Abnormal psychology Flashcards
Biological aetiology of depression
Biological Explanation of MDD
Genes and DNA:
Genes are made of DNA and dictate structure, function, and behavior.
Humans have ~20,000–25,000 genes on 23 pairs of chromosomes.
Each trait has two alleles (one from each parent).
MDD and genetics:
Specific genes, like the 5-HTT serotonin transporter gene, are linked to MDD.
Two mutated short alleles of 5-HTT → lower serotonin levels → higher risk of MDD.
Neurochemical Explanation of MDD
Neurotransmitter imbalance:
Key neurotransmitters: serotonin, noradrenaline, dopamine, acetylcholine.
Imbalance linked to MDD symptoms.
Serotonin hypothesis:
Reduction in serotonin → increased predisposition to depression.
Cortisol hypothesis (neurogenesis theory):
Focuses on the role of the HPA axis and neuron birth cessation.
Depression linked to:
Reduced neuron growth in the hippocampus and related networks (serotonin, dopamine, norepinephrine).
Overstimulation of the amygdala.
Elevated evening cortisol disrupting circadian rhythms.
Kendler et al (bio)
Aim:
- To investigate whether the heritability of major depression, which past studies estimate to be between 35-45%, holds true in a large Swedish sample.
- To explore potential gender differences in the heritability of major depression.
- To determine if genetic and environmental factors in major depression change over time.
Procedure:
The study utilized 15,493 complete twin pairs from the Swedish Twin Registry, born between 1886 and 1958, whose zygosity was confirmed. Telephone interviews were conducted between 1998 and 2003 by trained interviewers using modified DSM-IV criteria to assess lifetime major depression. Questions covered both “shared environment” and “individual-specific environment” to understand environmental factors affecting the twins’ likelihood of developing depression.
Findings:
- The heritability of major depression was found to be higher in women than men, with a significant difference in correlations between monozygotic and dizygotic twins. The overall heritability of major depression was estimated at 0.38.
- No evidence was found of changing genetic or environmental factors over time, either across birth cohorts from 1900 to 1958 or when split into pre-and post-World War II groups.
- The study confirmed previous findings on the heritability of major depression and revealed potential sex-specific genetic risk factors.
Conclusion:
This study demonstrates that the heritability of major depression is higher in women than in men and that genetic factors play a significant role in the disorder’s development, aligning with previous research. It also shows that genetic and environmental influences on depression appear stable over time, without significant differences across cohorts.
Kendler evaluation
- Correlational Study: No cause-and-effect relationship can be established.
- No Gene Isolation: Specific genes linked to depression were not isolated in the study.
- Self-Reported Data: Life events and depressive symptoms were self-reported, which could introduce bias, especially if men underreport depression symptoms.
- Validity Concerns: Diagnoses made by clinicians, as reported by the interviewees, were accepted, potentially impacting validity, as telephone diagnoses can be less reliable.
- Large Sample Size: The study’s large, homogenous sample strengthens the reliability of the findings and helps mitigate some concerns about the self-reported data.
- Retrospective bias: The past events may be ‘blurry’
Caspi et al (bio)
Aim:
The aim of this study was to investigate the relationship between a genetic predisposition (specifically the 5-HTT serotonin transporter gene) and the development of depression in response to stressful life events. The research sought to determine whether there was a gene-environment interaction (G x E) involving the 5-HTT gene mutation, which could explain individual differences in the susceptibility to depression when exposed to stressors.
Procedure:
Caspi and his team studied a cohort of 847 New Zealanders, all 26 years old, who had been assessed for mental health regularly until age 21. The participants were divided into three groups based on their 5-HTT alleles:
- Group 1 had two short alleles (mutation of the gene).
- Group 2 had one short and one long allele.
- Group 3 had two long alleles.
The participants completed a “Stressful life events” questionnaire covering 14 stressors, such as financial, employment, health, and relationship issues, experienced between ages 21 and 26. They were also assessed for symptoms of depression and suicidal ideation.
Findings:
The study found that individuals with one or more short versions of the 5-HTT gene demonstrated more symptoms of depression and suicidal ideation when exposed to stressful life events, compared to those with two long alleles. The effect was particularly strong among individuals who experienced more stressful events. However, simply having the gene did not guarantee the onset of depression—it was the combination of stressful life events and the gene that significantly increased the likelihood of depression.
Conclusion:
The study concluded that the 5-HTT gene’s interaction with environmental stressors plays a significant role in the development of depression. The research provides evidence of gene-environment interaction, where genetic vulnerability (short alleles of the 5-HTT gene) combined with life stressors increases the risk of depression. However, inheriting the gene alone does not directly lead to depression; environmental factors play a crucial role
Caspi evaluation
- Correlational Study: The study is correlational, meaning no definitive cause-and-effect relationship can be established between the 5-HTT gene and depression.
- Self-Report Bias: Data on stressful life events were self-reported, which introduces potential biases like recall bias—those prone to depression might recall negative events more easily.
- Holistic Approach: The study highlights a holistic view, acknowledging both biological (genetic) and environmental factors in depression, as opposed to a reductionist approach focusing on just one factor.
- Low Reliability: Follow-up studies, such as Risch et al. (2009), failed to replicate the findings, indicating the study may have low reliability.
- Limitations of Gene Expression: Some participants without the gene mutation still developed depression, suggesting that gene expression alone is not sufficient to cause depression.
- The study assumes that serotonin causes depression
Genetic aetiology evaluation
Strengths
- There are several longitudinal case studies and animal research that support the theories.
- The practical application of the theories has led to successful drug treatments that have improved some people’s lives.
Limitations
- Correlational research means that causation cannot be established and bidirectional ambiguity cannot be resolved.
- The Treatment Aetiology Fallacy –that is, the mistaken notion that the success of a given treatment reveals the cause of the disorder.
- Biological explanations cannot explain the range of symptoms associated with depression. There may be cultural and cognitive factors as well.
Cognitive aetiology
Cause of Depression: Rooted in negative automatic thoughts (negative self-schemas around failure, inadequacy, loss, worthlessness).
Key Components:
Negative Cognitive Triad: Negative views of the self, world, and future.
Negative Schemas: Triggered by life events.
Cognitive Biases: Faulty thinking patterns.
Types of Faulty Thinking (focus on 2):
Arbitrary Inference: Drawing conclusions without evidence.
Dichotomous Thinking: Viewing things in black and white (all-or-nothing).
Rumination Theory of Depression
Rumination: Repetitive focus on negative thoughts without solving the issue, making depressive symptoms worse.
Key Aspects:
Rumination vs. Problem-Solving: Rumination focuses on distress, not solutions, leaving people stuck.
Types of Rumination:
Brooding: Maladaptive, passive focus on distress (linked to self-criticism).
Reflection: More neutral, can help problem-solve but may still prolong negative emotions if excessive.
Impact on Depression: Rumination increases negative thoughts and reduces motivation, reinforcing a negative self-view and helplessness.
Depression Cycle: Rumination deepens depression, creating a cycle that’s hard to break.
Gender Differences: Women are more likely to ruminate, which may explain higher depression rates in women.
Treatment Approaches:
CBT, mindfulness, and acceptance-based therapies: Aim to reduce rumination, promote problem-solving, and improve mental health outcomes.
Alloy et al (cog)
Aim: Check if negative thinking ups the risk of depression or relapse in college students.
Procedure:
Freshmen sorted into High Risk (HR) and Low Risk (LR) by cognitive style.
50% had past depression.
Monitored for 5.5 years via stress/depression surveys + memory tests on emotional words.
Findings:
No history of depression: 17% HR vs 1% LR developed depression.
History of depression: 27% HR vs 6% LR relapsed.
HR remembered more negative words.
Conclusion: Negative thinking = key risk for depression onset + relapse.
Alloy evaluation
The study’s longitudinal design and method/data triangulation (e.g., questionnaires, interviews) enhance the credibility of the findings. However, as a natural experiment, it lacks experimental control, so causation cannot be firmly established. While the findings support cognitive vulnerability theory, they also suggest a more complex interaction between cognitive style, stress, and depression, possibly reflecting “domino causality” where multiple factors interplay. Additionally, cognitive vulnerability models inform Cognitive Behavioral Therapy (CBT), which has been effective in reducing depressive symptoms.
Joiner et al (cog)
Aim
Test if depressive (not anxious) thinking patterns (measured by DAS, CCL) lead to depressive symptoms (BDI) after stress.
Procedure
Sample: 119 U.S. psych students (avg. age 19).
Timeline: 2 weeks pre- and post-midterms (stressor).
Tests:
Dysfunctional Attitudes Scale (DAS) (pre-exams): Negative thinking patterns.
Cognitive Checklist (CCL) (pre- & post-exams): Depressive & anxious thoughts.
Beck Depression Inventory (BDI) (pre- & post-exams): Depressive symptoms.
Findings
High DAS + fail → ↑ BDI (more depressive symptoms).
High DAS + pass → no change in BDI.
Low DAS → No depressive symptoms (BDI) (pass/fail irrelevant).
Only depressive thinking patterns (CCL) linked to ↑ BDI, not anxious ones.
Conclusion
Negative thinking (DAS, CCL) → vulnerability to depressive symptoms (BDI) after failure.
Depressive cognitive style is crucial in depression onset.
Joiner et al evaluation
Strengths:
Prospective design: Tracks changes over time, addressing bidirectional ambiguity, and enhancing credibility on cognitive vulnerability and depressive symptoms.
Limitations:
Lack of control: Natural experiment design means extraneous variables could affect results.
Sample issues: Homogeneous group (American psychology students, mean age 19), limiting generalizability to other populations or age groups.
Measure of depressive symptoms: Only measured symptoms, not clinical depression, so it may not fully explain factors leading to Major Depressive Disorder.
Cognitive approach holistic evaluation
- The cognitive approach offers an alternative explanation for depression beyond the biological model.
- It suggests that our thinking patterns can act as a mediating factor in stress, either helping us cope or increasing the risk of depression.
- Optimistic thinking strategies may lower stress levels, potentially explaining why individuals with these strategies are less likely to develop depression.
- Not all pessimists experience depression, highlighting a limitation in the cognitive approach’s ability to fully explain the disorder.
- This limitation suggests that cognitive explanations alone are insufficient; integrating biological and sociocultural perspectives is necessary.
- Theory triangulation, combining cognitive, biological, and sociocultural explanations, forms the foundation of a more comprehensive understanding in modern psychology.
Sociocultural aetiology
Sociocultural Approach:
Mental health shaped by environmental factors (stressors + community resources).
Holistic view vs. other approaches.
Vulnerability Models:
Focus on risk + protective factors for developing disorders.
Cultural Explanatory Models (Kirkmayer):
Cultures define acceptable symptoms for mental distress.
Globalisation → evolving cultural views → rise in certain disorders.
Japan example:
Traditional: Sadness = spiritual growth + family connection.
Modern: Western symptoms of depression more common.
Brown and Harris (socio)
Aim:
Investigate how depression is linked to social factors and stressful life events in women.
Procedure:
458 women in South London surveyed about daily life and depressive episodes. Life events were rated for severity by independent researchers.
Findings:
8% of women (37) became clinically depressed; 33 of them experienced adverse life events.
Social class played a role; working-class women with children were 4x more likely to develop depression than middle-class women.
3 key factors:
Protective factors: High intimacy with husband, leading to higher self-esteem.
Vulnerability factors: Loss of mother before age 11, lack of confiding relationships, unemployment, and having more than 3 children under 14.
Provoking agents: Stressful life events leading to grief and hopelessness.
Conclusion:
Social factors, particularly life stress and social class, are linked to depression. Low social status is associated with higher exposure to vulnerability factors and provoking agents, while high social status is linked to more protective factors
Brown and harris eval
- use of semi-structured interviews to get an in-depth understanding of the participant’s situation as they see it themselves. This increased the credibility of the results
- The sample size of the original study was relatively large, making results potentially more reliable
- However, only females were interviewed so the results may not be generalised to men, but the relationship between stressful events and the onset of depression might be applicable to men as well
- In addition, this study is based on self-reporting of depressive episodes. Therefore, it is impossible to accurately determine the actual extent of depression for each of the women interviewed.
- Finally, this is an example of a survey. Because there is no manipulation of the IV, the findings cannot determine cause and effect. The findings are correlational in that they indicate that there is a relationship between sociocultural factors and depression, but since other variables were not controlled, it is possible that biological vulnerability may also play a role in this study. This is what modern research appears to indicate
Chiao and Blizinsky (socio)
Aim:
Explore the link between cultural values (individualism-collectivism) and the frequency of the 5-HTTLPR S allele, and how this affects the prevalence of mood and anxiety disorders globally.
Procedure:
Data from 29 countries, analyzing 5-HTTLPR S allele frequency, Hofstede’s individualism-collectivism scores, and mental health disorder prevalence. Historical pathogen prevalence was also considered for cultural evolution and genetic selection impact.
Findings:
Strong correlation: Collectivist cultures have higher frequencies of the S allele.
High pathogen prevalence: Linked to more collectivism and higher S allele frequency.
Lower anxiety/mood disorders: Observed in collectivist societies with higher S allele prevalence.
Conclusion:
Supports the culture-gene coevolution hypothesis: Collectivist values may buffer S allele carriers against affective disorders by promoting social harmony and reducing stress, acting as a protective adaptation.
Chiao and Blizinsky evaluation
- cross national scope: draws on data from 29 different countries, enhancing the generalisability of the results
- evidence for culture-gene coevolution, highlighting how sociocultural values can influence the prevalence of genetic traits in an environment
- the studies design is correlational; meaning it cannot establish a cause and effect relationship between cultural values, genetic traits, and depression rates. alternative explanations, such as reverse causality or confounding variables may be present
- potential response bias: cultural attitudes toward mental health can differ massively between different cultures. there may be an underreport or an underdiagnosis
- hofestedes cultural dimensions may not reflect cultural changes accurately→ does the way that Hofestede defines cultural dimensions still remain accurate today?
- doesnt tell us anything cognitive; doesnt explain why people may ruminate
- the study treats cultural values as relatively static, but cultures evolve. changes in globalisation, technology and migration may also have some adverse effects
Sociocultural holistic evaluation
Limitations of Vulnerability Models:
Can’t fully explain why some develop depression under stress.
Strengths:
Helps in prevention by boosting protective factors.
Explains changing prevalence rates (risk/protective factors evolve).
Gene-Environment Interaction:
Social stressors + biological factors → depression.
Highlights value of studying vulnerability factors.
Contrast:
Biological approach struggles to explain social stressor impacts alone.
Prevalence rates
Prevalence: the proportion of a population that has a psychological disorder at a specific point in time. For example, over 300 million people are estimated to suffer from depression, equivalent to 4.4% of the world’s population.
Incidence: The number of new cases diagnosed in a certain period of time within a population. This is often reported over a 12 month period
As with surveys, it should be acknowledged that prevalence rates are only estimates. If everyone in the population has been assessed, the rate found may be higher or lower than the survey estimate.
Differences in prevalence rates:
- Different genders have differing vulnerabilities (i.e. women are more vulnerable if they have:)
- loss of a loved one before the age of 11
- having 3 or more children under the age of 18
- lack of a confiding relationship
- unemployment
- Reporting bias- The artefact hypothesis
- observed more differences in prevalence rates may not reflect true differences but arise from reporting biases or methodological artefacts. This suggests that when both sexes have the same depressive symptoms, women are more likely to be diagnosed
- Cross cultural differences
- for example, between the UK and Japan
- Depression isn’t seen as socially acceptable in Japan. Instead, it is classed as Yuutsu, a low mood for a short period of time, so there will be a lower prevalence in Japan than in the UK
Amenson and Lewinsohn (prevalence)
Aim
To evaluate the artifact hypothesis, which suggests that gender differences in the prevalence of depression are due to differences in reporting and diagnosis rather than actual prevalence differences.
Procedure
- Participants: 998 individuals (312 men and 686 women) randomly selected from voter registration lists in Oregon.
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Methodology:
- Participants completed a 938-item questionnaire, recruited using an announcement mailed to 20,000 residents of Eugene and Springfield, Oregon, including the Center for Epidemiological Studies Depression Scale (CES-D), assessing depressive symptoms.
- Approximately 8-9 months later, participants underwent a 2-hour semi-structured clinical interview conducted by interviewers blind to the questionnaire data.
- Groups: Participants were divided into high, medium, and low symptom groups based on their CES-D scores.
Findings
- There were no significant gender differences in self-labeling of depressive symptoms or help-seeking behavior across symptom groups.
- Men and women with comparable CES-D scores were equally likely to receive a clinical diagnosis of depression, regardless of the interviewer’s gender.
- Agreement between self-labeling and clinical diagnosis was 81% for females and 92% for males.
Conclusion
The findings do not support the artifact hypothesis. Gender differences in depression prevalence are likely due to actual differences rather than reporting or diagnostic biases.
Amenson and Lewinsohn evaluation
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Strengths:
- High ecological validity: The study involved real-life contexts of discussing health and depressive symptoms.
- Large, randomized sample size increases generalizability within the US context.
-
Limitations:
- Cultural Bias: Conducted in the US (an individualistic culture), limiting cross-cultural applicability.
- Temporal Validity: Study is over 30 years old; societal attitudes and knowledge about mental health may have changed.
- Self-reporting Limitations: Women were less likely to self-label as depressed, suggesting potential underrepresentation in self-reported data.
Parker (prevalence)
Aim:
Compare Chinese (Malaysia) vs. Caucasian (Australia) MDD patients on:
Cognitive vs. somatic symptom recognition.
Reasons for seeking help.
Procedure:
50 Chinese + 50 Australian MDD patients.
Questionnaire on symptom frequency, distress, and help-seeking triggers.
Included cognitive (Western) + somatic (Singaporean) symptoms.
Translation + back-translation ensured accuracy.
Findings:
Somatic symptoms:
60% Chinese → somatic symptoms = primary help-seeking reason.
13% Australians → the same.
Cognitive/emotional symptoms:
Chinese → less acknowledgment (e.g., helplessness).
Australians → more emphasis on these symptoms.
Overall: Both groups reported a similar number of somatic symptoms.
Conclusion:
Cultural differences:
Chinese → stigma around emotional issues → focus on somatic symptoms.
Western cultures → focus on cognitive + emotional symptoms.
Parker evaluation
The study used a culturally relevant questionnaire, avoiding the imposition of a Western diagnostic tool, which is a strength. However, the use of DSM-IV criteria to select participants may limit the generalizability of the findings, as it could exclude individuals whose depression does not meet Western diagnostic criteria. Additionally, asking participants to recall the symptom that led them to seek help may be subject to memory distortion and demand characteristics, as patients might expect to emphasize emotional distress in a Western context. The relatively small differences between the two groups may be influenced by the Westernization of Malaysian society, suggesting that further research with more diverse cultures is needed to validate these findings.
Prevalence rates holistic evaluation
Strengths:
- Public Health and Resource Allocation: Understanding prevalence rates allows governments and organizations to allocate resources efficiently, plan mental health services, and address societal needs. For example, the rise in reported depression among youth may encourage investment in school-based mental health programs.
- Cultural and Temporal Insights: Prevalence studies reveal how cultural and environmental factors influence mental health, such as the globalization of Western disorders (e.g., anorexia in Hong Kong) or shifts in social stigma reducing barriers to diagnosis.
- Scientific Progress: These studies highlight the dynamic nature of mental health, showing how diagnostic criteria, improved awareness, or environmental changes can affect the understanding and treatment of disorders over time (e.g., declining schizophrenia hospital admissions due to evolving healthcare practices).
Limitations:
- Cultural Bias: Cross-cultural differences in symptom expression (e.g., somatic expressions of depression in China) challenge the validity of standardized diagnostic criteria. This can result in underdiagnosis or misdiagnosis in non-Western contexts, questioning the universality of disorders.
- Impact of Globalization: While globalization promotes awareness and treatment, it may impose Western definitions of mental illness on other cultures, potentially overlooking culturally specific experiences of distress (e.g., the rise of anorexia in Hong Kong following Western media coverage).
- Ethical Concerns and Pharmaceutical Influence: The role of pharmaceutical companies in shaping perceptions of mental illness raises ethical questions about whether increasing prevalence reflects genuine need or profit-driven marketing, as seen with the promotion of SSRIs in Japan.
- Methodological Challenges: Prevalence rates are affected by variability in diagnostic criteria, stigma, underreporting, and access to services. This creates challenges in comparing rates across regions or time periods and may lead to inaccuracies in understanding the true scope of mental health issues.
