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Plain Language Summaries (PLS)

What are Plain Language Summaries (PLS)?

PLS sit after the academic abstract. They consist of a plain language title (~50 words) and a clear summary of the article using non-technical language, making it accessible to a wider network of readers (~300 words). Many SAGE journals now accept PLS and some have made them mandatory for all submissions with an academic abstract. Make sure to check the journal’s submission guidelines for more information. If you have been invited to review a plain language summary, please refer to our reviewer gateway: How to Review Plain Language Summaries

  • PLS are published as peer-reviewed additions to articles 
  • PLS are written by the article authors and appear underneath the abstract.
  • All abstracts and PLS are open access, so they are available online for anyone to read
  • PLS can be disseminated across social media and shared with relevant organizations to increase awareness amongst those who are interested in the research topic
  • PLS are peer-reviewed alongside the original article by a PLS Reviewer

Writing a PLS

1.    Plan your PLS— 
Think carefully about your intended audience. Consider why your research should matter to them; what details may need to be expanded so that the reader can understand how your research was carried out, and the what the findings mean. It is just as important to consider what does not need to be included, i.e. what is not necessary for the reader to know for them to understand your research, as it is to consider what needs to be included. Be certain to ask yourself “is this necessary information” when writing your PLS. It should be balanced and accurate, avoiding speculation, exaggeration, or personal opinions. Do not assume the readers have prior knowledge on the topic.
2.    Convey the message of your research in plain language— 
Writing a PLS requires a different set of skills than producing a scholarly article. Use short concise sentences; use simplified terms and avoid jargon and acronyms; write in an active voice but avoid superlatives and metaphors if possible. Do not merely swap out jargon for with simplified terms. Your PLS should be tonally distinct from your abstract in order to accurately convey your research in a reader-centric and useful way for non-specialists.  
3.    Present your data—
Avoid complicated statistics or non-essential numbers. Use whole numbers, displayed as absolute numbers, percentages, or natural frequencies (e.g. 1 out of 10 people). Do not expect readers to do any calculations.
4.    Check the quality of your PLS—
Have a member of your target audience read your PLS and explain it back to you. Use their feedback to ensure your reader will have an accurate understanding of your article. 
Please refer to this blog post for further guidance. You can find examples of existing PLS on our patient microsite. Find out if the journal you are submitting to will accept a PLS on their Submission Guidelines page.

When writing a PLS, it is essential to capture the purpose, methods, results, and importance of your research. All PLSs should include the following items listed below. Additionally, we have included prompts to assist you in PLS writing.

1.    Aims and purpose of the research 

  • What is the research question you are exploring? 
  • What is/are your hypothesis(ese) or expectations prior to conducting the study?
  • What do you hope to find out?

2.    Background of the research

  • Why study this specific research question? Why does the research matter?
  • What is the scale of the issue? How broad is the topic, i.e. who is impacted by this research? 

3.    Methods and research design

  • What was your research design and why is it best method to exploring this issue?
  • What are the key variables/participants involved in your research?

4.    Results and importance

  • What did you find out? Was it what you expected or not?
  • Why should we care about these results? What are the implications of these results? 
  • What is the key message you wish to share? 

Example 1

Analysis of the nature and contributory factors of medication safety incidents following hospital discharge using National Reporting and Learning System (NRLS) data from England and Wales: a multi-method study


Introduction: Improving medication safety during transition of care is an international healthcare priority. While existing research reveals that medication-related incidents and associated harms may be common following hospital discharge, there is limited information about their nature and contributory factors at a national level which is crucial to inform improvement strategy. 
Aim: To characterise the nature and contributory factors of medication-related incidents during transition of care from secondary to primary care.
Method: A retrospective analysis of medication incidents reported to the National Reporting and Learning System (NRLS) in England and Wales between 2015 and 2019. Descriptive analysis identified the frequency and nature of incidents and content analysis of free text data, coded using the Patient Safety Research Group (PISA) classification, examined the contributory factors and outcome of incidents.
Results: A total of 1121 medication-related incident reports underwent analysis. Most incidents involved patients over 65 years old (55%, n = 626/1121). More than one in 10 (12.6%, n = 142/1121) incidents were associated with patient harm. The drug monitoring (17%) and administration stages (15%) were associated with a higher proportion of harmful incidents than any other drug use stages. Common medication classes associated with incidents were the cardiovascular (n = 734) and central nervous (n = 273) systems. Among 408 incidents reporting 467 contributory factors, the most common contributory factors were organisation factors (82%, n = 383/467) (mostly related to continuity of care which is the delivery of a seamless service through integration, co-ordination, and the sharing of information between different providers), followed by staff factors (16%, n = 75/467).
Conclusion: Medication incidents after hospital discharge are associated with patient harm. Several targets were identified for future research that could support the development of remedial interventions, including commonly observed medication classes, older adults, increase patient engagement, and improve shared care agreement for medication monitoring post hospital discharge.

Plain language summary

Study using reports about unsafe or substandard care mainly written by healthcare professionals to better understand the type and causes of medication safety problems following hospital discharge

Why was the study done? The safe use of medicines after hospital discharge has been highlighted by the World Health Organization as an important target for improvement in patient care. Yet, the type of medication problems which occur, and their causes are poorly understood across England and Wales, which may hamper our efforts to create ways to improve care as they may not be based on what we know causes the problem in the first place.

What did the researchers do? The research team studied medication safety incident reports collected across England and Wales over a 5-year period to better understand what kind of medication safety problems occur after hospital discharge and why they happen, so we can find ways to prevent them from happening in future.

What did the researchers find? The total number of incident reports studied was 1121, and the majority (n = 626) involved older people. More than one in ten of these incidents caused harm to patients. The most common medications involved in the medication safety incidents were for cardiovascular diseases such as high blood pressure, conditions such as mental illness, pain and neurological conditions (e.g., epilepsy) and other illnesses such as diabetes. The most common causes of these incidents were because of the organisation rules, such as information sharing, followed by staff issues, such as not following protocols, individual mistakes and not having the right skills for the task.

What do the findings mean? This study has identified some important targets that can be a focus of future efforts to improve the safe use of medicines after hospital discharge. These include concentrating attention on medication for the cardiovascular and central nervous systems (e.g., via incorporating them in prescribing safety indicators and pharmaceutical prioritisation tools), staff skill mix (e.g., embedding clinical pharmacist roles at key parts of the care pathway where greatest risk is suspected), and implementation of electronic interventions to improve timely communication of medication and other information between healthcare providers.

Example 2

A dynamic reframing of the social/personal identity dichotomy

For decades, scholars in organizational and social psychology have distinguished between two types of identity: social and personal. To what extent, though, is this dichotomy useful for understanding identities and their dynamics, and might a different approach facilitate deeper insight? Such are the guiding questions of this article. I begin by reviewing framings of the social/personal identity dichotomy in organizational psychology, and tracing its origins and evolution in social psychology. I then evaluate the strengths and limitations of this dichotomy as a tool for understanding identities. In an attempt to retain the dichotomy’s strengths and overcome its limitations, I present a modified conceptualization of the social and personal dimensions of identity, one that defines these dimensions based on psychological experience (not identity content), and treats them as two independent continua (not two levels of a dichotomy, or opposing ends of a continuum) that any given identity varies along across contexts.

Plain language summary

A single person can identify with lots of different aspects of their life: their family, community, job, and hobbies, to name but a few. In the same way it helps to group different items in a shop into sections, it can be helpful to group the different identities available to people into categories. And for a long time, this is what researchers have done: calling certain identities “social identities” if based on things like race and culture, and “personal identities” if based on things like traits and habits. In this paper, I explain that for various reasons, this might not be the most accurate way of mapping identities. Instead of categorizing them based on where they come from, I suggest it’s more helpful to focus on how identities actually make people feel, and how these feelings change from one moment to the next. I also point out that many identities can make someone feel like a unique person and part of a broader group at the same time. For this reason, it’s best to think of the “social” and “personal” parts of an identity not as opposites—but simply different aspects of the same thing.

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