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.
Edited by: Penny Bee, Helen Brooks, Patrick Callaghan and Karina Lovell
Helen Brooks and Penny Bee
Research activity does not finish when data analysis is complete. Once research findings are available, researchers still have obligations to fulfil. These obligations include sharing the findings with different audiences and ensuring maximum impact from the study. Dissemination refers to the active process of communicating research findings in a targeted and personalised way to identified relevant audiences who may be interested in the findings and/or able to benefit from them. This chapter describes some different ways in which research findings can be disseminated in order to increase the impact of research and ensure continued engagement with stakeholders.
Owen Price and Karina Lovell
Quantitative research uses large samples and, as such, the findings of well-conducted studies can often be generalised to larger populations. However, it is important that studies are well-designed to avoid errors in their interpretation and/or the reporting of inaccurate results. Misleading results from quantitative studies can have serious negative implications such as wasting public money on flawed policies and subjecting service users to ineffective or harmful treatments. This chapter explores descriptive and experimental quantitative research designs and examines, through case examples, the difference between cross-sectional, longitudinal and cohort studies. Factors leading to poorly and well-constructed studies are explored, along with a discussion of the key features of well-designed randomised controlled trials, the gold-standard design for testing treatment effectiveness.
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.
Designing and road testing new measurement scales
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.
Owen Price and Lauren Walker
It is of great importance that research projects are informed by sound ethics, properly planned, approved by an independent ethical board and rigorously monitored throughout the duration of the study. This chapter introduces four principles that govern the conduct of ethical research using relevant case examples to bring each principle to life. Topics explored include ‘informed consent’, capacity to provide consent, minimising and managing harm and the fair and equal treatment of study participants.
Andrew C. Grundy
This chapter defines and introduces the different stages of the research process: from identifying a problem, to reviewing the literature; then developing a research question; designing a study; obtaining funding and ethical approval; recruiting participants; collecting and analysing data; and reporting and disseminating findings. This chapter outlines how users of health services, their carers and family members, and other members of the public can be involved in these different research stages, and demonstrates the impact that this involvement can have. Examples of different ways of involving and engaging public members in research studies are drawn from the Enhancing the Quality of User-Involved Care Planning in Mental Health Services (EQUIP) research programme.
Kelly Rushton and Owen Price
A systematic review is a vital part of the research process. It forms a clear and rigorous summary of existing evidence relating to a treatment, presented in a useful and comprehensible way to inform other healthcare professionals’ decision-making. This chapter breaks down each stage of the systematic review process, inviting the reader to critically consider a range of methods and techniques for the inclusion and analysis of studies and their findings.
Helen Brooks, Penny Bee and Anne Rogers
Three main types of qualitative research methods were used within the EQUIP programme of work and these form the focus of this chapter: in-depth interviews, focus groups and observations. Throughout the chapter, the authors look at allied publications resulting from EQUIP as a way of providing examples of real life research to support the description of the methodological approaches provided. This chapter presents the three types of qualitative research methods, discusses the factors that influence the choice of research method, and gives practical advice on how to utilise qualitative research methods.