HRW presents on implicit methodologies at BHBIA19.05.2016
In the paper ‘all that glitters is not gold’ Nicola and Gareth get explicit about ‘implicit’ methodologies
At this year’s British Healthcare Business Intelligence Association (BHBIA) conference, the theme was ‘Red Alert’ and the conference took a cautionary tone highlighting key threats facing our industry. Some of these threats are more well-known (mergers & acquisitions, automation, lower research budgets, and greater time pressure) but others are less so. On day 1 HRW took to the stage to outline a critical area of interest that has some lurking threats: implicit methodologies.
In their main-stage paper, Nicola Vyas (Research Director and head of analytics) and Gareth Pritchard (Senior Statistician): outlined the difference between implicit and explicit factors based on decades of scientific research, and mapped this across to healthcare. Setting the scene by clarifying that although explicit factors like safety and efficacy can often be enough for a drug to succeed alone, implicit factors (such as manufacturer, class, endorsements, or marketing materials) can also swing against or in favour of a drug; and in an undifferentiated marketplace can make all of the difference.
They then proceeded to cover 6 different approaches aimed at uncovering the implicit response in market research, covering the approach itself, benefits and limitations of each:
- Implicit Association Test
- Evaluative priming
- Fast associations
- Galvanic Skin Response
- Facial coding
- EEG or MRI scanning
In particular, Nicola and Gareth emphasised how although these methods almost always highlight different results from ‘explicit’ questioning, that the different result doesn’t necessarily mean that you’ve accessed the implicit. There is a danger that because researchers can create a ‘narrative’ around research results and can present results from implicit tests as ‘deeper reality’ when in truth the method or the application has been flawed and the results are spurious.
They showcased results from real research as well as self funded case studies that related implicit methods versus real-life behaviours to identify where the implicit results were best related to the resulting behaviours and critical considerations to apply these methods properly and ensure you’re getting as close as possible to meaningful implicit outputs.
In the end they concluded by saying “We have only just started the journey in understanding implicit attitude” and underlined the importance of using alongside explicit methods and handling with care to ensure you aren’t making critical business decisions based on ‘implicit’ methods alone.