This category is about topics that are currently being researched about and where key findings are shared.
Here I sit. I am currently having a mental health crisis. But it is temporary. Literally, I approximate a period of six hours until I recalibrate myself. I think of son, my dear prince. I have plans some time this year to gift him my current iMac. I would certainly not like it if he saw me in this state. I wish I was not this reckless with my mental health. I don’t want to destroy all the progress I’ve made so far. But due to struggling with life, I had a micro relapse…
Hello. It’s Betshy here, reflecting from my quiet seaside corner where the waves remind me that healing often begins with understanding the smallest building blocks of life. As someone who has lived with complex mental health challenges, including a major disorder in remission, I’ve come to appreciate how nutrition intersects with our psychological landscape. Today, I explore an emerging yet under-discussed area: the relationship between vitamins and personality disorders.
While personality disorders (such as borderline, narcissistic, or antisocial) are primarily defined by enduring patterns of thinking, feeling, and behaving, growing evidence from nutritional psychiatry suggests that certain vitamin deficiencies or imbalances may influence symptom severity, emotional regulation, and even neurobiology (Bozzatello et al., 2024). This is not a claim that vitamins “cure” personality disorders—treatment remains multifaceted, often involving therapy like dialectical behaviour therapy—but rather an invitation to consider nutrition as a supportive factor in holistic care.
Personality disorders affect how individuals perceive themselves and relate to others, often rooted in genetic, environmental, and neurodevelopmental factors. Symptoms can include intense emotional instability, impulsivity, interpersonal difficulties, and distorted self-image, particularly in borderline personality disorder (BPD), the most researched in this context. Nutritional psychiatry examines how micronutrients support brain function, neurotransmitter synthesis, and inflammation regulation—processes that can modulate these traits. Deficiencies may exacerbate vulnerability, while adequate levels (or targeted supplementation) may offer adjunctive benefits.
Vitamin D stands out for its role in mood, impulsivity, and neuroprotection. Low serum levels are consistently linked to depressive symptoms, anxiety, and suicidal ideation—features that overlap significantly with BPD and other cluster B disorders. A 2023 study found vitamin D deficiency more prevalent in individuals with mood disorders and noted associations with higher depressive severity and agoraphobia in some psychiatric populations (Habib et al., 2023). In BPD specifically, research suggests testing for deficiency is worthwhile, as supplementation may reduce emotional dysregulation and self-harm risk. Vitamin D receptors are abundant in brain areas involved in emotion processing (amygdala, prefrontal cortex); and they modulate serotonin and dopamine pathways. Deficiency may heighten neuroticism and the general “p-factor” of psychopathology.
One study using polygenic scores for vitamin D found higher genetically predicted levels associated with lower neuroticism and overall psychiatric burden, even after controlling for confounders (Avinun et al., 2020). While direct large-scale trials in personality disorders are limited, the broader evidence supports screening and supplementation (typically 2,000–4,000 IU daily under medical supervision) as a low-risk adjunct, especially in northern climates or for those with limited sun exposure.
The B vitamins—particularly folate (B9) and cobalamin (B12)—are critical for one-carbon metabolism, homocysteine regulation, and neurotransmitter production. Deficiencies can elevate homocysteine, a neurotoxin linked to cognitive impairment, depression, and even psychotic features. In psychiatric inpatients, low B12 has been observed across disorders, with some studies noting higher prevalence in schizophrenia-spectrum and mood conditions. For personality disorders, emerging data suggest B-vitamin status influences impulsivity and emotional stability.
A systematic review and meta-analysis of B-vitamin supplementation found benefits for stress reduction in healthy and at-risk populations, with trends toward improved mood (Young et al., 2019). Folate deficiency has been tied to irritability and cognitive fog, while B12 shortfall can mimic or worsen depressive and dissociative symptoms common in BPD. One cross-sectional study in Iranian women linked higher dietary B6 intake to lower depression odds, though B12 showed mixed results. In clinical practice, correcting deficiencies (via blood tests for serum B12, folate, and homocysteine) can support overall mental resilience. Supplementation (e.g., methylfolate or sublingual B12) is sometimes used adjunctively, though evidence remains stronger for mood disorders than pure personality pathology.
Omega-3 fatty acids (often discussed alongside vitamins) show promise in reducing anger, impulsivity, and dissociative symptoms in BPD, per reviews of nutraceuticals in psychiatric disorders (Bozzatello et al., 2024). Zinc and magnesium also warrant mention for their roles in neurotransmitter balance and stress response, with deficiencies potentially amplifying anxiety and emotional lability.
Importantly, vitamins are not standalone treatments. Personality disorders require evidence-based psychotherapy as the cornerstone. Nutritional interventions work best as adjuncts—addressing deficiencies identified through testing rather than blanket supplementation. Factors like gut health, inflammation, and lifestyle (diet quality, sunlight, exercise) mediate effects. Genetic variations (e.g., MTHFR polymorphisms affecting folate metabolism) may influence individual responses.
Limitations in current research are clear: most studies focus on mood or anxiety rather than personality disorders specifically, sample sizes are small, and causation is hard to establish. Confounders like poor diet in severe mental illness or medication side effects complicate findings. Nonetheless, nutritional psychiatry is gaining traction, with calls for routine screening in psychiatric care (Firth et al., 2019).
In my own life and work on betshy.com, I’ve seen how addressing basic nutritional needs can support emotional stability amid life’s storms. For those with personality disorders, a thoughtful discussion with a clinician about vitamin status—especially D, B12, and folate—may open a gentle, supportive avenue for wellbeing. Small, evidence-informed steps can complement deeper therapeutic work, fostering greater self-compassion and resilience.
As research evolves, integrating nutrition into personality disorder care holds promise—not as a cure, but as a compassionate ally in the journey toward stability and growth.
Avinun, R. et al. (2020) ‘Vitamin D polygenic score is associated with neuroticism and the general psychopathology factor’, Personality and Individual Differences, 164, 110052. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC7107583/ (Accessed: 20 March 2026).
Bozzatello, P. et al. (2024) ‘Nutraceuticals in psychiatric disorders: a systematic review’, International Journal of Molecular Sciences, 25(9), 4824. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC11084672/ (Accessed: 20 March 2026).
Firth, J. et al. (2019) ‘The efficacy and safety of nutrient supplements in the treatment of mental disorders: a meta‐review of meta‐analyses of randomized controlled trials’, World Psychiatry, 18(3), pp. 308–324. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC6732706/ (Accessed: 20 March 2026).
Habib, M. et al. (2023) ‘Exploring the relationship between vitamin D deficiency and depression in patients with mood disorders’, Psychiatry Research, 328, 115472. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC10625912/ (Accessed: 20 March 2026).
Young, L.M. et al. (2019) ‘A systematic review and meta-analysis of B vitamin supplementation on depressive symptoms, anxiety, and stress: effects on healthy and ‘at-risk’ individuals’, Nutrients, 11(9), 2232. Available at: https://www.mdpi.com/2072-6643/11/9/2232 (Accessed: 20 March 2026).
The classical psychoanalytic theory of hysteria, developed primarily by Josef Breuer and Sigmund Freud in the late 19th century, represents one of the foundational pillars of modern psychology. It transformed the understanding of a condition once dismissed as “wandering womb” or demonic possession into a sophisticated model of unconscious conflict, repression, and somatic conversion. Although the term “hysteria” has largely been abandoned in contemporary diagnostic manuals (replaced by conversion disorder or somatic symptom disorder), the original theory remains influential in clinical practice, cultural studies, and the history of ideas. This essay outlines the historical context, core concepts, key mechanisms, landmark case studies, and lasting legacy of the classical psychoanalytic theory of hysteria.
In the 1880s, Jean-Martin Charcot at the Salpêtrière Hospital in Paris popularised the idea that hysteria was a neurological disorder triggered by trauma or suggestion. His dramatic public demonstrations of hypnotic induction and symptom reproduction captivated the young Sigmund Freud, who visited in 1885. Freud returned to Vienna convinced that hysteria was not merely neurological but psychological. Collaborating with his mentor Josef Breuer, Freud published Studies on Hysteria in 1895, the foundational text of psychoanalytic theory (Freud and Breuer, 1895). The book introduced the “talking cure” and laid the groundwork for the entire psychoanalytic enterprise.
The central innovation of the classical theory is the concept of conversion. Freud and Breuer argued that hysterical symptoms arise when a psychic conflict—usually sexual or traumatic in origin—is repressed from conscious awareness and “converted” into a physical symptom. The energy of the repressed affect is discharged somatically rather than psychologically, producing paralysis, blindness, convulsions, anaesthesia, or globus hystericus (a sensation of a lump in the throat). This conversion serves two purposes: it relieves the psychic tension (primary gain) and simultaneously expresses the forbidden wish or trauma in disguised form (secondary gain).
Breuer and Freud famously summarised their insight with the phrase: “Hysterics suffer mainly from reminiscences” (Freud and Breuer, 1895). The symptom is not random; it is symbolically related to the repressed memory or conflict. For example, a patient who cannot speak may be symbolically “silenced” by a traumatic secret.
Repression is the cornerstone mechanism. When an intolerable idea or affect threatens to enter consciousness, the ego represses it into the unconscious. The repressed material does not disappear; it remains charged with affect and seeks discharge through conversion or other compromise formations (dreams, slips, symptoms).
The therapeutic counterpart is catharsis—the release of the strangulated affect through verbalisation and emotional abreaction. Breuer’s famous patient “Anna O.” (Bertha Pappenheim) coined the term “talking cure.” Under hypnosis she recounted traumatic memories with full emotional intensity, after which her symptoms disappeared. Freud initially adopted hypnosis but soon replaced it with free association, arguing that conscious recall without resistance was more lasting (Freud, 1909).
The theory was built on detailed clinical material. Breuer’s Anna O. case illustrated how symptoms could shift as memories were uncovered (e.g., contractures appearing on the side opposite the traumatic memory). Freud’s “Dora” case (Ida Bauer, 1905) demonstrated the role of sexual conflict, transference, and dream analysis in hysteria. Dora’s symptoms (aphonia, cough) were interpreted as expressions of repressed sexual fantasies and revenge against her father and Herr K. (Freud, 1905).
These cases also revealed the limitations of the early model. Freud gradually recognised the importance of infantile sexuality and the Oedipus complex, moving away from a purely traumatic aetiology toward a developmental theory of neurosis.
By the early 20th century, Freud had largely abandoned the seduction theory (the idea that hysteria stemmed from real childhood sexual abuse) in favour of fantasy and internal conflict. Later analysts such as Sandor Ferenczi and Melanie Klein further developed the theory, emphasising object relations and pre-Oedipal trauma. The classical model was criticised for over-emphasising sexuality (feminists such as Hélène Cixous and Luce Irigaray saw it as pathologising women’s bodies) and for its lack of empirical rigour. Modern neuroscientific research has partially rehabilitated conversion disorder, showing altered brain connectivity in sensorimotor and limbic regions consistent with Freud’s ideas of repressed affect (Vuilleumier, 2014).
Although the diagnostic label has changed, the classical theory’s insights endure. Conversion symptoms still appear in clinical practice, often in patients with unresolved trauma. The emphasis on unconscious conflict, symbolic meaning, and the therapeutic power of narrative remains central to psychodynamic psychotherapy. In forensic settings, understanding hysterical mechanisms can help distinguish genuine symptoms from malingering. Culturally, the theory illuminates phenomena such as mass psychogenic illness, moral panics, and the somatic expression of social distress in marginalised groups.
In conclusion, the classical psychoanalytic theory of hysteria transformed medicine and psychology by revealing the mind-body connection as meaningful rather than mysterious. From Breuer and Freud’s 1895 Studies on Hysteria to contemporary neuroimaging, the core idea endures: symptoms that appear purely physical may carry profound psychological meaning. Understanding this legacy equips clinicians, scholars, and patients alike to approach somatic distress with empathy, curiosity, and respect for the unconscious.
Freud, S. and Breuer, J. (1895) Studies on hysteria. Standard Edition, Vol. 2. London: Hogarth Press. Available at: https://www.penguinrandomhouse.com/books/264434/the-divided-self-by-r-d-laing/ (Accessed: 18 March 2026).
Freud, S. (1905) Fragment of an analysis of a case of hysteria (Dora). Standard Edition, Vol. 7. London: Hogarth Press. Available at: https://www.freud.org.uk/works/1905/fragments-of-an-analysis-of-a-case-of-hysteria-dora/ (Accessed: 18 March 2026).
Freud, S. (1909) Notes upon a case of obsessional neurosis. Standard Edition, Vol. 10. London: Hogarth Press.
Vuilleumier, P. (2014) ‘Brain circuits implicated in psychogenic paralysis in conversion disorders and hypnosis’, Neurophysiologie Clinique, 44(4), pp. 323–337. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4141772/ (Accessed: 18 March 2026).
I’ve often grappled with questions of identity and stability. Who am I when the world feels unmoored? This personal reflection leads me to ontological insecurity—a profound concept from psychology and sociology that captures the fragility of our sense of self. In this piece, I’ll explore what ontological insecurity is, its origins, causes, manifestations, and implications, drawing on key theorists and contemporary examples. As someone profiling human experiences through a forensic lens, I find this topic not just academic but deeply human, offering insights into why we sometimes feel adrift in an ever-shifting world.
Ontological insecurity refers to a deep-seated anxiety arising from a disrupted sense of being, where individuals lose confidence in the stability of their self-identity, relationships, and the world around them. Coined by psychiatrist R.D. Laing in his seminal work The Divided Self (1960), it describes a mental state where the self feels vulnerable to dissolution, leading to disorientation and existential dread. Laing defined it as the inverse of ontological security—a “centrally firm sense of his own and other people’s reality and identity” (Laing, 1960). In this secure state, one experiences life as coherent and predictable; in insecurity, everyday existence becomes fraught with threats of implosion, engulfment, or petrification—fears of being overwhelmed by reality, turned to stone (emotionally frozen), or invaded by external forces.
Laing’s concept emerged from his psychoanalytic training and existential philosophy influences, particularly object relations theory and thinkers like Martin Heidegger and Jean-Paul Sartre. He applied it to schizophrenia, arguing that psychotic individuals lack the basic existential foundation others take for granted, leading to fragmented self-perception (Laing, 1960). This psychological framing views ontological insecurity as a core feature of severe mental distress, where the self is not “embodied” but constantly at risk. Modern research links it to self-disorders in schizophrenia spectrum conditions, including basic symptoms like distorted bodily experiences or hyper-reflexivity (Sass and Parnas, 2003).
Sociologist Anthony Giddens expanded the term in the 1990s, applying it to late modernity’s impact on identity. In Modernity and Self-Identity (1991), Giddens describes ontological security as the trust in the continuity of one’s self-narrative and social environment, maintained through routines and institutions. Ontological insecurity arises when rapid social changes—globalisation, technological disruption, fluid relationships—erode this stability, leaving individuals feeling unanchored (Giddens, 1991). For Giddens, modernity’s “reflexive project of the self” demands constant self-reinvention, but without solid foundations, it breeds anxiety. This sociological lens highlights how broader structures contribute to personal disquiet, beyond individual pathology.
Causes of ontological insecurity are multifaceted. In psychology, early childhood disruptions—unstable attachments, trauma, or neglect—can undermine the “basic trust” Erik Erikson described, leading to lifelong vulnerability (Erikson, 1950). Laing emphasised how “schizoid” personalities develop defensive detachment to avoid engulfment by others. Contemporary studies link it to adverse childhood experiences (ACEs), where chronic stress alters neurodevelopment, impairing self-coherence (Felitti et al., 1998).
Sociologically, modern life’s liquidity—fluid careers, disposable relationships, digital fragmentation—fuels insecurity. Zygmunt Bauman’s “liquid modernity” (2000) echoes Giddens, arguing that transient institutions leave individuals adrift, constantly renegotiating identity (Bauman, 2000). The COVID-19 pandemic exemplified this: lockdowns, disrupted routines, amplifying isolation and existential doubt. Research post-2020 shows increased ontological insecurity manifesting as identity crises, with many reporting a “loss of self” amid uncertainty (Oakes, 2023).
Manifestations vary. Psychologically, it may appear as chronic anxiety, depersonalisation (feeling detached from one’s body), or derealisation (world feels unreal). In extreme cases, it underpins psychotic experiences, where boundaries between self and other blur (Konecki, 2018). Sociologically, it drives behaviours like compulsive social media use for validation or avoidance of commitments, fearing engulfment. Examples abound: refugees experiencing cultural dislocation often report ontological insecurity, their sense of “home” shattered (Markham, 2021). In everyday life, job loss or divorce can trigger it, eroding the narrative continuity Giddens describes.
Impacts are profound. Ontologically insecure individuals may struggle with relationships, fearing intimacy as a threat to autonomy. In society, it contributes to polarisation, as people cling to rigid ideologies for stability (Urban Studies Institute, 2024). Health-wise, it correlates with depression, anxiety disorders, and even physical symptoms like fatigue, mirroring my own battles with hormonal imbalances.
Coping strategies draw from both fields. Therapeutically, mindfulness and schema therapy rebuild self-coherence (Young et al., 2016). Sociologically, fostering stable communities and routines counters modernity’s flux. As Laing suggested, acknowledging insecurity as part of the human condition can be liberating.
In conclusion, ontological insecurity is the existential unease from a fractured sense of being, rooted in psychological vulnerability and modern societal pressures. From Laing’s clinical insights to Giddens’ sociological frame, it explains much of contemporary disquiet. Understanding it empowers us to rebuild security—one routine, one connection at a time. As I navigate my own path, I find solace in this knowledge; perhaps you will too.
Bauman, Z. (2000) Liquid modernity. Polity Press. Available at: https://www.politybooks.com/bookdetail/?isbn=9780745624099 (Accessed: 10 March 2026).
Erikson, E. H. (1950) Childhood and society. Norton. Available at: https://wwnorton.com/books/9780393310344 (Accessed: 10 March 2026).
Felitti, V. J. et al. (1998) ‘Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults’, American Journal of Preventive Medicine, 14(4), pp. 245–258. Available at: https://www.ajpmonline.org/article/S0749-3797(98)00017-8/fulltext (Accessed: 10 March 2026).
Giddens, A. (1991) Modernity and self-identity: Self and society in the late modern age. Polity Press. Available at: https://www.politybooks.com/bookdetail/?isbn=9780745609324 (Accessed: 10 March 2026).
Konecki, K. T. (2018) ‘The problem of ontological insecurity: What can we learn from sociology today? Some Zen Buddhist inspirations’, Qualitative Sociology Review, 14(2), pp. 50–68. Available at: http://www.qualitativesociologyreview.org/PL/Volume42/PSJ_14_2_Konecki.pdf (Accessed: 10 March 2026).
Laing, R. D. (1960) The divided self: An existential study in sanity and madness. Penguin Books. Available at: https://www.penguinrandomhouse.com/books/264434/the-divided-self-by-r-d-laing/ (Accessed: 10 March 2026).
Markham, A. (2021) ‘Losing your sense of self: Ontological insecurity’, Annette Markham [blog], 6 November. Available at: https://annettemarkham.com/2021/11/losing-your-sense-of-self-ontological-insecurity (Accessed: 10 March 2026).
Oakes, M. B. (2023) ‘Ontological insecurity in the post-covid-19 fallout: Using existentialism as a method to develop a psychosocial understanding to a mental health crisis’, Health Psychology and Behavioral Medicine, 11(1), pp. 1–15. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC10425504/ (Accessed: 10 March 2026).
Sass, L. A. and Parnas, J. (2003) ‘Schizophrenia, consciousness, and the self’, Schizophrenia Bulletin, 29(3), pp. 427–444. Available at: https://academic.oup.com/schizophrBull/article/29/3/427/1879716 (Accessed: 10 March 2026).
Urban Studies Institute (2024) ‘Ontological insecurity in the modern world: Understanding its origins’, Urban Studies Institute, 21 July. Available at: https://urbanstudies.institute/urban-construct-development-dynamics/ontological-insecurity-modern-world-origins (Accessed: 10 March 2026).
Young, F. (2016) A history of exorcism in Catholic Christianity. Palgrave Macmillan. Available at: https://link.springer.com/book/9783319291116 (Accessed: 10 March 2026).
This essay dissects the notorious 2022 Edexcel GCSE Higher Tier Math Paper 1 question. Dubbed the “hardest GCSE maths question of all time,” it stumped countless students, sparking tears and debates. I explore three methods to conquer it—geometric (the intended GCSE approach), polar integration, and trig substitution—proving that no matter the path, the answer remains elegantly consistent. Whether you’re a student honing skills, a parent guiding learning, or simply a curious mind like me, this piece showcases the beauty of mathematical consistency and perseverance.
As a forensic psychoanalyst, I often reserve my opinion on situations that are frequently misunderstood and which cause great offence to particular communities. However, personally, I cannot, I don’t want to, and I will not tolerate any form of romanticisation of those who harm children sexually – the pederasts. Nowadays, there is plenty of that. There are pederast prophets in some religions, pederast presidents in some countries, and pederast people who migrate.
I lay in bed staring at the ceiling. Too many thoughts rush through my mind. Too many memories of injustices which might never end. A repertoire of traumas that I can only wish I could shake off. But I cannot; the scar that sexual abuse left in my life cannot be erased. It cannot be healed. It cannot be forgotten. It haunts me every day…
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When an incident happens, the first questions are usually: How likely is this to happen again? and How worried should we be? Whether you are talking about a workplace accident, a cybersecurity breach, a service outage, or a safety near-miss, measuring probability is how you move from gut feelings to informed decisions. (Aven, 2016)
Probability does not have to mean complicated math. In practice, teams estimate likelihood using multiple lenses: history, exposure, controls, early warning signals, and uncertainty.
Probability here can be understood in two complementary ways: the long-run relative frequency with which the incident occurs (frequentist interpretation) or the degree of belief we assign to the event given the available evidence (Bayesian interpretation). Both approaches are valid and widely used in practice; the choice depends on the amount and quality of data available, the regulatory context, and the need to incorporate expert judgment.
Measuring the probability of an incident — whether a workplace accident, cyber breach, medical error, financial loss, operational failure, or any other adverse event — is one of the most important skills in risk management, safety engineering, forensic analysis, insurance, public health, and strategic decision-making.
The simplest and oldest method applies when all outcomes are equally likely and the sample space is finite and known. In these cases, each outcome has the same chance of happening, making calculations easy. Probability is determined by the ratio of favorable outcomes to total outcomes. This basic principle forms the foundation for more complex probability theories, showing that understanding fundamental concepts can clarify more complex statistical models, particularly in gambling, game theory, and decision-making. Mastering this approach not only helps with basic probability calculations but also improves analytical skills in various real-world situations.
P(incident) = number of favourable outcomes ÷ total number of possible outcomes
Classic textbook examples include the roll of a fair die (P(rolling a 6) = 1/6) or the flip of a fair coin (P(heads) = 1/2). In real incident analysis this approach is rarely sufficient because most real-world events do not have equally likely, exhaustive, and mutually exclusive outcomes. It remains useful for teaching fundamental concepts and for highly symmetrical mechanical systems (e.g., the failure of one of n identical redundant pumps where each has the same failure probability) (Bedford and Cooke, 2001).
When historical data are sparse, unrepresentative, or entirely absent, we often find ourselves compelled to rely on expert judgment to guide decision-making processes.
In such circumstances, the intuition and insights of specialists with relevant experience become invaluable, serving as a compass in the midst of uncertainty.
Bayesian probability offers a robust framework for managing this uncertainty, as it treats probability not merely as a static measure, but as a dynamic degree of belief that evolves and is updated as new evidence arrives. This iterative process of refinement allows us to incorporate additional information seamlessly.
The primary principle governing this process is Bayes’ theorem, which serves as the foundation of Bayesian inference. It illustrates how one can adjust initial beliefs in response to new information. This theorem promotes a more adaptable mode of reasoning and emphasizes the significance of integrating prior knowledge with contemporary evidence, ultimately facilitating improved decision-making.
As additional data becomes available, individuals can revise their perspectives and predictions, resulting in a clearer and more accurate understanding of the circumstances at hand. By consistently employing this methodology, practitioners can navigate uncertainties with greater assurance and ensure their conclusions are informed by the most recent information, thereby enhancing both theoretical and practical applications in fields such as statistics, machine learning, and scientific research.
Posterior probability ∝ likelihood × prior probability
In odds form this becomes particularly intuitive for risk analysts:
Posterior odds = prior odds × likelihood ratio
Bayesian methods are especially powerful in incident risk assessment because they allow the formal combination of sparse failure data with structured expert elicitation. Protocols such as Cooke’s classical method or the Sheffield Elicitation Framework help reduce overconfidence and improve calibration of expert estimates (Aven, 2015).
When historical data exist, the most common practical method is the empirical (or relative-frequency) estimator:
P(incident) ≈ number of observed incidents ÷ total number of exposure opportunities
“Exposure opportunities” must be clearly defined and relevant — for example:
This estimator is unbiased in the long run, which means that as the number of observations increases, the estimates produced will converge to the true value. However, when the incident being measured is rare, the numerator becomes quite small, leading to challenges in the precision of the estimated values; consequently, the estimate can exhibit wide confidence intervals that may limit its practical use. Standard practice in such cases is to report the point estimate together with a 95% confidence interval to provide context and reliability to the results. This is often accomplished using established methods, such as the Wilson score or Clopper-Pearson method for calculating binomial proportions.
Additionally, when the events are particularly rare, the Poisson approximation is typically employed to enhance accuracy. Utilizing these statistical techniques becomes paramount in ensuring that the analysis remains credible and aligned with specific requirements in research, as evidenced in studies like that conducted by Vesely et al. in 1981, which highlights the importance of accurate statistical representation in conveying findings effectively. (Vesely et al., 1981).
When the base rate is extremely low, safety professionals often convert the probability into a failure rate λ (incidents per unit exposure) or mean time between failures (MTBF = 1/λ). For small probabilities, P(incident in time t) ≈ λ × t.
A raw count can mislead if activity levels change. Exposure-based measures normalise incident probability by the number of “chances” an incident had to occur. (Rausand, 2011)
Best for: environments where volume fluctuates.
Watch out for: poorly defined exposure units that do not reflect true risk opportunity.
Fault Tree Analysis begins with the undesired top event (the incident) and works backwards through logical gates (AND, OR, voting gates, etc.) to identify all combinations of basic events that can cause it. Once the tree is constructed, the probability of the top event is calculated by:
FTA explicitly models redundancy, common-cause failures, and human error, making it the industry standard in aerospace, nuclear power, rail, and process safety (NASA, 2011); (Rausand and Høyland, 2004).
Event Tree Analysis starts from an initiating event (e.g., loss of cooling, pipe rupture) and branches forward through the success or failure of each safety barrier to produce possible end states (safe shutdown, minor release, major accident, etc.). The probability of each end state is the product of the branch probabilities along that path.
ETA is frequently paired with FTA in bow-tie diagrams: FTA on the left (threats leading to the top event) and ETA on the right (consequence pathways) (Kumamoto and Henley, 1996).
Bow-tie diagrams integrate FTA (left side: threats → top event) and ETA (right side: top event → consequences) with preventive and mitigative barriers on each side. Quantitative bow-ties calculate incident frequency and conditional probabilities of different consequence severities.
When probabilities are uncertain or dependencies exist, Monte Carlo methods sample input distributions thousands or millions of times to produce a distribution of possible outcomes.
In incident modelling, Monte Carlo is used to propagate uncertainty through fault trees, event trees, or system reliability block diagrams, yielding:
LOPA is a semi-quantitative method commonly used in process safety.
It estimates the frequency of a consequence by multiplying:
Initiating event frequency × product of (1 – probability of failure on demand) for each independent protection layer (IPL)
LOPA bridges qualitative HAZOP and full QRA (CCPS, 2008).
Human errors contribute to many incidents. Methods such as HEART, THERP, CREAM, and SPAR-H assign nominal error probabilities modified by performance shaping factors (stress, training, time pressure, etc.).
Modern approaches increasingly use survival analysis, Cox proportional hazards models, random survival forests, or neural networks trained on historical incident data to predict time-to-incident or conditional probability.
Two teams can give the same probability estimate with very different certainty. Tracking confidence prevents false precision. (Aven, 2016)
Best for: decision-making under uncertainty.
Watch out for: ignoring confidence and treating all estimates as equally reliable.
These methods require large datasets but can capture complex interactions that traditional fault trees miss.
If you want a lightweight way to use these methods without building a full risk model, try this:
This gets you a probability estimate that is explainable, repeatable, and useful even for non-technical readers.
Measuring probability after an incident is less about finding a single “correct” number and more about building a reliable estimate that improves over time. The best teams combine data, structured judgement, and monitoring signals, then keep updating as they learn. (Aven, 2016)
Measuring the probability of an incident is never exact — it is always an informed estimate bounded by uncertainty. The best approach combines historical data where available (empirical), logical modelling of causal pathways (FTA, ETA, bow-tie), expert judgment updated with evidence (Bayesian), and propagation of uncertainty (Monte Carlo). Validation against real outcomes remains essential.
No single method is universally superior; hybrid techniques often yield the most defensible results. The goal is not perfect prediction but better decisions — reducing preventable incidents while accepting that some residual risk is unavoidable.
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