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(2012) investigate?","back":"Alcohol risk behaviour in India.","mcqOptions":[{"text":"Alcohol risk behaviour in India.","correct":true,"explanation":"The study examined patterns of alcohol use associated with an increased likelihood of harm among people living in urban and rural communities in India."},{"text":"Alcohol advertising in India.","correct":false,"explanation":"Advertising may influence alcohol consumption, but it was not the issue measured in this study. Dixit et al. investigated alcohol risk behaviour and its biosocial determinants."},{"text":"Alcohol withdrawal in India.","correct":false,"explanation":"Withdrawal concerns symptoms following reduced or stopped alcohol use, rather than risky drinking patterns. The study investigated alcohol risk behaviour in Indian communities."},{"text":"Alcohol treatment in India.","correct":false,"explanation":"The researchers did not assess a treatment programme or its effectiveness. They investigated alcohol risk behaviour and the factors associated with greater risk."}]},{"id":"6371e015-da5c-4ba9-b0d8-2d7e1acf7aab","cardType":"cloze","points":null,"front":"Dixit et al. (2012) studied urban and rural communities in [ ].","back":"Dixit et al. (2012) studied urban and rural communities in Aligarh, Uttar Pradesh, India.","mcqOptions":[{"text":"Aligarh, Uttar Pradesh, India","correct":true,"explanation":"Dixit et al. sampled urban and rural communities in Aligarh, a district located in the Indian state of Uttar Pradesh."},{"text":"Mumbai, Maharashtra, India","correct":false,"explanation":"Mumbai is in Maharashtra and was not the study location. Dixit et al. investigated communities in Aligarh, Uttar Pradesh, India."},{"text":"Jaipur, Rajasthan, India","correct":false,"explanation":"Jaipur is in Rajasthan, which can be confused with another northern Indian location. The research took place in Aligarh, Uttar Pradesh, India."},{"text":"Lucknow, Uttar Pradesh, India","correct":false,"explanation":"Lucknow is in the correct state but is the wrong city, making this a plausible geographical confusion. The study was conducted in Aligarh, Uttar Pradesh."}]},{"id":"12379840-c02a-4e75-9673-e5e3ef0e5de4","cardType":"basic","points":1,"front":"What was the main aim of Dixit et al. (2012)?","back":"Investigate biosocial determinants of alcohol risk behaviour.","mcqOptions":[{"text":"Investigate biosocial determinants of alcohol risk behaviour.","correct":true,"explanation":"The study aimed to identify biological and social characteristics associated with alcohol risk behaviour, allowing the researchers to determine which groups were most at risk."},{"text":"Investigate psychological effects of alcohol risk behaviour.","correct":false,"explanation":"The study did not primarily measure the psychological consequences of risky drinking. Its aim was to investigate the biosocial determinants associated with alcohol risk behaviour."},{"text":"Investigate treatment effectiveness for alcohol risk behaviour.","correct":false,"explanation":"No treatment was administered or compared, so effectiveness could not be assessed. The researchers instead investigated biosocial determinants of alcohol risk behaviour."},{"text":"Investigate genetic inheritance of alcohol risk behaviour.","correct":false,"explanation":"Genetic inheritance was not isolated or tested in this survey. The broader aim was to investigate biosocial determinants of alcohol risk behaviour."}]},{"id":"3160319a-8f19-4542-9106-e1ffc328b7a8","cardType":"cloze","points":null,"front":"[ ] includes drinking patterns that increase the chance of harm.","back":"Alcohol risk behaviour includes drinking patterns that increase the chance of harm.","mcqOptions":[{"text":"Alcohol risk behaviour","correct":true,"explanation":"Alcohol risk behaviour covers drinking patterns that raise the likelihood of physical, psychological or social harm, whether or not dependence has developed."},{"text":"Alcohol dependence","correct":false,"explanation":"Dependence involves features such as impaired control, tolerance or withdrawal and is narrower than the definition given. The broader term is alcohol risk behaviour."},{"text":"Alcohol tolerance","correct":false,"explanation":"Tolerance means needing more alcohol to achieve the same effect, not every drinking pattern that increases harm. The correct broader term is alcohol risk behaviour."},{"text":"Alcohol withdrawal","correct":false,"explanation":"Withdrawal refers to symptoms occurring when a dependent person reduces or stops drinking. Drinking patterns that increase the chance of harm are alcohol risk behaviour."}]},{"id":"61730431-5e2b-42ad-88a1-4f3cfc6830af","cardType":"cloze","points":null,"front":"An [ ] study looks for population patterns in health-related behaviours or conditions.","back":"An epidemiological study looks for population patterns in health-related behaviours or conditions.","mcqOptions":[{"text":"epidemiological","correct":true,"explanation":"Epidemiological research examines how health-related conditions or behaviours are distributed across populations, including their prevalence and associations with demographic or social factors."},{"text":"experimental","correct":false,"explanation":"Experimental research manipulates an independent variable to test its effect, rather than simply identifying population patterns. The definition describes an epidemiological study."},{"text":"ethnographic","correct":false,"explanation":"Ethnographic research explores cultures or social groups through detailed observation, rather than measuring population-level health patterns. The correct term is epidemiological."},{"text":"etiological","correct":false,"explanation":"Etiological research focuses specifically on the causes or origins of a condition. Research into population patterns of health-related behaviour is described as epidemiological."}]},{"id":"0bcfe68c-e885-4593-8924-55fd058b7b6e","cardType":"basic","points":2,"front":"Why did Dixit et al. use an epidemiological approach?","back":"To identify who was most at risk of harmful alcohol use.","mcqOptions":[{"text":"To identify who was most at risk of harmful alcohol use.","correct":true,"explanation":"An epidemiological approach compares patterns across population groups, enabling the researchers to identify the demographic, biological and social characteristics associated with harmful alcohol use."},{"text":"To establish what directly caused harmful alcohol use.","correct":false,"explanation":"A cross-sectional epidemiological survey can identify associations but cannot establish direct causation. It was used to identify who was most at risk of harmful alcohol use."},{"text":"To measure how alcohol treatment reduced harmful use.","correct":false,"explanation":"The study did not introduce or evaluate an alcohol treatment. Its epidemiological approach was intended to identify who was most at risk of harmful alcohol use."},{"text":"To predict when harmful alcohol use would stop.","correct":false,"explanation":"A one-time population survey cannot predict when an individual’s drinking will end. The approach identified who was most at risk of harmful alcohol use."}]},{"id":"3edf0a4a-eef8-400b-b47a-40043d06c187","cardType":"cloze","points":null,"front":"[ ] means how common something is in a population at a particular time.","back":"Prevalence means how common something is in a population at a particular time.","mcqOptions":[{"text":"Prevalence","correct":true,"explanation":"Prevalence is the proportion or number of people in a population who have a condition or display a behaviour at a specified time."},{"text":"Incidence","correct":false,"explanation":"Incidence counts new cases developing during a specified period, not all existing cases at a particular time. The latter measure is prevalence."},{"text":"Mortality","correct":false,"explanation":"Mortality measures deaths in a population, usually over a specified period. How common a condition or behaviour is at a particular time is prevalence."},{"text":"Morbidity","correct":false,"explanation":"Morbidity refers broadly to illness or disease within a population, rather than the specific proportion affected at a given time. That measure is prevalence."}]},{"id":"b30e94c0-8726-4642-a23f-0c6c6a34644c","cardType":"basic","points":1,"front":"What research design did Dixit et al. use?","back":"A cross-sectional survey.","mcqOptions":[{"text":"A cross-sectional survey.","correct":true,"explanation":"Data were collected from participants at one point in time to compare alcohol risk behaviour across groups, making the design a cross-sectional survey."},{"text":"A longitudinal survey.","correct":false,"explanation":"A longitudinal survey follows participants and gathers data repeatedly over time. Dixit et al. collected a snapshot of the population using a cross-sectional survey."},{"text":"A laboratory experiment.","correct":false,"explanation":"The researchers did not manipulate variables under controlled conditions, so the study was not an experiment. They used a cross-sectional survey of community participants."},{"text":"A clinical case study.","correct":false,"explanation":"A case study examines an individual or small unit in depth, whereas this research surveyed a population sample using a cross-sectional design."}]},{"id":"49d8ed66-0cac-43b8-8e1e-aabaa1d63389","cardType":"cloze","points":null,"front":"A [ ] design collects data at one point in time.","back":"A cross-sectional design collects data at one point in time.","mcqOptions":[{"text":"cross-sectional","correct":true,"explanation":"A cross-sectional design measures a sample at a single point in time, providing a snapshot of variables such as alcohol use and biosocial characteristics."},{"text":"longitudinal","correct":false,"explanation":"A longitudinal design collects data from the same participants over an extended period. The correct term is cross-sectional because the data were collected at one point in time."},{"text":"experimental","correct":false,"explanation":"An experimental design manipulates an independent variable to test its effect. The correct term is cross-sectional because this design measures variables at one point in time."},{"text":"repeated-measures","correct":false,"explanation":"A repeated-measures design exposes each participant to multiple conditions. The correct term is cross-sectional because the study collected its data at a single point in time."}]},{"id":"34cb96b5-4dc1-45b4-8028-f1006e271d2b","cardType":"basic","points":1,"front":"What design follows the same people over time?","back":"A longitudinal design.","mcqOptions":[{"text":"A longitudinal design.","correct":true,"explanation":"A longitudinal design repeatedly collects data from the same people over an extended period, allowing researchers to investigate changes and developments within participants."},{"text":"A cross-sectional design.","correct":false,"explanation":"A cross-sectional design collects data at one point in time, often from different groups. A longitudinal design follows the same people and measures them repeatedly over time."},{"text":"An independent groups design.","correct":false,"explanation":"An independent groups design uses different participants in each condition rather than following one group over time. The design described is a longitudinal design."},{"text":"A matched pairs design.","correct":false,"explanation":"A matched pairs design places similar participants in different conditions. Following the same individuals across multiple time points instead describes a longitudinal design."}]},{"id":"0b01bdcc-0e8a-4916-bb5f-50e4b1c2ca04","cardType":"basic","points":1,"front":"What type of method collected alcohol-use data?","back":"A structured interview or questionnaire.","mcqOptions":[{"text":"A structured interview or questionnaire.","correct":true,"explanation":"Alcohol-use data were gathered through a structured interview or questionnaire, giving participants standardised questions and allowing their responses to be scored consistently."},{"text":"An unstructured clinical interview.","correct":false,"explanation":"An unstructured clinical interview allows questions to vary between participants. The study instead used a structured interview or questionnaire to collect standardised alcohol-use data."},{"text":"A covert participant observation.","correct":false,"explanation":"Covert participant observation records behaviour without participants necessarily knowing they are being studied. Alcohol use was instead self-reported through a structured interview or questionnaire."},{"text":"A controlled laboratory experiment.","correct":false,"explanation":"A controlled laboratory experiment involves manipulating variables under standardised conditions. Dixit et al. collected alcohol-use information using a structured interview or questionnaire instead."}]},{"id":"553a33b9-286c-49b2-8058-4b79f2c0ac67","cardType":"basic","points":1,"front":"Which standardised alcohol screening tool is mentioned?","back":"AUDIT - Alcohol Use Disorders Identification Test.","mcqOptions":[{"text":"AUDIT - Alcohol Use Disorders Identification Test.","correct":true,"explanation":"AUDIT stands for Alcohol Use Disorders Identification Test. It is a standardised screening tool designed to identify hazardous or harmful patterns of alcohol consumption."},{"text":"DAST - Drug Abuse Screening Test.","correct":false,"explanation":"DAST screens for problems involving drugs other than alcohol, which makes it a tempting related acronym. The alcohol screening tool mentioned was AUDIT, the Alcohol Use Disorders Identification Test."},{"text":"GHQ - General Health Questionnaire.","correct":false,"explanation":"The GHQ assesses general psychological distress rather than specifically screening alcohol use. The named alcohol tool was AUDIT, the Alcohol Use Disorders Identification Test."},{"text":"BDI - Beck Depression Inventory.","correct":false,"explanation":"The BDI measures symptoms of depression, not risky alcohol consumption. Dixit et al. used AUDIT, which stands for Alcohol Use Disorders Identification Test."}]},{"id":"118c86d3-ff56-4d5d-a5e6-13f2c043981f","cardType":"basic","points":2,"front":"How can a standardised questionnaire improve reliability?","back":"Everyone gets the same questions and scoring system.","mcqOptions":[{"text":"Everyone gets the same questions and scoring system.","correct":true,"explanation":"Using identical questions and scoring reduces variation caused by researchers administering or interpreting the measure differently, making the data more consistent and replicable."},{"text":"Everyone gets different questions and scoring criteria.","correct":false,"explanation":"Changing questions and scoring between participants introduces inconsistency and reduces reliability. Reliability improves when everyone receives the same questions and is assessed using the same scoring system."},{"text":"Everyone gives the answers they think are acceptable.","correct":false,"explanation":"Giving socially acceptable answers creates social desirability bias and threatens validity rather than reliability. Reliability is improved through the same questions and scoring system for everyone."},{"text":"Everyone explains their answers in their own way.","correct":false,"explanation":"Open interpretation can make responses harder to compare and score consistently. A standardised questionnaire improves reliability by giving everyone the same questions and scoring system."}]},{"id":"d8718866-ad4c-4f9e-9033-336479ad4d3a","cardType":"basic","points":1,"front":"Was alcohol risk behaviour evenly spread across the population?","back":"No - it was associated with biosocial factors.","mcqOptions":[{"text":"No - it was associated with biosocial factors.","correct":true,"explanation":"Risky alcohol use varied in relation to biosocial characteristics, so it was not distributed evenly across the population. The findings established associations rather than causal relationships."},{"text":"Yes - it was equally common in all groups.","correct":false,"explanation":"The results did not show an even distribution across all groups. Risky alcohol use was associated with biosocial factors, meaning its prevalence differed according to participant characteristics."},{"text":"No - it was caused by biosocial factors.","correct":false,"explanation":"The study identified statistical associations but could not establish that biosocial factors caused risky alcohol use. Its cross-sectional, non-experimental design does not support causal conclusions."},{"text":"No - it was unrelated to biosocial factors.","correct":false,"explanation":"Treating alcohol risk as unrelated to participant characteristics reverses the finding. Risky alcohol use was associated with biosocial factors and therefore was not evenly distributed."}]},{"id":"93c69904-b0d1-4c59-8cb8-76ecc9ec4782","cardType":"basic","points":1,"front":"Which sex was risky alcohol use reported as more common among?","back":"Men.","mcqOptions":[{"text":"Men.","correct":true,"explanation":"Risky alcohol use was reported as more common among men, showing that sex was one of the biosocial factors associated with alcohol risk behaviour."},{"text":"Women.","correct":false,"explanation":"Reversing the reported sex difference gives the wrong conclusion. Dixit et al. found that risky alcohol use was more commonly reported among men."},{"text":"Neither sex.","correct":false,"explanation":"The study did report a sex difference in risky alcohol use. It was more common among men, rather than being absent in both sexes."},{"text":"Both sexes equally.","correct":false,"explanation":"Equal prevalence would mean that sex was not associated with risky alcohol use. The study instead reported that risky alcohol use was more common among men."}]},{"id":"91aa1dfd-93c9-4832-a907-8dc25e1c3952","cardType":"cloze","points":null,"front":"Dixit et al. found [ ], not proven causes, between biosocial factors and alcohol risk behaviour.","back":"Dixit et al. found associations, not proven causes, between biosocial factors and alcohol risk behaviour.","mcqOptions":[{"text":"associations","correct":true,"explanation":"Associations show that variables are statistically related, but they do not demonstrate that one variable causes another, particularly in a cross-sectional, non-experimental study."},{"text":"causes","correct":false,"explanation":"Calling the findings causes confuses correlation with causation. Dixit et al. found associations between biosocial factors and alcohol risk behaviour, without proving a causal relationship."},{"text":"contrasts","correct":false,"explanation":"Contrasts describe differences between categories rather than statistical relationships between variables. The study found associations linking biosocial factors with alcohol risk behaviour, not proven causes."},{"text":"coincidences","correct":false,"explanation":"Describing the findings as coincidences ignores the observed statistical relationships. Dixit et al. reported associations between biosocial factors and alcohol risk behaviour, although causation was not established."}]},{"id":"241df995-a98e-4cf7-9703-5523752a1fe0","cardType":"basic","points":2,"front":"Why can’t Dixit et al. show that residence caused risky drinking?","back":"Residence was not manipulated experimentally.","mcqOptions":[{"text":"Residence was not manipulated experimentally.","correct":true,"explanation":"Residence was observed rather than assigned by researchers, so the study identifies an association between residence and risky drinking but cannot establish that residence caused the drinking pattern."},{"text":"Residence was randomly allocated experimentally.","correct":false,"explanation":"Random allocation would strengthen a causal conclusion by reducing participant differences between conditions. In Dixit et al., residence was not manipulated, so only an association with risky drinking can be shown."},{"text":"Residence was not operationalised objectively.","correct":false,"explanation":"Residence was operationalised using urban and rural categories. The causal limitation instead arises because researchers did not manipulate residence and therefore could not control relevant extraneous variables."},{"text":"Drinking was manipulated by researchers experimentally.","correct":false,"explanation":"Risky drinking was measured rather than manipulated, but this alone does not explain the causal limitation. Residence was not experimentally manipulated, so alternative explanations for the association remain."}]},{"id":"ed8cfe03-f6b0-4e1c-bbc0-d69781383bb0","cardType":"basic","points":1,"front":"What data type is urban/rural residence?","back":"Nominal data.","mcqOptions":[{"text":"Nominal data.","correct":true,"explanation":"Urban and rural are separate named categories with no meaningful order or numerical distance between them, so residence produces nominal data."},{"text":"Ordinal data.","correct":false,"explanation":"Ordinal categories have a meaningful rank, such as low, medium and high. Urban and rural have no inherent order, so residence is nominal data."},{"text":"Interval data.","correct":false,"explanation":"Interval data use numerical measurements with equal intervals between values. Urban and rural are non-numerical, unordered categories, so residence is nominal data."},{"text":"Ratio data.","correct":false,"explanation":"Ratio data are numerical measurements with equal intervals and a true zero. Urban and rural are simply unordered labels, making residence nominal data."}]},{"id":"fd3d7a10-7e59-4da5-81de-e8080f0fb56e","cardType":"basic","points":1,"front":"Which test suits an association between two categorical variables?","back":"Chi-square test of association.","mcqOptions":[{"text":"Chi-square test of association.","correct":true,"explanation":"A chi-square test of association determines whether two categorical variables are related by comparing observed frequencies in each category with the frequencies expected by chance."},{"text":"Mann-Whitney U test.","correct":false,"explanation":"Mann-Whitney U compares ordinal or non-normally distributed scores from two independent groups. Two categorical variables instead require a chi-square test of association."},{"text":"Wilcoxon signed-ranks test.","correct":false,"explanation":"Wilcoxon signed-ranks compares paired ordinal or non-normally distributed scores. An association between two categorical variables is tested using a chi-square test of association."},{"text":"Spearman’s rho correlation.","correct":false,"explanation":"Spearman’s rho measures the correlation between two ranked or ordinal variables. Two categorical variables are analysed using a chi-square test of association instead."}]},{"id":"2bf67323-34fc-44c4-b19a-30a631034e58","cardType":"basic","points":1,"front":"Which test suits ordinal/skewed alcohol-risk scores from two independent groups?","back":"Mann-Whitney U test.","mcqOptions":[{"text":"Mann-Whitney U test.","correct":true,"explanation":"Mann-Whitney U compares scores from two independent groups when the data are ordinal or do not meet the assumptions required for a parametric test."},{"text":"Wilcoxon signed-ranks test.","correct":false,"explanation":"Wilcoxon signed-ranks is designed for related or repeated-measures scores. Because the two groups are independent, the appropriate non-parametric test is Mann-Whitney U."},{"text":"Independent-samples t test.","correct":false,"explanation":"An independent-samples t test assumes interval or ratio data with suitable parametric properties. Ordinal or skewed scores from independent groups require Mann-Whitney U."},{"text":"Spearman’s rho test.","correct":false,"explanation":"Spearman’s rho tests a correlation between two ranked variables rather than a difference between groups. Independent groups with ordinal or skewed scores require Mann-Whitney U."}]},{"id":"b12374e3-bc45-45ab-85f5-da87c9c77121","cardType":"basic","points":1,"front":"Which test suits before-and-after scores from the same participants?","back":"Wilcoxon signed-ranks test.","mcqOptions":[{"text":"Wilcoxon signed-ranks test.","correct":true,"explanation":"Wilcoxon signed-ranks compares two sets of ordinal or non-parametric scores from related participants, making it suitable for measurements taken before and after an intervention."},{"text":"Mann-Whitney U test.","correct":false,"explanation":"Mann-Whitney U compares scores from independent groups. Before-and-after measurements come from the same participants, so the appropriate non-parametric test is Wilcoxon signed-ranks."},{"text":"Chi-square test of association.","correct":false,"explanation":"Chi-square tests an association between categorical variables using frequencies. Before-and-after scores are paired measurements, so they require the Wilcoxon signed-ranks test."},{"text":"Spearman’s rho.","correct":false,"explanation":"Spearman’s rho tests whether two ranked variables are correlated. A before-and-after comparison tests a difference between paired scores, requiring Wilcoxon signed-ranks."}]},{"id":"b7e30067-46ea-4098-8f31-738f955e97b5","cardType":"basic","points":1,"front":"Which test suits a correlation between two ranked variables?","back":"Spearman’s rho.","mcqOptions":[{"text":"Spearman’s rho.","correct":true,"explanation":"Spearman’s rho measures the direction and strength of a correlation between two variables expressed as ranks or ordinal scores."},{"text":"Pearson’s r.","correct":false,"explanation":"Pearson’s r is the parametric correlation test, normally requiring interval or ratio data and a linear relationship. Ranked variables require the non-parametric Spearman’s rho."},{"text":"Mann-Whitney U.","correct":false,"explanation":"Mann-Whitney U tests for a difference between two independent groups, not a correlation. A relationship between two ranked variables requires Spearman’s rho."},{"text":"Wilcoxon signed-ranks.","correct":false,"explanation":"Wilcoxon signed-ranks compares paired sets of scores rather than testing a correlation. The relationship between two ranked variables is measured using Spearman’s rho."}]},{"id":"09938e48-f444-491b-9693-6495028ea4a5","cardType":"cloze","points":null,"front":"For Edexcel Psychology, the usual default significance level is [ ].","back":"For Edexcel Psychology, the usual default significance level is $p \\le .05$.","mcqOptions":[{"text":"$$p \\le .05$","correct":true,"explanation":"A result is conventionally treated as statistically significant in Edexcel Psychology when its probability under the null hypothesis is .05 or lower."},{"text":"$$p \\le .01$","correct":false,"explanation":"A .01 threshold is more stringent and may be specified in some research, but the usual default significance level for Edexcel Psychology is $p \\le .05$."},{"text":"$$p \\ge .05$","correct":false,"explanation":"This reverses the inequality. Statistical significance normally requires a probability equal to or below .05, so the default criterion is $p \\le .05$."},{"text":"$$p \\le .10$","correct":false,"explanation":"A .10 threshold allows a higher risk of rejecting a true null hypothesis than the conventional standard. Edexcel Psychology normally uses $p \\le .05$."}]},{"id":"64cf5003-8514-4176-8fd1-dbfc2b733fed","cardType":"basic","points":1,"front":"What is a strength of using real communities rather than a lab?","back":"Higher ecological validity.","mcqOptions":[{"text":"Higher ecological validity.","correct":true,"explanation":"Research conducted in real communities reflects participants’ usual environments and behaviour more closely, so its findings are more likely to apply to everyday life."},{"text":"Higher internal validity.","correct":false,"explanation":"Real community settings usually contain more uncontrolled extraneous variables, which can reduce internal validity. Their main advantage over laboratories is higher ecological validity."},{"text":"Higher experimental control.","correct":false,"explanation":"Laboratories generally provide greater control over variables and procedures than real communities. Community research is valuable because natural settings can produce higher ecological validity."},{"text":"Higher replicability.","correct":false,"explanation":"Natural community conditions are difficult to standardise exactly, so studies may be harder rather than easier to replicate. Their main strength is higher ecological validity."}]},{"id":"3514151c-976d-4811-9c9a-6ed0bbe36160","cardType":"basic","points":2,"front":"How can the findings help public health planning?","back":"Interventions can target groups most at risk.","mcqOptions":[{"text":"Interventions can target groups most at risk.","correct":true,"explanation":"Identifying groups with greater vulnerability allows public health organisations to direct prevention, education and treatment resources towards those most likely to experience harmful alcohol use."},{"text":"Interventions can target groups least at risk.","correct":false,"explanation":"This reverses the practical implication of the findings. Public health interventions should target groups most at risk, because concentrating resources there is most likely to reduce alcohol-related harm."},{"text":"Interventions can target all groups equally.","correct":false,"explanation":"Treating every group identically ignores differences in identified risk. The findings support targeting groups most at risk so that limited public health resources are used effectively."},{"text":"Interventions can target researchers collecting data.","correct":false,"explanation":"Researchers are not the population requiring alcohol-related intervention. The findings help planners identify and target groups most at risk of harmful alcohol use."}]},{"id":"01524b2c-58d8-4799-84e8-9517ca8e1c45","cardType":"basic","points":2,"front":"Why is a biosocial approach a strength?","back":"It reflects interacting biological and social influences.","mcqOptions":[{"text":"It reflects interacting biological and social influences.","correct":true,"explanation":"A biosocial approach recognises that behaviour can result from biological factors operating together with social conditions, providing a more comprehensive explanation than either type alone."},{"text":"It reflects only biological influences on behaviour.","correct":false,"explanation":"Focusing only on biology is a reductionist biological approach, not a biosocial one. The strength is that the approach reflects interacting biological and social influences."},{"text":"It reflects only social influences on behaviour.","correct":false,"explanation":"Considering social factors alone leaves out the biological component of a biosocial explanation. Its strength lies in reflecting interacting biological and social influences."},{"text":"It reflects separate biological and social influences.","correct":false,"explanation":"Merely listing biological and social factors misses the central idea that they influence one another. A biosocial approach is strong because it reflects their interaction."}]},{"id":"02dcc582-a131-4692-8481-e0f9cac9967c","cardType":"basic","points":1,"front":"What bias may affect self-reported alcohol use?","back":"Social desirability bias.","mcqOptions":[{"text":"Social desirability bias.","correct":true,"explanation":"Participants may underreport alcohol consumption to present themselves favourably or conform to social expectations, so self-reported drinking can be distorted by social desirability bias."},{"text":"Observer bias.","correct":false,"explanation":"Observer bias concerns researchers interpreting observed behaviour according to expectations. Private self-reports of alcohol use are instead especially vulnerable to social desirability bias."},{"text":"Publication bias.","correct":false,"explanation":"Publication bias occurs when studies with certain findings are more likely to be published. Distortion within participants’ alcohol reports is more specifically social desirability bias."},{"text":"Allocation bias.","correct":false,"explanation":"Allocation bias arises when participants are assigned unevenly to research conditions. Self-reported alcohol use is instead affected by social desirability bias when respondents manage impressions."}]},{"id":"340057ec-58a2-40b6-931d-f82849dddd97","cardType":"basic","points":2,"front":"How could social desirability bias affect validity?","back":"Reported drinking may not reflect actual alcohol use.","mcqOptions":[{"text":"Reported drinking may not reflect actual alcohol use.","correct":true,"explanation":"If participants alter their answers to appear socially acceptable, their reported drinking differs from their actual alcohol use, reducing the validity of the measurement."},{"text":"Reported drinking may not reflect the researchers’ expectations.","correct":false,"explanation":"Validity is not determined by whether results match researchers’ expectations. Social desirability lowers validity because reported drinking may not reflect actual alcohol use."},{"text":"Reported drinking may not reflect the sample’s average age.","correct":false,"explanation":"Average age is a demographic characteristic rather than the behaviour being measured. The validity problem is that reported drinking may not reflect actual alcohol use."},{"text":"Reported drinking may not reflect the study’s sample size.","correct":false,"explanation":"Sample size affects issues such as representativeness and statistical power, not the accuracy of individual reports. Social desirability means reported drinking may not reflect actual alcohol use."}]},{"id":"448f2cf8-71f8-4ffd-bb55-f7cf752dd345","cardType":"basic","points":2,"front":"Why may findings have limited generalisability?","back":"The study was culturally specific to Aligarh, Uttar Pradesh.","mcqOptions":[{"text":"The study was culturally specific to Aligarh, Uttar Pradesh.","correct":true,"explanation":"The study’s setting in Aligarh, Uttar Pradesh means its findings may reflect local cultural and social conditions, limiting generalisation to other populations or regions."},{"text":"The study was culturally specific to Mumbai, Maharashtra.","correct":false,"explanation":"This confuses the study location with another Indian city and state. The research was culturally specific to Aligarh, Uttar Pradesh, which limits wider generalisability."},{"text":"The study was culturally specific to Kolkata, West Bengal.","correct":false,"explanation":"Kolkata, West Bengal was not the culturally specific setting identified for this study. The relevant location was Aligarh, Uttar Pradesh, restricting broader generalisation."},{"text":"The study was culturally specific to Chennai, Tamil Nadu.","correct":false,"explanation":"This substitutes an unrelated Indian location for the study’s actual cultural setting. The study was specific to Aligarh, Uttar Pradesh, so findings may not transfer elsewhere."}]},{"id":"92b0b738-5e9e-4b87-8522-b1699f2b0a1b","cardType":"basic","points":1,"front":"Which ethical principle protects private alcohol-use data?","back":"Confidentiality.","mcqOptions":[{"text":"Confidentiality.","correct":true,"explanation":"Confidentiality requires researchers to keep participants’ alcohol-use information private and prevent identifiable personal data from being disclosed without appropriate permission."},{"text":"Informed consent.","correct":false,"explanation":"Informed consent ensures participants understand the study and voluntarily agree to take part. Confidentiality is the principle that specifically protects their private alcohol-use data."},{"text":"Right to withdraw.","correct":false,"explanation":"The right to withdraw allows participants to leave the research and sometimes remove their data. Confidentiality specifically requires private alcohol-use information to be protected."},{"text":"Protection from harm.","correct":false,"explanation":"Protection from harm requires researchers to minimise physical and psychological risks. The ethical principle directly concerned with keeping alcohol-use data private is confidentiality."}]}]}],"examCountdown":{"examDate":"2027-05-10","paperLabel":"Paper 1"},"heading":"Contemporary study: Dixit et al. (2012)","title":"Contemporary study: Dixit et al. (2012) Flashcards","topbar":{"backHref":"/as-level/psychology/edexcel/flashcards"},"topicSidebar":"$L38"}]}],"topicId":"12bef3e8-7902-5d47-b0ea-74c75aca8616","walled":"$L39"}],"$L3a","$L3b"]