The Application of Psychometrics for Measuring Health Outcomes and Quality of Life - Part 1

New dates TBC

There are currently no dates for this course. If you would like to register your interest, please complete this form and we will be in touch when new dates are released. This will not be before September 2024.

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About the course:

The aim of this two-day course is to provide participants with an introduction to psychometrics as applied to health. It will cover the core psychometric and statistical methods used in scale construction and the development of multi-item patient-reported outcome measures (PROMs).

The course will be interactive and practical. Sessions will be delivered using lectures and individual and small group practical exercises using real-world examples.

Feedback from previous attendees:

"The course delivery was excellent. The content was delivered clearly and in an accessible manner."

"Delivery speed and pace was good - as were the tasks alongside to consolidate knowledge learnt."

"Really great course."

Who will benefit from the course?

The course content is aimed at participants with no prior knowledge of psychometrics, or those who wish to refresh and gain more theoretical and practical knowledge in this area.

The course content is set at a basic/intermediate level. It will focus on classical methods of test construction and test of differential item function, but will also provide an introduction to modern psychometric methods such as Rasch models, item response theory and factor analysis for categorical data. It will be relevant to researchers, students, clinicians and other health care professionals and members of the pharmaceutical industry interested in using or developing PROMs.

Learning outcomes:

By the end of this course participants should be able to:

  • identify the key stages involved in scale construction and development
  • understand the qualitative process involved in the development of a PROM and item generation
  • describe the different ways of scoring and scaling a PROM and the theory underpinning these
  • understand exploratory (EFA) and confirmatory (CFA) factor analysis and be able to carry out EFA using SPSS
  • understand what is meant by reliability, validity, and responsiveness and be able to analyse and interpret these using SPSS
  • explore the above concepts using datasets from a range of existing disease-specific and generic PROMs
  • be aware of the use of different software other than SPSS where applicable.

Further learning: Part 2 (Advanced)

An advanced course will immediately follow part 1.  This will cover Rasch models, item response theory, confirmatory factor analysis and factor analysis for categorical data in more detail using MPlus software. 

Course faculty:

SCHARR Outcomes Group

Dates and times

Part 1

Dates and times to be confirmed

Part 2

Dates and times to be confirmed

Whole Course

Dates and times to be confirmed



Current UOS Staff/Students

Current members of University of Sheffield staff and current University of Sheffield students are eligible to book this course at a reduced rate. An active email address is required to book at this reduced rate.   

Please see Booking and payment section for further details.

All fees are VAT exempt.

Booking and payment

Payment can be made via credit / debit card or PayPal.

Non-University of Sheffield applicants - If your employer is paying your fees and they require an invoice, please ensure you have your purchase order details before making your booking. 

Current University of Sheffield staff and students – If you would prefer to be invoiced or to pay via an internal transfer, a purchase order will be required before you make your booking.  Please contact your department administrator or finance team for help with this.

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Course delivery and requirements

Course delivery method TBC


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The content of our courses is reviewed annually to make sure it is up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research, funding changes, professional accreditation requirements, student or employer feedback, outcomes of reviews, and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

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