Communicating in lay language

Lay communication is an important skill for researchers. Examples of lay communication include writing lay summaries in grant applications, reporting to your funders, working with policy makers, staging public engagement events, PPI activities – and of course, speaking to your friends and family about what you do.   

Successful lay communication can be an extremely effective tool in research dissemination if done correctly.  

Where to start?  

  • Who are your audience? What do they already know?  
  • Why are you speaking to them?  
  • What do you want to tell them?  

Building an easily understandable research story   

  • Beginning – What is the background? Why is your research question important?  
  • Middle – What are you doing?  
  • End – How will your research make a difference?  
  • Consider – What are your take-home messages? What can you omit without changing the message?  

Top tips for communicating in plain English   

  • Consider your audience carefully  
  • Speak to colleagues for guidance or examples, and ask for help and/or feedback if you are unsure  
  • Practice with a non-scientist – could be a friend/partner/child/grandparent  
  • Do not reuse work intended for other audiences (unless appropriate) 
  • Do not use acronyms or complicate matters with too much scientific detail  
  • Avoid incomprehensible diagrams and graphs  
  • Do not make assumptions about what the reader will know  

Remember -  those affected by some types of arthritis (Uveitis for example) might have compromised vision and visual impairments. It is important to consider what accessible versions of your work are needed. For advice, visit Core principles for accessible design in print | CharityComms  

An example of lay language 

"Research using smartphones by University of Manchester and funded by Versus Arthritis has shown how people with arthritis can predict how the weather will affect their pain. Data collected over 15 months showed people experienced greater discomfort on humid and windy days, whilst dry days were least likely to be painful. This can help people living with arthritis plan their days around their pain." 

Its technical summary is found here: 

Patients with chronic pain commonly believe their pain is related to the weather. Scientific evidence to support their beliefs is inconclusive, in part due to difficulties in getting a large dataset of patients frequently recording their pain symptoms during a variety of weather conditions. Smartphones allow the opportunity to collect data to overcome these difficulties. Our study Cloudy with a Chance of Pain analysed daily data from 2658 patients collected over a 15-month period. The analysis demonstrated significant yet modest relationships between pain and relative humidity, pressure and wind speed, with correlations remaining even when accounting for mood and physical activity. This research highlights how citizen-science experiments can collect large datasets on real-world populations to address long-standing health questions. These results will act as a starting point for a future system for patients to better manage their health through pain forecasts.