Evolution and development of methodologies in social and behavioural science research in relation to oral health.
Sarah R BakerLisa J HeatonColman Patrick Joseph McGrathPublished in: Community dentistry and oral epidemiology (2023)
The aim of this introductory paper is to provide an overview of key methodological developments in social and behavioural research in oral health. In the first section, we provide a brief historical perspective on research in the field. In the second section, we outline key methodological issues and introduce the seven papers in the theme. Conceptual models can contextualize research findings and address the 'why' and 'how' instead of 'what' and 'how many'. Many models exist, albeit they need to be evaluated (and adapted) for use in oral health research and in specific settings. The increasing availability of big data can facilitate this with data linkage. Through data linkage, it is possible to explore and understand in a broader capacity the array of factors that influence oral health outcomes and how oral health can influences other factors. With advances in statistical approaches, it is feasible to consider casual inferences and to quantify these effects. There is a need for not only individual efforts to embrace causal inference research but also systematic and structural changes in the field to yield substantial results. The value of qualitative research in co-producing knowledge with and from human participants in addressing 'the how' and 'the why' factors is also key. There have been calls to employ more sophisticated qualitative methods together with mixed methods approaches as ways of helping to address the complex or Wicked Problems in population oral health. In the final section, we outline possible future methodological directions in social and behavioural oral health research including participatory approaches and the development of core outcome sets. Our overriding goal in the paper is to facilitate a critical debate in relation to methodological issues which can be used to improve understanding and generate knowledge in population oral health and that this, in turn, will help inform oral health policy and practices.
Keyphrases
- oral health
- big data
- healthcare
- mental health
- public health
- machine learning
- artificial intelligence
- systematic review
- endothelial cells
- electronic health record
- high resolution
- genome wide
- high throughput
- study protocol
- sensitive detection
- human immunodeficiency virus
- single cell
- gene expression
- deep learning
- antiretroviral therapy
- single molecule
- induced pluripotent stem cells