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How to Write a Research Proposal: (with Examples & Templates)

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Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.  

Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.  

This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.  

What is a Research Proposal ?  

A research proposal¹ ,²  can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.   

With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.  

Purpose of Research Proposals  

A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.  

Research proposals can be written for several reasons:³  

• To describe the importance of research in the specific topic  
• Address any potential challenges you may encounter  
• Showcase knowledge in the field and your ability to conduct a study  
• Apply for a role at a research institute  
• Convince a research supervisor or university that your research can satisfy the requirements of a degree program  
• Highlight the importance of your research to organizations that may sponsor your project  
• Identify implications of your project and how it can benefit the audience  

What Goes in a Research Proposal?    

Research proposals should aim to answer the three basic questions—what, why, and how.  

The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.  

The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.  

The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.   

Research Proposal Example  

Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.  

Structure of a Research Proposal  

If you want to know how to make a research proposal impactful, include the following components:¹  

1. Introduction  

This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.  

2. Literature review  

This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.  

3. Objectives  

Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.  

4. Research design and methodology  

Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.  

5. Ethical considerations  

This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.  

6. Budget/funding  

Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.  

7. Appendices  

This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.  

8. Citations  

Important Tips for Writing a Research Proposal  

Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5  

The Planning Stage  

• Manage your time efficiently. Plan to have the draft version ready at least two weeks before your deadline and the final version at least two to three days before the deadline.
• What is the primary objective of your research?  
• Will your research address any existing gap?  
• What is the impact of your proposed research?  
• Do people outside your field find your research applicable in other areas?  
• If your research is unsuccessful, would there still be other useful research outcomes?  

  The Writing Stage  

• Create an outline with main section headings that are typically used.  
• Focus only on writing and getting your points across without worrying about the format of the research proposal , grammar, punctuation, etc. These can be fixed during the subsequent passes. Add details to each section heading you created in the beginning.   
• Ensure your sentences are concise and use plain language. A research proposal usually contains about 2,000 to 4,000 words or four to seven pages.  
• Don’t use too many technical terms and abbreviations assuming that the readers would know them. Define the abbreviations and technical terms.  
• Ensure that the entire content is readable. Avoid using long paragraphs because they affect the continuity in reading. Break them into shorter paragraphs and introduce some white space for readability.  
• Focus on only the major research issues and cite sources accordingly. Don’t include generic information or their sources in the literature review.  
• Proofread your final document to ensure there are no grammatical errors so readers can enjoy a seamless, uninterrupted read.  
• Use academic, scholarly language because it brings formality into a document.  
• Ensure that your title is created using the keywords in the document and is neither too long and specific nor too short and general.  
• Cite all sources appropriately to avoid plagiarism.  
• Make sure that you follow guidelines, if provided. This includes rules as simple as using a specific font or a hyphen or en dash between numerical ranges.  
• Ensure that you’ve answered all questions requested by the evaluating authority.  

Key Takeaways   

Here’s a summary of the main points about research proposals discussed in the previous sections:  

• A research proposal is a document that outlines the details of a proposed study and is created by researchers to submit to evaluators who could be research institutions, universities, faculty, etc.  
• Research proposals are usually about 2,000-4,000 words long, but this depends on the evaluating authority’s guidelines.  
• A good research proposal ensures that you’ve done your background research and assessed the feasibility of the research.  
• Research proposals have the following main sections—introduction, literature review, objectives, methodology, ethical considerations, and budget.  

Frequently Asked Questions  

Q1. How is a research proposal evaluated?  

A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6  

• Significance —Does the research address any important subject or issue, which may or may not be specific to the evaluator or university?  
• Content and design —Is the proposed methodology appropriate to answer the research question? Are the objectives clear and well aligned with the proposed methodology?  
• Sample size and selection —Is the target population or cohort size clearly mentioned? Is the sampling process used to select participants randomized, appropriate, and free of bias?  
• Timing —Are the proposed data collection dates mentioned clearly? Is the project feasible given the specified resources and timeline?  
• Data management and dissemination —Who will have access to the data? What is the plan for data analysis?  

Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?  

A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.  

Q3. How long should a research proposal be?  

A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.  

Q4. What are the common mistakes to avoid in a research proposal ?  

A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7  

• No clear objectives: Objectives should be clear, specific, and measurable for the easy understanding among readers.  
• Incomplete or unconvincing background research: Background research usually includes a review of the current scenario of the particular industry and also a review of the previous literature on the subject. This helps readers understand your reasons for undertaking this research because you identified gaps in the existing research.  
• Overlooking project feasibility: The project scope and estimates should be realistic considering the resources and time available.   
• Neglecting the impact and significance of the study: In a research proposal , readers and evaluators look for the implications or significance of your research and how it contributes to the existing research. This information should always be included.  
• Unstructured format of a research proposal : A well-structured document gives confidence to evaluators that you have read the guidelines carefully and are well organized in your approach, consequently affirming that you will be able to undertake the research as mentioned in your proposal.  
• Ineffective writing style: The language used should be formal and grammatically correct. If required, editors could be consulted, including AI-based tools such as Paperpal , to refine the research proposal structure and language.  

Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.  

This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.  

References  

• Sudheesh K, Duggappa DR, Nethra SS. How to write a research proposal? Indian J Anaesth. 2016;60(9):631-634. Accessed July 15, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037942/  
• Writing research proposals. Harvard College Office of Undergraduate Research and Fellowships. Harvard University. Accessed July 14, 2024. https://uraf.harvard.edu/apply-opportunities/app-components/essays/research-proposals  
• What is a research proposal? Plus how to write one. Indeed website. Accessed July 17, 2024. https://www.indeed.com/career-advice/career-development/research-proposal  
• Research proposal template. University of Rochester Medical Center. Accessed July 16, 2024. https://www.urmc.rochester.edu/MediaLibraries/URMCMedia/pediatrics/research/documents/Research-proposal-Template.pdf  
• Tips for successful proposal writing. Johns Hopkins University. Accessed July 17, 2024. https://research.jhu.edu/wp-content/uploads/2018/09/Tips-for-Successful-Proposal-Writing.pdf  
• Formal review of research proposals. Cornell University. Accessed July 18, 2024. https://irp.dpb.cornell.edu/surveys/survey-assessment-review-group/research-proposals  
• 7 Mistakes you must avoid in your research proposal. Aveksana (via LinkedIn). Accessed July 17, 2024. https://www.linkedin.com/pulse/7-mistakes-you-must-avoid-your-research-proposal-aveksana-cmtwf/  

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STF's and STJ's Tax Agenda for the 2nd Half of 2024

With the mid-year recess ending, Brazil’s Superior Courts are preparing to review certain notable tax thesis in the second half of 2024.

Among the tax cases before the Federal Supreme Court (STF), the following stand out:

• Topic 118: This is a tax thesis derived from the “Thesis of the Century” that challenges the inclusion of the ISS in the PIS and COFINS calculation basis. Extraordinary Appeal No. 592616 has been included in the plenary trial docket of  August 28, 2024  after the cancellation of the request by Justice Luiz Fux in May of this year. The request had been included in the trial session of August 2021, when Reporting Justice Celso de Mello proposed a thesis favorable to the taxpayers, and Justice Dias Toffoli presented a dissenting vote. Justice de Mello’s position is based on the understanding that the ICMS collection technique is different from that of ISS, which is not subject to non-cumulative principle, so the price of the service includes the amount corresponding to municipal tax, and the service provider earns its own revenue, which becomes part of its permanent assets. In the most recent decision, the justices voted 4­–4.
• Theme 1280: This is a thesis about the collection of PIS and COFINS on the revenues of closed supplementary pension entities. Extraordinary Appeal No. 722528 has been included in the virtual plenary session from  August 9, 2024, to August 16, 2024.
• Themes 630 and 684: The virtual plenary session from  August 9, 2024, to August 16, 2024 , will analyze the temporal aspect covered by the thesis regarding the constitutionality of the levy of PIS and COFINS over revenue from movable or immovable assets, when constituting the taxpayer's business activity, considering that the economic result of this operation coincides with the concept of revenue or gross revenue, taken as the sum of revenue arising from the exercise of business activities. Taxpayers have requested that the decisions have "forward" effects so that contributions will only be levied on these revenues once the thesis has been established by the STF.
• Theme 816: Extraordinary Appeal No. 882461 is related to the levy of ISS on toll manufacturing operations and the limitation of the late payment penalty to 20%, and it is also scheduled to be analyzed in the STF’s  August 28, 2024  session. Before the request for review by Justice Alexandre de Moraes, in the virtual plenary, the vote was 6–0, in favor of the taxpayer.

The Superior Court of Justice’s (“STJ”) published August 2024 trial docket includes the following cases:

• Theme 1191: Related to the refund or compensation of amounts overpaid from ICMS-ST depending on proof that the charge was not passed on to third parties, Special Appeal No. 2035550 will be addressed in the STJ’s 1st Session, on the trial docket for  August 14, 2024 .
• AR 6134, 6138, and 6141: The Federal Government filed these suits in an attempt to reverse an STJ decision that recognized the non-levy of IPI on the resale of imported goods . The Federal Government is arguing that the levy is due considering the STJ’s subsequent establishment of Theme 906. The lawsuits will be addressed in the STJ’s 1st Session, on the trial docket for  August 14, 2024 .
• Theme 1245: This is an analysis of the validity of Actions for Reversal of Judgment filed by the Federal Government against decisions in disagreement with the rules for the effects established in the "Thesis of the Century." Special Appeals No. 2054759 and 2066696 will be addressed in the STJ’s 1st Session, on the trial docket for  August 14, 2024 .

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Generative AI

Transforming Qualitative Research: The Power of Generative AI in Report Creation

Crafting detailed reports can often feel like a marathon—not just consuming time but also draining energy and mental clarity. Imagine spending hours sifting through data, then painstakingly piecing together insights only to worry about potential errors creeping in. Many professionals have endured this cycle until generative AI brought a revolutionary change. By harnessing advanced algorithms and natural language processing, generative AI transforms mountains of raw data into coherent, insightful reports within minutes. For instance, platforms like Discuss utilize these technologies to rapidly summarize research findings with precision and clarity. This shift not only accelerates productivity but also boosts confidence in data-driven decisions—delving deeply into why this matter is our next step.

Generative AI revolutionizes report creation by automating repetitive tasks, generating tailored insights, and facilitating the synthesis of complex data. Through its ability to quickly analyze and structure information, generative AI empowers users to craft comprehensive and impactful reports efficiently.

Advantages of Generative AI in Report Creation

Generative AI revolutionizes how reports are generated. Traditionally, crafting reports involves sifting through vast amounts of data, selecting pertinent information, and then weaving it into a coherent narrative. This process can be time-consuming, often taking days or even weeks. However, generative AI turbocharges this process by leveraging natural language processing (NLP) and machine learning algorithms to swiftly analyze extensive datasets, extract valuable insights, and produce comprehensive reports in a fraction of the time it would take a human.

The beauty of generative AI lies in its ability to not only crunch numbers but also craft engaging narratives from the data. It harnesses patterns within the data to form compelling and insightful reports. Business leaders and decision-makers no longer need to wade through mountains of raw data to glean insights; instead, they are presented with clear, concise reports ready for consumption.

For example, platforms like Discuss , powered by generative AI, automatically summarize key findings from research data. These platforms distill complex data sets into actionable insights to quickly convey the essence of the information making comprehensive reports easier than ever. This capability enables businesses to swiftly interpret results and make informed decisions confidently, thereby enhancing market research efforts and facilitating product development.

So, the advantages are crystal clear: generative AI not only saves time but also ensures that reports are consistently accurate, insightful, and easy to understand—a significant asset in today’s fast-paced, data-driven business landscape.

In this age of data abundance and rapid decision-making cycles, the demand for increased efficiency and accuracy has never been more pressing. Let’s now explore how generative AI plays a key role in meeting these critical requirements.

Increased Efficiency and Accuracy

Generative AI has transformed the otherwise time-consuming process of report creation. Traditionally, data analysis and report drafting would take days of exhaustive work, meticulous organization, and extensive scrutiny. However, with the advent of AI-powered tools, this once labor-intensive task is now streamlined to occur within a matter of hours.

Imagine a scenario where an entire team is dedicated to meticulously analyzing data, crunching numbers, and compiling reports. Weeks go by as each team member dissects different sections of the data, cross-references figures, and meticulously combs through multiple drafts before finally producing a comprehensive report. Now, contrast that with generative AI: a tool capable of processing vast amounts of data at rapid speeds, quickly sifting through and interpreting complex datasets to extract key insights.

This level of automation not only reduces the hours invested in manual labor but also accelerates the decision-making process for businesses. With timely access to accurate data insights, organizations can pivot strategies swiftly, accelerating their competitive edge in the market. By empowering teams with more time for strategic thinking and decision-making, generative AI enhances overall organizational agility and responsiveness in ever-evolving market landscapes.

In addition to efficiency gains, generative AI is renowned for its unmatched accuracy in interpreting and presenting data. Human errors are common when it comes to manual data entry and analysis – even the most detail-oriented professionals are susceptible to making mistakes. However, with AI-driven platforms like Discuss , manual errors are significantly minimized through the automated interpretation of complex datasets.

Some may argue that relinquishing control to machines could lead to oversights or misinterpretations that may go unchecked in automated processes. But conversely, the risk of human bias or interpretation errors is far greater when compared to the consistent precision ensured by AI-driven platforms like Discuss’.

By leveraging generative AI’s ability to streamline processes and minimize human error, organizations are embracing higher levels of efficiency, accuracy, and trust in their decision-making efforts – all crucial components for long-term success in today’s rapidly changing business landscape.

Enhancing Business Operations with AI-Generated Reports

Imagine a world where AI-generated reports not only save time but also significantly enhance decision-making. With a profound grasp of your business’s data and trends, these reports are invaluable for driving intelligent, informed decisions.

Time-saving Integration: When we talk about saving time, it’s more than just an hour or two. It’s about allowing employees to focus on strategic tasks that truly propel the business forward. These AI-generated reports bear the burden of handling data, freeing up hours for your team to concentrate their attention where it’s most needed.

This isn’t merely a theory; studies have shown that businesses can save a substantial amount of time by integrating AI in their report generation process. In fact, AI-driven market research tools can generate insights up to 5 times faster than traditional methods.

Improved Decision-Making: Quick and accurate report generation is worth its weight in gold. Timely access to comprehensive data enables businesses to make well-informed decisions promptly. For instance, a company utilizing Discuss’ AI capabilities could swiftly respond to market trends and customer feedback, facilitating agility and quick adjustments to remain competitive in their industry.

Let’s take the example of a retail business needing immediate insight into customer preferences. By harnessing generative AI to rapidly compile and analyze customer feedback, real-time insights into purchasing behaviors are obtained, enabling swift adjustments to satisfy customers promptly.

Immediate Access to Crucial Information: Generative AI-powered reports offer critical insights at record speeds and organize data for better understanding of complex trends and patterns. This ability to quickly process data can mean the difference between staying ahead of the curve or falling behind due to delayed responses arising from slow data processing.

It’s evident that the impact of generative AI on business operations extends beyond time-saving — it fundamentally shapes how decisions are made, empowering companies to adapt quickly and effectively in rapidly changing environments.

The transformative power of AI doesn’t stop there; let’s now explore its capabilities in decision-making and content generation.

AI Capabilities in Decision-Making and Content Generation

When considering decision-making, the traditional image that comes to mind is of individuals analyzing data to find patterns and make choices. However, with generative AI, these processes have become more efficient and creative than ever before. Let’s explore how AI brings personalized insights and enhances creativity in report creation.

Personalized Insights

One of the most significant advantages of using generative AI for report creation is its ability to customize reports based on specific business needs and preferences. Whether it’s tailoring the level of detail, selecting key metrics, or highlighting relevant trends for a particular decision-maker, the AI ensures that the generated reports are highly personalized. This means decision-makers receive only the most crucial information aligned with their specific role and responsibilities within the organization.

For instance, if a senior executive needs a concise overview of financial performance to guide strategic planning, the generative AI can compile a comprehensive yet succinct report with critical KPIs, market trends, and other relevant data points. On the other hand, if a marketing manager requires detailed customer segmentation analysis, the AI can deliver an in-depth report focusing on consumer behavior patterns, regional preferences, and engagement metrics. This level of personalized insight generation not only saves time but also empowers decision-makers to make informed choices aligned with their specific focus areas.

Enhanced Creativity

Generative AI algorithms have redefined content creation by synthesizing information in novel ways that may be overlooked by human analysts. With its advanced natural language processing capabilities, Discuss’ generative AI goes beyond mundane data summaries and provides unique interpretations of complex datasets. By identifying hidden trends and extracting actionable recommendations, the AI adds a layer of creativity to report generation that is both insightful and forward-thinking.

This enhanced creativity manifests in various forms such as identifying unconventional correlations within datasets, uncovering emerging market opportunities, or suggesting innovative strategies based on predictive analysis. The ability of generative AI to connect disparate pieces of information and identify previously unseen patterns enriches the quality and depth of insights provided in reports.

Furthermore, generative AI amplifies creativity by producing cohesive narratives from disjointed datasets, transforming raw numbers into compelling and coherent stories. This storytelling approach not only captures attention but also facilitates better understanding and retention of complex data among decision-makers.

In essence, generative AI brings a new dimension to decision-making by offering tailored insights and fostering creative content generation that transcends traditional analytical boundaries.

As we continue our exploration of the capabilities of AI in report creation, let’s now shift our focus to the impact of advanced language models on business intelligence and strategic decision-making.

Real-World Applications of AI in Report Creation

When it comes to report creation, generative AI has proven to be a game-changer across various industries. Let’s explore some concrete examples of how AI is used to streamline and enhance the process of creating reports.

Case Studies

In retail, generative AI revolutionizes the way sales data is analyzed. Instead of spending hours sifting through sales and customer data manually, AI rapidly and accurately analyzes this information to produce reports highlighting best-selling products and customer preferences. This not only saves time but also provides valuable insights for retailers to optimize their product offerings and marketing strategies. Similarly, in financial services, AI is utilized for precise risk assessments and investment analysis. By leveraging advanced algorithms and predictive modeling, financial institutions can generate comprehensive reports that aid in making strategic and informed decisions. Across various sectors, clients of Discuss , including Edgewell Personal Care , have reported significant improvements in the speed and quality of their market research reports, showcasing the versatile applicability of AI in report creation.

How Generative AI Technology Works

Generative AI might sound complex, but it’s essentially a set of intelligent algorithms working together to comprehend and produce human-like text. At the heart of these algorithms are transformers—they’re like the brains of the operation. The more they practice, the better they become at understanding and generating various types of text, from paragraphs to in-depth reports.

To dive further into this, these models are trained on extensive datasets—think of it as a student preparing for an exam. The more books they read and notes they take, the better they’ll perform on the test. Similarly, AI models are fed vast amounts of information so they can excel at creating reports that are not just detailed but also highly adept at grasping the context.

Practical Implementation

Now, let’s examine how this functions in practical terms. Take a tool like Discuss for example—it enables users to input all kinds of raw data, which the AI then processes to produce detailed summaries, themes, and insights, giving you well-organized and informative reports. It’s akin to having an incredibly astute assistant who sifts through all the data and compiles everything you need in a structured and clear report. Moreover, as new data keeps coming in, the AI learns and becomes even more proficient at creating reports that precisely align with your requirements.

This adaptive learning capability is genuinely potent because it signifies that the generated reports are incessantly growing and enhancing, much like your business does.

By transforming raw data into clear and meaningful reports—and continually becoming more intelligent—generative AI has revolutionized the process of producing precise and impactful reports for businesses.

The remarkable capability of generative AI technology to learn and adapt is reshaping how businesses analyze data, creating unprecedented opportunities for innovation and efficiency. Explore how generative AI can transform your approach to report creation with Discuss .

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Virtually any amount increased the risk for cancer, and there were no heart benefits, the researchers reported.

By Roni Caryn Rabin

Even light drinking was associated with an increase in cancer deaths among older adults in Britain, researchers reported on Monday in a large study. But the risk was accentuated primarily in those who had existing health problems or who lived in low-income areas.

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• Open access
• Published: 12 August 2024

Patient responsiveness as a safewards fidelity indicator: a qualitative interview study on an acute psychiatric in-patient ward

• Veikko Pelto-Piri 1 ,
• Lars Kjellin 1 ,
• Gabriella Backman 2 ,
• Karoline Carlsson 3 &
• Anna Björkdahl 4  

BMC Health Services Research volume  24 , Article number:  922 ( 2024 ) Cite this article

Metrics details

The Safewards model aims to reduce conflict and use of containment on psychiatric wards. To evaluate the implementation of Safewards and understand why it is effective in some settings but not in others, it is important to assess the level of implementation fidelity. To do this, the Safewards Fidelity Checklist (SFC) is often used, which focuses on objective visual observations of interventions but does not include patient responsiveness. The latter is a key indicator of implementation fidelity and includes engagement, relevance, acceptability and usefulness. The aim of the present study was to investigate the fidelity of Safewards implementation on an acute psychiatric ward from the perspective of patient responsiveness.

The study was conducted on a ward for patients with mainly affective disorders. To assess the general level of fidelity the SFC was used together with a detailed ward walkthrough. Ten patients were interviewed with a focus on patient responsiveness to each of the seven interventions implemented on the ward. Data were analysed using qualitative descriptive analysis.

The findings indicate high implementation fidelity, which was reflected in the SFC assessment, walkthrough and patient responsiveness. Patients gave examples of improvements that had happened over time or of the ward being better than other wards. They felt respected, less alone, hopeful and safe. They also described supporting fellow patients and taking responsibility for the ward climate. However, some patients were unfamiliar with a ward where so much communication was expected. Several suggestions were made about improving Safewards.

Conclusions

This study confirms previous research that patient responsiveness is an important factor for achieving fidelity in a prevention programme. The patients’ descriptions of the acceptability, relevance and usefulness of the specific interventions reflected to a high degree the objective visual observations made by means of the SFC and ward walkthrough. Patient engagement was demonstrated by several suggestions about how to adapt the interventions. There is potential to obtain valuable input from patients when adapting Safewards in practice. This study also presents many examples of practical work with these interventions and the effects it can have on patients’ experiences of care.

Peer Review reports

The use of coercion in European psychiatric and mental health services has been extensively criticized for violating the UN General Assembly agreement on the Convention on the Rights of Persons with Disabilities and the Convention Against Torture and Other Cruel, Inhuman or Degrading Treatment or Punishment [ 1 , 2 , 3 ]. An implication of these conventions is that states should actively work towards finding ways to minimize or even abolish policies that allow coercive treatment and other coercive measures within the psychiatric services. However, in Sweden as in most Western countries, legislation still enables the use of coercive measures when certain criteria are deemed to be present [ 4 ]. Although often controversial, the aim of these pieces of legislation is to prevent harm, initiate necessary treatment and allow the patient to recover and accept continuous care on a voluntary basis.

Patients have often experienced psychiatric wards as unsafe places with shortcomings in therapeutic relationships and strict but unpredictable rules [ 5 , 6 , 7 ]. Patients have also reported being exposed to harm and re-traumatization during care episodes, which jeopardizes the recovery process [ 6 , 8 , 9 , 10 ]. For staff, working in an environment that includes violence and coercive measures can cause emotional and psychological problems as well as an increased risk of long-term sick leave [ 11 , 12 ]. There is a relationship between the use of coercive measures and violence in psychiatric services that has been suggested to create a negative spiral of risk and incident escalation in which patient aggression may lead to restrictive practices, which in turn may trigger further patient aggression [ 13 ]. However, the incidence of violence and coercive measures can be prevented by, for example, the use of therapeutic relationship strategies and improving the ward culture [ 14 ].

Historically, Sweden has employed more coercive measures in psychiatric care compared to many other European countries [ 15 ]. The Swedish government has faced criticism from the Committee of the Convention on the Rights of Persons with Disabilities for its excessive use of coercive measures [ 16 ]. During recent decades, several nationwide projects aimed at reducing violence and restrictive practices in inpatient psychiatry have been initiated and funded by the Swedish government. Nevertheless, according to national registers, coercive measures such as the use of seclusion, restraint and involuntary medication have not been reduced [ 17 ]. Internationally, various promising alternative interventions have been developed for psychiatric in-patient services. Most countries do not have any mandatory legislation or policies to ensure that these interventions are implemented, and they are rarely evaluated on a large scale [ 18 , 19 ]. Currently, one of the best known hospital-based programmes is the Safewards model [ 13 , 18 ]. Safewards, which includes ten interventions, focuses on preventing conflict and the use of containment (Table  1 ) [ 5 , 20 , 21 ]. However, implementation is complex, as in order to change the service culture, the model comprises several parallel interventions involving both staff and patients [ 14 , 18 , 19 ].

Patient participation is an important part of the Safewards implementation, preferably in the form of a continuous co-creation process between staff and patients [ 22 , 23 , 24 ]. In cases where Safewards was successfully implemented, patients reported a stronger sense of community, safety and calm [ 5 , 25 ]. They also described feeling less isolated, more hopeful and positive about their stay in addition to experiencing increased respect on the part of staff. In a study by Kennedy et al. [ 26 ], the implementation and possible improvement of the ten Safewards interventions were discussed from the perspective of consumers. It was concluded that although the model does not address important issues regarding the nature of involuntary treatment, the interventions may minimize harm and increase safety. Staff perceptions of Safewards have varied, from high and enthusiastic acceptance along with the belief that the model has a positive impact on conflict and containment, to poor participation and negative perceptions [ 21 ]. Staff working with patients who have intellectual disabilities reported positive experiences, such as fewer violent incidents and feeling safer [ 27 ]. They also described an increased sense of community with patients and were more positive about being part of the ward community. Several studies, including a randomized controlled trial, demonstrated a reduced incidence of violence and coercive measures after implementation of Safewards, while others did not show any significant effects [ 28 ]. In some studies, the extent of the reduction was attributed to the high fidelity of the implementation, which means that to a great degree the interventions were delivered by staff as intended [ 29 , 30 , 31 ].

Implementation fidelity is often measured to evaluate outcomes and better understand why an intervention is successful or unsuccessful [ 32 ]. It can be defined as to what degree an intervention or program is implemented as intended by those who developed it [ 32 ]. If an intervention lacks the expected outcomes, an evaluation of fidelity can indicate whether this is due to poor implementation or an inadequate intervention. In a complex intervention such as Safewards, the level of implementation fidelity can be influenced by many factors. Therefore, it is often recommended that those involved in implementation research and clinical development should collaborate with staff and patients within the healthcare system [ 33 ]. In a conceptual framework, Carroll [ 34 ] suggests that when evaluating implementation fidelity the focus should be on adherence. Adherence refers to the implementation adherence to the content, coverage, dose and duration of the intervention. Four potential modifiers will have an impact on the level of adherence: intervention complexity, facilitation strategies, quality of delivery, and participant responsiveness and capacity. The four adherence modifiers influence each other and there is evidence that for example quality of delivery is associated with participant responsiveness [ 35 ]. Participant responsiveness includes both those delivering and receiving the intervention and, in a health care context, refers to the willingness and ability of staff and patients to be involved and engaged. High patient responsiveness is achieved when patients are positive about and actively involved in the intervention. Furthermore, it entails patients’ positive perceptions of the acceptability, relevance, usefulness and outcomes of the intervention [ 32 ]. Given that many Safewards interventions require active patient participation, patient responsiveness is a crucial modifier for adherence and, consequently, the evaluation of implementation fidelity. For example, for Safewards to be implemented as intended and reach expected positive outcomes, the intervention ‘Discharge messages’ requires patients to write messages to other patients, ‘Mutual help meetings’ requires patients to actively participate and thank other patients, and ‘Know each other’ requires patients to write something about their personal hobbies and interests. At the same time, patient responsiveness and the quality of staff delivery of the interventions are mutually reinforcing adherence modifiers, in which high quality delivery by staff enhances patient responsiveness, and engaged patients contribute to better delivery quality by staff [ 36 , 37 ].

The implementation fidelity of Safewards is often assessed by using the Safewards Fidelity Checklist (SFC), an instrument that mainly examines the number of interventions implemented by staff. In addition, there is an open text box in the SFC used for documenting the most significant staff responses to Safewards [ 38 ]. However, concerns have been raised about the SFC’s focus on objective and visible implementation evidence [ 29 , 39 , 40 ]. Moreover, the SFC does not include aspects of patient responsiveness, or patients’ perceptions of how Safewards interventions are implemented by staff [ 13 , 32 ]. This may reflect a general lack of the patient perspective in the research on Safewards [ 21 ]. In one study however, the open text box in the SFC was modified to collect responses from both staff and patients [ 25 ]. Fidelity evaluation development is vital for the Safewards evidence base, as high-quality fidelity assessments affect study validity and can provide a deeper understanding of why Safewards is effective or not [ 40 ]. In this development, it is necessary to include patient responsiveness as an important fidelity modifier. The aim of the present study was therefore to investigate the Safewards implementation fidelity on an acute psychiatric ward from the perspective of patient responsiveness.

Setting and sample

The study was conducted in a 13-bed acute psychiatric inpatient ward, mainly for patients with affective disorders. The ward was chosen because the ward manager and team there had reported the successful implementation of the Safewards intervention. Coercive measures decreased by 75% and short-term sick leave among staff by 30%. Common diagnoses/syndromes were mood disorders, anxiety disorders, crises, personality disorders and neuropsychiatric conditions. The duration of care episodes averaged 11 days. The professional categories at the ward included specialized psychiatric nurses, registered nurses, assistant nurses, a psychiatrist, an assistant physician and a social worker. On the ward, patients received acute psychiatric care including psychiatric nursing, medical treatment, one-to-one support, psychoeducation and basic Dialectical Behavioral Therapy. Patients could also participate in activities such as walks, games and art. The psychiatric care at the ward focused on empowering people to take responsibility for their own abilities to deal with difficulties. Safewards supported the nursing staff in these efforts. The care was also moving towards a more person-centred approach during the implementation of Safewards.The ward manager was highly committed to the implementation of Safewards, and the team saw themselves as stable with positive group dynamics. At the time of our data collection they had implemented eight of the ten Safewards interventions over an almost three-year period in a co-creation process where they were divided into five groups. Each group was responsible for the implementation of two interventions.

Participants for the interviews were recruited by KC and GB, registered nurses at the ward at the time of the interviews and master students of psychiatric nursing, to become specialized psychiatric nurses. They wrote a master’s thesis in which they inductively analysed the interviews from a nursing perspective. The inclusion criteria were that the patient could speak Swedish, was able to provide informed consent to participate and should have been in the ward for at least five days in order to have experience of the care and interventions. First, general information about the study was presented by KC and GB to patients at a Mutual help meeting. No patient signed up for an interview after the information. The interviewers then recruited patients face-to-face at the ward after consultation with the ward manager to assess that the patients were capable to give their informed consent. Patients were provided with both verbal and written information regarding the study. This included details about the voluntary nature of participation, the purpose of the study, and the intended use of the data. Specifically, it was explained that the data would be utilized by students (the interviewers) for their master’s theses as well as by researchers for publications. The face-to-face recruitment resulted in ten people agreeing to participate, while three declined. No questions were posed about the reason for declining. We interviewed ten patients, one man and nine women, of whom four were aged 30 years or younger, four were between 31 and 40 and two 61–70 years.

Data collection

KC and GB collected the data. As a first step, a modified version of the SFC (see Supplementary Material 1 ) [ 38 ] was used in order to assess the general implementation fidelity of Safewards on the ward. The SFC was filled in along with a detailed ward walkthrough observation of visible signs of Safewards, which were documented and commented on separately.

Subsequently, patient interviews were conducted over a 20-day period based on an interview guide that contained questions about seven of the ten interventions. The Positive words intervention was excluded due to the focus on the quality of staff handover content, which cannot be observed by patients.

The Soft words and Reassurance interventions are not reported in this article because they were not implemented at the time of the interviews. The patients were asked about their observations of manifest signs of Safewards as well as quality aspects of the interventions. Each intervention was briefly explained, and the participants were asked: (1) what they thought of the intervention, (2) about positive and negative experiences and (3) how the intervention could be improved (see Supplementary Material 2 ). The interviewers were instructed to use prompting, for example asking the patient to clarify what they meant by a statement, to obtain in-depth information. The interview guide functioned as intended at the first interview and no changes were made to it.

Seven of the patients were interviewed on the ward during their stay, and three who had been discharged agreed to be interviewed in a separate room next to the ward. The interviews, which lasted 26–85 min, were audio recorded and transcribed verbatim. They were performed in a single session, seven interviews were done by two interviewers and three interviews with only one interviewer present. Field notes were not taken as it was anticipated that the interviewers, who were actively working in the environment, would find it challenging to document these observations. The transcripts were not returned to the participants for comment. After ten interviews, patients gave similar information about how they perceived Safewards and enough of various kinds of events where Safewards had played a role.

Analysis and interpretation

The Safewards interventions were used as categories. Within these categories, a qualitative descriptive text was written about the SFC and the walkthrough, while a qualitative descriptive analysis of the interview content was conducted [ 41 , 42 , 43 ]. We used the qualitative descriptive analysis method, as we aimed to obtain a straightforward qualitative description of patients’ responsiveness to the Safewards interventions [ 42 ]. The analysis started with GB and VP reading the transcripts to gain an overview of the content of the interviews. GB summarized every patient’s view of the seven interventions based on the interview guide. VP merged these summaries into a single summary, which was discussed with AB and LK. VP read through all the interviews to add more relevant information and suitable quotations to the result section. All co-authors commented on the results section and which quotations were the most relevant. The names in the quotations were changed and the pronoun ”she” was used for all participants to protect their identity. The participants were not asked to provide feedback on the findings.

In general, the findings indicated that the patients had noted the implementation of Safewards and were positive about it. Some gave examples of improvements that had happened over time or of the ward being better than other wards. They expressed that staff now had a more positive attitude when interacting with patients. The ward and staff were perceived as welcoming, familiar, supportive and felt safer. The patients felt respected, less alone and more hopeful. All these perceptions seemed to contribute to the patients’ experiences of the ward as a safe environment. They also expressed taking responsibility for other patients and the ward climate in general.

In this section, we first provide a brief description of the Safewards implementation fidelity as revealed by the SFC and the walkthrough. Thereafter we present the patients’ responsiveness to Safewards. A summary of the findings is presented in Table 2 .

Discharge messages

Sfc/walkthrough.

There was a big tree painted on the wall with discharge messages in the corridor opposite the ward entrance. Patients were asked to leave a message in connection with their discharge. At the time of the fidelity check, there were 27 discharge messages and a brochure with information about the intervention.

Patient responsiveness

It was great, it’s the first thing you [as a patient] see, there were so many beautiful leaves, just being able to read it when you’re standing outside the nurses’ station waiting …. That was also something that I noticed right away when I walked in, literally the first thing… Pat. 7.

Most patients considered the location of the discharge tree to be appropriate, that it was aesthetically beautiful, and that they took the time to read the messages. A patient described how she “naturally” drawn towards the tree because of its location and often stood there waiting for medicine or staff. The tree gave comfort during bad days, as it was hopeful and invigorating to read that others had received help from staff and recovered, which created a sense of safety. It also sparked a curiosity about previous patients: What happened after discharge? Some gained a new perspective on how to approach their problems, while others just learned to accept the situation, trusting that it will improve and letting their recovery take time. It was important for patients that the messages were positive and encouraging. Sometimes they could think long and hard about what they wanted to convey when it was time for discharge.

Some felt that the environment around the discharge tree was often too noisy, a lot of people passing by all the time, which made it difficult to absorb the messages. One patient thought that her fellow patients should thank themselves and not the staff.

Know each other

There were two folders in the common area of the ward presenting each of the 23 staff members on a separate page. Patients had a small whiteboard with pre-defined suggested categories outside their rooms where they could write about themselves. However, there were no written know-each-other messages from patients at the time of the walkthrough. The reason for using a board instead of pages in a folder was that for most patients the care episodes were relatively short.

It gave more hope in a way …. That you [staff members] really show who you are and that you are passionate about your work. Yes, I really felt like I had come to the right ward when I read your folder [with presentations]. Pat. 3.

It felt welcoming that staff had made an effort to create the folder with information about their interests and other personal details. Knowing something about the staff members who were working at the ward contributed to safety. It also facilitated daily communication and made it easier to ask for help. The fact that the presentations were always available meant that patients could learn about staff members and fellow patients at their own pace. Some had read the staff presentations several times. The intervention reduced the power difference between staff and patients because staff members became persons and not “just their nursing scrubs”. A patient reported feeling touched by the fact that staff presented themselves. It felt familiar and positive.

At the time of the interviews, some patients had written about themselves on the whiteboard outside their room. They thought that it was especially fun and interesting to read about fellow patients. A patient who presented herself on the whiteboard felt respected and appreciated reading others’ presentations. Even those who wanted “to be a little anonymous” or did not consider it necessary to write about themselves appreciated the possibility. They thought it was good that patients could write about how they, for example, wanted to be treated by others. Some patients considered that it was difficult to expose oneself in a presentation when feeling unwell and could be reluctant to present themselves “fully” because of the risk of prejudice.

At times it felt a little less safe to be able to do it, there can be a lot of prejudice about me because …. I do this and I do that. I sometimes felt a little …. tingle in my stomach maybe, but then I thought – No, to hell with it, I can be myself and it may seem very crazy and all. I care less about that because I’m here to help as well, to improve this system. Pat. 6.

There were several similar statements where patients expressed that they wanted to take responsibility for the ward climate and safety. Patients had ideas about how to improve the intervention, for example by providing more information about the intervention and its purpose, that it had too many pre-defined suggested categories to choose from and that the folders should be updated with new information about and pictures of those staff members who were not yet included in the presentations. A patient thought that the staff only revealed “their good side” and should also inform about their weaknesses.

Clear mutual expectations

There were several posters in the ward pertaining to Clear mutual expectations. Before the implementation started, interviews were conducted by a Peer support person focusing on this topic with patients.

Patients had seen the poster and been informed about the intervention. They expressed that the expectations promoted mutual respect and taking responsibility for the ward environment without aggressive behaviour. Several patients mentioned that they could go to the poster when they lacked information and could also help their fellow patients to adhere to rules so as not to annoy staff. Some were of the opinion that everyone must take responsibility and that some people may need to be reminded of it. They thought that the mutual expectations contributed to a good and safe environment and appreciated that the staff had made an effort to create the expectations, which gave them hope.

I have both good and bad experiences of inpatient care and care in general, but it was hopeful because it has been difficult to be cared for as an inpatient, but this was like physical evidence that you [staff members] actively work to make it better, somehow. And it gave me hope …., it made me a bit calmer that “Okay, maybe this time it can be different” so …. to make changes in health care is quite (laughter) difficult and big, so just managing to get the posters printed and put them up means a hell of work. So .... that was helpful.

Patients also pointed out that it can be difficult to have clear mutual expectations in an environment where people are so sick, but that it is a good strategy to encourage everyone to take responsibility. The intervention reduced the power difference between staff members and patients.

Patients made some suggestions for improvement, for example keeping promises, as staff members sometimes made promises that were either fulfilled late or not at all. Other suggestions were using a different font to make the poster easier to read and making patients aware of the intervention by providing more information about it at the Mutual help meetings. 

You [staff] could show it differently, not just text. I don’t know what it could be but something, pictures, photographs …. Yes, a picture and text I think, because a picture can be associated with [something] and I will be more likely to remember it. Pat. 10.

Mutual help meetings

The staff arranged Mutual help meetings every weekday morning after breakfast in the dining room. There was a folder for staff use in which the structure of the meetings was described. Patient information was also displayed prominently in the ward.

A number of patients found the morning meetings beneficial and helpful, as they provided an overview of the day. At the meeting, everyone was given the opportunity to talk about issues that felt difficult but also to express positive feelings. It was a good forum for asking about something or gaining information about what would happen during the day. The opportunity to express gratitude at the meeting was considered a good start to the day.

…and it was great that the staff brought up, for example, “It was really hard to get to work because it was raining …. but I’m grateful that I’m here now”. And it felt great that they are grateful that they are here …. And I thought that was among the best things I experienced in the ward. Pat. 6.

The fact that the staff dared to bring up subjects that they thought were problematic and what they were grateful for made it easier for patients to become more communicative. It was difficult for patients to know what was appropriate and how much to open up and communicate about their personal life. Some of them stated that they wished to remain anonymous during their stay in the ward. Talking to other patients made it easier to be open, which could be especially difficult on days when they felt very unwell. They reported that they sat relatively quietly and just listened at the first few meetings, but later became more communicative. Patients thought that the meetings motivated them and made them feel less alone. It felt positive that everyone wished each other a good day. These meetings helped to create a social community in the ward.

Yes, often it is …. you [the chair, a staff member] present which day it is and the date and who has a name day …. And then there is a round where everyone gets to express what they think, that they wish everyone a good day, that they are grateful to be here …. or you can say that you would like help to withdraw money. And then it’s written down and …. it feels good that everyone wishes each other a good day, I think, it’s a nice little start to the day. Pat. 9.

Having the meeting early in the morning was experienced as both positive and negative. It was nice to sit and have breakfast in peace and quiet, hence attending the meeting was an effort but at the same time it was positive to obtain information about the day. As a patient, there was a risk of feeling pressurized into participating when the meeting started immediately after breakfast in the common dining room. There were patients who often overslept and therefore did not attend many meetings.

Patients had suggestions for improvements. They noted that each chairperson structured the meeting differently, which was frustrating. They wanted the structure of the meetings to remain more or less the same. Hearing about other people’s problems could be negative for their own well-being and therefore they stated that the meetings should mainly focus on positive aspects.

Bad news mitigation

One of the headings in the digital agenda for handover reports was Bad news mitigation aimed at routinely raising the question of whether any patients had received or might receive bad news. A laminated information sheet about how patients who had received bad news should be dealt with was on the table in the conference room where the handovers took place. There was also a box of “treats”, such as tea and biscuits, which could be used during Bad news mitigation meetings with patients.

Some patients reported receiving bad news that was difficult to handle, but that they had received good support from staff.

Well, when I was hospitalized last time, my grandfather was very, very ill and …. Then I got support from the staff when, when I was informed about that …. Yes, we sat and talked and so …. Yes, it was good. Pat. 10.

There were also patients who did not receive any bad news themselves but who observed others having done so. They stated that their fellow patients had received compassionate and empathetic care. Patients experienced that staff noticed when they needed to talk about something or required support in a tricky situation. Staff support made them feel safe, more communicative and less lonely.

I experienced that you [staff members] are present when, for instance, you speak in a way that the person really understands and that you are really there, also some minutes afterwards, so that the person calms down and really understands what has happened and you speak in a calm voice. Pat. 2.

According to the patients, an example of bad news was that relatives were not welcome at the ward during the Covid-19 pandemic. It was difficult for staff to explain why friends and family were not allowed to visit patients. In such a case, it would have been helpful to receive accurate information about the situation; otherwise, patients might think that it was their own fault and would develop “dark thoughts”.

Calm down methods

The ward had a sensory room and a calm down cabinet, with many different sensory items and equipment that could be used for calming purposes, like hug chair, weight vest and blanket, ice pack and a Star Projector. In addition, there was an “emotion-map” on the wall containing a description of emotions and their functions as well as suggestions for calming strategies that could be used to cope with various emotions.

I was stressed and then I was given a heated cushion, because it could help me handle anxiety, and it did, I never thought of that myself before. Pat. 5.

The calm down methods were appreciated by patients, many of whom perceived that the intervention worked well and created a feeling of safety. Patients expressed that they had been helped by the sensory room, a quiet place to calm down in, or by items from the calm down cabinet. They also reported that staff helped them to find strategies to deal with anxiety and emotions. Some patients also noticed that staff members helped fellow patients to calm down. They found it positive that staff noticed patients who were having a hard time and tried to find ways to help them calm down.

Patients considered the activities organized in the ward, including playing games, going for walks together and music quizzes, as very helpful ways to handle difficult emotions. The activities made patients feel seen, heard, and less alone in difficult situations. Patients described working on their crisis plan together with staff. Even before admission some had several strategies for independently managing to calm challenging emotions. They felt that staff respected them, listened, reminded them about their strategies and provided support for finding new strategies. In some situations, patients could find receiving help difficult and frustrating, although it was often perceived as valuable. Below is a quotation from a patient who received help from staff to write a list of strategies she could use when needing to calm down.

I thought it was very good that when I had a very severe anxiety attack, someone asked “Okay, but where are you on your list?” …. I had a copy by my bed so I could check it …. and it was very nice that, for instance, I was allowed to go out and smoke even though it wasn’t smoking time because a cigarette calms me down, like, that someone took the time to do it. I think that I was listened to and the staff reminded me of skills that I know work for me. Pat. 7.

One patient did not seem to know about the intervention. She said that patients must not show emotions in psychiatry because of the risk of being medicated, instead of being offered a chat or a hug. The need for social distancing during the pandemic was difficult for those who liked getting a hug. This patient used her own strategies without talking to staff. Another patient had sometimes wished to receive support more quickly but said that she understood that staff had a lot to do.

A Talk Down poster was visible to staff. Every two weeks staff members practised the talk down intervention in training sessions with role play.

So, I noticed that staff knew exactly what to do when it happened, … trying to punch or break free from a hold, when everyone joins up and helps, talks calmly and methodically to the person and then someone tells everyone else to go to their rooms while you [staff member] help to calm that person down. Pat. 2.

While the participants did not report being involved in a de-escalation process, they described how staff members managed aggressive behaviour from patients as well as an accident. Staff members did so calmly and efficiently to ensure that the situation would not escalate. Patients also observed that staff sometimes restricted patients in order to prevent them from creating trouble for other patients.

So, there are many situations all the time. It’s good that you [staff] try to be as flexible as possible so that it doesn’t create chain reactions …. That we kind of feel worse as a result. For instance, if someone has to be put in restraints, that it is not …. It may not be very dignified and therefore better that others don’t see it. Pat. 10.

The patients’ care episodes differed, for some it was chaotic, and they had seen events that were difficult or unpleasant, which created a feeling of lack of safety. Even if they themselves could handle their emotions, they found it difficult to witness when others felt unwell. Some patients described that the ward was calm during their own care episode, while others only experienced a single situation where a fellow patient was aggressive.

To summarize, the findings indicate high implementation fidelity, both in terms of the SFC and the patients’ responsiveness to Safewards. The seven interventions implemented were all clearly observable at the SFC/walkthrough. Evaluation of patient responsiveness to the implementation of Safewards may differ from that of patients’ experiences of Safewards in general. This is because responsiveness more specifically refers to patients’ enthusiasm and engagement, in addition to their perception of the acceptability, usefulness and relevance of Safewards. The results of the present study contain many examples of how patients describe responsiveness based on these attributes. For example, patients expressed that the discharge tree provided comfort during bad days, as it created hope (usefulness). The attached Know each other folder could also make them familiar with staff members at their own pace (acceptability) and one patient heard a staff member at a Mutual help meeting saying that she was grateful to be on the ward, which was described as one of the best things that particular patient had experienced on the ward (enthusiasm).

The patients described staff behaviour and the ward climate as positive, and that the interventions and other activities involving staff members created a feeling of safety and could distract from difficult thoughts and feelings. They felt respected, less alone, hopeful and safe. This is similar to the results of Maguire et al. [ 25 ] and Fletcher et al. [ 5 ], who described patients’ feelings of hope, safety, respectful relationships and sense of community on wards in which Safewards was implemented. In our study, the patients more clearly emphasized that they took responsibility for others and the ward environment than was the case in the aforementioned studies. Some patients were surprised that they were expected to take responsibility, while others considered it a matter of course. Although not fully clear, it is possible that the interventions involving Clear mutual expectations and Mutual help meetings could have encouraged patients to take a more active role in ward responsibilities and supporting others, or to realize that such behaviours were appreciated on the ward. There is a lack of research on assuming responsibility and naturally occurring peer support among patients [ 44 ]. However, our study indicates that patient engagement in Safewards may enhance opportunities for self-help and peer support, both within Safewards interventions (e.g., Calm Down methods and Mutual Help Meetings) and through spontaneous initiatives. In this way, active patient participation in the implementation of Safewards appears to encourage empowerment and support recovery processes which in turn may reduce conflict and containment [ 45 ].

Several participants experienced it as challenging being in a ward where so much communication between patients and staff as well as among the patients themselves was expected, for example through Mutual help meetings and Discharge messages. Patient engagement was demonstrated by several communication related improvement suggestions made about Safewards, such as more accessible information by means of simplified text or use of pictures. Similarly, an important factor in implementation is dosage, meaning patients’ level of exposure to the interventions [ 46 ]. A participant in this study had previously experienced that it was necessary to adapt to the ward rules and routines and not show negative emotions to avoid the risk of coercive measures. As this patient did not exhibit anxiety to staff members, no Calm down methods were used. Several studies indicate that many patients have similar thoughts [ 6 , 47 , 48 , 49 , 50 ]. Therefore, it is important to ensure that the interventions are sensitive to individual patient needs and that person centredness is not compromised.

The present study is a first attempt to examine implementation fidelity to Safewards interventions by focusing on patient responsiveness. Including participant responsiveness when measuring implementation fidelity is important especially in complex interventions. In a review of complex rehabilitation interventions that examined 43 studies from a theoretical implementation perspective, the responsiveness of the participants, both staff and patients, was the most frequently mentioned factor affecting fidelity [ 51 ]. In research on Safewards, the focus has often been on the general response of staff and sometimes patients, as opposed to their response to specific interventions. When focusing on the responsiveness to the different interventions, we also gained information about strategies to facilitate implementation, delivery quality and adherence [ 32 ]. It became clear that despite Safewards, staff occasionally seemed to have difficulties dealing with certain situations. Patients who observed this could perceive the ward as an unsafe environment.

According to the patients, inconsistencies in staff behaviour and different ways of implementing the interventions affected the quality of delivery; this was particularly obvious in the Mutual help meeting intervention. Hence, staff responsiveness to, and way of working with, the Safewards interventions had a direct impact on patients’ responsiveness to them and whether or not they perceived them as helpful. It has been suggested that participant responsiveness may have a major impact on fidelity, and the connection between staff and patient responsiveness has been described by Carroll et al. [ 32 ] as a key aspect of implementation. This connection may be of particular importance when implementing an intervention such as Safewards, which aims at reducing levels of conflict and containment. Providing a therapeutic ward environment, including therapeutic engagement by staff in collaboration with patients, have been described as central to the reduction of conflict and restrictive practices, as well as to the quality of mental health nursing practice [ 52 , 53 ]. Therefore, for staff to implement Safewards in a task-orientated and instrumental fashion without positive responsiveness is unlikely to be successful.

An important determinant of successful implementation of an intervention is local and organizational leadership [ 54 ]. Findings from our study suggest that leaders responsible for the implementation of Safewards, need to recognize the importance of facilitating for a positive patient and staff responsiveness. For example, they should be aware of any negative conclusions about the effectiveness of Safewards based solely on observations of staff performing Safewards activities without identifying a lack of positive responsiveness. Therefore, it is likely that the implementation of Safewards would benefit from leaders actively supporting this aspect in their implementation strategies.

Strengths and limitations

Our study adds to the sparse literature on patient experiences of the Safewards model. The results are relevant for clinical practice when implementing Safewards, as they provide insights into patient responsiveness to and suggestions about how to improve specific Safewards interventions. Possible pitfalls in the implementation process may thereby be avoided.

A main limitation is that the study was conducted at only one ward, mainly comprising patients treated for affective disorders. Interviews from other wards with different patient profiles may have contributed more knowledge about patient responsiveness and further suggestions for improvement. Another limitation is that observations, recruitment of participants and interviews were conducted by staff employed at the ward, possibly leading to bias in observations, selection of patients, and their responses to the interview questions. As the interviewers had been engaged in the implementation of Safewards at the ward, they may have reported more observations on the SFC than an independent researcher would have done and may also have selected favourably disposed patients for interview. Some patients were interviewed while still on the ward in a dependent situation. We handled this bias by giving clear instructions to the interviewers and the ward manager about which patients could be interviewed, how to use the SFC and the interview guide. Clear questions in the interview guide were posed to encourage patients to be critical and make suggestions for improvement. These were single session interviews. We did not contact the patients again, even though it could have provided valuable knowledge. We saw it as both ethically and practically problematic. Reminding people of their time on a psychiatric ward can arouse many emotions and it is often difficult to get in touch with former patients. On the other hand, it is a strength that the interviewers were very familiar with the work at the ward and had wide experience of communicating with patients, possibly leading to richer responses. After the information at the Help meeting no patient immediately signed up for an interview. Some patients may have a lack of energy, and some may not dare to speak or ask questions in front of others in a group. However, the interviewers noticed that all participating patients wanted to take part of the study and express their thoughts about their stay at the ward. Despite the shift in direction towards becoming a more patient-centred ward, many suggestions for improvement emerged that the staff had not previously received from patients. To increase trustworthiness all authors took part in the analysis. The authors possess diverse backgrounds, including mental health nursing, social work, and psychiatric health services research. The primary author also has personal experience with psychiatric inpatient care as a patient. These varied competencies and experiences enhance the potential for multiple perspectives in analysing the interview material.

This study confirms previous research that patient responsiveness is an important factor in the assessment of fidelity in prevention programs, such as Safewards. The patients’ descriptions of the acceptability, relevance and usefulness of the specific interventions, to a high degree reflected the objective visual observations made through the SFC and ward walkthrough. Patient engagement was demonstrated by several suggestions about how to adapt the interventions in order to make them more useful and accessible. This shows a potential to obtain valuable input from patients when implementing and adapting Safewards in a ward and to achieve high quality implementation and levels of fidelity. This study is also clinically relevant as it presents many examples of practical work with these interventions and their effects on patients’ experiences of care.

Data availability

The data are not available because it could compromise the individual privacy of participants. They are stored at the University Health Care Research Center, Region Örebro County, and may be requested by other researchers.

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Acknowledgements

The authors extend their gratitude to all the patients who participated in this study, to the ward manager who made it possible to conduct the study and to Gullvi Nilsson who was the language proofreader of this script.

The study was funded by AFA Insurance (No. 190272) and Region Örebro County. The funding bodies have not influenced the research design, the procedure or work on the manuscript.

Open access funding provided by Örebro University.

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Veikko Pelto-Piri & Lars Kjellin

Psychiatric outpatient clinic, Region Värmland, Kristinehamn, Sweden

Gabriella Backman

Psychiatric Outpatient Clinic, Västra Götalandsregionen, Alingsås, Sweden

Karoline Carlsson

Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden

Anna Björkdahl

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Contributions

VP (male, PhD, social worker, investigator at organizational level in psychiatry and research supervisor), LK (male, PhD, psychiatric health services researcher and research supervisor) and AB (female, PhD, specialized psychiatric nurse, investigator at organizational level and researcher) designed and planned the study. GB (female, specialized psychiatric nurse) and KC (female, specialized psychiatric nurse) conducted the interviews. The analysis was performed by VP and GB with the support of all co-authors. VP wrote a first draft of the manuscript, after which all authors contributed to the various revisions and approved the final draft.

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Correspondence to Veikko Pelto-Piri .

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Written information about the study was provided with the invitation to participate. Those who agreed to participate received both oral and written information from the interviewer and written informed consent was obtained. We were careful to emphasize that participation was voluntary and that their decision whether or not to participate would not affect their care. The study was approved by The Swedish Ethical Review Authority, Uppsala, Sweden, No. 2020–03881.

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Pelto-Piri, V., Kjellin, L., Backman, G. et al. Patient responsiveness as a safewards fidelity indicator: a qualitative interview study on an acute psychiatric in-patient ward. BMC Health Serv Res 24 , 922 (2024). https://doi.org/10.1186/s12913-024-11326-z

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Trump's claims of a migrant crime wave are not supported by national data

WASHINGTON — When Donald Trump speaks at the southern border in Texas on Thursday, you can expect to hear him talk about “migrant crime,” a category he has coined and defined as a terrifying binge of criminal activity committed by undocumented immigrants spreading across the country.

“You know, in New York, what’s happening with crime is it’s through the roof, and it’s called ‘migrant,’” the former president said at a rally in Michigan earlier this month. “They beat up police officers. You’ve seen that they go in, they stab people, hurt people, shoot people. It’s a whole new form, and they have gangs now that are making our gangs look like small potatoes.”

Trump has undoubtedly tapped into the rising anger over crimes allegedly committed by undocumented migrants that have gained national attention — most recently, the killing of college student Laken Riley in Georgia last week, after which an undocumented migrant from Venezuela was arrested and charged with her murder, and the much-reported fight between New York police officers and a group of migrant teens.

According to a recent Pew  poll , 57% of Americans said that a large number of migrants seeking to enter the country leads to more crime. Republicans (85%) overwhelmingly say the migrant surge leads to increased crime in the U.S. A far smaller share of Democrats (31%) say the same. The poll found that 63% of Democrats say it does not have much of an impact.

But despite the former president’s campaign rhetoric, expert analysis and available data from major-city police departments show that despite several horrifying high-profile incidents, there is no evidence of a migrant-driven crime wave in the United States.

That won’t change the way Trump talks about immigrants in his bid to return to the White House, as he argues that President Joe Biden’s immigration policies are making Americans less safe. Trump says voters should hold Biden personally responsible for every crime committed by an undocumented immigrant.

An NBC News review of available 2024 crime data from the cities targeted by Texas’ “Operation Lone Star,” which buses or flies migrants from the border to major cities in the interior — shows overall crime levels dropping in those cities that have received the most migrants.

Overall crime is down year over year in  Philadelphia ,  Chicago , Denver ,  New York  and Los Angeles. Crime has risen in  Washington, D.C ., but local officials do not attribute the spike to migrants.

“This is a public perception problem. It’s always based upon these kinds of flashpoint events where an immigrant commits a crime,” explains Graham Ousey, a professor at the College of William & Mary and the co-author of “Immigration and Crime: Taking Stock.” “There’s no evidence for there being any relationship between somebody’s immigrant status and their involvement in crime.”

Ousey notes the emotional toll these incidents have taken and how they can inform public perception, saying, “They can be really egregious acts of criminality that really draw lots of attention that involve somebody who happens to be an immigrant. And if you have leaders, political leaders who are really pushing that narrative, I think that would have the tendency to sort of push up the myth.”

“At least a couple of recent studies show that undocumented immigrants are also not more likely to be involved in crime,” Ousey says — in part because of caution about their immigration status. “The individual-level studies actually show that they’re less involved than native-born citizens or second-generation immigrants.”

Another misconception often cited by critics is that crime is more prevalent in “sanctuary cities.” But a Department of Justice report found that “there was no evidence that the percentage of unauthorized or authorized immigrant population at the city level impacted shifts in the homicide rates and no evidence that immigration is connected to robbery at the city level.”

Trump’s campaign claims without evidence that those statistics obscure the problem.

“Democrat cities purposefully do not document when crimes are committed by illegal immigrants, because they don’t want American citizens to know the truth about the dangerous impact Joe Biden’s open border is having on their communities,” Karoline Leavitt, Trump campaign press secretary, said in a statement. “Nevertheless, Americans know migrant crime is a serious and growing threat; and the murder, rape, or abuse of one innocent citizen at the hands of an illegal immigrant is one too many.”

Trump has been pushing the argument that immigrants bring crime since launching his first campaign in 2015, often featuring at his rallies the family members of those who were killed by undocumented immigrants who had been drinking and driving. And his arguments are not new — opponents of immigration have long tried to make the case that migrants bring crime.

National crime data, especially pertaining to undocumented immigrants, is notoriously incomplete. The national data comes in piecemeal and can only be evaluated holistically when the annual data is released.

The data is incomplete on how many crimes each year are committed by migrants, primarily because most local police don’t record immigration status when they make arrests. But the studies that have been done on this, most recently by the University of Wisconsin-Madison, show that in Texas, where police do record immigration status, migrants commit fewer crimes per capita.

In December 2020, researchers studying Texas crime statistics found that “contrary to public perception, we observe considerably lower felony arrest rates among undocumented immigrants compared to legal immigrants and native-born U.S. citizens and find no evidence that undocumented criminality has increased in recent years.”

Olympia Sonnier is a field producer for NBC News. 

Garrett Haake is NBC News' senior Capitol Hill correspondent. He also covers the Trump campaign.

More From Forbes

Five practical applications of ai in automation.

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Jakob Freund is the CEO of Camunda , a software company innovating end-to-end process orchestration.

Both AI and automation are changing the nature of work. When used together, these two technologies hold great promise to improve human productivity and make existing business processes more efficient. While much of the recent media focus has been on generative AI applications like ChatGPT, there are many other practical uses of AI in automation that can both improve internal productivity and drive better customer experiences.

These technologies can be grouped into three overall areas of impact: generative, predictive and augmented intelligence.

• Generative: In this context, generative AI algorithms can be used to create new content or generate code in response to training datasets.

• Predictive: Teams can use predictive AI algorithms to make decisions or improve processes based on previous outcomes.

• Augmented Intelligence: This AI technology has the capacity to accelerate decision-making processes that typically require human intervention.

Let’s take a look at five practical applications of AI that fall within these three categories and how they can improve enterprise automation outcomes.

1. Continuously Improving Processes

It is possible to improve end-to-end processes by combining process orchestration with AI. For example, a process orchestration system gathers data on process execution and performance across a variety of endpoints (e.g., the people, systems and devices that make up a process). This process execution data can be fed into a predictive AI model to make predictions about how certain processes will perform (e.g., process duration), based on the performance of similar processes in the past.

The holy grail of self-healing processes isn’t far away with the addition of emerging augmented intelligence models. This technology has the potential to detect bottlenecks in processes, provide suggestions for enhancement and either automatically update models or update them following human validation of the decision.

2. Generating Process Testing Data

One compelling use of generative AI involves the generation of testing data for processes. For example, there are many ways that forms can produce errors, based on typical human errors—think about the myriad ways of representing dates (1.15.23 versus 15.1.23 versus January 15, 2023, etc.).

Using past human behavior as a reference, the system can create tests that have the potential to "challenge" a form, including scenarios like inputting incorrect numeric values, surpassing character limits and so on.

3. Accelerating Decision-Making

Many organizations already use automation to accelerate certain decisions, such as accepting or rejecting a mortgage application based on an applicant’s credit score and perceived risk profile. Predictive AI can be used alongside decision models to accelerate certain decision-making, such as predicting instances of fraud based on previous user data in a fraud-prevention scenario.

Companies with advanced AI capabilities can harness machine learning-ready datasets from a process orchestration system, seamlessly integrating them with internal datasets to anticipate patterns and extract valuable insights for informed decision-making.

4. Streamlining Human Tasks

Generative AI can play an important role in streamlining certain human tasks. Take, for example, a community market that wants to process applications for new vendors. By incorporating the ChatGPT API into a process model, the market could automate the extraction of pertinent data from forms to produce either acceptance or rejection emails—and generate descriptions for each approved vendor to be featured on the market's website.

5. Developing Process Models

The business and enterprise software architects or developers who write code for process models could benefit from generative AI, as well. Teams can explore the use of open-source code generators like GitHub Copilot to build and code a process model, drawing inspiration from existing models established within the organization.

Rather than beginning from square one, these tools can effectively optimize limited development resources and enhance the level of automation across the entire organization.

Potential Challenges Of Applying AI In Automation

While there are many possibilities for applying AI to automating your processes, organizations should be aware of the potential risks and challenges. Some common challenges include:

• Data Preparation Overhead: Preparing data for machine learning can be time-consuming, with data scientists and engineers spending much of their effort on this task. Gartner reports that 85% of AI projects fail, and only 53% progress from prototype to production due to data-related challenges.

• Addressing Accuracy And Bias: Accuracy and bias are persistent concerns in AI. Biased training data can lead to biased results. Human supervision is essential to verify results and mitigate these issues, especially in critical automation applications like credit assessment.

• Data Security Risks: Using publicly available models can pose security risks to sensitive data such as PII and intellectual property. Organizations often develop proprietary models from internal datasets to enhance data security and protect corporate information.

While these challenges, and others, should be taken into account when considering AI implementation, they should not deter organizations from exploring AI solutions. AI, when used in conjunction with process orchestration, has the capacity to enhance automation levels, leading to improved business operations and customer experiences.

Using Orchestration As An Accelerant For AI

Today, there are many terms to explain the optimized use of AI combined with other automation technologies—ranging from intelligent automation to hyperautomation . Ultimately, process orchestration can serve as an effective jumping-off point for the effective use of AI and automation, ensuring that the various endpoints of a process and components of the hyperautomation tech and business stacks are operating in concert with one another.

The ultimate goal is an efficient, optimized end-to-end process that improves both the employee experience and customer-facing applications. That goal is well within reach as organizations accelerate along their journey with both process orchestration and AI.

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A Practical Approach to Tailor the Term Long COVID for Diagnostics, Therapy and Epidemiological Research for Improved Long COVID Patient Care

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• Published: 11 August 2024

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• Kathryn Hoffmann   ORCID: orcid.org/0000-0001-8760-4250 1 ,
• Michael Stingl 2 ,
• Liam O’Mahony 3 &
• Eva Untersmayr 4  

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The term long COVID (LC) effectively describes the broad long-term disease burden of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infections, encompassing individual suffering and significant socioeconomic impacts. However, its general use hampers precise epidemiological research, diagnostics and therapeutic strategies. Misinterpretations occur, for example, when population surveys are compared to studies using health record data, because both refer to these data as LC. This also emphasizes the need for different terminology. The National Institute for Health and Care Excellence (NICE) rapid guideline differentiates ongoing symptomatic COVID-19 from post-COVID conditions, yet real-world observations challenge these two subgroup definitions. We propose refining the term LC into three subgroups: ongoing symptomatic COVID-19, SARS-CoV-2 induced or exacerbated diseases and post-acute COVID condition. This stratification aids targeted diagnostics, treatment and epidemiological research. Subgroup-specific documentation using the International Classification of Diseases, Tenth Revision (ICD-10) codes ensures accurate tracking and understanding of long-term effects. The subgroup of post-acute COVID condition again includes various symptoms, syndromes and diseases like post-exertional malaise (PEM), dysautonomia or cognitive dysfunctions. In this regard, differentiation, especially considering PEM, is crucial for effective diagnostics and treatment.

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The term long COVID (LC) is very well suited to describe the overall disease burden that can result from infection with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) in an individual [ 1 ]; the personal disease burden, tremendously reduced quality of life and socioeconomic implications at the population level show the overall impact of the condition and importance of meaningful preventive measures. However, the term is not well suited to providing a tailored approach to epidemiological research, initial diagnostics and therapy because of the need for differentiation regarding the various symptoms and syndromes subsumed under the term LC to be able to offer physicians precisely targeted and effective solutions in the daily practice [ 2 ].

For example, there are always misunderstandings when interpreting frequency data on LC after a SARS-Cov-2 infection. Even without going into limitations of the different methodologies in more detail, there is a big difference between asking the population whether they experienced symptoms lasting > 4 weeks after a SARS-CoV-2 infection and using health record data as the basis for the calculations. For the population survey, all long-term effects experienced will be reported, whether due to a more severe course of COVID-19 or newly acquired symptoms, syndromes, or illnesses as a post-acute result of the infection. When using health record data, only the related diagnoses found and documented by physicians and then defined by researchers are used; this means, depending on the definition, only a part of all long-term effects is recognized. Here, the misunderstandings start because all of this is usually called LC.

Therefore, the National Institute for Health and Care Excellence (NICE) rapid guideline has already attempted an initial distinction of the term LC by delineating “ongoing symptomatic COVID-19” from the “post-COVID condition,” with the criterion that it cannot be explained by alternative diagnoses like the WHO did and additionally introduced ICD-10 code U09.9 for the post-COVID condition [ 3 , 4 ]. However, according to this NICE definition, ongoing symptomatic COVID-19 ends after 12 weeks, which often does not correspond to the observable reality of the disease like for formerly critically ill patients as well as conditions like severe myocarditis. How should we proceed if symptoms of diseases were induced, triggered or exacerbated by SARS-CoV-2 but themselves fall under the alternative diagnosis of, e.g., autoimmune, cardiovascular or neurodegenerative disease? An extensive recent report by the National Academies of Sciences, Engineering and Medicine comprehensively outlines the various health impacts associated with LC [ 5 ]. The findings indicate that LC is a multifaceted chronic condition, manifesting in > 200 different health effects across multiple organ systems [ 5 ]. These effects encompass both new onset symptoms and the exacerbation of pre-existing conditions [ 5 ]. A recent publication by Ewing et al. (2024) additionally described LC as a disease with a spectrum of pathology [ 6 ]. They recommended even broadening the definition of long-term effects not only to include diseases and organ damage caused by SARS-CoV-2 but also (currently still) asymptomatic organ damage, which can lead to various health impacts such as increased risk for heart attacks and strokes in the future [ 6 ]. Xie et al. also calculated the risk and burden of long-term effects of a SARS-CoV-2 infection by including many organ systems and related diseases, naming it post-acute sequelae of SARS-CoV-2 infection (PASC) [ 7 ]. This term is also widely used in scientific literature and is probably, together with the more colloquial term LC, the adequate term for the whole disease spectrum from acute to post-acute when it comes to pathomechanism research and showing the full impact of damage.

However, this is generally not what doctors mean by LC when they see patients, since probably few doctors would describe, document and code, for example, a heart attack or autoimmune disease induced by a previous SARS-CoV-2 infection as LC, PASC, or post-COVID condition. It has not been called post-bacteremia syndrome in the past if a patient developed a stroke during bacteremia. What doctors are most likely to diagnose as LC is what NICE [ 3 ] has summarized as ongoing symptomatic COVID-19 or post-COVID condition as well as what the ESCMD rapid guideline describes [ 8 ]. Nevertheless, tailored terms are additionally needed for the other long-term effects mentioned above.

Therefore, we propose to use the term LC or PASC only if aiming at including all long-term effects, and the terms for the three subgroups are described in Fig.  1 for more targeted sampling or stratification approaches, which do not include all long-term effects. Additionally, we propose to consider the three subgroups for a more targeted diagnostic strategy if a patient with long-COVID symptoms comes into the doctor's office. We further differentiated the definition of the third subgroup in a second step.

Group: Ongoing symptomatic COVID-19: Prolonged courses of severe COVID-19, e.g., acute respiratory distress syndrome (ARDS), severe pneumonia, myocarditis, multisystem inflammatory syndrome (MIS), symptoms due to organ damage during severe COVID-19 (e.g., brain, heart, kidney, lung damage) or therapy (e.g., ventilation, post-ICU syndrome) with symptoms that persist up to 12 weeks. After 12 weeks, we suggest to name it “(fibrosis as) ongoing sequelae of COVID-19,” for example.

Group: SARS-CoV-2 induced, triggered or exacerbated diseases. Symptoms for > 4 weeks due to worsening of an existing pre/chronic/residual disease due to SARS-CoV2 infection and/or post-acute new onset of diseases associated with SARS-CoV2 infection (e.g., thrombosis, embolism, stroke, cardiovascular disease, asthma, atypical pulmonary fibrosis, autoimmune disease, diabetes, dementing syndromes) and/or related increased risks. An example would be “SARS-CoV-2 triggered asthma bronchiale” or “SARS-CoV-2 exacerbated lupus erythematosus.”

Group: Post-acute COVID condition (cannot be explained by another diagnosis like the ones above) instead of post-COVID condition to make it clearer that this is an expression of a post-acute infection syndrome caused by SARS-CoV-2 with symptoms that persist for > 3 months but could be present even before.

Description of the terms for the three proposed long-COVID subgroups over time

Since LC/ PASC is a spectrum, the three subgroups can also occur in different combinations and influence each other.

Most important in the context of the sub-group building is that for the first two subgroups in contrast to subgroup 3, there are already known, clearly graspable diagnostic markers and, for the most part, guideline-compliant treatment options as shown for example for neurological symptoms by Frontera et al. [ 9 ]. This means that symptoms due to a possible affiliation to the first two subgroups must be excluded using excellent but common differential diagnostics to then take an equally careful diagnostic approach for subgroup 3.

To differentiate the first subgroup would additionally make sense in terms of known risk factors for LC, which overlap largely with risk factors for severe acute disease progression [ 10 ]. Prolonged courses and immediate organ damage resulting from the acute disease occur mainly in severe acute infections. The first subgroup of LC might currently be most amenable to prevention if severe courses of acute COVID-19 can be limited or prevented as much as possible. This is also precisely the subgroup for which vaccination, medication and the reduction of other factors responsible for the risk of a severe COVID-19 course including MIS have already been shown to reduce the risk of LC [ 11 ]. These considerations are in line with previous comments about the differentiation of LC symptoms: “Long haulers who survived severe acute SARS-CoV-2 infection are most likely to be men older than 50 years with lingering tissue damage and scarring (subgroup 1; added by authors). People with long COVID after a less severe infection are most likely to be younger women (aged 36–50 years) whose acute infection has triggered adverse physiological responses (subgroup 3; added by authors)" [ 2 ]. Indeed, it was shown that the decline of the overall LC frequencies after infection between 2020 and 2022 was the result of two key drivers: availability of vaccines and changes in the characteristics of the virus—which made the virus less prone to causing severe acute infections and related long-term effects [ 7 ].

Subgroup 2 includes LC symptoms caused by the diseases for which a significant increase in risk could be shown because of SARS-CoV-2 infection. Importantly, first hints regarding the cumulative risk of re-infections in particular in subgroup 2 are reported in the literature [ 12 , 13 ]. Therefore, in particular the number of individuals with a new onset or worsening of disease might increase over time as new patients with LC symptoms occur because of ever-new infections with novel variants cycling through the population. A challenge for subgroup 2 is that the new disease onset might also be after 12 weeks, and links with the causative SARS-CoV-2 infection might be increasingly difficult to identify and document as sequelae of the SARS-CoV-2 infection, in particular if clinicians are not used to link responsible pathogens to long-term effects. However, a recent study showed that even 3 years after the initial infection, new diseases, syndromes and symptoms can occur [ 14 ]. Therefore, it might be useful to implement it in the documentation of diseases linked to certain pathogens.

For subgroup 3, if taking the definition of “cannot be explained by another diagnosis” seriously, it becomes increasingly clear that standard diagnostics and treatment options are usually not fit for purpose and that this is the group with the most similarities to previously known post-acute infection conditions. It was previously stated that “…post-acute infection syndrome with clear physiological dysfunction…is often not consistently apparent using standard medical diagnostic tests. This discrepancy highlights the need for a new generation of more sensitive testing procedures for people with post-acute infectious syndrome" [ 2 ]. In line with this, we suggest using post-acute-COVID condition instead of just post-COVID condition for the post-acute infection syndrome (PAIS) triggered by SARS-CoV-2 [ 15 ]. Moreover, this is the subgroup of long-COVID which occurs often even after a mild SARS-CoV-2 infection [ 2 ].

PAIS are not new [ 15 ]. The term PAIS, however, is an umbrella term for dysfunctions and damage that can occur after the acute phase of illness with certain pathogens. Individual post-acute infection symptoms and syndromes already identified are for example [ 15 ]: post-exertional malaise (PEM), dysautonomia (DA), e.g., postural tachycardia syndrome (PoTS), dysregulation of the immune system, e.g., mast cell overactivation (MCAS)-like syndromes, and cognitive dysfunctions. This is exactly where the stratification of this group should start when it comes again to research, diagnosis and therapy. Most importantly, we suggest always differentiating between patients with post-acute COVID condition with and without the existence of PEM. The presence of PEM makes an important difference when it comes to treating patients [ 16 ]. Unlike all other patient groups, patients with PEM must first have their condition stabilized by pacing [ 1 , 17 ]. Pacing must be considered in all further forms of treatment and always come first. This is a major challenge since graduate activation therapy is a successful form of therapy, e.g., for PoTS when occuring alone, but must not be treated according to standard autonomic dysfunction guidelines in patients with PEM being also present [ 18 ]. Patients with post-acute COVID condition with PEM are, therefore, particularly vulnerable and at high risk of suffering a chronic course as is seen in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) type of post-acute COVID condition with its hallmark symptom PEM [ 1 , 17 ].

Figure  2 illustrates the mainly assumed mechanisms and related symptoms that should be considered concerning more sensitive new and modern diagnostic techniques regarding post-acute COVID condition. At the center of consideration, special relevance has to be given to the occurrence of PEM [ 16 , 17 , 18 , 19 , 20 , 21 ].

Mainly assumed mechanisms and related symptoms of post-acute COVID condition that should be considered concerning more sensitive new and modern diagnostic techniques

Moreover, as stated before, the current definition and linked International Classification of Diseases, Tenth Revision (ICD-10) code raise the question of correct documentation and coding options for long COVID symptoms as shown in the latest data from Statistics Canada, in which only 5.7% of LC sufferers received a corresponding diagnosis [ 22 ]. How are the symptoms of subgroups 1 and 2 documented and coded if the existing ICD-10 code U09.9 is only to be used for the post-COVID condition, although subgroups 1 and 2 are also sequelae of the SARS-CoV-2 infection?

We suggest coding the respective disease and/or symptom as the principal diagnosis for the first two subgroups and U09.9 as the secondary diagnosis, in contrast to coding U09.9 as the principal diagnosis for subgroup 3, the post-acute COVID group and the corresponding symptoms and syndromes subsumed under the term post-acute COVID, such as PoTS with G90.80 or ME/CFS with G93.3, as the secondary diagnosis. For example, registry studies and studies that use medical records as the basis for their data could, then, clearly show which damage is caused by SARS-CoV-2 as a whole and which is caused by subgroup 3 alone, the post-acute infection syndrome group, provided that the differential diagnosis by the doctors carrying out the diagnostics and their documentation is correct and carefully carried out. This would be feasible for other pathogens, too, where also a long-term overview of the damages is needed.

In summary, we recommend utilizing the term "LC" or "PASC" when referring to the comprehensive spectrum of long-term effects. For more precise sampling or stratification that does not encompass all long-term effects, the terms associated with the three subgroups should be employed. On the one hand, doctors should clearly differentiate the diagnostic pathways for patients to be able to assign risk factors more clearly. On the other hand, this subdivision is important to have a basis for uniform clinical coding for epidemiological research, for example. In addition, the third subgroup, the post-acute infectious syndrome post-acute COVID condition, must also be further stratified since it is essential for diagnostic and therapeutic developments. It is especially important to consider the presence of PEM.

This article is based on previously conducted studies and does not contain any new studies with human participants or animals performed by any of the authors.

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Kathryn Hoffmann designed and conceived the work, drafted the manuscript, and revised it substantially. Michael Stingl, Liam O'Mahony, and Eva Untersmayr have made substantial contributions to the conception of the work and substantially revised it. All authors have approved the submitted version.

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Hoffmann, K., Stingl, M., O’Mahony, L. et al. A Practical Approach to Tailor the Term Long COVID for Diagnostics, Therapy and Epidemiological Research for Improved Long COVID Patient Care. Infect Dis Ther (2024). https://doi.org/10.1007/s40121-024-01025-x

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DOI : https://doi.org/10.1007/s40121-024-01025-x

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