Open online courses on basic life support: Availability and resuscitation guidelines compliance

Birkun, Alexei; Gautam, Adhish; Trunkwala, Fatima; Böttiger, Bernd W.

doi:10.1016/j.ajem.2022.08.013

Cited by 10 publications

(16 citation statements)

References 29 publications

(34 reference statements)

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“…Notwithstanding the higher quality of source articles compared with QAS responses, in many cases, the source content was also omitting relevant evidence-based instructions on first aid. This supports earlier studies which found that information on first aid presented online on websites, 8,9 in mobile apps, 20 videos, 21 or within online courses curricula 10 is largely of poor quality. It is also worthy of note that EMS telephone numbers suggested by the source articles and the QAS responses in most cases were inconsistent with the search region that represents another important limitation to the use of the search engine as a means of informational support in a real-life emergency.…”

Section: Discussionsupporting

confidence: 90%

“…Although major search engines use algorithms to prioritize high-quality sources in their search results, a number of studies have shown that health-related information found online, including information on first aid, is commonly non-evidence-based and low in quality. [8][9][10] Incorrect, incomplete, or irrelevant information on first aid may produce inappropriate and harmful actions, potentially affecting health outcomes.…”

Section: Introductionmentioning

confidence: 99%

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Dr. Google’s Advice on First Aid: Evaluation of the Search Engine’s Question-Answering System Responses to Queries Seeking Help in Health Emergencies

Birkun

Gautam²

2023

Prehosp. Disaster med.

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Introduction: The ever-growing penetration of internet and mobile technologies into society suggests that people will increasingly use web searches to seek health-related information, including advice on first aid in medical emergencies. When a bystander is incompetent in first aid and has no immediate support from Emergency Medical Services (EMS), as it happens in low-resource settings or in disasters, instructions found online could be the sole driver for administering first aid before arrival of professional help. Study Objective: The aim of this study was to evaluate quality of advice on first aid generated by a web search engine’s question-answering system (QAS) in response to search queries concerning provision of help in common health emergencies. Methods: In December 2022-January 2023, an English-language search was carried out in Google with ten queries based on the keyword combinations (what to do OR how to help) AND (bleeding OR chest pain OR choking OR not breathing OR seizure). The search engine’s QAS responses (up to 11 per search query) were evaluated for compliance with the International Federation of Red Cross First Aid Guidelines 2020 using the pre-developed checklists. Results: Out of 98 QAS items generated by Google, 67.3% (n = 66) were excluded, mainly because the QAS answers did not address original queries. Eligible unique QAS responses (n = 27) showed poor coverage of the guideline-compliant instructions on first aid. Mean percentage of QAS responses providing a first aid instruction with complete adherence to the guidelines varied from 0.0 for choking to 19.5 for seizure. Only three (11.1%) QAS responses contained an explicit instruction to access EMS, while 66.7% (n = 18) included directions either contradictory to the guidelines and potentially harmful (eg, use of home remedies in chest pain) or inapplicable for an untrained person (eg, use of tourniquet in bleeding). Conclusion: Although the search engine’s QAS responds to user’s inquiries concerning assistance in health emergencies, the QAS-generated answers, as a rule, omit potentially life-saving evidence-based instructions on first aid and oftentimes give advices noncompliant with current guidelines or inadequate for untrained people, and thus create risks for causing harm to a victim.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Dr. Google’s Advice on First Aid: Evaluation of the Search Engine’s Question-Answering System Responses to Queries Seeking Help in Health Emergencies

Birkun

Gautam²

2023

Prehosp. Disaster med.

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“…Various formats of online training exist, including those incorporating pre-training and post-training assessments, interactive video modules, virtual reality simulations, nonpresential practical sessions using mannequins with automated real-time feedback and assessments conducted at 3 and 6 months. [31][32][33][34] A study conducted in China, exploring knowledge and attitudes towards AED usage, identified key barriers. Lack of proficiency in resuscitation techniques and limited practical skills were identified as significant impediments.…”

Section: Open Accessmentioning

confidence: 99%

“…The COVID-19 pandemic has significantly increased the prevalence of online training in general, with a notable surge in courses focused on CPR and AED usage. Various formats of online training exist, including those incorporating pre-training and post-training assessments, interactive video modules, virtual reality simulations, non-presential practical sessions using mannequins with automated real-time feedback and assessments conducted at 3 and 6 months 31–34…”

Section: Introductionmentioning

confidence: 99%

Online platform for cardiopulmonary resuscitation and automated external defibrillator training in a rural area: a community clinical trial protocol

Taverna-Llauradó,

Martínez-Torres,

Granado-Font

et al. 2024

BMJ Open

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IntroductionSudden death resulting from cardiorespiratory arrest carries a high mortality rate and frequently occurs out of hospital. Immediate initiation of cardiopulmonary resuscitation (CPR) by witnesses, combined with automated external defibrillator (AED) use, has proven to double survival rates. Recognising the challenges of timely emergency services in rural areas, the implementation of basic CPR training programmes can improve survival outcomes. This study aims to evaluate the effectiveness of online CPR-AED training among residents in a rural area of Tarragona, Spain.MethodsQuasi-experimental design, comprising two phases. Phase 1 involves assessing the effectiveness of online CPR-AED training in terms of knowledge acquisition. Phase 2 focuses on evaluating participant proficiency in CPR-AED simulation manoeuvres at 1 and 6 months post training. The main variables include the score difference between pre-training and post-training test (phase 1) and the outcomes of the simulated test (pass/fail; phase 2). Continuous variables will be compared using Student’s t-test or Mann-Whitney U test, depending on normality. Pearson’s χ2test will be applied for categorical variables. A multivariate analysis will be conducted to identify independent factors influencing the main variable.Ethics and disseminationThis study adheres to the tenets outlined in the Declaration of Helsinki and of Good Clinical Practice. It operated within the Smartwatch project, approved by the Clinical Research Ethics Committee of the Primary Care Research Institute IDIAP Jordi Gol i Gurina Foundation, code 23/081-P. Data confidentiality aligns with Spanish and European Commission laws for the protection of personal data. The study’s findings will be published in peer-reviewed journals and presented at scientific meetings.Trial registration numberNCT05747495.

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“…Except for several exploratory studies, [4][5][6][7][8][9] the LLM-based chatbots currently lack evaluation in terms of perspective application in emergency medicine. In relation to resuscitation research and practice, where implementation of contemporary digital technologies is encouraged, 10,11 it seems important and well-timed to examine the practicability of utilizing the LLM-powered chatbots in two directions: (1) to generate guideline-consistent advice on help in cardiac arrest (for purposes of public resuscitation education or for just-in-time informational support of untrained lay rescuers in a real-life emergency), and thus to contribute towards the promotion of community response to out-of-hospital cardiac arrest; and (2) to evaluate the quality of information on resuscitation available online (that is known to be generally low [12][13][14] ) and suggest how to enhance the content. The latter could help to establish systematic quality surveillance and assurance for publicly available resources on resuscitation and reduce potential harm from misinformation.…”

Section: Introductionmentioning

confidence: 99%

Large Language Model (LLM)-Powered Chatbots Fail to Generate Guideline-Consistent Content on Resuscitation and May Provide Potentially Harmful Advice

Birkun,

Gautam

2023

Prehosp. Disaster med.

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Introduction:Innovative large language model (LLM)-powered chatbots, which are extremely popular nowadays, represent potential sources of information on resuscitation for the general public. For instance, the chatbot-generated advice could be used for purposes of community resuscitation education or for just-in-time informational support of untrained lay rescuers in a real-life emergency.Study Objective:This study focused on assessing performance of two prominent LLM-based chatbots, particularly in terms of quality of the chatbot-generated advice on how to give help to a non-breathing victim.Methods:In May 2023, the new Bing (Microsoft Corporation, USA) and Bard (Google LLC, USA) chatbots were inquired (n = 20 each): “What to do if someone is not breathing?” Content of the chatbots’ responses was evaluated for compliance with the 2021 Resuscitation Council United Kingdom guidelines using a pre-developed checklist.Results:Both chatbots provided context-dependent textual responses to the query. However, coverage of the guideline-consistent instructions on help to a non-breathing victim within the responses was poor: mean percentage of the responses completely satisfying the checklist criteria was 9.5% for Bing and 11.4% for Bard (P >.05). Essential elements of the bystander action, including early start and uninterrupted performance of chest compressions with adequate depth, rate, and chest recoil, as well as request for and use of an automated external defibrillator (AED), were missing as a rule. Moreover, 55.0% of Bard’s responses contained plausible sounding, but nonsensical guidance, called artificial hallucinations, that create risk for inadequate care and harm to a victim.Conclusion:The LLM-powered chatbots’ advice on help to a non-breathing victim omits essential details of resuscitation technique and occasionally contains deceptive, potentially harmful directives. Further research and regulatory measures are required to mitigate risks related to the chatbot-generated misinformation of public on resuscitation.

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Open online courses on basic life support: Availability and resuscitation guidelines compliance

Cited by 10 publications

References 29 publications

Dr. Google’s Advice on First Aid: Evaluation of the Search Engine’s Question-Answering System Responses to Queries Seeking Help in Health Emergencies

Dr. Google’s Advice on First Aid: Evaluation of the Search Engine’s Question-Answering System Responses to Queries Seeking Help in Health Emergencies

Online platform for cardiopulmonary resuscitation and automated external defibrillator training in a rural area: a community clinical trial protocol

Large Language Model (LLM)-Powered Chatbots Fail to Generate Guideline-Consistent Content on Resuscitation and May Provide Potentially Harmful Advice

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