Evidence map›Paper›PMID 35288922›Full record

ArticleLa Tunisie medicale

Bibliometric profile of the doctoral thesis at the Faculty of Medicine of Sousse (Tunisia).

Ahmed Ben Abdelaziz, Abdelnour Errafei, Sarra Melki, Asma Ben Abdelaziz, Dhekra Chebil, Mohamed Azzaza

Abstract read
In one paragraph

Article in La Tunisie medicale. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. La Tunisie medicale · 2024
    Article
  3. La Tunisie medicale · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ahmed Ben Abdelaziz
Abdelnour Errafei
Sarra Melki
Asma Ben Abdelaziz
Dhekra Chebil
Mohamed Azzaza

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDescribe the bibliometric profile of medical dissertations in Sousse Faculty of Medicine (SOFM) in Tunisia.

methodsThis is a cross-sectional bibliometric study of all dissertations defended from 2001 to 2005. The data were collected through a reading grid applied to the cover page, conclusion, and summary of the thesis. The specialty of the dissertation has been attributed to its first director. Themes were defined by the "essential descriptor", chosen from the descriptors used for the indexing.

resultsThe 670 theses collected, all written in French except one in Arabic, were original, pedagogic or bibliographical works in respectively 93.3%, 6.4%, and 0.3% respectively. "Community and Preventive Medicine" was the discipline that generated the most theses with a proportion of 8.9%. About half (48%) of the dissertations were supervised by two directors. The first director was a University Hospital Professor or an Associate Professor of Conferences, respectively in 34% and 42% of cases. The chairman of the thesis jury belonged to the same specialty as the first director and was from the same department in respectively 54% and 41% of cases. Four "essential descriptors" were frequently cited as indexation of the dissertation: "tumor", "CD-Rom", "trauma", and "diabetes". These dissertations were "clinical" type in 68% of cases, of which around 80% were "case studies".

conclusionThe doctoral dissertation in SOFM was characterized by the orientation towards clinical and epidemiological research and the preference for general medicine and community health themes. It's often recourse to a basic research estimate and its writing in French would be two factors limiting its scientific promotion and its social influence.

Indexed as

BibliometricsMedicineCross-Sectional StudiesFacultyHumansTunisia

Identifiers

PMID35288922
PMCPMC8974409

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.