Methods (Edexcel A-Level Psychology): Revision Notes
Researching Mental Health
Introduction to research methods in clinical psychology
Investigating the causes of mental health problems and evaluating treatment effectiveness requires robust research methodologies. Clinical psychologists employ various research designs depending on their aims, whether they need primary or secondary data, and whether they seek to understand developmental changes, cross-sectional patterns, cultural variations, or individual experiences.
Primary and secondary data
Primary data refers to information collected directly by researchers from participants. This typically involves designing studies where researchers gather data themselves, which offers greater control over the research process. However, collecting primary data is time-consuming and requires careful consideration of ethical issues when working with patient groups. Researchers must ensure proper consent procedures and safeguards are in place.
Secondary data involves using evidence that other researchers have already collected. This might include peer-reviewed journal articles or publicly accessible statistics. Using secondary data is more efficient and avoids some ethical concerns associated with direct patient contact. However, researchers cannot verify the reliability or validity of the original research methods.
If the original study had methodological flaws, these problems will affect any conclusions drawn from the secondary data. This is particularly problematic when multiple sources of secondary data are combined, as researchers may unknowingly base their conclusions on unreliable or invalid evidence.
Longitudinal studies
What are longitudinal studies?
Longitudinal research tracks a single sample group over an extended time period, often comparing participants' performance with their own earlier measurements. This design allows researchers to observe developmental or time-based changes through patterns in repeated measurements. In mental health research, clinicians may monitor symptom changes in patient groups receiving particular treatments. Measurements of symptom expression and severity are taken at specific intervals throughout the treatment period, enabling psychologists to determine whether symptoms reduce and thus assess treatment effectiveness.
Evaluation
Strengths
The primary advantage of longitudinal research in clinical psychology is its ability to measure time effects reliably. Since patients with the same mental health condition often experience different symptoms, comparing different individuals is problematic due to individual differences. Longitudinal designs avoid this issue by comparing individuals with themselves over time, isolating the effect of time on behaviour. This is essential when evaluating whether treatments genuinely improve patients' quality of life over extended periods.
By tracking the same individuals over time, longitudinal studies eliminate the confounding variable of individual differences that plague other research designs. This makes them particularly valuable for assessing long-term treatment outcomes.
Weaknesses
However, longitudinal research must continue for lengthy periods, which creates several problems. Participants may drop out, die, or become unable to be contacted, reducing sample size and potentially invalidating final outcomes. This phenomenon is known as attrition.
Common Problem: Outdated Findings
By the time meaningful data emerges for analysis, the findings may be irrelevant. Clinical psychology rapidly evolves with new theories and treatments, particularly regarding biological factors and drug therapies. Research that publishes findings years after starting may be outdated by the time conclusions are drawn.
Cross-sectional studies
What are cross-sectional studies?
When researchers need a rapid assessment of behaviour in a specific population, they typically employ a cross-sectional design rather than waiting for longitudinal data. Cross-sectional research uses a large group of people from the sample population to obtain a representative 'cross-section' of the target population, then draws conclusions from data gathered from this group. For instance, researchers investigating the experience of schizophrenia across different age groups could sample participants of various ages simultaneously rather than conducting time-consuming and expensive longitudinal research.
Evaluation
Strengths
The key advantage is speed of data collection, meaning conclusions can be used and acted upon quickly. Results are more likely to be valid because they reflect current circumstances rather than conditions several years prior, making them more applicable at the time of reporting.
Weaknesses
The major limitation is that comparisons occur between different groups of people, making individual differences likely to affect conclusions. Cross-sectional studies may produce issues with cohort effects, where research results can be attributed to being raised in a particular time period or place.
This impacts research into abnormal behaviours, as not all groups in age-based schizophrenia studies would have experienced identical cultural ideals and images. This makes the groups incomparable because they were subject to different social and cultural contexts during their development.
Cross-cultural methods
What are cross-cultural methods?
Cross-cultural research takes samples from different cultural groups to compare similarities and differences, considering how culture may influence the behaviour being investigated. This approach is relevant in clinical psychology for several reasons. Researchers may question whether patients' experiences of schizophrenia are identical across cultures, whether symptoms manifest consistently in all cultural groups, or whether treatments are equally effective across different cultural backgrounds.
Evaluation
Strengths
Taking measurements in one cultural group and comparing them with measurements from a different cultural group allows researchers to understand culture's role in the validity and reliability of clinical psychology diagnoses. Cross-cultural research can identify aspects of abnormal behaviour attributable purely to biological factors, thereby identifying universal behavioural trends that remain unaffected by cultural variation.
Cross-cultural research also reduces ethnocentrism in psychological studies and conclusions, improving research generalisability.
Wider Issues: Culture
An advantage of cross-cultural methods is they enhance clinicians' understanding of cultural factors that should be considered when diagnosing and treating patients from different cultural groups, especially when the patient's culture differs from the clinician's own. Doctors diagnosing and treating patients from different cultural backgrounds must be encouraged to refer to cross-cultural evidence to understand patients' subjective experiences.
Weaknesses
The disadvantage is that conducting research across cultures creates likely conflicts between the cultural values of some or all participants and those of the researcher. Consequently, conclusions drawn may lack validity if interpretation of patients' behaviours fails to account for their own cultural backgrounds.
Meta-analysis
What is meta-analysis?
Meta-analyses examine secondary data from multiple studies conducted by other researchers, combining findings to draw overall conclusions. A meta-analysis is typically conducted when extensive psychological research exists but firm conclusions cannot be drawn without comparing the research, or when research findings appear inconsistent. Researchers identify studies from various places, cultures and times that have all investigated the same area, aiming to bring findings together.
This enables them to consider information gathered from a large overall sample size rather than conducting primary data collection. In clinical psychology, researchers have conducted meta-analyses in various areas, including therapy and treatment effectiveness across different patient groups. Meta-analysis focuses on effect sizes, so a meta-analysis examining CBT effectiveness would analyse the size of the CBT effect found across all gathered research.
Evaluation
Strengths
The benefit of meta-analyses is that conclusions can be drawn from a vast array of different areas and a large overall sample, very quickly and at much less cost than conducting all the studies independently. They also avoid ethical concerns associated with conducting research on participants directly.
Weaknesses
However, a major disadvantage is that researchers lack involvement in gathering the data directly, so undisclosed reliability or validity issues in data gathering methods may exist.
Critical Issue: Publication Bias
Publication bias may significantly impact meta-analyses' validity. Research producing null effects may not be published and would therefore be ignored by meta-analytic research, which generally focuses on peer-reviewed publications. This suggests that evidence produced by meta-analyses is often biased against research where no effect has been found.
Some researchers include unpublished work in their analysis to make data more valid, but this creates an increased risk of using data that has not been scrutinised by peer review in the same way.
The use of case studies
What are case studies?
Case studies involve studying individuals or small groups with some unique characteristic or experience. Researchers conducting case studies employ various research methods to gather information about the group, then triangulate the data to draw conclusions. In clinical psychology, these case studies may focus on people with rare symptoms or individuals taking part in specific therapies.
Evidence gathered from case studies is often qualitative, allowing in-depth analysis of the group being studied. This enables conclusions to be highly valid for the sample being studied. In clinical psychology, this means that a comprehensive understanding of the patient's problems can be assessed and all factors potentially affecting them can be considered.
Key Definition: Triangulate
To take multiple pieces of information and draw them together to make an overall conclusion.
Example case study
Case Study Example: The 'Thursday Group' (Lavarenne et al., 2013)
One case study by Lavarenne et al. (2013) examined a session known as the 'Thursday group' – a support group for patients, most suffering from schizophrenia or schizoaffective disorder, who meet weekly. The group's purpose is to support patients by providing structure to help them cope with their illness and encouraging connection with others who are generally quite isolated in everyday life.
Study Details:
- Ten members from various local out-patient and in-patient services attended the local area group
- Members had been attending for between three weeks and 22 years
- Sessions were not recorded, but group leaders noted key points about patients' behaviour, expressions and comments immediately afterwards
Specific Session Examined: The case study reports on one specific session with six patients present, just before Christmas, where group members were facing a break of more than seven days before their next meeting due to the holidays. The key theme leaders noted in this session was 'fragile ego boundaries' – a breakdown in the line people draw between the real and the unreal, or their own thoughts and those of other people. They suggested the group may be reacting to the potential change in routine by having a break from the group for more than the usual one week.
Evaluation
Strengths
Research like this provides brilliant insight into the behaviour of patients involved, offering rich qualitative data about patient experiences and group dynamics.
Weaknesses
However, this relies heavily on the researcher's interpretation. In the Lavarenne et al. (2013) study, there is concern that group leaders' memory may be inaccurate as they do not record the sessions. If they recall something incompletely or inaccurately, or interpret information subjectively, the conclusions drawn could be unreliable or invalid.
Limited Generalisability
A small group of participants is unlikely to represent the whole target population; therefore, the population validity of the research could be extremely limited. The six patients attending the 'Thursday group' in the above study are unlikely to represent all patients with psychotic illness, so the results' usefulness is questionable.
The use of interviews in clinical psychology
What are interviews?
Interviews involve verbal questioning of patients to gather information from them. Interviews can be:
- Structured – involving a specific list of questions
- Semi-structured – involving a range of themes to explore
- Unstructured – where the direction of the conversation can be decided along the way
Example interview study
Interview Study Example: Psycho-educational Group Treatment (Vallentine et al., 2010)
Research reported by Vallentine et al. (2010) used semi-structured interviews to gather information from a patient group about their experiences as part of a psycho-educational group treatment programme.
Participants:
- 42 males detained in Broadmoor high-security hospital
- Most had received a diagnosis of schizophrenia or a similar disorder
- All were part of a programme aimed at helping them understand and cope with their illness
Method: The aim of the interviews was to understand their experience better, but also get information about how the group could be improved in the future. Following the interviews, a content analysis was conducted on the data gathered to identify key themes in the responses.
Key Findings: Four core themes were identified:
- 'What participants valued and why'
- 'What was helpful about the group'
- 'Clinical implications'
- 'What was difficult/unhelpful'
Important Results:
- Patients valued knowing and understanding their illness
- Group sessions allowed them to understand their own symptoms and how other people's experiences were similar
- Many reported increased confidence in dealing with their illness, which made them more positive about the future
Evaluation
Strengths
Gaining information from interviews allows patients to fully explain their own point of view, which should help researchers understand their perspective more clearly. Using semi-structured or unstructured interviews allows more detail to be gained from patients.
The researchers in Vallentine et al. (2010) recorded their interviews to allow them to play back and check the accuracy of the data they report on. This means they can check the reliability of the interpretation using the themes by having another researcher also code the data.
Weaknesses
A key limitation is the lack of standardisation when using less structured interview formats, which reduces reliability in data gathering. However, this must be balanced against the benefit of gaining richer, more detailed information from patients.
Grounded theory
What is grounded theory?
Grounded theory is a method devised by Glaser and Strauss in the 1960s for developing theory from research evidence. This data gathering and analysis method generally focuses on qualitative research (although not exclusively) and does not begin in the traditional scientific way of developing hypotheses that are then tested and adapted by research. Instead, research is conducted to gather information about something of interest and the theory emerges gradually from the data as it is gathered and analysed. This is known as an inductive method.
The researcher must first identify the area of behaviour they are interested in, and where they can gather information about this. As data is gathered, 'codes' and 'categories' can be drawn from what participants have said. The researchers will begin by coding everything the same way until they begin to see patterns. As theoretical concepts begin to become apparent, these codes may become more specific but initially they are likely to be very broad.
As researchers gather their evidence, they will 'memo' their work, adding comments to try to develop clarity about what the data is showing them. This can help them to identify the links between different themes that are emerging from the data.
Once clear theoretical concepts have become obvious, researchers will start to selectively code only the relevant data they gather, and they will move to sampling that gathers more evidence to support what they are already beginning to see. For example, once they know what information they need to develop their understanding of the emerging concepts, they will work out who they need to talk to next to get this information. Once a clear theoretical concept has developed, researchers can then review other literature and develop the theory in more detail.
Process Example: Nathaniel (2007) Nursing Practice Study
Nathaniel (2007) was interested in nursing practice and began by gaining information from nurses. As data was gathered:
- Initial Coding Phase: Everything was coded broadly until patterns began to emerge
- Memo Phase: Researchers added comments to develop clarity about what the data showed
- Selective Coding Phase: Once theoretical concepts became clear, only relevant data was coded
- Targeted Sampling Phase: Researchers identified specific individuals to interview to gather supporting evidence
- Theory Development Phase: Clear theoretical concepts were developed and related to existing literature
Evaluation
Strengths
An advantage of using this type of method to develop theory is that the evidence is integrated into the theory; therefore, the theory itself should have a good degree of validity.
Grounded theory is particularly useful in clinical psychology where researchers are interested in the beliefs, opinions and experiences of service users of the NHS or other health professionals. This is because it is unlikely that a researcher could propose possible themes/codes without asking the service user; instead they emerge from the analysis.
Weaknesses
However, this could be compromised if the data gathered to develop the theory was problematic in some way.
Potential Issues with Grounded Theory
- Researcher Bias: If researchers were in any way biased in their gathering or interpretation of the data, the theory would be based on subjective opinion and not actually 'grounded' in evidence
- Selective Sampling Problems: By selectively sampling data as the theory begins to emerge, researchers may 'force' the data to support the theory they think is emerging, potentially missing contradictory evidence
- Reliability Concerns: Another person conducting the same research or coding the same data could come to a very different conclusion about the theoretical concepts
- Time-Consuming Process: This type of research takes a very long time to gather and analyse information, especially in the early phases when researchers are unclear about exactly what they are looking for
While conducting the initial coding of every piece of information, researchers will need to try to interpret the viewpoint of all of the information as well as trying to decide how the data should be coded. Doing this will inevitably take a lot of time, and also a lot of skill on the part of the researcher.
Key Points to Remember:
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Primary data involves direct collection from participants, whilst secondary data uses existing research – each has distinct advantages regarding control, time, and validity
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Longitudinal studies track the same participants over time, allowing measurement of temporal effects but facing attrition and outdated findings issues
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Cross-sectional studies provide quick snapshots of populations but are vulnerable to individual differences and cohort effects
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Cross-cultural methods compare different cultural groups, reducing ethnocentrism and identifying universal trends, but face interpretation challenges
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Meta-analyses combine multiple studies to draw large-scale conclusions efficiently but are vulnerable to publication bias and undisclosed methodological issues
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Case studies provide rich, in-depth understanding through triangulation but have limited generalisability and rely heavily on researcher interpretation
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Interviews (structured, semi-structured, or unstructured) give valuable patient perspectives but may lack standardisation and reliability
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Grounded theory develops theories inductively from qualitative data, ensuring evidence-based concepts, but is time-consuming and vulnerable to researcher bias in sampling and coding