Mental health stigma: the role of dualism, uncertainty, causation and treatability
Bibliographic record
Abstract
Public stigma on mental health has been defined as 'the set of negative attitudes and beliefs that motivate individuals to fear, reject, avoid and discriminate against people with mental illness'. Stigma causes immense suffering to people with mental disorders across the globe. According to a recent Human Rights Watch report, people with mental health conditions are still shackled in 60 countries. Nearly nine out of 10 mental health service users in England have experienced discrimination. Stigma can be perpetuated by people in all walks of life, including the family and friends of those with mental disorders, and healthcare professionals, including those working in mental health. The adverse consequences of stigma include shame, self-blame, isolation and discrimination. Examples of discrimination experienced by people with mental health disorders include others avoiding their company, and education, employment and housing opportunities being withheld. Stigma can deter people with mental health problems from seeking help and leads to poor adherence to treatment. People with mental disorders have high rates of physical comorbidity and higher mortality compared with the general population. The reasons for these health disparities are multifactorial, but discrimination and diagnostic overshadowing are believed to contribute. Mental health stigma has many causes including lack of knowledge and inaccurate beliefs, especially regarding the relationship between mental illness and violent behaviour. In this article, we highlight mind-body dualism and an underappreciation of the similarities that can exist between mental and physical disorders as contributory factors to stigma. Negative assumptions about psychiatry include it involving uncertainty, the causation of disorders being poorly understood and conditions having poor treatability. These are misleading generalisations, but more relevant to this article is the fact that these features can be encountered in both psychiatry and general medicine.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".