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Record W2615767977 · doi:10.1111/jan.13338

Research publication performance of Australian Professors of Nursing & Midwifery

2017· editorial· en· W2615767977 on OpenAlexaboutno aff
Lisa McKenna, Simon Cooper, Robyn Cant, Fiona Bogossian

Bibliographic record

VenueJournal of Advanced Nursing · 2017
Typeeditorial
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipNursing researchExcellenceWatsonDisciplineGovernment (linguistics)SociologyNursingPolitical scienceLibrary sciencePublic relationsMedical educationMedicineSocial science

Abstract

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Professors of nursing and midwifery are recognized as discipline leaders and thus have a key role to play in the development of disciplinary knowledge, especially through their research activity. Watson and Thompson (2008) paraphrased the research and scholarship roles of the professoriate, from the UK National Conference of University Professors, as a requirement to “maintain individual authoritative industry in scholarship and research” (p 981). This prompts us to ask: Are Australian nursing and midwifery professors leading the way in research? Mindful of the recent report on UK nursing professors’ citations and h-indices (Watson, McDonagh, & Thompson, 2017), we examined the research outputs of Australian nursing and midwifery professors. We grouped the disciplines as research outputs are listed together in research performance assessments. Position descriptions for senior academic nursing and midwifery appointments globally have a strong focus on conduct of research. For example, a professor's main responsibilities include: “to develop the research activities of the university” (University of Surrey, 2016) or to “drive globally competitive research …” (University of Newcastle, 2017). Institutional research profiles are assessed in Australian universities using the Excellence in Research for Australia (ERA) exercise developed by the Australian Research Council (ARC, 2016a). In addition to the annual Higher Education Research Data Collection (which is used by the government to allocate funding), the ERA process requires itemized data for research outputs, income, full time equivalent staff, esteem measures, patents and research commercialization classified according to the Australian Bureau of Statistics’ Field of Research (FOR) classification scheme. The FOR code “Nursing” includes the discipline of midwifery and hence we consider the disciplinary contributions together. In the last ERA round, 876.4 FTE positions yielded research income of over AU$115 million, and research outputs totalling 4,977. Most were journal articles (94%); the remaindering consisting of book chapters (3%), conference papers (1%) and non-traditional research outputs (NTRO) (1%) (Australian Research Council, 2016a). The performance of 19 institutions achieved the highest possible ranking (a score of 5 “above world standard”) in the Nursing Field of Research. Thus, from both institutional and disciplinary perspectives, it is important to understand the research publication output of the Australian nursing and midwifery professoriate. The h-index has been proposed as a measure of publication productivity and impact (Hirsch, 2005). This aims to measure the cumulative impact of a researcher's lifetime publication output through the number of citations achieved in relation to a set of the individual's most cited articles. If an author has 10 publications and each of these is cited 10 or more times, the h-index is 10. It does not collect citations for lesser cited articles (“one-hit wonders”) and corrects for uncited papers. Any additional citations over the recorded volume are also disregarded. It relates to journal articles alone, and not books, conference papers or other media. Thus, it provides a focused snapshot of an author's journalistic works based on quality and quantity, Hunt and Cleary (2010). The h-index has shown considerable reliability when tested in various settings (Bormann & Daniel, 2007). Both the Web of Science and SCOPUS have been used as appropriate search engines for reviewing the h-index of nursing researchers. In 2011, Hunt et al. published a ranking of Australian nursing researchers who had an h-index of 10 or more, based on the SCOPUS database. These 24 nurses had a mean h-index of 14.17 and a range of citations from 283 to over 4600. Latterly, in the UK, Watson et al. (2017) found the median h-index for Professors of Nursing was 12 (mean = 12.66) with the highest being 39, accessed via Web of Science. Prior to this, a survey of 16 leading UK nursing professors’ publications in 2010 revealed an h-index mean of 11 (Thompson & Watson, 2010). In Canada, a 2009 survey of the top 20 nursing academics publishing research found that h-indices ranged from 14 to 23 (Hack, Crooks, Plohman, & Kepron, 2010). Although no overall data were presented, these authors concluded that an h-index of between 10–14 represented an “excellent” research record, while an h-index over 15 was an “exceptional” record in nursing. Australian nursing/midwifery professorial appointments in October 2016 were identified through their respective institutional web profiles and then searched by author using the SCOPUS database (SCOPUS was selected as it is the database used in data collection for ERA). The total number of citations of each individual, and the h-index (including self- citations) as of October 2016 were recorded, together with brief demographics (qualifications, sex and employment). A secondary search was also made for the records of Australian Associate Professors. Data were analysed using summary statistics (means, median and interquartile range) and independent t tests. The sample comprised 150 professors of nursing employed in substantive appointments in 34 Australian universities and one vocational college. We excluded one professor whose substantive appointment appeared to be in the USA and a further vocational college was identified that did not employ at professorial level. Most were female (86%) and most professors held a doctoral qualification (88%), while there was no difference in publication rates between females and males. The number of authored publications ranged from 2 to 436, and the median h-index was 14 (Table 1). There were 33 professors with an h-index of between 10-13, indicative of a good level of research productivity, according to categories suggested by Hack et al. (2010). 25:41 50:69 75:98 25:308 50:677 75:1,124 25:10 50:14 75:19 We further categorized results using the interquartile range, which indicated that 84 professors achieved a high level of performance, being in the top two quartiles. Furthermore, 46 achieved an excellent h-index of 14–18, and 38 achieved an outstanding h-index between 19 and 33. This indicates significant escalation in performance since 2010 (Hack et al., 2010). Publication performance data for Australian associate professors (n = 100) were also collected in a similar fashion. This revealed a lesser publication record with a median of 26 publications (range 1–256), median 176 citations, and median h-index of 7 (range 1–24). Six associates had no h-index. Thus, we suggest the Australian h-index and range for professors compares well with UK measures (mean = 12.66; range 0–39)—also from 2016 (Watson et al., 2017). The current results indicate that most of the Australian nursing professoriate are making a strong contribution to research publication productivity. We recognize, however, that there are limitations in our approach as sampling may not have captured professors in nursing and midwifery who have wider institutional roles and thus are not identified by discipline or represented on school web pages. Furthermore, we were unable to distinguish between types of professorial appointments (teaching and research, research only or teaching focused) or assess research performance relative to appointment type. We also acknowledge that citation rates and the h-index are blunted measures and can, for example, be increased through self-citations. However, Hunt, Jackson, Watson, and Thompson (2011) suggested that this has a negligible effect of around a one-point increase. Furthermore, citations are influenced by career length, they never reduce and thus retired professors maintain their citation rates, while new appointees need time in the chair to build research outputs and citations. This temporal relationship aside, there are a group of professors whose research outputs are negligible. This finding may be an artefact of poor reporting of outputs, although the institutional benefit of ensuring accurate reporting for ERA would suggest that this is not the case. Furthermore, these professors would be included in FTE staff ratios in determining institutional performance. What this does suggest is that some professorial appointments are not research dependent and are based on other capabilities, perhaps relating to teaching and administration or NTRO or other impact measures unrelated to research performance. A broader framework of research performance measures is currently being developed and piloted as a companion to ERA in Australia. This will examine “how universities are translating their research into economic, social and other benefits and encourage greater collaboration between universities, industries and other end-users of research” (Australian Research Council, 2016b). This national assessment follows the UK Research Excellence Framework initiative in highlighting translational impacts of research. The disciplines of nursing and midwifery may well be more aligned to demonstrating research impact in this way. The next challenge for the professoriate will be in evidencing this performance. Australian nursing and midwifery professors are in the top two quartiles of research productivity when measured by the h-index, with “excellent” and “outstanding” research records. Research performance appears to be well within international bounds and reflects well on the research leadership of the Australian professoriate.

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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)0.058
metaresearch head score (Gemma)0.151
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Open science, Research integrity
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.377
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.151
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0760.052
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0060.000
Research integrity0.0010.003
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 head0.684
GPT teacher head0.672
Teacher spread0.012 · 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".

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Citations14
Published2017
Admission routes1
Has abstractyes

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