Advancing Statistical Literacy in Eye Care: A Series for Enhanced Clinical Decision-Making: Part 1: Introduction to Statistical Tools for Eye Care Research

Daniela Oehring, Pedro Miguel Serra

Research output: Contribution to journalReview articlepeer-review

1 Downloads (Pure)

Abstract

Purpose. Advancements in eye and vision care hinge on the
rigorous application of research and the precise interpretation
of clinical data. However, the field of Eye and Vision Research
(EVR) frequently encounters research waste attributed to
methodological flaws and improper statistical analyses, un-
dermining the validity of studies and inefficiently utilising
substantial financial resources. This paper, the first instalment
in the series “Advancing Statistical Literacy in Eye Care: A Se-
ries for Enhanced Clinical Decision-Making,” aims to address
these challenges by enhancing the statistical literacy of eye
care professionals.
Material and Methods. Through a comprehensive narrative
literature review and the generation of simulated clinical
datasets, this study identifies essential statistical concepts,
common pitfalls, and best practices pertinent to EVR. The
literature review used multiple databases, including PubMed,
Scopus, and Web of Science, focusing on peer-reviewed
articles and professional textbooks relevant to statistical
methodologies. Simulated datasets reflecting realistic clin-
ical measurements, such as pupil diameter, refractive error,
central corneal thickness, and intraocular pressure, were
created using Python to illustrate key statistical principles
and their applications.
Results. The paper explores fundamental statistical con-
cepts, including data types (nominal, ordinal, metric), data
preparation techniques, handling missing data and outliers,
and applying descriptive statistics. Additionally, it explores
data distribution characteristics, normality assessment, and
data transformation methods to ensure robust and reliable
statistical analyses. By bridging theoretical knowledge with
practical examples, this instalment seeks to equip eye care
professionals with the tools to critically evaluate research,
integrate evidence-based practices, and contribute mean-
ingfully to the scientific community.
Conclusion. This study establishes a foundational framework
to enhance statistical literacy among eye care professionals
by exploring essential statistical concepts and best practices
in EVR. By addressing common methodological flaws and im-
proper analyses, it aims to reduce research waste and improve
the validity of studies. Ultimately, this initiative is expected
to promote more accurate data interpretation, better clinical
decision-making, and improved patient care in the field of
eye and vision health.
Original languageEnglish
Article number1
Pages (from-to)1
Number of pages20
JournalOptometry & Contact Lenses
Volume5
Issue number1
DOIs
Publication statusPublished - 31 Dec 2024

Keywords

  • Statistical Literacy
  • Eye Care
  • Clinical Decision-Making
  • Eye and Vision Research
  • Descriptive Statistics
  • Data Analysis
  • Research Methodology

Fingerprint

Dive into the research topics of 'Advancing Statistical Literacy in Eye Care: A Series for Enhanced Clinical Decision-Making: Part 1: Introduction to Statistical Tools for Eye Care Research'. Together they form a unique fingerprint.

Cite this