Issues in the Diagnosis of Schizophrenia (AQA A Level Psychology): Revision Note

Co-morbidity & symptom overlap

• Co-morbidity is when one patient is diagnosed with two or more mental illnesses

  • E.g,. patients with schizophrenia are at an increased risk for the development of depression as the two illnesses may share a common aetiology and/or genetic basis

  • One of the difficulties in diagnosing a co-morbid patient is trying to ascertain the extent of one illness over another, particularly when there is symptom overlap (e.g. Is this depression or is it part of patient X’s schizophrenia?)

• Symptom overlap is when two or more illnesses share some of the same symptoms

  • e.g., avolition (a negative symptom of schizophrenia) overlaps with symptoms of depression - lethargy, lack of motivation, neglecting  personal hygiene, etc

  • One of the major issues for clinicians when faced with symptom overlap is that the DSM and the ICD use different criteria to classify the same symptoms

    • e.g., the DSM might produce a diagnosis of schizophrenia, whereas the ICD diagnosis might be bipolar disorder for the same set of symptoms

Research which investigates co-morbidity & symptom overlap

• Newson et al. (2021) conducted a meta-analysis of 107,349 adults; significant symptom overlap was found across different DSM-5 disorder categories where criteria do not sufficiently distinguish between schizophrenic symptoms and those of co-morbid/overlapping disorders such as depression

  • Strengths of this study include the use of secondary data, which means that the research process is swift and cost-effective

  • Limitations include a lack of insight into why symptom overlap and co-morbidity occur, i.e. no explanatory power

• Buckley et al. (2009) found that schizophrenia has the following co-morbidities: 50% for depression; 47% for substance abuse disorder; 29% for PTSD; 23% for OCD; 15% for panic disorder

  • Strengths of this study include the support it provides for co-morbidity as a diagnostic issue

  • Limitations include the lack of clarity as to why depression has higher rates of co-morbidity than other disorders

Gender & culture bias in diagnosis

Gender bias

• Gender bias in diagnosis refers to any instances of a person being diagnosed according to their gender, rather than their symptoms

  • E.g., a female is not diagnosed with schizophrenia even when she presents with symptoms, as the clinician may view her as a ‘hysterical female’ rather than taking her symptoms seriously (an example of alpha bias)

• Gender bias may also occur when a clinician does not take a patient’s gender into account when making a diagnosis, e.g. male models of health are used to diagnose a woman

• Clinicians may also not pay enough attention to the fact that the risk factors for developing schizophrenia are different for males and females, so there should be no ‘one size fits all’ approach (an example of beta bias)

Culture bias

• Culture bias in diagnosis refers to instances where a clinician does not take a patient’s culture into account when making a diagnosis

  • E.g., if the Western biomedical model is used to diagnose people from non-Western cultures, it may (and does) result in African patients being overdiagnosed with schizophrenia due to a lack of understanding of culture-specific symptoms

    • e.g. ukuthwasa - this has some symptom overlap with schizophrenia, so a British clinician is likely to make a diagnosis of schizophrenia, whereas in Africa, the symptoms are often seen as spiritual empowerment rather than a psychiatric disorder

Research which investigates gender & culture bias in diagnosis

• Hambrecht et al. (1993) found that males and females are equally at risk of developing schizophrenia, but schizophrenia is underdiagnosed in women 

  • Strengths of this study include the representative nature of the sample, addressing issues such as alpha bias and beta bias in diagnosis

  • Limitations include explanations as to why schizophrenia is underdiagnosed in women and what can be done to address this

• Schwartz et al. (2019) found evidence that African Americans are 2.4 times more likely to be diagnosed with schizophrenia compared with non-African American individuals, which points to culture bias in the diagnostic process and cultural insensitivity on the part of clinicians

  • Strengths of this study include good application, i.e. the findings of this research could be used to inform diagnosis going forward

  • Limitations include the use of rating scales to assess symptoms, i.e. the fine detail of the symptoms is lost when having to apply a standardised measure to them

Link to Issues & Debates:

Mental illness is a socially sensitive topic, so researchers must be particularly mindful of how their research will be interpreted and commented on once it is published. Gender and culture are ‘hot topics’ in the media generally, so how research is conducted and presented must not be seen to perpetuate stereotypes or to encourage prejudice and discrimination of people based on their gender, sexuality, culture or ethnicity.