a level psychology > Clinical Methodology > Flashcards

Clinical Methodology Flashcards

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1
Q
A
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1
Q

quantitative data

A
  • data which is numerical
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2
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qualitative data

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  • data which is descriptive
  • difficult to define numerically
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3
Q

primary data

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  • gathered first hand from source
  • directly from the researcher
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4
Q

examples of primary data

A
  • Milgram 1963
  • Bandura 1961
  • Rosenhan 1973
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5
Q

ways to collect primary data

A
  • questionnaires
  • observations
  • content analyses
  • experiments
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6
Q

benefits of primary data

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  • data specifically relates to aims/hypothesises of study
  • can give information that is unique to the aim of the research
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7
Q

clinical example of collecting primary data

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  • clinical interviews with mentally ill patients
  • regarding their symptoms and experiences
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8
Q

secondary data

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  • has already been gathered by someone else
  • used by someone else for further research
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9
Q

examples of secondary data

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  • primary data from other researchers that is reused for a different purpose
  • data that are produced for another purpose
  • e,g statistics in a newspaper
  • assessing peer reviewed articles
  • public access statistics
  • census
  • organisations records
  • evidence taken from publications e.g newspaper/TV articles
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10
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clinical example of secondary data

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  • hospital records considering doctor notes on a patient during a hospital stay
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11
Q

primary data - strengths

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  • valid
  • credible
  • time
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12
Q

primary data - weaknesses

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  • cost
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13
Q

secondary data - strengths

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  • relative cost
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14
Q

secondary data - weaknesses

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  • validity
  • credibility
  • time
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15
Q

primary data - relative cost

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  • expensive to obtain
  • as each researcher has to start from the beginning of a study and follow the whole study through
  • requires resources
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16
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secondary data - relative cost

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  • cheaper
  • as data already exists
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17
Q

primary data - validity

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  • gathered 1st hand
  • following careful generalisation of variables
  • using carefully chosen procedures
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18
Q

validity - secondary data

A
  • has been gathered for different purposes
  • has already been analysed
  • bringing subjectivity
  • less valid
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19
Q

primary data - credibility

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  • more trustworthy as it has more validity
  • objectivity in data collection
  • controls over sample/other variables
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20
Q

credibility - secondary data

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  • lack credibility
  • researchers not involved in data collection
  • we do not know how valid/scientific data collection methods were
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21
Q

time - primary data

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  • gathered at time of study
  • conclusions gathered at this time
  • applicable to how society is now
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22
Q

time - secondary data

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  • data may have been gathered some time ago
  • conclusions drawn from data may not be valid
  • as cultures, people change over time
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23
Q

cross cultural designs

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  • taking samples from different cultural groups
  • comparing results
  • to assess similarities/differences between them
  • allowing consideration of how culture may impact behaviour
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24
how are cross cultural designs used in clinical
- experiences of SZ patients in different cultures - to determine whether the same symptoms are presented or whether treatments are equally effective
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what debate can cross cultural research help to investigate
nature - nurture
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how can cross cultural designs discuss nature nurture debate
- if same procedures used in different cultures - and same results are found - suggests results are due to nature - is biological demonstrating a universal law - if different behaviours are found - it is likely due to different cultural practices - = nurture
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how could cross cultural designs be ethnocentric
- by judging 1 culture against your own - often drawing negative and invalid conclusions - happens as we do not know enough about other cultures
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how can cross cultural research remove ethnocentric views
- if researcher immerses themselves in the culture - learns about it fully - can be ethnographic
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how does ethnographic research improve cross cultural designs
- improves generalisability
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how do clinicians benefit from cross cultural designs
- improve their understanding of cultural factors they need to consider - during diagnosis and treating patient - from a culture different to their own - they may need to consider research available and subjective experiences of the patient
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emic approach
- studying cultures that looks at a culture from within it - to find out about its norms and ideas - focuses on 1 culture to understand it
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etic approach
- studying cultures that looks at norms and ideas between cultures - looks at cultures from outside - draws on data from many cultures
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when is an etic approach used
- when researchers are looking for universal laws of behaviour - comparing cultures
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Lin - schizophrenia
- looked at cross culturally - was found prevalence seemed similar across all cultures - symptom similarities outweighed differences across cultures - only difference was outcomes - patients in developed countries had more positive outcomes
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cross cultural studies - universal behaviour
- researchers can see if behaviour is universal - is not affected by cultural differences - they can compare prevalence of mental illnesses across cultures - look for cultural variation in mental illness and diagnosis - they can identify universal trends and specific variation - allowing diagnosis and treatments to be updated and tailored to individual cultures
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cross cultural studies - generalisations
- between cultures can be made - building a body of knowledge - if SZ is diagnosed using ICD 10 - which is used in many different cultures/countries - knowing that SZ is found universally is important
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cross cultural studies - reliability
- high - if same procedures repeated in different cultures they are likely to be carefully documented - so study can be easily repeated - checking for consistency in findings
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cross cultural research - reducing ethnocentrism -
- as research highlights cultural similarities and differences across mental illness - findings more generalisable to a range of patients - even when working with patients from a different culture to your own
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cross cultural studies - observer bias
- researchers have expectations about how they anticipate other cultural groups to behave - may affect measurements
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how can we remove observer bias in cross cultural research
- use of local researchers
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cross cultural studies - communication difficulties
- if researcher is conducting a study in a different culture and language to their own - causing misunderstandings of diagnosis and treatments - overcome with local researchers
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cross cultural designs - using procedures which have been developed in 1 country but are not valid elsewhere
- may make other individuals culture appear abnormal or inferior if they completed this test - imposed etic
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imposed etic
- when a technique or psychological test is used in 1 culture - even though it was designed for used in another
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cross cultural research - stereotypes
- participants in research may not be representative of that culture - yet we make generalisations about the whole culture - leading to stereotypes/labels of mental health - which aren't reflective of that culture
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cross cultural research - validity
- if features of a culture are socially constructed - thoughts, behaviours, attitudes, emotions are not comparable between cultures - as what is being measured is different - validity of measurement would only be found within the culture issues are set in
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strengths - cross cultural research
- reduces level of ethnocentrism - standardised procedures can be used across cultures for accurate comparisons - can identify elements of abnormal behaviour that can be attributed to purely biological factors = done by universal trends that seem to remain unaffected by cultural variation
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cross sectional research
- takes a quick snap shot of behaviour in a population - rather than waiting for longitudinal data to be gathered
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cross sectional research - method
- large sample of people used - to get a good cross section of whole target population - sample of participants over a wide range of characteristics are measured at the same time - measure of participants at 1 time not over time
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clinical example of a cross sectional quantitative design
- investigating whether peer victimisation is positively related to psychosocial maladjustment - meta analytic review of cross sectional studies - of association of peer victimisation with psychosocial maladjustment - mean effect sizes were calculated for association between peer victimisation and each form of maladjustment
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forms of maladjustment
- depression - loneliness - social anxiety - self worth
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results - cross sectional study example
- victimisation is most strongly related to depression - least strongly related to anxiety - no evidence that victimisation is more strongly related to social than psychological forms of maladjustment - effect sizes were stronger when the same informants were used to assess both victimisation and maladjustment than when different informants were used
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cross sectional study example - design strengths
- provide strong background for more complex research into course and treatment of victims distress
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cross sectional research - data gathered quickly
- allowing conclusions to be drawn and acted on more rapidly
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cross sectional research - validity
- more valid - as findings will be reported at the time - when they have most application in the clinical setting
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cross sectional research - ethics
- more ethical - participants are only studied 1 at a time - research is less of an intrusion on their lives - easier to find participants - participants may find discussing their symptoms distressing as a confirmation of their mental state
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cross sectional research - individual differences
- involve different people - participant variables will not likely be controlled for - e.g personal experiences of the symptoms of an illness
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longitudinal research
- involves studying the same participants over a long period of time - documenting any changes that occur - development of time based changes can be seen through pattern of measurements
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example of how longitudinal research is used in clinical psychology
- may monitor symptoms in a patient group undergoing certain treatment - measurement may be of symptom expression and severity at certain intervals over a specific time period - demonstrating any reduction in symptoms - which would indicate treatment effectiveness
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longitudinal research - methods - clinical
- tracking progress of a mental illness throughout a lifespan - to document change in symptoms and intensity of a particular disorder - vary in length
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what different things may longitudinal research cover based on clinical
- assessing long term effectiveness of treatment programmes - change in symptoms and severity throughout course - detailing number of relapses and hospitalisations during/after treatment - looking at attitudes towards mental illness and how they have changed over time e.g assessing factors such as media or changes in politics
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example of longitudinal research - named
Goldstein
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Goldstein
- measured gender differences in SZ - in terms of their experiences such as how they coped with everyday life - over 5/10 yr period recorded number of hospitalisations and amount of time spent in hospital
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longitudinal designs - best way to see how a disorder develops
- we follow the same individual - monitor the same people over time
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longitudinal designs - practical issues
- take a long time - requires lots of financial input throughout the time and as a way to keep participants - this includes researcher time
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longitudinal research = high validity
- participant variables controlled - same participants are used throughout the study - comparisons are more meaningful - as there are less extraneous variables - affecting conclusions - in depth study - involves a range of research methods - rich and in depth data collected
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example of using a longitudinal study which has high validity
- considering impact of ACT over time - same patients are monitors throughout meaning factors e.g gender are controlled
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example of the range of methods used in a longitudinal study e.g anorexia
- data about weight loss - gain patterns - diagnostic interviews - allows rich and reliable in depth data is gathered
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Validity - bad - longitudinal studies
- participants are studied for a long period of time - relationships can form between patient and researcher - causing researcher bias - as researcher becomes too close to the patient
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Why may researcher bias occur particularly in clinical psychology
- patients classed as a vulnerable group - some studies may involve patient and researcher becoming quite close - due to sensitive nature of measures involved
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longitudinal studies - demand characteristics
- patients are involved in study for long time - as they become further involved in the study - they may start to display demand characteristics - as they try to meet the aims of the study
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Longitudinal research - high drop out rate
- research is a big commitment - patients are more vulnerable - so it is more difficult to remain in the study - if too many drop out - less valid - sample may no longer be representative - as those with more severe symptoms may all drop out so researcher is left with biased sample
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Longitudinal studies - ethics
- participants commit to study for a long period of time - research may become intrusive causing distress to participants - ethical issues are important to consider as patients are vulnerable
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What must researchers do in any longitudinal study to remain ethical
- repeatedly gain consent - e.g with each different research method and measure - remind participants of their right to withdraw regularly
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Longitudinal study - out dated
- clinical psychology is a fast paced area - with new ideas and treatments constantly being developed - if a study takes 10yrs to complete and publish - there may have been so many developments research is no longer valid
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Cross sectional study - Hyde et al
- cognitive decline and schizophrenia - patients with chronic SZ - age 18-69 - divided into different age cohorts - intellectual deterioration measured
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Hyde et al - what measures were used
- Mini mental state examination for intellectual deterioration - Dementia rating scale - other tests known to be sensitive to cognitive impairment in progressive dementia - Boston Naming test
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Hyde et al - how were extraneous variables controlled
- rigorous screen test - to check for any co morbid condition which may affect their CNS function
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Hyde et al - findings
- no evidence of accelerated intellectual decline - performance on Boston baking test declined with age significantly - more age related than illness - mean test performance were abnormal across all age groups - intellectual function does not seem to markedly decline during adulthood of patients with Sz
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Harvey et al - longitudinal study
- cognitive decline in late life schizophrenia - geriatric chronically hospitalised patients - 326 geriatric chronic long stay sz patients - patients shower cognitive and functional impairments that were in decline post illness onset - 30 months - 2 separate assessments of patients
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Harvey et al DV
- Cognitive and functional impairments - measured using clinical dementia rating scale
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Harvey et al - findings
- of pps who had less severe scores at the start of the study - 30% had declined further by the second assessment - only 7% of sample had improved in their functioning - several characteristics of patients at baseline assessment predicted increased risk for cognitive and functional decline - including lower levels of education, older age, more severe positive symptoms
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Cohort
Group of people being studied
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Cohort effects
- factors relating to the group of people being studied which may make them special in some way - making them not entirely comparable to another similar group - who may be selected for a replication of the study - these factors cannot be controlled - could become a confounding variable - relate to things which happened to that specific generation of children
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Example of cohort effects
- children who have lived through a world war - children who have been subjected to educational initiative which have gone out of fashion - economic recession
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Cohort effects - cross sectional studies
- each group of children in the sample will have lived through differing social and economic circumstances - may not be the same - we cannot be sure that differences between the children’s behaviour is due to differences in age or differing experiences
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Cohort effects - longitudinal studies
- affects generalisability - findings and conclusions will only apply to groups of people who have lived through similar social and economic circumstances
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Cross sectional research - evaluate - validity
- results collected at a time they are most relevant - e.g researchers collecting information on positive SZ symptoms at the time helps create fast treatments - findings can be reported at the time they have the most application in a clinical setting = not years later
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Cross sectional studies - internal validity - evaluate
- individual differences are likely to greatly impact results - participants gender / social class/ age cannot be controlled - many participant variables can’t be controlled for such as personal experiences with symptoms - more extraneous variables
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Cross sectional studies - reliability - evaluate
- standardised procedures - same procedure given to the different sample groups - studies can be repeated easily to check for consistency in n the data - check conclusions and findings are accurate
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Cross sectional studies - ethics - evaluate
- participants often give consent - only studied for short period - less intrusive - patients may be discussing stressful symptoms so more ethical that it is done in a short time frame
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Other strengths of cross sectional research
- data gathered faster than longitudinal research allowing conclusions to be drawn and acted upon more rapidly - more likely to be valid as findings will be reported at the time - when they have most application in the clinical setting
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Longitudinal studies - generalisability - evaluate
- attrition rates are extremely high - people who drop out share similar traits - e.g those who experience more severe symptoms - reduced sample size - findings aren’t representative to target population - cohort may not be representative of generations to come - e.g children who grew up in wars experience cannot be replicated - therefore unique behaviours were developed - findings may not be applicable to treat future generations - not representative of target population
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Longitudinal research - reliability - evaluate
- try to use standardised procedures and test the cohort in the same way - sample are told to complete similar tasks - allows data trends to be found amongst sample - allowing effective treatments to be developed
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Validity -evaluate - longitudinal studies
- over long periods of time researchers form relationships affecting results - clients with mental health conditions are vulnerable causing closeness - causing researcher bias as researcher lets feelings skew their findings
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Reliability - longitudinal studies - evaluate
- if researcher drops out before study ends - new researcher may take over introducing new research methods - no continuity - experiments cannot be replicated and results can’t be compared - to investigate things such as whether the treatment has been effective
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Longitudinal studies - Hawthorne effect
- confounding variable in studies - where participants work harder or have better health outcomes - because of their boost to their self esteem for being monitored in a study
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Ethics longitudinal studies - participants develop personal problems
- researchers can try to identify risk factors to give an early warning of how a person is going to turn out - unless there is an intervention - can identify people who benefit most from types of therapy - giving optimum treatment
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Longitudinal studies - ethics - child’s development
- interfering with the children’s development just by studying them - this can be better or worse - children cannot consent - only presumptive from parents
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How did Goldstein use interviews
- interviewers used specially developed questions to give characteristics of SZ - to measure symptoms
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Interviews
- look at interview flash card deck and go through - all info is there :)
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Case studies A01
- in depth investigations of a single individual or small group - often used to study rare phenomena - involve use of multiple collection methods of data - data collected is often qualitative giving rich and detailed descriptions of subject being studied - often longitudinal - follow subject over a period of time to observe changes
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Idiographic approach
- focuses on individual and their unique experiences
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Nomothetic approach
- aims to establish general laws and principles to populations
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Triangulation
- used to enhance credibility and validity of findings of case studies - as they rely on qualitative data and in depth analysis - helps ensure conclusions are well supported - using multiple data sources
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Case study - Luk and Agoha
- investigated impact of cultural beliefs on mental health presentation and treatment - focuses on individuals from specific cultural backgrounds and their understanding and experience of mental illness - highlights importance of culturally sensitive approaches in diagnosis and treatment - emphasising that mental health professions need to consider cultural context to provide care
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Strengths - case studies
- good at finding in detail and depth info about a small group - ecological validity - allows research to examine complex interactions between different factors that influence behaviours
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Case studies - good at finding in depth and detailed information about patients
- allows symptoms to be explored - mental health looked at in greater detail - so we can find effective treatments
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Case studies - ecological validity
- takes place in real world / hospitals - findings are likely to be applicable to real world scenarios - increased chances of better treatment
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Case studies - allows researchers to examine complex interactions between different factors that influence behaviour
- helps understand how biological social and psycholoxal factors interact - to contribute to a disorder
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Case studies - weaknesses
- not generalisable - time consuming and subjective - not reliable
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Case studies - not generalisable
- often only an individual or small group studied - often people with unusual conditions and symptoms - findings may not be applicable to other mental health disorders - or other people with that disorder
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Case studies - time consuming and subjective
- researchers spend a long time with patients - subject to researcher bias and losing objectivity - as they get too close with a patient - as patient is more vulnerable - less valid
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Case studies - reliable ?
- unique and difficult to replicate - specific to patient and situation - hard to replicate to verify findings
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Meta analysis
- research strategy where researchers examine the results of several previous studies - carrying out statistical analysis to assess the effect or direction of the data
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When do scientists conduct meta analysis
- when they want to know the answer to a question which has been studied a lot - by pooling data from multiple studies - to arrive at 1 combined answer - used when smaller studies have been conducted - and an overall conclusion is needed
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Clinical example as to when meta analysis is needed
- range of different studies considering the effectiveness of a particular treatment - meta analysis gives a stronger conclusion about this
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Aim of a meta analysis
- to find patterns - look at studied which collect data using similar methods to be able to compare - should only include studies which have sound methodology - only the best evidence is pulled together
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What studies do researchers use in a meta analysis
- variety of paces, cultures and times - which have all tested the same area - so lots of information can be gathered - forming an extensive overall sample size - without conducting primary research
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Difference between meta analysis and literature review
- meta analysis = involves reanalysing data to find an overall measure of significance - literature review = reports on background information and previous findings from other research with no statistical analysis to
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Carlson et al - literature review
- to pool together research investigating impact of various neurotransmitters on SZ - therefore conclude about appropriate treatments and the need for further developments
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Research Carlson et al looked at
- animal studies - studies with schizophrenic patients - studies assessing effectiveness of different treatments
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Strengths - meta analysis
- improved generalisability - increased objectivity - helps resolve conflicting evidence
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Meta analysis - generalisability
- examines consistency of results across different populations, settings and study designs - more likely to be applicable to a wider population
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Meta analysis - objectivity
- uses a systematic approach to summarising findings - only the best evidence is used
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Meta analysis - helps resolve conflicting evidence
- by providing a quantitative summary of overall evidence - it can identify whether effect is consistently positive or negative - providing an overall conclusion about treatment
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Meta analysis - negatives
- publication bias - oversimplified res arch - time consuming
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Meta analysis - publication bias
- studies with statistically significant results are more likely to be published than those with null/negative findings - leading to overestimation of true effect size - disproportionate number of positive studies - decrease validity
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Meta analysis - oversimplified complex research
- by reducing research - missing out important details and contextual factors - this may limit effectiveness of interventions
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Meta analysis - time consuming
- complex - challenging process for researchers who have limited resources - they need to complete: - data extraction - quality assessment - statistical analysis
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