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 overlaps with symptoms of depression – lethargy, lack of motivation, neglecting  personal hygiene

• Symptom overlap makes it difficult to distinguish between disorders, e.g., both schizophrenia and bipolar disorder can involve positive symptoms (such as delusions) and negative symptoms (such as avolition)

  • This means the same individual could receive different diagnoses from different clinicians or under different classification systems

• Schizoaffective disorder illustrates symptom overlap; it is a diagnostic category for individuals who show a significant combination of mood disorder symptoms (e.g., depression or mania) and psychotic symptoms (hallucinations, delusions, negative symptoms)

  • There is ongoing debate over whether schizoaffective disorder is genuinely distinct from schizophrenia and bipolar disorder, or whether it simply represents the overlap between them

    • Distinguishing between these three diagnoses is one of the most difficult decisions clinicians face

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 the symptoms of schizophrenia and those of co-morbid/overlapping disorders

  • 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 comorbidities: 50% for depression, 47% for substance abuse disorder, 29% for PTSD, 23% for OCD, 15% for panic disorder

  • If around half of those diagnosed with schizophrenia also have depression, either clinicians are poor at distinguishing the two conditions (a problem for diagnosis), or very severe depression closely resembles schizophrenia - in which case the two might be better understood as related conditions

Evaluation of co-morbidity & symptom overlap as issues in diagnosis

Strengths

• Research into co-morbidity has practical application: van Dee et al. (2023) found that co-occurring symptoms (e.g., depression) reduce the probability of remission in schizophrenia, and that the most impactful co-morbidities differ between individuals

  • Identifying which co-morbidities most affect remission allows treatment to be tailored to the individual, improving prognosis

• Recognising co-morbidity has driven integrated care, where mental health, physical health and substance-abuse services are coordinated rather than separate

  • This matters because medications can interact, e.g., some antipsychotics increase the risk of diabetes, so treating conditions in isolation can do harm

Limitations

• Symptom overlap means early intervention opportunities are missed: initial symptoms of schizophrenia are non-specific (low mood, social withdrawal) and resemble depression

  • This delays diagnosis, which is a serious problem as early treatment predicts better long-term outcomes

• Apparent symptoms of schizophrenia may have non-psychotic origins, e.g., substance use and extreme sleep deprivation can both produce psychotic-like experiences

  • Misattribution could lead to someone receiving antipsychotic medication for a condition they do not have

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

• Escobar (2012) points out that (overwhelmingly white) psychiatrists may tend to over-interpret symptoms and distrust the honesty of Black patients during diagnosis

• Positive symptoms such as hearing voices may also be more acceptable in some cultures because of beliefs about communication with ancestors, so such experiences may be more readily reported

  • To a clinician from a different cultural tradition, they can appear bizarre and irrational

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 

  • However, the study identifies the underdiagnosis without explaining it - later research (Cotton et al., 2009) suggests a mechanism

• Cotton et al. (2009) found that women with schizophrenia typically function better than men, being more likely to work and to have good family relationships

  • This high functioning may explain underdiagnosis: symptoms may be masked, or good interpersonal functioning may make cases seem too mild to warrant a diagnosis

• 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

Issues & Debates

• Diagnosing schizophrenia carries serious social consequences, including stigma and negative stereotypes (e.g., being seen as dangerous or incompetent)

  • Misdiagnosis can result in individuals being incorrectly labelled, affecting employment, relationships, and self-esteem

  • This makes the diagnosis of schizophrenia a socially sensitive issue and highlights the ethical responsibility of clinicians to ensure diagnoses are accurate, culturally appropriate, and handled with care