Page 50 - ISMCON souvenir 2021

ISMSCON - 2021

The objective was to compare the utility and effectiveness of PBL versus traditional teaching techniques
(didactic) for Biostatistics.
MATERIALS AND METHODS: The study was conducted in the department of Community Medicine,
Government Medical College, Azamgarh (Uttar Pradesh) from March to November 2019. A total number
of 96 medical students of the final professional part-I were randomly divided into two groups. ‘Group
A’ underwent didactic lecturing whereas “Group B” had problem based learning for identified topics in
Bio-statistics. The teaching material and instructors were the same for both groups. Two weeks after
completion of sessions, students’ assessment was carried out for both groups.
RESULTS: The study demonstrated that the PBL method was a more effective way of teaching learning
statistics compared to didactic lecturing. A significant difference (P < 0.05) was observed between the
mean examination score of Group A (traditional teaching technique) and Group B (PBL). Group B had
higher scores than group A in all assessment heads (Objective, Subjective(Descriptive), and Viva-voce).
PBL was perceived to be a student centric Teaching learning method promoting analytical skills, critical
thinking & overall self directed learning.
CONCLUSION: PBL teaching method was found to be effective in improving the students’ performance
in Statistics in comparison to didactic lecturing(TTT).
Key Words: Bio-statistics, PBL, TTT, Assessment & UG medical students

OS9: EXTENSION OF SYSTEMATIC REVIEW TO BIG DATA

Anitha Cecelia and Neeraj Pandey
Cognizant Technology Solutions
anitha.cecelia@cognizant.com

Key words: Big data, Systematic review
The guidelines and recommendations for practice of Systematic Reviews (SR) are well established.
Biostatisticians can confidently try implementing these learnings in the world of big data to extract
meaningful real-life solutions and new hypothesis for clinical trials

Big data is a term that describes huge volumes of data, which is quite challenging to manage. Big data
is characterized by volume, velocity, and variety, including structured, semi-structured and unstructured
data from different sources and in different sizes, but in all cases, processing implies advanced analytic
techniques. Many secrets of human disease may lurk under the vast ocean of big data, waiting to be
decoded.
Systematic Literature Review (SLR), or Systematic Review, is a method to identify, evaluate and summarize
the state-of-the-art of a specific theme. SLR involve a comprehensive plan and search strategy derived
a priori, with the goal of reducing bias by identifying, appraising, and synthesizing all relevant studies
on a particular topic. Moreover, SLR allows the collection from databases restrictively, which allows an
analysis with lower bias than traditional reviews.

The five steps in systematic review can be adapted for big data. The first step of framing questions for a
review can be done. The second step of identifying relevant work might be a tricky process. The third step
of assessing the quality of studies must be elaborately defined. Most effort must be streamlined towards
step 2 and 3. Fourth step is summarizing the evidence. The fifth step is interpreting the findings.
In systematic review, the aim is to construct a general vision of a specific question and give it a fair
summary of the literature. This approach can be extended to Big data considering it like literature. This
can enable biostatisticians to develop more real-world hypothesis and these findings can serve as
evidence for meaningful sample size calculations for clinical trials.

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