International Journal of Population Data Science

Top Research Topics at International Journal for Population Data Science?

International Journal for Population Data Science mainly tackles studies in Cohort, Health care, Demography, Government and Mental health. The studies in Cohort featured incorporate elements of Cohort study and Emergency medicine. Health care research featured in the journal incorporates concerns from various other topics such as Emergency department, Family medicine and Medical emergency.

International Journal for Population Data Science addresses concerns in Demography which are intertwined with other disciplines, such as Socioeconomic status, Logistic regression, Pediatrics and Census. Discussions in it are anchored in the subject of Government and the similar topic of Public relations. The research on Public relations tackled can also make contributions to studies in the areas of Corporate governance and Data sharing.

The Mental health study which was featured in it aims to expound on the research in Psychiatry.

• Cohort (17.46%)
• Health care (15.57%)
• Demography (14.58%)

What are the most cited papers published in the journal?

• Consensus Statement on Public Involvement and Engagement with Data-Intensive Health Research. (31 citations)
• Data Centre Profile: The Provincial Health Data Centre of the Western Cape Province, South Africa (25 citations)
• Building the National Database of Health Centred on the Individual: Administrative and Epidemiological Record Linkage - Brazil, 2000-2015. (13 citations)

Research areas of the most cited articles at International Journal for Population Data Science:

The published papers are organized to reinforce research efforts on Record linkage, Health care, Government, Data access and Public engagement. The works on Record linkage tackled in the journal articles bring together disciplines like Linkage (mechanical) and Data science. While work presented in the most cited articles provide substantial information on Health care, it also covers topics in Public health surveillance, Public sector, Corporate governance and Medical emergency.

What topics the last edition of the journal is best known for?

• Law
• Internal medicine
• Statistics

The previous edition focused in particular on these issues:

International Journal for Population Data Science tackles a plethora of topics, such as Health care, Demography, Cohort, Emergency department and Population health. The journal served as a forum through which researchers explored different topics like Health care and Context (language use). International Journal for Population Data Science explores issues in Demography which can be linked to other research areas like Incidence (epidemiology), Socioeconomic status, Disease and Census.

In addition to Cohort research, it aims to explore topics under Social competence, Child development, Record linkage, Special needs and Ethnic group. It explores topics in Emergency department which can be helpful for research in disciplines like Telephone triage, Family medicine, Medical emergency, Attendance and Addiction. Aside from discussions in Indigenous, International Journal for Population Data Science also deals with the subject of Colonialism which intersects with Public relations disciplines.

The most cited articles from the last journal are:

• Linking Sensitive Data: Methods and Techniques for Practical Privacy-Preserving Information Sharing: Synopsis by Kerina Jones (4 citations)
• Reporting of gestational diabetes and other maternal medical conditions: validation of routinely collected hospital data from New South Wales, Australia (2 citations)
• Creation of the first national linked colorectal cancer dataset in Scotland: prospects for future research and a reflection on lessons learned. (1 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in International Journal for Population Data Science (based on the number of publications) are:

• Ashley Akbari (71 papers) published 3 papers at the last edition, 10 less than at the previous edition,
• Ronan A Lyons (61 papers) published 1 paper at the last edition, 11 less than at the previous edition,
• Hude Quan (49 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Ruth Gilbert (37 papers) published 2 papers at the last edition, 2 less than at the previous edition,
• Marni Brownell (37 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in International Journal for Population Data Science (based on the number of publications) are:

• Swansea University (194 papers) published 5 papers at the last edition, 25 less than at the previous edition,
• University of Calgary (100 papers) published 2 papers at the last edition, 5 less than at the previous edition,
• University of Manitoba (94 papers) published 4 papers at the last edition, 19 less than at the previous edition,
• Cardiff University (71 papers) published 5 papers at the last edition, 4 less than at the previous edition,
• University of Edinburgh (67 papers) published 2 papers at the last edition, 7 less than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 4.35% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 45.45% were posted by at least one author from the top 10 institutions publishing in the journal. Another 13.64% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 22.73% of all publications and 18.18% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Prospects and Academic Routes

One of the missing elements that could add depth to this article is a section discussing the career prospects and academic routes related to this field. A prospective student or researcher may want to understand how studying Population Data Science can open doors to fulfilling careers and what might be the academic journey one should take. One of the professions closely related to Population Data Science is being a substance abuse counselor. Studying and analyzing population data can greatly assist in understanding and combating complex public health issues like substance abuse. If you are interested in how a career in Population Data Science can contribute to important societal issues and pave a path for a fulfilling career such as a substance abuse counselor, you can discover more here: How to become a licensed substance abuse counselor in South. In this route, you'll be able to employ the principles of Population Data Science to help address substance abuse on a community or even national level. Your understanding of Cohort studies, Health Care systems, and Demography would be immensely useful in developing effective interventions and policies that address substance abuse. In conclusion, the field of Population Data Science offers interesting and impactful career pathways coupled with research opportunities that can contribute significantly towards addressing various public health problems.