Essay Competition
Sign up to our 1:1 mentoring scheme where you will be assigned a medical student or junior doctor who can assist you with your application for free.
Click here to learn more.
2024 Essay Winners
Artificial Intelligence: Friend or Foe of Healthcare Professionals?
Although the concept of Artificial Intelligence (AI) has a seventy-year history, only recently have its synergistic and generative capabilities reached a performance level suitable for real-world applications. Spanning data mining, complex statistical modelling, deep machine learning, computer vision systems and predictive natural language, AI now has the capacity to structure, analyse and present information in a manner beginning to rival human capabilities, including that of healthcare professionals. Here, AI tantalisingly offers enormous scope for improving speed, accuracy, and cost-effectiveness across everything from disease prevention to drug discovery, and in the face of booming demand, it will revolutionise diagnosis, treatment, and recovery as well as how healthcare is delivered.
AI’s potential application spans the entire range of medical specialisms, promising to become a professional’s best friend throughout training and in practice. AI is already used in a range of focussed areas. For example, streamlining workflows and optimising staff and resource scheduling allows professionals to focus on more complex aspects of patient care. Software such as ‘Notatio Copilot’ can listen to consultations, extract clinical information, and generate consistent, digitised notes instantly available via mobile phone. In the future, this will expand to include making comparisons across related data, reaching evidenced conclusions, and suggesting further investigations or treatments. Other examples include the rapid analysis of imaging data (X-rays, MRI, CT scans etc.) or pathology samples (examining tissue or other disease indicators under a microscope). AI enables earlier detection of many conditions including breast, skin, and prostate cancers, eye, heart, and neurological diseases, foetal complications, endocrine disorders and stroke. This aids faster treatment and significantly improves the patient experience and clinical outcome (Kumar et al 2023). AI trained on 130,000 images of over 2,000 skin diseases proved as effective as a dermatologist in detecting malignancy (Esteva et al, 2017). Trials are underway for AI-assisted operations, helping plan and execute a wider range of procedures, reducing recovery time and costs (Moglia et al, 2021). AI is helping epidemiologists better understand and predict population-level health trends, disease risks, and the efficacy of interventions. It can forecast drug or vaccine potential, uncover novel uses for existing drugs, and increase the efficiency of clinical trials, notably being deployed in genomic sequencing of SARS-Cov-2 (Abubaker et al, 2022). AI is also aiding the interrogation of genomic data to identify disease markers and predict treatment responses, heralding personalised medicine optimised for an individual patient (NHS England 2023). The UK government is drawing upon the NHS’s unique data repository spanning the health of over sixty million people and investing millions in digital transformation (including AI) across health and social care (Community Practitioner 2023). Several NHS Trusts already collaborate with research organisations, pharmaceutical companies, and technology firms (including The Alan Turing Institute, DeepMind, Sensyne, and IBM). Telemedicine, in which health is monitored remotely via wearable devices such as ‘Doc@Home’, is widely used for geriatric, cardiac, and mental health patients and in ‘virtual wards’ (NHS England, 2023). AI-enabled processing of this data improves healthcare accuracy, efficiency and accessibility aiding provision in remote locations or where regular clinics would be difficult.
Clearly, AI is a healthcare tool with a widening capability to directly improve working practices and patient care. In that respect, it is a friend not just to healthcare staff but to the wider population. Yet it is important not to get carried away. Whilst there is undoubtedly monumental potential, there is also the prospect of significant downsides which will directly and indirectly impact healthcare professionals, and it is crucial we consider and take steps to mitigate these. The most obvious limitation of AI in healthcare is the availability, reliability, and security of the sensitive data with which AI is trained and upon which algorithms are derived. Data input into these applications must represent the population on which the AI will be deployed. Unfortunately, much existing data is incomplete or biased in some way, such as the underacknowledged differences in presentation between male and female cardiac patients (St Pierre et al, 2022) or images of skin disorders being mostly on white skin (we must ensure AI reliably detects disease across all skin tones). Trust is a cornerstone of medicine, so biases and inequalities must be eliminated, not enshrined or exacerbated (Kizilcec et al, 2024). Additionally, the sheer scale and complexity of the algorithms powering machine learning make understanding precisely how AI reaches a given result very difficult to disentangle. Doctors not only must be aware of the technical nuances in interpreting AI output, but also need to be able to explain them to patients so they understand their prognosis and can meaningfully consent to treatment. Consent also extends to the implications of AI for patient data, specifically how it will be validated and used, whether the right to opt out will continue to be feasible, and the implications for patient privacy when anonymised data could be reconstructed across multiple data sources to re-identify an individual. Alongside this, commercial algorithms are closely guarded secrets and it remains to be seen how this will impact understanding, acceptance, and legal liability for errors. Equally, some patients may enthusiastically grasp the broad concept of AI without appreciating its limitations, developing unrealistic expectations and subsequent dissatisfaction with the healthcare they receive.
AI also raises longer-term professional fears, including redundancy. Medicine’s extended, arduous, and expensive training is founded upon an expectation of employability that reflects both this and the ongoing challenges the job entails. What may start as a useful tool may become a standard against which professionals are monitored, and if AI can do the job round the clock without error or fatigue, how can a human compete? The flip side is the potential for over-reliance on automated output, resulting in a gradual erosion of first-hand critical thinking and ethical decision-making. A computer spitting out the answer is likely to diminish a perspective otherwise honed over years of experience. Also, if AI handles less-challenging patients, what does that mean for those whose shift comprises only the most difficult, cognitively- and emotionally-draining cases? Burnout is a key driver of the healthcare staffing crisis worldwide, so AI must empower personnel by supporting professional autonomy and satisfaction, not add to existing burdens (Chen et al, 2023). This links closely to accountability and ethical concerns. Where AI is involved in challenging, life-altering decisions, what should be done if there is a significant discrepancy between the healthcare professional’s clinical judgement and the AI’s recommendation? Where does moral, legal, and regulatory responsibility lie? Who ultimately controls AI and how can they be held to account for their creation?
At the same time, the cost of developing, training, and deploying AI in healthcare will be staggering. While many such applications will eventually lead to greater efficiencies, the up-front costs will take decades to recover and, in the meantime, costs will be borne by taxpayers or through higher healthcare or insurance charges. Financing healthcare is a key component of the current crisis, and aging populations with more complex health needs will only fuel further rationing of care, exacerbating existing digital, financial, and other inequalities of access. Some would argue that the millions invested in AI now would be better spent repairing dilapidated hospitals, reducing waiting times, eliminating barriers to healthcare, and addressing staff attrition. Perhaps we should get patients out of corridors, and healthcare staff on a salary commensurate with the job they do before we boost the profits of technology companies. Others counter that investment in AI in the areas of prevention, screening and early diagnosis is exactly what will reduce pressures throughout healthcare and achieve a far better outcome for patients, staff, and society.
So, is AI a foe? In the short-term, I believe not, as these tools complement and augment rather than replace the professional. We are in a honeymoon period, playing with possibilities across myriad medical arenas and the future appears one of boundless potential. However, AI’s longer-term prognosis is much more uncertain. Computing advances will continue to be rapid and ultimately transformational - the AI we marvel at today will not be the AI we experience in twenty- or thirty-years’ time. Our grandchildren’s medics will not be trained or practice medicine in the same way ours do today, but there will still be doctors, nurses, paramedics, and myriad other professionals striving to give us the best possible healthcare. These professions will necessarily adapt and evolve in response to AI and any other impacts the future holds, but the obstacles that must be overcome are significant.
There is however one area where AI can only scratch the surface - our humanity. Empathy, caring, and compassion lie at the heart of the practitioner-patient relationship and have the power to instil courage, inspire trust, and banish isolation. Despite its advantages, beneath AI’s carefully-constructed veneer lies a machine. Deep down we will always know that and so continue to value human contact (Ruggeri, 2024). Equally, once AI’s novelty wears off and its inherent negatives have emerged, like Pandora we may not be able to put them back in the box. So, the challenge for us now is to establish ethical and regulatory frameworks that balance leveraging AI’s benefits while addressing its challenges and ensuring the well-being of professionals and patients alike. AI should be regarded as a co-pilot rather than an auto-pilot, retaining human oversight and patient contact as sacrosanct. Regulation must also remain flexible enough to cope with the unpredictable course AI is likely to take, and recognise that it will not develop in isolation but will integrate exponentially with other developing medical innovations such as nanotechnology and robotics. But that is a whole other essay…
1,592 words (excluding title and references).
References
Abubaker B.S., Ibrahim N.K., Abubaker B.H., Hashem A.R., 2022. Covid-19 and Artificial Intelligence: Genome sequencing, drug development and vaccine discovery. J Infect Public Health. February;15(2) Pp289-296. Available at www.pubmed.ncbi.nlm.nih.gov/35078755 (accessed 15 March 2024).
Chen, V., Liao, Q.V., Vaughan, J.W., Bansal, G., 2023. Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations Proceedings of the ACM on Human-Computer Interaction, Volume 7 Issue CSCW2 Article No: 370, Pp 1–32. 04 October 2023. Available at www.dl.acm.org/doi/10.1145/3610219 (acessed 16 March 2024).
Community Practitioner, 2023. Artificial Intelligence in Healthcare: Friend or Foe? 13th November 2023. Available at www.communitypractitioner.co.uk/artificial-intelligence-in-healthcare-friend-or-foe (accessed 12 March 2024).
Cowan, H., 2023. AI in Medicine: Friend or Foe? Readers Digest Health. Published 18th October 2023, available at www.readersdigest.co.uk/health/ai-in-medicine (accessed 12 March 2024).
Esteva, A., Kuprel, B., Novoa, R.et al., 2017. Dermatologist-level classification of skin cancer with deep neural networks, Nature 542, P115–118.Published 25 January. Available at www.nature.com/articles/nature21056 (accessed 16 March 2024).
Kizilcec R.F, Shung D.L., Sung, J.J.Y., 2024. Human-machine interaction: AI-assisted medicine, instead of AI-driven medicine. From Chapter 10 in Artificial Intelligence in Medicine, ed. Sung J.J.Y., Stewart C., Academic Press, Pages 131-140. Available at www.sciencedirect.com/science/article/abs/pii/B9780323950688000108 (accessed 20 March 2024).
Kumar, Y., Koul, A., Singla, R. et al., 2023. Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda. Journal of Ambient Intelligence and Human Computing 14, Pp 8459–8486. Published 13 January. Available at www.link.springer.com/article/10.1007/s12652-021-03612-z#Abs1 (accessed 24 March 2024).
NHS England, 2023. Artificial Intelligence (AI) and Machine Learning. Version 1.1, 14 June. Available at www.england.nhs.uk/long-read/artificial-intelligence-ai-and-machine-learning (accessed 18 March 2024).
Ruggeri, A., 2024 Artificial Kindness, New Scientist, 9 March, Pp 33-35.
St Pierre S.R., Peirlinck M., Kuhl E., 2022. Sex Matters: A Comprehensive Comparison of Female and Male Hearts. Frontiers in Physiology, 22 March. Available at www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2022.831179/full (accessed 17 March 2024).Discuss the impact of the difference in healthcare access between populations of different socio-economic backgrounds.
The accessibility of healthcare services, both on a national and international scale, is heavily impacted by the socio-economic circumstances of a patient, a family, a community and on a much wider scale, society. Socio-economic backgrounds are just one of the many factors that affect the healthcare one receives, and it intersects closely with other ‘social determinants of health’, a term coined by Sir Michael Marmot in his book ‘The Health Gap’, which describes factors that influence an individual’s well-being. These include education, housing, employment, and forms of discrimination that will impact the accessibility and quality of healthcare received, all influenced by the more wide-scale factors of politics, economics and social policies. It is often very easy to accuse lifestyle habits and ‘choices’ as the primary cause of ill-health, however it is important to revise this perspective and realise that socio-economic factors and its interconnected components play a very crucial role, perhaps more important than lifestyle factors, in determining one’s health outcomes.
It is very easy to assume the extremes in socio-economic backgrounds and simply consider the two opposite ends – being rich and poor. It is a known fact that the rich have better healthcare access, primarily due to accessing healthcare whenever and wherever – using both public and private healthcare. When considering other factors, the rich are put at a social advantage, and tend to have higher qualities of life. They are better predisposed to prioritising their health by eating well, ensuring healthy lifestyle choices are made, such as regular exercise, managing stress and taking up early detection and treatment opportunities. On the other end of the spectrum, the world’s poorest evidently experience poorer health outcomes, with higher rates of social disadvantage. However, it is important to understand health inequalities through the lens of the ‘social gradient of health’, which describes how an individual’s socioeconomic position will impact their health. This is the idea that health inequalities affect everyone, and their position on the socioeconomic spectrum is determined by alterable social injustices that perpetuate unfairness and the social classification of health.
These health inequalities manifest in individuals’ ability to access healthcare of a certain quality. In this essay, I will explore the relationship between socio-economic backgrounds and healthcare access through the lenses of financial burdens, geography, limited resources, health literacy and stress, and delve into its impact on proportionally disadvantaged groups.
Financial constraints can severely limit access to healthcare. Particularly in countries without universal healthcare systems, individuals must seek health insurance or health insurance premiums. For those where these payments are financially constraining, the cost of medical care is not covered. This means healthcare services, including regular routine check-ups, purchasing medication, and preventative screenings are made inaccessible to those who cannot afford the high cost. Additionally, to relieve financial pressure, individuals may choose to delay certain medical appointments, restricting the accessibility of these services, which leads to disparities in health outcomes. The impact of financial constraints strongly intersects with geography and location. Transportation costs come in addition to medical expenses, which can make a medical trip costly, hindering healthcare access for marginalised populations. For example, residents in more rural areas, which may have reduced medical facilities, means these patients, if need be, may have to travel someplace else for the procedure or consultation, and the accessibility and reliability of the transportation system will impact the cost.
Education ensures a fundamental level of health literacy, giving people the knowledge and power to make decisions about their lifestyles, and awareness about how these actions will affect their health. Unfortunately, despite the existence of state-funded education in the UK, there is a greater incidence of low health literacy in low-income individuals. Various studies have investigated the causal relationship between poverty and poor attainment in education across the world. A study released by UCL researchers, which used data from the Millenium Cohort study, found that ‘Children who were most disadvantaged between the ages of 0-5 were four and a half times more likely to do worse at school at the age of 17 compared to those in the highest income group’. The reasons behind this are complex and numerous, but when considering the impact this has on healthcare access, the effects are profound. Without adequate literacy skills, individuals may struggle to comprehend medical terminology they are presented with, along with general advice given to them. This strongly intersects with language barriers for ethnic minorities, which are put at a substantial disadvantage, prohibiting effective understanding for certain treatments and comprehension of the health system. The pressure health systems are under may also perpetuate disengagement from low-income individuals, who may feel apprehensive about seeking an appointment, for fear of not utilising the time properly or not being able to comprehend the information completely. Low-income individuals may also lack access to reliable sources of medical information, including books, the internet and healthcare professionals, which means they are unable to access this information easily. This causal relationship between education and socio-economic position plays an important role in determining health literacy, and therefore access to healthcare.
Among the world's poorest are women. This is a pertinent example of how socio-economic status intersects with gender bias. Women account for 75% of the world’s unpaid work, and because of systemic bias, are often left financially disadvantaged to their male counterparts. Unpaid work includes caring for children, housework and errands for extended family. It is estimated that women do at least twice as much unpaid work as men, totaling up to $10.8 trillion globally. Gender bias has manifested in the form of gender pay gaps and decreased employment opportunities, which has meant that women, on average, are left with a smaller amount of disposable income compared to their male counterparts. This means less money is available for health insurance premiums, medication expenses, and any services that require payment. In addition, women of lower socio-economic backgrounds may live in areas with limited access to healthcare facilities, and face long waiting times due to overstretched systems and underfunding.
High levels of constant stress are strongly associated with poverty, as well as other mental health problems, including depression, schizophrenia and substance abuse, the study ‘Psychological Perspectives on Poverty’, released 2015, found. Financial constraints can cause stress to occur through struggling to prioritise basic needs, such as balancing the need for food, housing and utilities over healthcare expenses One of the main problems with stress is that it causes reduced health-seeking behaviour. This presents several problems. If the patient prioritises more immediate needs, this delays a healthcare appointment, which means they may be missing potentially vital opportunities for detection. High levels of stress can also complicate already quite complicated systems, like navigating the complexities of healthcare systems, from booking an appointment to understanding the advice given. The incidence of stress has been proven to be intrinsically linked to the development of mental health problems, and the symptoms of these conditions may hinder treatments and follow-up care.
The incidence of diabetes is an important example of how the disparity in socio-economic backgrounds affects healthcare access and thus health outcomes. As Sir Michael Hurst, President of the International Diabetes Federation, pointed out, there is a false idea that diabetes is ‘a disease of the wealthy’. Evidence directly contradicts this statement. A systemic review and meta-analysis, carried out in 2011, which investigated the relationship between Type 2 diabetes incidence and socio-economic position, found that lower incomes increased the risk of developing diabetes by 40%. This study took into consideration other factors, and so after statistically controlling for other factors, lower-income males were 94% more likely to have type 2 diabetes while lower income females were 175% more likely to have type 2 diabetes. This data directly disproves the notion that diabetes is highly influenced by lifestyle and choice – and very much at the hands of financial situations, which perhaps restrict choice and freedom. There is much debate about the causation of diabetes by socio-economic position, however one important risk factor was access to healthcare. Diabetic patients need unlimited access to medical care services as the condition requires long-term management, and this is perhaps one of the reasons for its association with poverty. In countries that require health insurance, many low-income families cannot afford this cost, so receive fewer check-ups and examinations. Considering the different environments people live in, access to state-of-art facilities in urban areas is not mirrored in rural areas, therefore disadvantaging rural inhabitants. Additionally, studies have identified more factors that limit diabetics’ access to healthcare, and these include a lack of knowledge of the disease, limited distribution of insulin, institutional factors that hinder uptake and lack of detection clinics. The strong association between poverty and diabetes rates can be linked to healthcare access, which on a larger scale is linked to institutional factors.
One's socio-economic background heavily impacts the healthcare access and healthcare provision received. It is important to consider the ways in which different forms of discrimination are connected to positions on the social gradient through an intersectional lens, to better understand the multiple dimensions of social disadvantage and how they influence health trajectories. These social determinants of health are avoidable, and must be deconstructed to provide more equal, standardised, high quality for anyone accessing healthcare services.
Word count: 1535 words
Referencing:
IJE (2011) Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis [Online] Available at: https://academic.oup.com/ije/article/40/3/804/745640 (Accessed: 01 April 2024).
Bird, Y. et al. (2015) The relationship between socioeconomic status/income and prevalence of diabetes and associated conditions: A cross-sectional population-based study in Saskatchewan, Canada, International journal for equity in health. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4603875/ (Accessed: 01 April 2024).
UCL (2023) Poorest children have worse health and educational outcomes in adolescence, UCL News. Available at: https://www.ucl.ac.uk/news/2023/mar/poorest-children-have-worse-health-and-educational-outcomes-adolescence (Accessed: 01 April 2024).
PPN (2015) A review of psychological research into the causes and consequences of poverty. Available at: https://ppn.nhs.uk/north-west/resources/news/item/a-review-of-psychological-research-into-the-causes-and-consequences-of-poverty (Accessed: 01 April 2024).
Perez, C.C. (2020) Invisible women. Random House UK.
Marmot, M. 2015. The Health Gap. Bloomsbury.
Artificial Intelligence: friend or foe of healthcare professionals?
Will AI cause you more harm than good? There is no denying that the way we work is evolving rapidly and with the help of AI (artificial intelligence), even healthcare is developing at an unforeseen pace. Although, we cannot ignore that AI is still a controversial subject. This essay will explore if the negatives of AI will outweigh the positives it brings to the medical industry, especially to healthcare professionals.
The journey of AI traces back to as early as 1958 when John McCarthy invented the programming language ‘LISP’ which provided data in a more simplified form to enable flexibility for numerous amounts of applications (The Editors of Encyclopaedia Brittanica,2023). From here on, many computer scientists continued to construct, improve, and apply their knowledge to shape AI into its’ best form. We see this a year later, when Oliver Selfridge published; Pandemonium: A Paradigm for Learning,’ proposing a new model which possesses the ability to recognise patterns with the information assigned to it (Selfridge,1988). After these foundations had been set, the AI programme continued to expand with the help of numerous scientists. They extended AI into different systems incorporating new algorithms, data and language to create an interactive programme for many professions to access.
Through the foundational process of ‘LISP,’ we can use this to manage massive quantities of medical research to swiftly retrieve the necessary information to study trends within medicine to aid efficient treatments and provide the best care possible for known diseases. Additionally, AI’s many programmes set the groundwork for addressing unidentified diseases in the upcoming future. AI also seeks to analyse personal patient data to accommodate specific care plans by processing a patient’s genetic information as well as other influencing lifestyle factors and symptoms. This will help to: minimize patient waiting times; reduce workload for healthcare professionals and overall improve quality of life.
Worldwide trials have been executed to put artificial intelligence machines to the test so we can see how effective they truly are. In a particularly notable trial, researchers at Moorfields Eye Hospital in London trialled an AI system which resulted in matching over 50 eye diseases with a 94% accuracy rate. Impressively, aligning with many of the world’s best eye experts (England,2019). According to professor Pearse Keane, this system has the ‘potential to be developed further for hundreds of other sight-threatening eye diseases’ which reinforces the idea of AI being able to assist new and upcoming diseases (Lily Ramsey 2023). Additionally, AI systems have undergone trials in other healthcare departments such as the Accident and Emergency (A&E) department to predict those in need of hospital care in the near future, with the aim to reduce waiting times. A study presented by the Office of National Statistics portrayed that the percentage of patients waiting longer than four hours in A&E increased from 8.1% in 2013 to a concerning 42.4% in 2023 (Watts and Waters,2024). In response to this, a trial based in Staffordshire aimed to reduce this by using AI to triage patients so those with worsening conditions can be prioritised and promising results demonstrated a reduction of an average of 35% in attending patients to A&E (Sollof,2022).
However, even though numerous statistics indicate AI to be a useful source in the healthcare field and for those involved within it, there are also negatives to be cautious about. Firstly, AI lacks emotional intelligence in contrast to healthcare professionals because AI’s primary function is to detect and manage data rather than consult patients with empathy and a level of consideration which are both vital characteristics needed in a healthcare environment. An article published by The Lancet conducted a study which showed 79.4% of a group of patients found it worrisome that a computer does not consider feelings (Young et al.,2021). This highlights how emotional understanding is vital for patient satisfaction as not just the physical, but mental needs of a patient need to be attended to for their well-being. Arising ethical issues associated with AI shows how patient confidentiality is one of the key concerns. AI has the potential to automatically share data without full consent, leaving patient data at a substantial risk of potential cyber-attacks. The NHS is proof that these attacks are indeed possible as reported by INews that the NHS endured a large cyber-attack back in August 2022. This incident was a major breach in patient confidentiality, and according to Dr Andrew Molodynski, a mental health lead at the British Medical Association, the AI systems endanger patient care, unlike health care professionals who undergo several training programmes and must abide by codes of conduct to ensure they avoid situations like these in order to promote the patient’s safety first (Dimsdale,2022).
Furthermore, AI is technology-based meaning malfunctions within medical machines and AI systems are highly probable. Such risks could potentially endanger a patient’s life, which could easily be avoided if doctors performed the surgeries. Moreover, technology is always unpredictable despite how many trials machines go through. Therefore, compromising a patient’s survival rate for the sake of time-saving could even be considered cruel and may intervene with the ethical pillar of non-maleficence. This may cause backlash from healthcare professionals as it disrupts a patient’s safety so legal accountability will be left for the professionals to face. Nevertheless, it should not be dismissed that AI allows for new opportunities such as minimally invasive surgery by introducing AI navigation-assisted technology like Imatics. Imatics is a system that aims to develop different targeted therapies to activate the immune system to destroy cancer cells and is still currently on trial which also highlights the promising future of AI within oncology (Immatics,2020). Rather than demoting healthcare professionals, AI serves as a tool to assist them. A multidisciplinary team is vital for the ability to use these new AI devices correctly and ensure the systems run smoothly. Doctors elevate patient care by using their human expertise to review AI-created patient plans and treatments whilst ensuring the right diagnosis is given to improve medical accuracy. As seen from the earlier statistics that 79.4% of patients were anxious about the lack of emotional intelligence in AI, it becomes visible how essential healthcare professionals are, to be able to achieve the best standard of care. By harnessing AI’s added knowledge and the emotional awareness of healthcare professionals can create a balance between human and artificial systems to maintain a fast-working, efficient environment for individuals. Instead of interpreting AI as having no emotional awareness as a disadvantage, we can comprehend it as a positive attribute as programmes will avoid biased opinions when dealing with decision-making by looking purely at the facts rather than potential emotional
attachments to patients. Regarding, AI’s potential risks of oversharing patient confidentiality and programmed malfunctioning, it is important to recognise that as humans we are all prone to human error meaning, that healthcare professionals also have the potential to overshare patient’s private information and make surgical mistakes accidentally. This does not mean they are not necessary within the healthcare field. Similarly, AI still fulfils a remarkable, significant role in improving the healthcare system alongside healthcare professionals. Falsely, AI is often seen to eventually ‘take over’ human jobs and roles but instead, it adds more responsibility for humans, especially for medical practitioners such as nurses and care assistants. AI can attend to tasks such as organising paperwork or tracking patients’ progress which frees up time for nurses to focus on the patients’ needs and enhance their expertise that may benefit future patients. Studies from the University of Southhampton state,’86% of registered nurses are reported leaving necessary care undone on their last shift due to lack of time’ which reinforces that nurses are completely overworked meaning they are unable to provide efficient care for everyone. So, with the help of AI, their time can be managed more effectively (Ball, 2015). Medical carers can also educate themselves on new medical knowledge provided by AI while AI can also facilitate them in making certain decisions without consulting with a doctor first meaning, they’re given greater independence to take on more responsibilities.
Is AI a friend or foe of healthcare professionals? Overall, this essay details the specifics of AI’s role in healthcare, expressing both its drawbacks and benefits that AI brings for healthcare professionals. While I believe that healthcare professionals will always continue to be of utmost importance, AI is needed to be able to adapt to new demands in the medical industry, However, AI should always be used with caution giving it all the more reason to why AI systems and professionals should co-exist together for the benefit of upcoming advancements in healthcare. Just like the evolution of man, AI is evolving to accommodate the needs of the medical world and favour both healthcare professionals' and patients’ best interests.
Word Count:1455
Reference List
Ball, J. (2015) “Research shows nurses are short on time, not compassion,” The Conversation, 12 May. Available at: http://theconversation.com/research-shows-nurses-are-short-on-time-not-compassion-41475 (Accessed: April 1, 2024).
Dimsdale, C. (2022) NHS cyber attack hits patient care with records left in ‘chaos’ three months on, iNews. Available at: https://inews.co.uk/news/nhs-cyber-attack-lives-risk-mental-health-care-systems-chaos-three-months-1947561 (Accessed: April 1, 2024).
England, N. H. S. (no date) NHS England » NHS aims to be a world leader in artificial intelligence and machine learning within 5 years, Nhs.uk. Available at: https://www.england.nhs.uk/2019/06/nhs-aims-to-be-a-world-leader-in-ai-and-machine-learning-within-5-years/ (Accessed: April 1, 2024).
Immatics (2020) Immatics. Available at: https://immatics.com/ (Accessed: April 1, 2024).
Lily Ramsey, L. L. M. (2023) World-first AI model can detect eye diseases and predict systemic health, News-Medical. Available at: https://www.news-medical.net/news/20230913/World-first-AI-model-can-detect-eye-diseases-and-predict-systemic-health.aspx (Accessed: April 1, 2024).
Selfridge, O. G. (1988) “(1958) O. G. Selfridge, ‘Pandemonium: a paradigm for learning,’ Mechanisation of Thought Processes: Proceedings of a Symposium Held at the National Physical Laboratory, November 1958, London: HMSO, pp. 513-526,” in Neurocomputing, Volume 1. The MIT Press, pp. 117–122.
Sollof, J. (2022) AI predictive trial in Staffordshire reduces A&E admissions by 35%, Digital Health. Digital Health Intelligence. Available at: https://www.digitalhealth.net/2022/08/ai-predictive-trial-staffordshire-hn-reduce-ae-admissions/ (Accessed: April 1, 2024).
The Editors of Encyclopedia Britannica (2023) “John McCarthy,” Encyclopedia Britannica.
Watts, A. and Waters, M. (2024) Accident and Emergency wait times across the UK - Office for National Statistics, Gov.uk. Office for National Statistics. Available at: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthcaresystem/articles/accidentandemergencywaittimesacrosstheuk/2024-02-28 (Accessed: April 1, 2024).
Young, A. T. et al. (2021) “Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review,” The Lancet. Digital health, 3(9), pp. e599–e611. doi: 10.1016/s2589-7500(21)00132-1.
2022 Essay Winners
Would Decriminalisation of Possession and Personal Use of Drugs Benefit the NHS?
In the UK, it is currently illegal to take, carry, make, or supply drugs, with the penalty ranging between a fine and a prison sentence. However, this approach is not effective, since drug misuse and addiction are widespread problems in our society, and they put immense strain on the NHS every year. Perhaps rehabilitation would be more effective than punishing drug users like criminals- the Executive Director of the Canadian Public Health Association once said, ‘If you want to deal with drugs, you need to deal with the reasons why people use drugs’ (CMAJ, 2014). The decriminalisation of drugs involves ceasing to treat drug possession and personal use as illegal, and I believe that, with increased funding on rehabilitation and mental health facilities, this would greatly benefit the NHS.
Decriminalisation consistently results in lower addiction and substance abuse rates. For example, in 2001, Portugal decriminalised the possession of all drugs for personal use. In 1974, the strict Estado Novo regime ended, and this led to a 27 year-long war on drugs in Portugal. Drug use soared: by 2000, 1% of the population was addicted to heroin, and Portugal had the highest HIV infection rate in the EU. This is when Portugal decriminalised the possession of drugs, and since then levels of drug use have been below the European average (Sellers, 2022). The number of deaths caused by drug overdose fell to just 16 in 2012 (Drug Policy Alliance, 2015): this is a stark contrast to England and Wales, where the total number of deaths related to drug misuse was 1,605 in 2011 (NHS Statistics on Drug Misuse, 2012). This data clearly illustrates how effective decriminalisation was in Portugal, after it led to an enormous decrease in levels of drug use, and the number of deaths due to overdose has plummeted too. Drug users are now treated like unwell patients who need rehabilitation, and addiction is seen as a mental illness. Therefore, I believe that this approach would benefit the NHS since it has proven to be extremely successful in Portugal. It would reduce the strain on the NHS, as drug use rates would likely fall here in the UK too, leading to reduced addiction rates and fewer deaths due to drug overdose. If fewer people are addicted to drugs, the annual cost of drug addiction for the NHS would fall, saving valuable NHS money and resources.
Furthermore, decriminalisation would result in rehabilitation for drug misuse becoming more accessible, thus making it easier for people to get help earlier. People who suffer from drug issues would be less likely to overdose, and fewer people would suffer from long-term health conditions as a result of their drug use. Drug users suffer from a wide variety of health conditions, including mental health issues (depression, anxiety, psychosis, etc.), heart disease, blood-borne viruses, and lung disease (Public Health England, 2022). One example of this is HIV- sharing syringes is the second riskiest behaviour for contracting HIV (Centers for Disease Control and Prevention, 2019). Decriminalisation would result in fewer people sharing syringes, thus reducing the rates of HIV in the UK. The NHS would then be put under less strain, as fewer drug users would be suffering from this chronic condition and fewer NHS resources and funds would need to be allocated to treating and monitoring HIV. Another example is mental health conditions. Drugs can have a drastic effect on your mental health; many affect your mood and can lead users to develop conditions such as anxiety, depression, psychosis, and this can result in suicide. A reduction in drug rates due to decriminalisation would significantly reduce the number of people living with these conditions.
NHS mental health services are already incredibly stretched, and, over time, decriminalisation would reduce the number of people needing to access these services. Annually, drug misuse costs the NHS around £488 million in England (Morse, 2017). I believe that decriminalisation would benefit the NHS because it would reduce the amount of money that the NHS would need to spend on drug misuse, addiction, and treating long-term health conditions as a result of drug use. This money would be better spent on improving rehabilitation facilities and increasing their capacities, and on expanding mental health facilities too. Therefore, this would make rehabilitation more accessible, so drug users would be able to access rehab and mental health support easier. Overall, the cost of drug misuse, addiction, and overdose for the NHS would decrease, and this money would be best spent on improving rehabilitation and mental health care. These services would be under less strain and drug users would be able to access the support they need to recover and reintegrate back into society.
Decriminalising drugs would also reduce the number of people in prison for drug offences. For example, in Portugal, over half of the prison population was there for drug-related reasons (Sellers, 2022). Since drugs have been decriminalised for personal use, this has fallen from 40% to just 15% (Transform Drug Policy Foundation, 2021). It is clear from this evidence that decriminalising drugs for personal use would reduce the number of people in British prisons. Prisons have extremely detrimental effects on both a person’s physical and mental health. The isolation from family, shame, emotional stress, and lack of control in prisons often lead to mental health problems such as anxiety and depression. Many people turn to drugs to deal with these issues, and this, alongside the rampancy of illicit drugs in prisons, often makes people’s substance abuse problems worse rather than better whilst they are in prison. Keeping as many people out of prison as possible would reduce the number of people suffering from severe mental health problems, thus reducing the strain on the NHS. This would, in turn, reduce the number of people turning to drugs as a way of coping with these issues. Prisons are also very damaging to a person’s physical health- people in prisons are disproportionately likely to suffer from chronic conditions, such as diabetes. Health care in prisons is often low-quality and difficult to access, and other problems such as overcrowding and poor hygiene make it challenging for people to live healthy lives whilst in prison. Chronic conditions require years of monitoring and reducing numbers in prisons would lower the number of people living with these conditions. I believe that decriminalising drugs would benefit the NHS because it would lower the number of people in prisons. Therefore, fewer people would develop physical and mental health conditions in prison, thus cutting costs and reducing the strain on the NHS. These costs could potentially fund rehabilitation services, which are cheaper and often more effective than prisons. This could further reduce the number of people with substance abuse issues, as they could be rehabilitated and reintegrated back into society instead of being locked away.
Some people may argue that decriminalisation would increase addiction rates, and the NHS hasn’t got the mental health or rehabilitation facilities to cope with this. An increasing number of people are in contact with drug services in England, and decriminalisation would only cause this number to increase. Very dangerous drugs would become much cheaper and more accessible, which would encourage experimentation and it could lead to an increase in cases of overdose. Also, it could lead to an increase in syringe sharing, which is the second riskiest behaviour for contracting HIV. Drug misuse currently costs the NHS £488 million every year (Morse, 2017), and decriminalisation would only further increase this cost. Overall, some may argue that decriminalisation would not benefit the NHS because it would increase the accessibility of dangerous drugs, hence leading to more cases of overdose. The NHS is already stretched to its limit, and more overdoses would put further strain on frontline NHS workers in busy Emergency Departments. There is not adequate mental health support available to treat the psychological consequences that will follow on from an increase in drug misuse, and HIV cases would rise due to increased syringe sharing. The NHS would not be able to cope with this further pressure with the current level of funding, so decriminalisation would not be beneficial.
In conclusion, I believe that decriminalising the personal use and possession of drugs would benefit the NHS because addiction and substance abuse rates would drop, more people affected by drug misuse would be able to access help, and the number of people suffering from mental and physical health problems due to conditions in prisons would decrease. This would ease a lot of strain from an already-stretched NHS. For decriminalisation to work, I believe that the government would need to increase funding of rehabilitation and treatment facilities, but overall, this would be the best way of tackling addiction and substance abuse in the UK, since individuals are more likely to find recovery in rehabilitation than in jail.
References
CMAJ (2014) Decriminalize drugs and use public health [Online]. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4081223/Sellers, W. (2022) The decriminalisation of illegal drugs: a legal minefield [Online]. Available at: The decriminalisation of illegal drugs: a legal minefield – Will Sellers (royalhospitalschool.org)
Drug Policy Alliance (2015) Drug Decriminalization in Portugal: A Health-Centered Approach [Online]. Available at: https://drugpolicy.org/sites/default/files/DPA_Fact_Sheet_Portugal_Decriminalization_Feb2015.pdf
NHS Statistics on Drug Misuse (2012) Statistics on Drug Misuse- England, 2012 [Online]. Available at: https://digital.nhs.uk/data-and-information/publications/statistical/statistics-on-drug-misuse/2012
Public Health England (2022) Misuse of illicit drugs and medicines: applying All Our Health [Online]. Available at: https://www.gov.uk/government/publications/misuse-of-illicit-drugs-and-medicines-applying-all-our-health/misuse-of-illicit-drugs-and-medicines-applying-all-our-health
Centers for Disease Control and Prevention (2019) Injection Drug Use and HIV Risk [Online]. Available at: https://www.cdc.gov/hiv/pdf/risk/cdc-hiv-idu-fact-sheet.pdf
Morse, G. (2017) Addiction and Substance misuse pathways [Online]. Available at: http://tvscn.nhs.uk/wp-content/uploads/2017/12/Gordon-Morse-Addiction-and-Substance-misuse-pathways-1.pdf
Transform Drug Policy Foundation (2021) Drug Decriminalization in Portugal: Setting the Record Straight [Online]. Available at: https://transformdrugs.org/blog/drug-decriminalisation-in-portugal-setting-the-record-straight
Help improve In2MedSchool by filling in our feedback form.
This will allow us to better support aspiring medics aiming to study Medicine in the UK.
2023 Essay Winners
Designer Babies and Genetic Engineering: The Ethical Considerations
Advancements in the field of genetic engineering have opened up extraordinary possibilities, including the potential to create ‘designer babies’. Designer babies have their genetic makeup intentionally modified to possess specific traits. This concept exhibits the opportunity for medical breakthroughs and the prevention of genetic disorders. Regardless, the complex ethical considerations must be addressed, analysing the tension between our desire to improve the well-being of future generations and the ethical implications of these modifications. It raises fundamental questions about the limits of human intervention in the natural order of life. This essay aims to explore the ethical considerations surrounding designer babies and genetic engineering, exploring the implications for individual autonomy, social justice, the potential unintended consequences, and the essence of what it means to be human.
The concept of parents or society influencing a child’s genetic makeup raises numerous concerns, where it introduces the possibility of overruling an individual’s natural genetic attributes and imposing their desired traits upon them. Utilising genetic engineering as a tool to modify human traits challenges the fundamental principle of individual autonomy – an integral pillar of medical ethics. An individual should have the right to self-determination. To which extent do we consider this practice going too far? Do we have the right to modify the genetic heritage of future generations without their consent? Individuals have a fundamental right to their genetic information and the ability to make decisions about their bodies. It poses ethical dilemmas regarding the balance between parental choice and the child's rights.
The availability of these technologies to create designer babies may hinder the progress that we have made as a society to eradicate social inequalities. Instead, we may exacerbate them. If these technologies become accessible only to the wealthy or privileged communities, it could instigate a divide between genetically-enhanced individuals and those without modifications. In addition to the existing social inequalities, further societal divisions may arise, based on genetic characteristics. This could lead to a society where those who are genetically modified have distinct advantages in areas, such as education, employment, and social standing. Genetic enhancements should be made accessible to all individuals, ensuring social justice and distributing these technologies in a fair and just manner so that there are equal opportunities for all individuals. We do not want a system that prioritises genetic privilege over capabilities and efforts. We want genetic engineering to act as a tool for promoting human well-being and reducing suffering.
Genetic engineering is a novel concept that we have not fully comprehended. We cannot guarantee that the technology lacks the risk of unintended consequences, where it may have long-term effects on individuals and future generations. This is because pursuing designer babies involves altering their genetic code – a complex and intricate system, introducing a considerable level of uncertainty and risk since it is challenging to predict the precise outcomes of genetic modifications. Therefore, it does raise ethical concerns about the potential for unintended harm. Scientists and society should be responsible for thoroughly evaluating the risks and benefits of genetic engineering, before implementing these modifications. It requires rigorous scientific research, transparent evaluation processes, and robust regulations to ensure that genetic engineering interventions are safe and effective. Ethical considerations demand a cautious approach to prevent harm and prioritise the well-being of individuals and society.
The idea of designer babies is a slippery slope in terms of eugenics. Despite the potential for genetic engineering in the use of preventing severe genetic disorders, there is a risk that individuals may use it for non-essential enhancements or cosmetic modifications. This could lead to a society that places unnecessary importance on specific traits, encouraging discrimination based on natural genetic attributes. Individuals who do not possess these enhanced traits may face marginalisation or prejudice. Unfortunately, it would promote a narrow ideal of what is considered ‘desirable’ or ‘normal’, setting unrealistic standards that cannot be attained without alterations. If genetic engineering becomes a widely-accepted practice, it could create a market-driven demand for ‘designer traits’, establishing a two-tiered society for those with financial means to afford to enhance their children’s genetic makeup and others without access to these technologies. However, it is challenging to maintain boundaries and prevent the misuse or abuse of these technologies. There should be careful consideration of the purposes for which genetic engineering is allowed, and strict guidelines to prevent its misuse.
Human nature and identity are fundamental aspects of what it means to be human. The notion of genetic engineering and designer babies challenges our understanding of these concepts, raising ethical considerations. Although genetics shape our physical traits and certain aspects of our cognitive abilities, human nature encompasses much more than our genetic makeup. Human identity is a complex interaction of genetics, environment, culture, and personal experiences. It encompasses our emotions, creativity, moral reasoning, and social relationships. Genetic engineering raises concerns about reducing human identity to mere genetic determinism. This approach overlooks the richness and diversity of human experiences. Our identity is not limited to a predetermined set of genetic traits but due to the relationship between our genetics and the dynamic interactions we have with the world around us. Genetic engineering should be approached with caution, ensuring that it respects and preserves the essence of human nature and identity.
The ethical considerations surrounding designer babies and genetic engineering are complex and multifaceted. While genetic technologies offer the potential to eradicate genetic disorders and improve the quality of life for individuals, we cannot overlook the ethical implications. When we navigate the ethical landscape of genetic engineering, we have to respect individual autonomy, ensure social justice, consider unintended consequences, guard against a slippery slope, and maintain a deep appreciation for human nature and identity. We must engage in comprehensive and inclusive ethical discussions to shape responsible guidelines that uphold human values and promote the well-being of all individuals. Once the ethical considerations have been addressed, we can harness the potential of genetic engineering while safeguarding against the risks and ensuring that its applications align with our principles and aspirations for a just and fair society.
Word Count: 1001 words
References
Interesting Engineering, 2019. Designer Babies: Gene-Editing and the Controversial Use of CRISPR. (online) Available at: https://interestingengineering.com/science/designer-babies-gene-editing-and-the-controversial-use-of-crispr. (Accessed 19th June 2023)
Scientific American, 2021. A New Era of Designer Babies May Be Based on Overhyped Science. (online) Available at: https://www.scientificamerican.com/article/a-new-era-of-designer-babies-may-be-based-on-overhyped-science/. (Accessed 19th June 2023)
The Guardian, 2017. Designer babies: an ethical horror waiting to happen? (online) Available at: Designer babies: an ethical horror waiting to happen? | Reproduction | The Guardian. (Accessed 19th June 2023)
The Embryo Project Encyclopaedia, 2011. Ethics of Designer Babies. (online) Available at: https://embryo.asu.edu/pages/ethics-designer-babies. (Accessed 19th June 2023)
MIT Technology Review, 2015. Engineering the Perfect Baby. (online) Available at: https://www.technologyreview.com/2015/03/05/249167/engineering-the-perfect-baby/. (Accessed 19th June 2023)
Why Sleep? The Physical and Mental Health Ramifications of Sleep Deprivation
Sleep is one of the most underrated bodily functions that occurs in terms of its benefits to the body. In this essay, I will discuss the various ways that sleep affects us individually and as a national (or global) community.
Sleep is both important physiologically and psychologically in various ways. Physiologically, sleep acts as a recovery period for the body and mind, where the body can repair itself from the activities of the day. After sleeping for the proper amount of time and having good sleep quality, we are better at making decisions as we are more alert. Lack of sleep can be detrimental to both the individual that lacks sleep and the community the individual interacts in. Sleep deficiency can lead to industrial accidents and various diseases, as the body needs sleep to ward off disease. Man-made disasters, for instance, the Chernobyl nuclear plant accident was caused in part by the sleepiness of an operator who had poor sleep. A shorter duration of sleep has also been linked to the development of coronary artery calcification in the concerned individuals, and the presence of which is usually a predictor of coronary heart disease. Lack of sleep is known to negatively affect the immune system of individuals over a sustained period of deficient sleep. Mentally, sleep deprivation can lead to depression and anxiety, which can worsen over a continued lack of sleep. (MedlinePlus, 2017). Despite these glaring effects, it is estimated that around 1 in 3 adults in the United States of America report that they do not get enough sleep or rest evert day. And this results in almost 40% of adults commenting that they have fallen asleep during the day mistakenly at least once a month. (National Heart, Lung, and Blood Institute, 2022).
Sleeping helps to maintain many vital bodily functions, so it heavily impacts health. Consistent, adequate sleep is also a reliable predictor of living a longer and more productive life (healthysleep.med.harvard.edu, 2008). One way sleep does this is by playing an important role in affecting how we perform when we are awake. The amount of sleep alone is not important, but also the quality of the sleep. Decrease in overall sleep time can increase the chances of one forgetting things more easily and being less effective in memory storage, learning, judgement and mood (American Thoracic Society, 2018). Sleep quality can even go so far as to affect the balance and posture of individuals when sleep quality begins to and continues to decrease (Montesinos et al., 2018). This has a knock-on effect on the daily activities the individual undertakes throughout the day.
Sleep cycles consist of five different stages: the wake state, the N1 stage, N2 stage, N3 stage and REM stage (Patel and Araujo, 2018). The body uses the different stages of sleep for different processes, for example the N2 stage, which is the stage of deeper sleep, is used to consolidate information into the memory by the process of sleep spindles. The N3 stage is used by the body to repair tissues and strengthen the immune system. During Non-REM sleep, breathing and heart rates slow. These stages of sleep can be monitored and evaluated using different machines, including an electroencephalogram (EEG). Research shows that the pattern of these sleep stages can be altered by other external factors, for example, biological and clinical factors (Yetton et al., 2018). Different parts of the brain are involved in the whole process of sleep because of the uniqueness of its ability to regulate core processes of the body during its occurrence. Some parts of the brain involved in sleep are the pineal gland, which is responsible for releasing the hormone melatonin, which aids sleep, and the brain stem, which sends out signals to the muscles of the body to relax to prevent people from acting out their dreams whilst they are sleeping. Figure 1 clearly shows the different stages of sleep we are in as the night progresses.
Sleep problems are very common in developed countries, and they exist in different ways. Between 50 and 70 million people in the United States of America are suffering from chronic sleep and wakefulness disorders. These are deficits mainly in either the quality of sleep or the quantity of sleep. Sleep disruption is a term that describes conditions that affect the continuity of sleep. These sleep disruptions are mainly caused by lifestyle choices and other factors for example, other medical conditions. The short-term effects of sleep disruptions are different in both adolescents and adults, these categories can further be divided into healthy and unhealthy or with existing medical conditions. (Medic, Wille and Hemels, 2017). However, there are some implications that occur generally across the whole population. Some of these implications are increased chances of certain diseases like diabetes mellitus and cardiovascular diseases (Chattu et al., 2018).
Interestingly, amidst the long list of consequences, sleep disruption also has some benefits which include energy conservation and modulation of memory (Feriante and Singh, 2020). But it is evident that the disadvantages of sleep disruption far outweigh the advantages of it. Examples of common sleep disorders include sleep apnea, which is a breathing disorder that is prevalent when the individual is sleeping. Sleep apnea causes pauses in breathing for short periods of time whilst sleeping. Sleep apnea is further divided into central and obstructive sleep apnea. The more problematic type of sleep apnea tends to be obstructive because it is associated with a larger range of health problems including pulmonary hypertension and thinking problems (Suni and Singh, 2020). Another common sleep disorder is narcolepsy, which is a disorder of sleep regulation that is caused neurologically. People with narcolepsy often experience uncontrollable and sudden episodes of falling asleep, even during the daytime (Cleveland Clinic, 2020).
In conclusion, sleep is essential for the daily, efficient functioning of the body. Reliant on this underrated process are many processes, and this highlights that high quality sleep for the right duration of time is essential, and not to be considered as a luxury, as sleep is commonly viewed.
References
American Thoracic Society (2018). American Thoracic Society. [online] Available at: https://www.thoracic.org/patients/patient-resources/resources/sleep-and-performance.pdf [Accessed 19 Jun. 2023].
Chattu, V., Manzar, Md., Kumary, S., Burman, D., Spence, D. and Pandi-Perumal, S. (2018). The Global Problem of Insufficient Sleep and Its Serious Public Health Implications. Healthcare, 7(1), p.1. doi:https://doi.org/10.3390/healthcare7010001.
Cleveland Clinic (2020). Common Sleep Disorders: Symptoms, Causes & Treatment. [online] Cleveland Clinic. Available at: https://my.clevelandclinic.org/health/articles/11429-common-sleep-disorders. [Accessed 19 Jun. 2023].
Feriante, J. and Singh, S. (2020). REM Rebound Effect. [online] PubMed. Available at: https://www.ncbi.nlm.nih.gov/books/NBK560713/ [Accessed 19 Jun. 2023].
healthysleep.med.harvard.edu. (2008). Sleep and Health | Need Sleep. [online] Available at: https://healthysleep.med.harvard.edu/need-sleep/whats-in-it-for-you/health [Accessed 19 Jun. 2023].
Medic, G., Wille, M. and Hemels, M. (2017). Short- and long-term Health Consequences of Sleep Disruption. Nature and Science of Sleep, [online] 9(9), pp.151–161. doi:https://doi.org/10.2147/nss.s134864.
MedlinePlus (2017). Sleep and your health: MedlinePlus Medical Encyclopedia. [online] Medlineplus.gov. Available at: https://medlineplus.gov/ency/patientinstructions/000871.htm [Accessed 19 Jun. 2023].
Montesinos, L., Castaldo, R., Cappuccio, F.P. and Pecchia, L. (2018). Day-to-day variations in sleep quality affect standing balance in healthy adults. Scientific Reports, 8(1). doi:https://doi.org/10.1038/s41598-018-36053-4.
National Heart, Lung, and Blood Institute (2022). Sleep Deprivation and Deficiency - What Are Sleep Deprivation and Deficiency? | NHLBI, NIH. [online] www.nhlbi.nih.gov. Available at: https://www.nhlbi.nih.gov/health/sleep-deprivation [Accessed 19 Jun. 2023].
Patel, A.K. and Araujo, J.F. (2018). Physiology, Sleep Stages. [online] Nih.gov. Available at: https://www.ncbi.nlm.nih.gov/books/NBK526132/ [Accessed 19 Jun. 2023].
Sleep Foundation (2023). Available at: https://www.sleepfoundation.org/wp-content/uploads/2023/03/SF-23-069_SleepCycle_Chart_Mobile-768x988.png [Accessed 19 Jun. 2023].
Suni, E. and Singh, A. (2020). Sleep Apnea: Symptoms and Causes. [online] Sleep Foundation. Available at: https://www.sleepfoundation.org/sleep-apnea. [Accessed 19 Jun. 2023].
Yetton, B.D., McDevitt, E.A., Cellini, N., Shelton, C. and Mednick, S.C. (2018). Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks. PLOS ONE, 13(4), p.e0194604. doi:https://doi.org/10.1371/journal.pone.0194604.
2025 Essay Competition
Our next essay competition will launch in early 2025.
More information will be available here and on our social media platforms in due course.