Causality in mental distress

what is causality/ aetiology

The study of factors, mechanisms and relationships between factors and mechanisms that cause mental distress

what is causal attribution

every-day, common-sense explanations of behaviour and its consequences

How is clinical psychology predicted

Sufficient causes

The outcome (Y) should always occur when causal factor is present

• Currently none for mental distress

• e.g., depression does not always occur after abuse, low serotonin, poverty, inequality, bullying etc.

Necessary causes

Y never occurs without the prior occurrence of X. Currently none for mental distress

Insufficient causes 

Y occurs only after X occurs alongside another variable (Z). E.g., a person might develop schizophrenia (Y) only when they carry a genetic susceptibility (Z) and are exposed to a life stressor (X)

Difficulties with causality in mental distress

• cross sectional studies- not prospective

• impossible to include all influences due to time periods, different places & interactions

• practical & ethical limitations in manipulating influences (e.g., ethnicity & trauma)

• sensitive~ sampling bias

• often not aware of/ cannot articulate all factors 

• unconscious biases (e.g., norms & values) 

• measurement- lack of validity on diagnostic categories, descriptive labels, can have different forms 

3 broad approaches to study causality

• deductive approach

• inductive approach

• epidemiological approach

Deductive approach

Tests a theory of causality using pre-determined values (surveys, experiments)

Inductive approach 

Explores experiences, and links them to causal theories OR devise new causal theories (case studies, interviews, focus groups) 

Epidemiological approach

Studies determinants and distribution of health-related topics.

Outline a survey method

• Ask participants directly about the occurrences of variables associated with distress. (Clinical interviews, self-report questionnaires)

• Participants can be sampled via quasi-random sampling. e.g., every 20th person on electoral register.

• Uses a predefined range of variables of interest.

Advantages of survey methods

• Useful if large random samples are used together with valid and reliable clinical instruments

• Explores real variation in influences and mental distress

• Can be used longitudinally

Disadvantages of survey methods

• Data depends on the questions being asked and the preconceptions of the researcher

• Depends on what participants are able and willing to tell the researchers

• Some people with relevant mental health experiences might be excluded if quasi-random sampling is used

Outline experimental method 

• Manipulate a variable (X) to explore its effect on another variable (Y)

• Random sampling of participants

• The sample is then divided into an experimental and a control group

• Differences are compared between the groups in a set of relevant measures.

• e.g., RCTs

Advantages of experiments

• Can provide the strongest inference of causality

• High internal validity since they provide a controlled environment

Disadvantages of experiments 

• Cannot be generalised to the entire population (small sample)

• Does not test hypotheses

• Can be difficult to relate back to quantitative findings (specific)

Epidemiogical studies

• Medical approach

• Study the determinants and distribution of health-related topics.

• Frequently uses clinical information gathered by doctors and other professionals

• Studies how frequently diseases occur in different populations

• Link variations in the prevalence of diseases to other variables

  • e.g., SES, lifestyle choices, employment history…

Advantages of epidemiological studies:

• Often provides the most comprehensive picture of associations between demographic characteristics, lifestyle variables, and distress

• Can access in-patient, clinic and hospital populations (and community samples)

• Can be more effective than survey methods due to its access to clinical information

Disadvantages of epidemiological studies

• Data is based on diagnostic categories, which are argued to lack validity

• Prone to pre-existing biases that are difficult to measure

relational factors

• families

• early experiences

• trauma & abuse

biological factors

• neurotransmitters

• brain structure

• genetics

social factors

• inequalities/poverty

• gender/sexual orientation

• ethnicity/disability

Models

• Neurodevelopmental models

• Trauma models

• Traumagenic neurodevelopmental models

• Biopsychosocial models

What is the biomedical model (BMM)

• Assumes that individual differences in biological processes

• E.g. neurotransmitters, genes, brain structure and functioning cause mental distress.

  • Serotonin hypothesis- depression caused by low levels of serotonin= low mood

  • Dopamine levels and schizophrenia

  • Temporal lobe and schizophrenia

  • Frontal lobe and depression

• There is no meaningful distinction between mental and physical diseases

• Mental distress can be treated with biological treatments

Erritzoe et al study (2023)

• Brain imaging comparing 17 ppts with depression to 20 healthy controls.

• Gave amphetamine to stimulate serotonin release

• Measured how much serotonin was binding to receptors in the brain using radio-active tracing.

• Participants diagnosed with depression had a lower level of serotonin compared to controls

• Suggests reduced neurotransmission of serotonin in people with depression

Early 20th century methods 

• Penicillin 

• Electro-convulsive therapy (ECT) to stimulate activity in regions of the brain.

• Lobotomies as a treatment approach, e.g. for depression and schizophrenia

Psychopharmological revolution (1950s-1960s)

• Medication to reduce mental distress

• Introduction of the chemical imbalance theory of depression.

• Publication of DSM-III in 1980 introducing diagnostic criteria for mental distress.

• Marketing of biomedical advances and growing collaborations with the pharmacological industry.

• Growing ties between patient advocacy groups, APA, and National Institutes.

Criticisms of BMM

• No clear evidence for the chemical imbalance theory when pooling results together

  • Moncrieff et al., 2022; Read & Moncrieff, 2022

• SSRI efficacy does not prove that depression is caused by reduced levels of serotonin

  • Lacasse & Leo, 2005.

• Biological differences might result from medication or mental distress

  • Causal relationship is the other way around

  • (e.g., Moncrieff et al., 2022), which is often not controlled for in research)

Schmall et al (2015) 

• Looked at hippocampus

• Depression associated with smaller hippocampus

• Hippocampi volume positively associated with number of depressive episodes

Criticism of Schmall et al

Criticisms

• Promotion, research funding, and selective reporting (Deacon, 2013; Ioannidis, 2008).

• Biomedical beliefs might increase stigma (Clement et al., 2010; Schomerus et al., 2012)

• Validity of diagnostic categories (e.g., DSM) – can we even identify biomarkers for such heterogeneous experiences?

  • E.g., depression can be diagnosed with 227 different symptom combinations

• Reductionist

  • Is it realistic to ignore non-biological factors that might cause distress?

  • Does it map onto the causal beliefs that people have about their own experiences of mental distress?

Read et al (2015)

• Large sample of > 1800 ppts in New Zealand who were prescribed anti-depressants

• Were asked their causal beliefs- Diverse range of causal beliefs, e.g. chemical imbalance, stress, relationship problems, childhood trauma

• Those with biomedical causal beliefs thought of anti-depressants as more effective

• But – sampling bias

Kemp et al (2014) 

• Experiment in ppts with recurrent depression:

• Ppts were either told that they had low (condition 1) or normal (condition 2) serotonin levels

• Measured expectations about prognosis/recovery

• Ppts in the ‘low serotonin’ condition were more pessimistic about their recovery 

Larkings et al (2017)

• Thematic analysis of semi-structured interviews with 23 service users

• Participants felt that causal beliefs were important, frequently thought about them

• But, were rarely addressed in treatment

•  Could increase insight, symptom management, and reduce self-blame

• Congruence with clinician is key for therapeutic alliance and recovery process