A comparison of bibliometric indicators in occupational therapy journals published in English

2019 ◽  
Vol 86 (2) ◽  
pp. 125-135 ◽  
Author(s):  
Ted Brown ◽  
Sharon A. Gutman

Background. The use of bibliometrics to evaluate the quality and impact of refereed journals has increased along with access to electronic databases and citation counts. Purpose. This analysis compared and contrasted the range of publication metrics available for English-language occupational therapy journals. Method. Bibliometric data were sourced for 23 English-language occupational therapy journals, including data from the Journal Citation Reports (JCR) 2- and 5-year impact factor, JCR Immediacy Index, Eigenfactor Score, Article Influence Score, Scopus Source Normalized Impact per Paper, SCImago Journal Rank (SJR) score, and ResearchGate journal impact score. H-indexes for journals were also sourced. Findings. The American Journal of Occupational Therapy had the highest publication metrics. SJR-based scores included a larger number of journals, whereas JCR-based metrics were more restrictive in the number of journals included. Implications. Multiple metrics should be used to comprehensively understand occupational therapy journal performance.

2021 ◽  
Vol 6 (4) ◽  
pp. 332-343
Author(s):  
Nawar Muneer J. Algthami ◽  
Nazimah Hussin

We examined the trend of studies on interlocking directorates in family businesses using bibliometric data mined from the Scopus database. Search terms including “family business” and seven other variant terms (including family ownership) plus a wildcard (interlock*) yielded only 17 peer-reviewed papers written in the English Language, published between 1999 and 2020. We used graphical tools to summarise the data. Pearson’s r was employed to analyse the data on three of Scopus’ bibliometric indicators (CiteScore, SCImago Journal Rank, and Source Normalized Impact per Paper) using JASP. The only 17 articles on interlocking directorates in family business poorly compare with the 4,792 articles returned when the wildcard was dropped. Thus, the data show that interlocking directorates in family businesses is a grossly neglected niche in the otherwise steadily maturing field of family business research. The distribution of the scanty literature by country of origin, research purpose pursued, theories employed as explanatory frameworks, the most frequently studied interlocking directorate typologies, and their respective implications were pointed out.


2021 ◽  
pp. 1-22
Author(s):  
Metin Orbay ◽  
Orhan Karamustafaoğlu ◽  
Ruben Miranda

This study analyzes the journal impact factor and related bibliometric indicators in Education and Educational Research (E&ER) category, highlighting the main differences among journal quartiles, using Web of Science (Social Sciences Citation Index, SSCI) as the data source. High impact journals (Q1) publish only slightly more papers than expected, which is different to other areas. The papers published in Q1 journal have greater average citations and lower uncitedness rates compared to other quartiles, although the differences among quartiles are lower than in other areas. The impact factor is only weakly negative correlated (r=-0.184) with the journal self-citation but strongly correlated with the citedness of the median journal paper (r= 0.864). Although this strong correlation exists, the impact factor is still far to be the perfect indicator for expected citations of a paper due to the high skewness of the citations distribution. This skewness was moderately correlated with the citations received by the most cited paper of the journal (r= 0.649) and the number of papers published by the journal (r= 0.484), but no important differences by journal quartiles were observed. In the period 2013–2018, the average journal impact factor in the E&ER has increased largely from 0.908 to 1.638, which is justified by the field growth but also by the increase in international collaboration and the share of papers published in open access. Despite their inherent limitations, the use of impact factors and related indicators is a starting point for introducing the use of bibliometric tools for objective and consistent assessment of researcher.


2021 ◽  
pp. 016555152110597
Author(s):  
Sumeer Gul ◽  
Aasif Ahmad Mir ◽  
Sheikh Shueb ◽  
Nahida Tun Nisa ◽  
Salma Nisar

The manuscript processing timeline, a necessary facet of the publishing process, varies from journal to journal, and its influence on the journal impact needs to be studied. The current research looks into the correlation between the ‘Peer Review Metrics’ (submission to first editorial decision; submission to first post-review decision and submission to accept) and the ‘Journal Impact Data’ (2-year Impact Factor; 5-year Impact Factor; Immediacy Index; Eigenfactor Score and Article Influence Score). The data related to ‘Peer Review Metrics’ (submission to first editorial decision; submission to first post-review decision and submission to accept) and ‘Journal Impact Data’ (2-year Impact Factor; 5-year Impact Factor; Immediacy Index; Eigenfactor Score and Article Influence Score) were downloaded from the ‘Nature Research’ journals website https://www.nature.com/nature-portfolio/about/journal-metrics . Accordingly, correlations were drawn between the ‘Peer Review Metrics’ and the ‘Journal Impact Data’. If the time from ‘submission to first editorial decision’ decreases, the ‘Journal Impact Data’ increases and vice versa. However, an increase or decrease in the time from ‘submission to first editorial decision’ does not affect the ‘Eigenfactor Score’ of the journal and vice versa. An increase or decrease in the time from ‘submission to first post-review decision’ does not affect any ‘Journal Impact Data’ and vice versa. If the time from ‘submission to acceptance’ increases, the ‘Journal Impact Data’ (2-year Impact Factor, 5-year Impact Factor, Immediacy Index and Article Influence Score) also increases, and if the time from ‘submission to acceptance’ decreases, so will the ‘Journal Impact Data’. However, an increase or decrease in the time from ‘submission to acceptance’ does not affect the ‘Eigenfactor Score’ of the journal and vice versa. The study will act as a ready reference tool for the scholars to select the most appropriate submitting platforms for their scholarly endeavours. Furthermore, the performance and evaluative indicators responsible for a journal’s overall research performance can also be understood from a micro-analytical view, which will help the researchers select appropriate journals for their future scholarly submissions. Lengthy publication timelines are a big problem for the researchers because they are not able to get the credit for their research on time. Since the study validates a relationship between the ‘Peer Review Metrics’ and ‘Journal Impact Data’, the findings will be of great help in making an appropriate journal’s choice. The study can be an eye opener for the journal administrators who vocalise a speed-up publication process by enhancing certain areas of publication timeline. The study is the first of its kind that correlates the ‘Peer Review Metrics’ of the journals and the ‘Journal Impact Data’. The study’s findings are limited to the data retrieved from the ‘Nature Research’ journals and cannot be generalised to the full score of journals. The study can be extended across other publishers to generalise the findings. Even the articles’ early access availability concerning ‘Peer Review Metrics’ of the journals and the ‘Journal Impact Data’ can be studied.


Children ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. 1024
Author(s):  
Laura Reche-Olmedo ◽  
Laura Torres-Collado ◽  
Laura María Compañ-Gabucio ◽  
Manuela Garcia-de-la-Hera

Food selectivity is common in children with autism spectrum disorder (ASD). It can be defined as the unwillingness to eat common or new foods, resulting in a lack of variety in the diet or limited food consumption for multiple reasons, such as inflexibility or sensory alterations. We conducted a peer scoping review to describe the interventions that are carried out from occupational therapy (OT) in children with ASD with food selectivity. Two authors independently searched the databases PubMed, Scopus, Web of Science, and EMBASE, as well as the OT journals indexed in Journal Citation Reports. Articles exploring OT interventions in children (≤12 years) with ASD and food selectivity, published in Spanish or English, with experimental design, and with full text available were included. Of the 1445 articles identified, 8 articles met the inclusion criteria. Three main intervention categories were identified: sensory–behavioral, family focused, and other interventions. Most of the interventions from OT were aimed at treating sensory–behavioral aspects. Only three articles described interventions led exclusively by occupational therapists, and the rest were led by a multidisciplinary team. Finally, although these interventions are not exclusive to OT, occupational therapists can participate together with other professionals as an essential component in the treatment of food selectivity in children with ASD.


2008 ◽  
Vol 16 (3-4) ◽  
pp. 85-87
Author(s):  
Stela Filipi-Matutinovic ◽  
Aleksandra Popovic ◽  
Sanja Antonic

Impact factor (IF) of journals is assumed an adequate measure of its importance in the scientific communication of a defined subject. It is important to have in mind that IF is varying very much in time. The range of IF for journals classified in the subject group ONCOLOGY is analyzed for the period 2000-2006. There are only seven of 127 journals in year 2006 which have IF higher than 10. The highest impact in the analyzed period has the journal CA-CANCERJ CLIN, varying from 24,674 to 63,342, but the important fact about that journal is that it publishes very small number of articles annually. The number of journals on the list also changed from 103 in 2000 to 127 in year 2006. Only one journal from the list is published in German and five are multilingual, all the rest are published in English language. Besides US (66), Great Britain (29), Holland (7), and Switzerland (6), all other 11 countries have few journals, mostly situated in the last part of the list ranked by IF. When choosing where to publish their results, scientists should consider all available facts about a journal - from its IF and the way it changes with time, to its openness, availability in libraries and on the WWW, possibility to keep author rights and put the article in an open access repository, where it will get more attention from authors that do not have access to that journal, etc.


2018 ◽  
Vol 13 (1) ◽  
pp. 24-26 ◽  
Author(s):  
Richard Hayman

A Review of: Chang, Y-W. (2017). Comparative study of characteristics of authors between open access and non-open access journals in library and information science. Library & Information Science Research, 39(1), 8-15. http://dx.doi.org/10.1016/j.lisr.2017.01.002   Abstract  Objective – To examine the occupational characteristics and publication habits of library and information science (LIS) authors regarding traditional journals and open access journals. Design – Content analysis. Setting – English language research articles published in open access (OA) journals and non-open access (non-OA) journals from 2008 to 2013 that are indexed in LIS databases. Subjects – The authorship characteristics for 3,472 peer-reviewed articles. Methods – This researcher identified 33 total journals meeting the inclusion criteria by using the LIS categories within 2012 Journal Citation Reports (JCR) to find 13 appropriate non-OA journals, and within the Directory of Open Access Journals (DOAJ) to identify 20 appropriate OA journals. They found 1,665 articles by 3,186 authors published in the non-OA journals, and another 1,807 articles by 3,446 authors within the OA journals. The researcher used author affiliation to determine article authors’ occupations using information included in the articles themselves or by looking for information on the Internet, and excluded articles when occupational information could not be located. Authors were categorized into four occupational categories: Librarians (practitioners), Academics (faculty and researchers), Students (graduate or undergraduate), and Others. Using these categories, the author identified 10 different types of collaborations for co-authored articles. Main Results – This research involves three primary research questions. The first examined the occupational differences between authors publishing in OA journals versus non-OA journals. Academics (faculty and researchers) more commonly published in non-OA journals (58.1%) compared to OA journals (35.6%). The inverse was true for librarian practitioners, who were more likely to publish in OA journals (53.9%) compared to non-OA journals (25.5%). Student authors, a combined category that included both graduate and undergraduate students, published more in non-OA journals (10.1%) versus in OA journals (5.0%). The final category of “other” saw only a slight difference between non-OA (6.3%) and OA (5.5%) publication venues. This second research question explored the difference in the proportion of LIS authors who published in OA and non-OA journals. Overall, authors were more likely to publish in OA journals (72.4%) vs. non-OA (64.3%). Librarians tended to be primary authors in OA journals, while LIS academics tend to be primary authors for articles in non-OA publications. Academics from outside the LIS discipline but contributing to the disciplinary literature were more likely to publish in non-OA journals. Regarding trends over time, this research showed a decrease in the percentage of librarian practitioners and “other” authors publishing in OA journals, while academics and students increased their OA contributions rates during the same period.  Finally, the research explored whether authors formed different types of collaborations when publishing in OA journals as compared to non-OA journals. When examining co-authorship of articles, just over half of all articles published in OA journals (54.4%) and non-OA journals (53.2%) were co-authored. Overall the researcher identified 10 types of collaborative relationships and examined the rates for publishing in OA versus non-OA journals for these relationships. OA journals saw three main relationships, with high levels of collaborations between practitioner librarians (38.6% of collaborations), between librarians and academics (20.5%), and between academics only (18.0%). Non-OA journals saw four main relationships, with collaborations between academics appearing most often (34.1%), along with academic-student collaborations (21.5%), practitioner librarian collaborations (15.5%), and librarian-academic collaborations (13.2%). Conclusion – LIS practitioner-focused research tends to appear more often in open access journals, while academic-focused researcher tends to appear more often in non-OA journals. These trends also appear in research collaborations, with co-authored works involving librarians appearing more often in OA journals, and collaborations that include academics more likely to appear in non-OA journals.


2020 ◽  
Vol 10 (15) ◽  
pp. 5135
Author(s):  
Nuria Caballé-Cervigón ◽  
José L. Castillo-Sequera ◽  
Juan A. Gómez-Pulido ◽  
José M. Gómez-Pulido ◽  
María L. Polo-Luque

Human healthcare is one of the most important topics for society. It tries to find the correct effective and robust disease detection as soon as possible to patients receipt the appropriate cares. Because this detection is often a difficult task, it becomes necessary medicine field searches support from other fields such as statistics and computer science. These disciplines are facing the challenge of exploring new techniques, going beyond the traditional ones. The large number of techniques that are emerging makes it necessary to provide a comprehensive overview that avoids very particular aspects. To this end, we propose a systematic review dealing with the Machine Learning applied to the diagnosis of human diseases. This review focuses on modern techniques related to the development of Machine Learning applied to diagnosis of human diseases in the medical field, in order to discover interesting patterns, making non-trivial predictions and useful in decision-making. In this way, this work can help researchers to discover and, if necessary, determine the applicability of the machine learning techniques in their particular specialties. We provide some examples of the algorithms used in medicine, analysing some trends that are focused on the goal searched, the algorithm used, and the area of applications. We detail the advantages and disadvantages of each technique to help choose the most appropriate in each real-life situation, as several authors have reported. The authors searched Scopus, Journal Citation Reports (JCR), Google Scholar, and MedLine databases from the last decades (from 1980s approximately) up to the present, with English language restrictions, for studies according to the objectives mentioned above. Based on a protocol for data extraction defined and evaluated by all authors using PRISMA methodology, 141 papers were included in this advanced review.


2020 ◽  
pp. 104973152096377
Author(s):  
Monit Cheung ◽  
Patrick Leung

Purpose: With journal publishing being an important task for academicians, this article aims to help faculty and researchers increase their productivity by identifying journals with influential impacts on producing scientific knowledge. Method: Since 2004, the authors compiled and updated a journal list annually for social work faculty to use. This list aims to help faculty and researchers, including doctoral students, identify journals with significant scholarly impacts in social work and related fields for national and international recognition. Results: A total of 221 journals are included in the study, covering 44 social work journals with two indexes reported in the Journal Citation Reports® with Journal Impact Factor® and the h-index. Discussion: This list aims to help scholars find appropriate journals for article submissions. The criteria for the authors to select journals to be included in the publication list are also discussed.


2016 ◽  
Vol 10 (04) ◽  
pp. 527-555
Author(s):  
Lubomir Stanchev

In this article, we examine an algorithm for document clustering using a similarity graph. The graph stores words and common phrases from the English language as nodes and it can be used to compute the degree of semantic similarity between any two phrases. One application of the similarity graph is semantic document clustering, that is, grouping documents based on the meaning of the words in them. Since our algorithm for semantic document clustering relies on multiple parameters, we examine how fine-tuning these values affects the quality of the result. Specifically, we use the Reuters-21578 benchmark, which contains [Formula: see text] newswire stories that are grouped in 82 categories using human judgment. We apply the k-means clustering algorithm to group the documents using a similarity metric that is based on keywords matching and one that uses the similarity graph. We evaluate the results of the clustering algorithms using multiple metrics, such as precision, recall, f-score, entropy, and purity.


Sign in / Sign up

Export Citation Format

Share Document