Big Data in Clinical Psychology and Ment (977C8)
Big Data in Clinical Psychology and Mental Health
Module 977C8
Module details for 2025/26.
15 credits
FHEQ Level 7 (Masters)
Module Outline
This module recognises the growing importance of Big Data in informing Clinical Psychology and mental health research and practice. Big Data refers to datasets which are large or complex, which can be interrogated to identify patterns, trends or associations over time. Big Data arises from a wealth of sources including existing research data and open access datasets, medical records, and digital technologies. We'll explore approaches to searching, synthesising and analysing big data. This module will provide insight into Big Data in the context of Clinical Psychology, specifically how it innovates research and clinical practice.
Full Module Description
This module will allow students to develop their understanding of advanced research methods in clinical psychology. Topicsmay include global approaches to mental health research, service user involvement or randomised control trials. Successful students will gain an in-depth understanding of the importance of advanced techniques and ways of working in addressing research questions in clinical psychology and mental health research, and explore the strengths and limitations of various methods and perspectives on research.
Module learning outcomes
Demonstrate an understanding of how big data can be used to enhance our knowledge in mental health research and clinical practice.
Critically evaluate the use of big data in mental health research and clinical practice
Identify the key ethical considerations of big data in mental health research and clinical practice
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 100.00% | |
| Coursework components. Weighted as shown below. | ||
| Report | T2 Week 4 | 30.00% |
| Group Presentation | T2 Week 11 | 20.00% |
| Report | T2 Week 7 | 50.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Spring Semester | Workshop | 2 hours | 11111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Faith Matcham
Convenor, Assess convenor
/profiles/199181
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