5.22 - Researching Mental Health - notes
5.22 - Researching Mental Health
Longitudinal studies
A longitudinal study is a research method that follows the same group of participants over an extended period, often years or decades, to observe changes and developments.
Key features of longitudinal studies
- Duration and tracking - Participants are monitored over time, with data collected at set points, such as at regular intervals.
- Consistency in testing - The same tasks or measures are used each time to assess improvements or changes in behaviour.
- Purpose - To examine how time influences specific variables, like skill development or symptom progression.
Application to mental disorders
Longitudinal studies are particularly useful for mental health research because disorders like Parkinson's disease or unipolar depression evolve over time. Individuals continue living and adapting after diagnosis. This method is also practical because patients often require repeated hospital visits for ongoing care.
Cross-sectional studies
A cross-sectional study is a research method that examines different groups of people at a single point in time to identify patterns or relationships between variables. Unlike longitudinal approaches, it provides a snapshot rather than ongoing tracking.
Key features of cross-sectional studies
- Single time point - Data are collected once from all participants.
- Group comparisons - Different cohorts (groups) are compared, such as by age, culture, or other factors.
- Purpose - To explore simple links, like how one variable relates to another, quickly and efficiently.
Application to mental disorders
These studies suit investigating experiences of conditions like depression across variables such as age or cultural background. For instance, comparing depression symptoms in young adults versus older groups can highlight differences in prevalence or expression. This generates data for hypotheses, though it does not explain causes – only associations.
Example in mental health research
- Method - Test groups of females at different ages (e.g., teens, young adults, middle-aged) at one time to measure diagnosis rates.
- Results - Findings might show higher diagnosis percentages in older age groups.
- Conclusions - This indicates a trend of increasing diagnoses with age, which could inform further research into reasons, like life stressors.
- Limitations - It reveals correlations but not why the pattern occurs; additional methods are needed for deeper insights.
This approach is common due to its speed, requiring only one testing session per participant.
Cross-cultural methods
Cross-cultural methods in psychology examine similarities and differences in behaviours, norms, and mental health across cultural groups. These methods address how cultural factors influence diagnosis and treatment to prevent biases.
Rationale for cross-cultural research
Cultural norms can lead to misdiagnosis if a psychiatrist from one culture evaluates someone from another. For example, behaviours seen as withdrawn in one culture might be valued as respectful in another, like among some Asian-American groups where subservience is praiseworthy. Mental health professionals must consider these differences to avoid labelling normal cultural traits as abnormal.
Main approaches in cross-cultural methods
- Etic approach - Focuses on universal similarities by studying multiple cultures from an outsider's perspective. It uses standardised tools, like tests from the researcher's culture, to draw broad conclusions. However, this can impose an "imposed etic," assuming tools are valid everywhere, which may not hold (e.g., diagnostic manuals like the DSM might not fit all cultures).
- Emic approach - Emphasises unique aspects of individual cultures, studied from an insider's viewpoint. Findings apply only to that specific culture, making them more tailored but less generalisable.
Applications and challenges
Etic findings can be generalised across cultures (although they may not be valid). Emic findings are applied only to the culture from which they were derived.
Meta-analysis
Meta-analysis is a statistical method that combines results from multiple existing studies on the same topic to identify overall trends and draw more reliable conclusions. It acts as research on previous research, pooling data to overcome limitations in individual studies.
Key features of meta-analysis
- Process - Researchers review published studies, analyse their findings, and integrate them to spot common patterns.
- Data type - Uses secondary data (information collected by others), not new primary data.
- Purpose - To uncover a "common truth" hidden by errors or variations in single studies.
Advantages in mental health research
Many studies suffer from small sample sizes, which limits reliability due to resource constraints. Meta-analysis addresses this by aggregating data from various studies, increasing the effective sample size and strengthening conclusions. For example, it can reveal consistent effects of treatments for disorders like schizophrenia across diverse research.
This method helps to draw reliable and valid conclusions based on broader evidence.
Primary and secondary data
Primary data are original information gathered firsthand by the researcher for a specific purpose. They present original thinking or new information.
Secondary data involve analysing existing information collected by others, often repurposed to answer new questions.
Case studies in clinical psychology
A case study is an in-depth examination of an individual, group, or event, using multiple data sources to understand complex issues. In clinical psychology, case studies are valuable when controlled experiments are impractical.
Key features of case studies
- Data collection - Involves observations, interviews, and client self-reports from various perspectives.
- Process - The researcher compiles and interprets information to form a detailed narrative.
- Purpose - To gain real-world insights into rare or unique situations, like living with schizophrenia.
Application and requirements
Case studies help therapists understand patient experiences, leading to tailored diagnoses and treatments. For example, they reveal the daily challenges of mental disorders, informing therapy. However, they should only be conducted by qualified professionals, such as psychiatrists or therapists, to ensure ethical and accurate handling.