Dataset Information

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models.

ABSTRACT: OBJECTIVES:Effective researcher assessment is key to decisions about funding allocations, promotion and tenure. We aimed to identify what is known about methods for assessing researcher achievements, leading to a new composite assessment model. DESIGN:We systematically reviewed the literature via the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols framework. DATA SOURCES:All Web of Science databases (including Core Collection, MEDLINE and BIOSIS Citation Index) to the end of 2017. ELIGIBILITY CRITERIA: (1) English language, (2) published in the last 10 years (2007-2017), (3) full text was available and (4) the article discussed an approach to the assessment of an individual researcher's achievements. DATA EXTRACTION AND SYNTHESIS:Articles were allocated among four pairs of reviewers for screening, with each pair randomly assigned 5% of their allocation to review concurrently against inclusion criteria. Inter-rater reliability was assessed using Cohen's Kappa (?). The ? statistic showed agreement ranging from moderate to almost perfect (0.4848-0.9039). Following screening, selected articles underwent full-text review and bias was assessed. RESULTS:Four hundred and seventy-eight articles were included in the final review. Established approaches developed prior to our inclusion period (eg, citations and outputs, h-index and journal impact factor) remained dominant in the literature and in practice. New bibliometric methods and models emerged in the last 10 years including: measures based on PageRank algorithms or 'altmetric' data, methods to apply peer judgement and techniques to assign values to publication quantity and quality. Each assessment method tended to prioritise certain aspects of achievement over others. CONCLUSIONS:All metrics and models focus on an element or elements at the expense of others. A new composite design, the Comprehensive Researcher Achievement Model (CRAM), is presented, which supersedes past anachronistic models. The CRAM is modifiable to a range of applications.

SUBMITTER: Braithwaite J

PROVIDER: S-EPMC6475357 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models.

Braithwaite Jeffrey J Herkes Jessica J Churruca Kate K Long Janet C JC Pomare Chiara C Pomare Chiara C Boyling Claire C Bierbaum Mia M Clay-Williams Robyn R Rapport Frances F Shih Patti P Hogden Anne A Ellis Louise A LA Ellis Louise A LA Ludlow Kristiana K Austin Elizabeth E Seah Rebecca R McPherson Elise E Hibbert Peter D PD Westbrook Johanna J

BMJ open 20190330 3

<h4>Objectives</h4>Effective researcher assessment is key to decisions about funding allocations, promotion and tenure. We aimed to identify what is known about methods for assessing researcher achievements, leading to a new composite assessment model.<h4>Design</h4>We systematically reviewed the literature via the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols framework.<h4>Data sources</h4>All Web of Science databases (including Core Collection, MEDLINE and BIOSIS ...[more]

PMID: 30928941

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Project description:The online public food environment (OPFE) has had a considerable impact on people's lifestyles over the past decade; however, research on its exposure is sparse. The results of the existing research on the impact of the food environment on human health are inconsistent. In response to the lack of food elements in the definition of the food environment and the lack of a clear method to assess the health attributes and the impact degree of the food environment, we proposed a new analytical framework based on the latest disease burden research, combining the characteristics of China's current food environment, from the perspective of environmental science. We redefined the food environment and proposed that food and its physical space are two core elements of the food environment. Accordingly, we extracted four domains of characteristics to describe the basic components of the food environment. Using the sales records, we designed an approach by referring to the standard process of environmental health indicators, including the health attributes and the impact degree of the food environment, to measure the OPFE of takeaway food outlets. Further, we conducted a case study and extracted three domains of characteristics for more than 18,000 effective takeaway meals from 812 takeaway food outlets located in 10 administrative subdivisions in the Haidian District and Xicheng District of Beijing Municipality. The results showed that more than 60% of single meals sold by takeaway food outlets were considered as healthy, and only 15% of takeaway food outlets sold healthy meals exclusively. Additionally, there were significant differences in health effects among different types of food environments, and high-risk areas of different types of food environments can be spatially identified. Compared with the counting method in the availability of food environment, the proposed new approach can depict food environment characteristics not only in the macro-scale like the counting method but also in the meal-scale. The indicators could be useful for large-scale and long-term monitoring of food environmental changes due to their simple calculation and design depending on the food delivery platform.

Dataset Information

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models.

Publications

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models.

Similar Datasets

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