Open Access (free)

Psychometrics

Designing and road testing new measurement scales

Patrick Callaghan

This chapter will examine the origins of measurement scales in research by considering the science of psychological testing. In particular the chapter provides a brief definition of a measurement scale, outlines why scales are used, examines the design and evaluation of scales, discusses what the responses to scales mean, outlines advantages and limitations of their use, and provides examples of measurement scales developed and used in the EQUIP project and other published mental health research. In recent years, as a response to criticisms that measurement scales are often not patient-oriented, we have seen increasing emphasis placed on the development of Patient Reported Outcomes Measures (PROMs). These tend to be less focussed on symptoms and more on the everyday experiences of people using services. They are much more likely to be designed and developed in collaboration with service users. The EQUIP research project developed a good quality PROM for assessing user and carer involvement in care planning, the first such measure of its kind in mental health.

Open Access (free)

Patrick Callaghan and Penny Bee

Quantitative data analysis makes sense of numerical data. We can use numbers to summarise the experiences or characteristics of a group of participants, for example their average age or the number of symptoms they report. We can also use numbers to look at people’s behaviours, experiences and views. Perhaps most importantly, we can use numbers to look at differences between groups of people or the same group over time. This can help us understand the effect of new treatment or policy initiatives, both in terms of the type of effect (e.g. does a new policy make things better, worse or leave things unchanged?) and the size of its impact (e.g. are any changes big enough to be meaningful or could they have happened just by chance?). This chapter explores some of the different approaches to analysing numerical data, examines the difference between descriptive and inferential statistics, and highlights some of the ways in which you can begin to interpret research data presented as numbers.

Open Access (free)

Edited by: Penny Bee, Helen Brooks, Patrick Callaghan and Karina Lovell

This handbook is written for patients and members of the public who want to understand more about the approaches, methods and language used by health-services researchers. Patient and public involvement (PPI) in research is now a requirement of most major health-research programmes, and this book is designed to equip these individuals with the knowledge and skills necessary for meaningful participation. Edited by award-winning mental-health researchers, the book has been produced in partnership with mental-health-service users and carers with experience of research involvement. It includes personal reflections from these individuals alongside detailed information on quantitative, qualitative and health-economics research methods, and comprehensively covers all the basics needed for large-scale health research projects: systematic reviews; research design and analysis using both qualitative and quantitative approaches; health economics; research ethics; impact and dissemination. This book was developed during a five-year research programme funded by the UK’s National Institute for Health Research (NIHR) called Enhancing the Quality of User Involved Care Planning in Mental Health Services (EQUIP). The handbook clearly outlines research practices, and gives an insight into how public and patient representatives can be involved in them and shape decisions. Each chapter ends with a reflective exercise, and there are also some suggested sources of additional reading. People who get involved in health research as experts from experience now have a textbook to support their research involvement journey.