Causality in mental distress Flashcards
1
Q
what is causality?
A
- Aetiology or causality is the study of factors, mechanisms, and relationships between factors and mechanisms that cause mental distress
○ Factors that cause mental distress specifically- Often we immediately think about causes e.g. problems at uni, relationships- these are causal attributions
- Causal attributions are every day, common sense explanations of behaviour and its consequences
- Causality is not a straightforward concept because we cannot see it- we do not see causality happening in the real world
- Clinical psychology is predicated on notions of causality
○ E.g. most clinical interventions assume that changes in one variable (for example dysfunctional thoughts) will lead to changes in mental distress (for example, reduced anxiety) - Clinical psychologists will therefore develop causal models that are trying to explain relationships between variables that could cause mental distress
- Causal models are then used to inform psychological assessment and clinical interventions
Clinical psychology does not doubt causality- interventions change causal factors to reduce mental distress e.g. reducing anger problems to eliminate violent behaviour (assuming a causal relationship)
2
Q
thought experiment
A
- Used to show how we can only infer causality because of observed relationships that we can see- wet grass outside so we assume it has rained
- Correlating rain with wet grass so we can understand how the physical world works
Large debate about whether looking at causal relationships reflects what exists or whether we assume it to make sense of what is happening around us
- Correlating rain with wet grass so we can understand how the physical world works
3
Q
how do we establish causality?
A
- Covariation: If X is a cause of Y, then X should occur more often than not when Y is present
- If we think that someone engages in binge drinking as a result of negative emotions, this means that more often than not they drink when they feel low. Many people do it in certain contexts e.g. only when in a social setting not alone- hard to establish covariation in research
- Problems with covariation- hard to establish a causal relationship because there could be a third variable that causes both variables e.g. broken relationship causes negative emotions and binge drinking
- We need to know that the cause proceeds the mental distress in time to establish a causal relationship
2. Temporal precedence: the cause must precede mental distress in time
3. Alternative explanations: must be able to exclude any alternative explanations for the causal relationships
4. Logical connections: must be able to explain how X causes Y - Where psychological theory comes in
Important for causal models to explain how they lead to mental distress
4
Q
causality in mental distress
A
- Causality in mental distress is probabilistic, which means that causal influences change the likelihood of mental distress occurring
- There are many possible causes of mental distress and often there is more than one causal influence
○ Any type of model has to be able to account for different causes not just one factor- cannot be reductionist - Causality in mental distress is ‘over determined’ which means that mental distress can often be explained in more than one way
○ Often mental distress can be explained by multiple valid explanations which can account for why mental distress developed but some exclude each other e.g. biomedical model vs social model- both are often not true at the same time (over determined) - Causal influences on metal distress operate contingently, meaning they interact with each other in way that are difficult to predict and to identify
○ Operate contingently- interact and depend on each other
Difficult to predict how and when they will interact with each other e.g. stress and trauma interact with neurological processes but difficult to predict which trauma/which processes
- There are many possible causes of mental distress and often there is more than one causal influence
5
Q
sufficient causes
A
- Y always occurs after X
○ For example, the consumption of carbohydrates and glucose rich foods (X) can lead to raised blood glucose levels (Y) in people who have diabetes- But Y can also occur in the absence of X
○ There are no identified sufficient causes for mental distress
For example, depression does not always occur after abuse, low serotonin, poverty, inequality, bullying etc
- But Y can also occur in the absence of X
6
Q
necessary causes
A
- Y never occurs without the prior occurrence of X
○ For example, an STI (Y) never occurs without the prior occurrence of sexual contact (X)- But X can also occur without leading to Y
For example, not everybody who is depressed has low serotonin, or experienced bullying, abuse, poverty etc
- But X can also occur without leading to Y
7
Q
insufficient causes
A
- Y only occurs after X occurs with another variable (Z). Y does not occur when X occurs alone
○ For example, a person might develop a particular condition such as schizophrenia (Y) only when they carry a genetic susceptibility (Z) and are exposed to a life stressor (X)
For mental distress, there are only sufficient causes- and there are many insufficient causes that interact with each other
8
Q
difficulties
A
- Many studies (and clinical assessments) are cross sectional rather than longitudinal
○ The evidence measures mental distress and causal factors at the same time- there are ways in which we can measure experiences before mental distress e.g. attachment and personality so we can guess a causal relationship but nothing is longitudinal (follow people over time and measure causal factors and mental distress)- Difficult to prospectively study important influences. For example, the impact of parenting practices only becomes apparent many years later
- Many influences occur over different time periods, happen in different places and interact with other variables
- It is impossible for studies to include all important influences
○ Researchers have to choose what to measure- selection bias - Practical and ethical limitations in manipulating causal influences on mental distress to establish cause and effect e.g. ethnicity
○ Best test of causality is if we manipulate a causal factor and see if it induces mental distress but it is hard to manipulate factors such as trauma and socioeconomic status in a lab - Many important influences are sensitive- sampling bias
○ Sensitive for participants to talk about trauma- end up with a sampling bias in studies where participants who are more comfortable in engaging with the topic participate
○ Might not capture results for people who find this matter very triggering - We are often not aware of all factors that lead to feeling distressed. It is difficult, not impossible to articulate all causal influences on ones distress
○ Hard to identify what it is that makes you have a low mood- often takes years of analysis to discover the cause of mental distress - Researchers and clinicians may have (unconscious) biases that influence measurement and models
- Causal attributions are always influenced by social and cultural norms and values
- How we measure mental distress can limit the conclusions we draw e.g. the lack of validity of the diagnostic categories used in research
○ When people are diagnosed with different forms of mental distress they have to have 5/9 symptoms present (from DSM)- if you create a depressed and non depressed group they won’t be that different (median split)- this makes it hard to detect causality
Also different combinations of symptoms and experiences- people in each group are not similar to each other so it is hard to find a common causal factor
9
Q
‘schizophrenia does not exist’
A
- These authors argue that what we call schizophrenia refers t a spectrum, where people are more vulnerable to hallucinations
Criticism about mental distress- people often get categorised but it does not refer to real forms of mental distress in the real world
10
Q
methods to study causality
A
- Deductive approach- tests a theory of causality using predetermined variables e.g. surveys, experiments etc
○ Preconceived theories about factors that cause mental distress then set up an experiment- Inductive approach- explores experiences, and links them to causal theories or devise new causal theories (case studies, interviews, focus groups etc)
○ Researchers have no preconceived ideas- instead capture the experiences of those with mental distress and work backwards - Epidemiological approach- studies determinants and distribution of health related topics
Looks at prevalence in different groups and link to different factors
- Inductive approach- explores experiences, and links them to causal theories or devise new causal theories (case studies, interviews, focus groups etc)
11
Q
survey method- deductive
A
- 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. the electoral register
- Uses a predefined range of variables at interest
○ Start with a theory then measure this - Advantages
○ 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- easier to implement this over time - Disadvantages
○ Data depends on the questions being asked and the preconceptions of the researcher- researcher makes a decision which inevitably means other things are not being mentioned
○ 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
12
Q
experiments- deductive
A
- Manipulate a variable (X) to explore its effect on another variable (Y)
- Participants are sampled in a random way
- The sample is then divided into an experimental group and control group
○ Differences in two groups due to the manipulation of a causal factor - Differences are compared between the groups in a set of relevant measures e.g. RCTs
○ Randomised control trials- follow this experimental design but double blinded (participants and researchers do not know who is in what group and which group is which) - Advantages
○ Can provide the strongest inference of causality
○ High internal validity since they provide a controlled environment - Disadvantages
○ Low external validity- difficult to generalise a controlled environment to the ‘real world’
○ We can’t control many other confounding variables
○ Convenience sample (e.g. student samples) means important causal influences in other groups might be missed
Ethical and practical constraints
13
Q
qualitative studies- inductive
A
- deals with language, images and non numerical data rather than measures, scales or questionnaires
- Does not test preconceived hypotheses
- Many approaches and methods e.g., interviews, focus groups, observation, ethnography
- Advantages
○ Explores how the meaning of causal influences impacts peoples experiences
○ Can help identify the causal order or temporal precedence
§ More in depth and can help identify which causal factor comes first and the interactions between influences interact in mental distress
○ Can tell us something about how different influences interact in mental distress
○ Good for generating new hypotheses for quantitative studies
○ Good for studying complex cases - Disadvantages
○ Cannot be generalised to the entire population
§ Sample sizes are small because analysis is in depth- not about generalisation it is about finding things to test further
○ Does not test hypotheses
§ Based on qual findings you can create quant studies
○ Can be difficult to relate back to quantitative findings
14
Q
case studies- inductive
A
- in-depth analysis of a real life case
- Advantages
○ Useful to generate new hypotheses
○ Helpful to explore complex phenomena
○ Can help to identify rare occurrences
○ Can help identify some the meanings associated with quantitative findings - Disadvantages
Cannot be generalised to the entire population
- Advantages
15
Q
epidemiological studies
A
- Study the determinants and distribution of health related topics
- Frequently uses clinical information gathered by doctors and other professionals
○ Based on medical framework and research- tries to then link the number of diagnoses of mental distress to all of these lifestyle factors they are also measuring - Studies how frequently diseases occur in different populations
- Link variations in the prevalence of diseases to other variables such as SES, lifetsyle choices, employment history
- Advantages
○ Often provides the most comprehensive picture of associations between demographic characteristics, lifetsyle 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
○ Data is based on diagnostic categories which are argued to lack validity
Prone to pre-existing biases that are difficult to measure
- Frequently uses clinical information gathered by doctors and other professionals