) in systematic reviews, but limited evidence about how best to do this. We aimed to document the evidence-base relating to stakeholder involvement in systematic reviews and to use this evidence to describe how stakeholders have been involved in systematic reviews. Methods We carried out a scoping review, following a published protocol. We searched multiple electronic databases (2010–2016), using a stepwise searching approach, supplemented with hand searching. Two authors independently screened and discussed the first 500 abstracts and, after clarifying selection criteria, screened a further 500. Agreement on screening decisions was 97%, so screening was done by one reviewer only. Pre-planned data extraction was completed, and the comprehensiveness of the description of methods of involvement judged. Additional data extraction was completed for papers judged to have most comprehensive descriptions. Three stakeholder representatives were co-authors for this systematic review. Results We included 291 papers in which stakeholders were involved in a systematic review. Thirty percent involved patients and/or carers. Thirty-two percent were from the USA, 26% from the UK and 10% from Canada. Ten percent (32 reviews) were judged to provide a comprehensive description of methods of involving stakeholders. Sixty-nine percent (22/32) personally invited people to be involved; 22% (7/32) advertised opportunities to the general population. Eighty-one percent (26/32) had between 1 and 20 face-to-face meetings, with 83% of these holding ≤ 4 meetings. Meetings lasted 1 h to ½ day. Nineteen percent (6/32) used a Delphi method, most often involving three electronic rounds. Details of ethical approval were reported by 10/32. Expenses were reported to be paid to people involved in 8/32 systematic reviews. Discussion/conclusion We identified a relatively large number (291) of papers reporting stakeholder involvement in systematic reviews, but the quality of reporting was generally very poor. Information from a subset of papers judged to provide the best descriptions of stakeholder involvement in systematic reviews provide examples of different ways in which stakeholders have been involved in systematic reviews. These examples arguably currently provide the best available information to inform and guide decisions around the planning of stakeholder involvement within future systematic reviews. This evidence has been used to develop online learning resources. Systematic review registration The protocol for this systematic review was published on 21 April 2017. Publication reference: Pollock A, Campbell P, Struthers C, Synnot A, Nunn J, Hill S, Goodare H, Watts C, Morley R: Stakeholder involvement in systematic reviews: a protocol for a systematic review of methods, outcomes and effects. Research Involvement and Engagement 2017, 3:9. https://doi.org/10.1186/s40900-017-0060-4

Measurement of patients' knowledge of their medication in community pharmacies in Portugal

El objetivo do artículo es determinar el conocimiento de los pacientes sobre sus medicamentos. Estudio observacional descriptivo transversal. El conocimiento se midió mediante un cuestionario válido y fiable (CPM-PT-PT), a los pacientes que acudieron a las farmacias comunitarias participantes en el estudio solicitando uno o varios medicamentos en el Área Metropolitana de Lisboa. Se determinó el conocimiento en sus cuatro dimensiones: objetivo terapéutico, proceso de uso, seguridad y conservación de los medicamentos que el paciente utiliza. Participaron 35 farmacias, obteniéndose 633 pacientes válidos. El 82.5% (IC95%: 79,3%-85,3%) no conocen el medicamento que utilizan. En todos los ítems, hubo un alto porcentaje de pacientes con conocimiento incorrecto, destacando especialmente las precauciones (44,7%). La dimensión que menos conocen los pacientes fue la "seguridad del medicamento" (1,9%). 8 de cada 10 pacientes de la población no conocen el medicamento que utilizan. La mayor carencia de información correcta corresponde a la "seguridad" del medicamento.The scope of this article is to determine patients' knowledge about the medication they take. For this purpose, a cross-sectional, observational and descriptive study was conducted. Knowledge was measured by a valid and reliable questionnaire (CPM-PT-PT), given to the patients attending community pharmacies participating in the study, who had prescriptions for one or more drugs in the Lisbon Metropolitan Area. Knowledge was assessed in four dimensions: therapeutic objective, process of use, safety and maintenance of the medications that the patient takes. Thirty-five pharmacies participated, and 633 valid patients were obtained. Fully 82.5% (95% CI: 79.3% -85.3%) were uninformed about the nature of the drug they use. In all items, there was a high percentage of patients with incorrect knowledge, with emphasis on precautions (44.7%). The dimension that the patients were least aware of was "drug safety" (1.9%). Eight out of 10 patients in the population do not know what drug they use. The highest lack of correct information was with respect to the "safety" of the medication

Validation of Automated Data Abstraction for SCCM Discovery VIRUS COVID-19 Registry: Practical EHR Export Pathways (VIRUS-PEEP)

BACKGROUND: The gold standard for gathering data from electronic health records (EHR) has been manual data extraction; however, this requires vast resources and personnel. Automation of this process reduces resource burdens and expands research opportunities. OBJECTIVE: This study aimed to determine the feasibility and reliability of automated data extraction in a large registry of adult COVID-19 patients. MATERIALS AND METHODS: This observational study included data from sites participating in the SCCM Discovery VIRUS COVID-19 registry. Important demographic, comorbidity, and outcome variables were chosen for manual and automated extraction for the feasibility dataset. We quantified the degree of agreement with Cohen\u27s kappa statistics for categorical variables. The sensitivity and specificity were also assessed. Correlations for continuous variables were assessed with Pearson\u27s correlation coefficient and Bland-Altman plots. The strength of agreement was defined as almost perfect (0.81-1.00), substantial (0.61-0.80), and moderate (0.41-0.60) based on kappa statistics. Pearson correlations were classified as trivial (0.00-0.30), low (0.30-0.50), moderate (0.50-0.70), high (0.70-0.90), and extremely high (0.90-1.00). MEASUREMENTS AND MAIN RESULTS: The cohort included 652 patients from 11 sites. The agreement between manual and automated extraction for categorical variables was almost perfect in 13 (72.2%) variables (Race, Ethnicity, Sex, Coronary Artery Disease, Hypertension, Congestive Heart Failure, Asthma, Diabetes Mellitus, ICU admission rate, IMV rate, HFNC rate, ICU and Hospital Discharge Status), and substantial in five (27.8%) (COPD, CKD, Dyslipidemia/Hyperlipidemia, NIMV, and ECMO rate). The correlations were extremely high in three (42.9%) variables (age, weight, and hospital LOS) and high in four (57.1%) of the continuous variables (Height, Days to ICU admission, ICU LOS, and IMV days). The average sensitivity and specificity for the categorical data were 90.7 and 96.9%. CONCLUSION AND RELEVANCE: Our study confirms the feasibility and validity of an automated process to gather data from the EHR

Validation of automated data abstraction for SCCM discovery VIRUS COVID-19 registry: practical EHR export pathways (VIRUS-PEEP)

BackgroundThe gold standard for gathering data from electronic health records (EHR) has been manual data extraction; however, this requires vast resources and personnel. Automation of this process reduces resource burdens and expands research opportunities.ObjectiveThis study aimed to determine the feasibility and reliability of automated data extraction in a large registry of adult COVID-19 patients.Materials and methodsThis observational study included data from sites participating in the SCCM Discovery VIRUS COVID-19 registry. Important demographic, comorbidity, and outcome variables were chosen for manual and automated extraction for the feasibility dataset. We quantified the degree of agreement with Cohen’s kappa statistics for categorical variables. The sensitivity and specificity were also assessed. Correlations for continuous variables were assessed with Pearson’s correlation coefficient and Bland–Altman plots. The strength of agreement was defined as almost perfect (0.81–1.00), substantial (0.61–0.80), and moderate (0.41–0.60) based on kappa statistics. Pearson correlations were classified as trivial (0.00–0.30), low (0.30–0.50), moderate (0.50–0.70), high (0.70–0.90), and extremely high (0.90–1.00).Measurements and main resultsThe cohort included 652 patients from 11 sites. The agreement between manual and automated extraction for categorical variables was almost perfect in 13 (72.2%) variables (Race, Ethnicity, Sex, Coronary Artery Disease, Hypertension, Congestive Heart Failure, Asthma, Diabetes Mellitus, ICU admission rate, IMV rate, HFNC rate, ICU and Hospital Discharge Status), and substantial in five (27.8%) (COPD, CKD, Dyslipidemia/Hyperlipidemia, NIMV, and ECMO rate). The correlations were extremely high in three (42.9%) variables (age, weight, and hospital LOS) and high in four (57.1%) of the continuous variables (Height, Days to ICU admission, ICU LOS, and IMV days). The average sensitivity and specificity for the categorical data were 90.7 and 96.9%.Conclusion and relevanceOur study confirms the feasibility and validity of an automated process to gather data from the EHR