Introduction
Abnormality in psychology is often understood as behaviour that deviates significantly from societal norms, causes distress, or impairs an individual’s ability to function effectively in daily life. Psychologists employ various definitions, such as statistical infrequency and deviation from ideal mental health, alongside theoretical approaches like the biomedical and cognitive models, to conceptualise and address mental illness. While these frameworks provide valuable insights into the nature of psychological disorders, each carries inherent strengths and limitations, particularly in terms of objectivity, cultural relevance, and effectiveness of treatment. This essay explores these definitions and approaches in detail, critically evaluating their applicability and implications. The discussion begins by examining statistical infrequency as a measure of abnormality, followed by Jahoda’s concept of ideal mental health. Subsequently, the biomedical approach, which attributes mental illness to biological factors, and the cognitive approach, which focuses on faulty thought patterns, are appraised with attention to their theoretical underpinnings and treatment efficacy. Through this analysis, the essay aims to highlight the complexities of defining and treating mental illness, advocating for an integrated perspective in modern psychological practice.
Statistical Infrequency
Statistical infrequency defines abnormality as behaviour that is rare or uncommon within a given population. This approach relies on the concept of normal distribution, where behaviours or traits falling outside two standard deviations from the mean are considered statistically abnormal. For instance, an IQ score below 70 or above 130 is deemed rare and thus potentially indicative of abnormality. This method is often used in clinical diagnostics due to its reliance on objective, numerical criteria, providing a seemingly scientific basis for identifying disorders such as intellectual disability (American Psychiatric Association, 2013).
However, while this definition offers a quantifiable measure, it has notable limitations. A key strength lies in its objectivity, as it avoids subjective judgement by focusing on data-driven cut-off points. Yet, it fails to differentiate between desirable and undesirable rarities; a high IQ, for example, is statistically infrequent but not negative. Furthermore, many mental health conditions, such as depression, are relatively common in populations, meaning they would not be classified as abnormal under this criterion despite their impact (Kessler et al., 2005). Additionally, cultural and situational factors are overlooked, as what is statistically rare in one context may be typical in another. Therefore, while statistical infrequency is useful as a starting point, it is insufficient as a standalone diagnostic tool.
Deviation from Ideal Mental Health
In contrast to statistical measures, deviation from ideal mental health, proposed by Jahoda (1958), offers a more holistic perspective. Jahoda outlined six criteria for optimal mental health: an accurate perception of reality, self-actualisation, positive self-esteem, autonomy, environmental mastery, and resistance to stress. Abnormality, under this framework, is identified when an individual fails to meet these standards, highlighting areas of psychological distress or dysfunction.
This definition has the strength of focusing on positive mental health rather than merely the absence of illness, providing a comprehensive view that can guide treatment goals. However, it is not without flaws. The criteria are rooted in Western, individualistic values, creating an ethnocentric bias that may not apply to collectivist cultures, such as those in Japan or Colombia, where group identity often takes precedence over autonomy (Markus & Kitayama, 1991). Moreover, the standards are arguably unrealistic, as few individuals consistently meet all six criteria. Finally, the subjective nature of concepts like self-actualisation makes them difficult to measure scientifically. Thus, while Jahoda’s model is conceptually valuable for understanding wellbeing, its practical application as a diagnostic tool is limited by cultural bias and subjectivity.
Biomedical Approach
The biomedical approach posits that mental illness results from biological factors, including neurotransmitter imbalances, genetic predispositions, brain structural abnormalities, or infections. This model treats psychological disorders akin to physical illnesses, often adopting a reductionist stance by seeking a single biological cause. For example, depression is frequently linked to low serotonin levels, while schizophrenia shows higher concordance rates in identical twins, suggesting a genetic basis (Sullivan et al., 2003). Research using brain imaging further supports this by identifying structural differences in individuals with certain disorders.
A key strength of this approach is its scientific rigour, employing objective methods such as brain scans and genetic testing to provide evidence-based insights. Treatments, including drug therapies like selective serotonin reuptake inhibitors (SSRIs) for depression and electroconvulsive therapy (ECT) for severe cases, often yield quick symptom relief and are widely implemented within the UK’s National Health Service (NHS, 2021). However, the approach is not without criticism. It often ignores psychological and environmental factors, as correlation does not imply causation in biological findings. Moreover, while effective in targeting specific symptoms, treatments carry risks such as side effects, dependency, and ethical concerns, particularly with historical practices like lobotomy. Alternatives like cognitive behavioural therapy (CBT) may offer longer-term benefits with lower relapse rates (Hollon et al., 2006). Additionally, overmedicalisation risks neglecting social stressors. In conclusion, while the biomedical approach offers a robust scientific foundation, its reductionist nature limits its scope, necessitating a broader perspective.
Cognitive Approach
The cognitive approach attributes mental illness to faulty thinking patterns, suggesting that negative schemata developed from early experiences lead to cognitive biases, which in turn influence emotions and behaviours. Beck’s Cognitive Triad, for instance, explains depression through persistent negative views of the self, the world, and the future (Beck, 1967). Similarly, Ellis’s ABC model (Activating event, Beliefs, Consequences) posits that irrational beliefs about events trigger emotional distress, forming the basis for Rational Emotive Behaviour Therapy (REBT) (Ellis, 1962).
This approach is supported by evidence from the effectiveness of CBT, which challenges negative thoughts through reality testing and goal-setting, proving particularly effective for conditions like depression and anxiety with lower relapse rates compared to drug treatments (Hollon et al., 2006). Its focus on empowering individuals to manage their thought processes is a notable strength. However, concepts like schemata are vague and challenging to measure empirically, raising questions about whether cognitive distortions are causes or consequences of mental illness. Furthermore, CBT requires patient motivation and may be less suitable for severe conditions like psychosis. Compared to biomedical treatments, it is slower to produce results, though combined therapies often yield optimal outcomes. Social and cultural factors may also be underrepresented, as the focus remains on individual cognition. Ultimately, the cognitive approach offers practical, long-term strategies but overlooks biological underpinnings, highlighting its reductionist tendencies in a different form.
Overall Conclusion
In summary, defining and addressing abnormality in psychology is a multifaceted endeavour, with each framework offering unique insights and challenges. Statistical infrequency provides an objective measure but fails to account for the desirability of rare traits or cultural nuances. Jahoda’s deviation from ideal mental health presents a holistic vision of wellbeing, yet it is hindered by ethnocentric bias and unrealistic standards. The biomedical approach, grounded in scientific evidence, excels in short-term symptom relief but often neglects environmental and psychological factors due to its reductionist focus. Conversely, the cognitive approach empowers individuals through practical coping mechanisms, though it similarly disregards biological contributions. These limitations underscore the necessity of the biopsychosocial model, which integrates biological, psychological, and social dimensions to provide a comprehensive understanding of mental illness. Indeed, modern psychological practice would benefit from such an integrated framework, ensuring that treatment is tailored to the complex, individual nature of disorders. This approach not only enhances diagnostic accuracy but also improves therapeutic outcomes, reflecting the intricate interplay of factors in mental health.
References
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- Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005) Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62(6), pp. 593-602.
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- Sullivan, P. F., Neale, M. C., & Kendler, K. S. (2003) Genetic epidemiology of major depression: Review and meta-analysis. American Journal of Psychiatry, 157(10), pp. 1552-1562.
