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behaviour."},{"text":"variable","correct":false,"explanation":"A variable is any factor that can take different values, whereas an abstract psychological idea inferred indirectly from behaviour is specifically called a construct."},{"text":"hypothesis","correct":false,"explanation":"A hypothesis is a testable prediction about variables or outcomes. The underlying abstract idea inferred from behaviour is instead called a construct."},{"text":"operational definition","correct":false,"explanation":"An operational definition states how a concept will be measured in a particular study. The abstract concept being represented is called a construct."}]},{"id":"1d13fa0a-feb2-4809-9f83-49c01e62a577","cardType":"basic","points":1,"front":"When studying anxiety as an unseen construct, what must researchers do first?","back":"They must operationalise it in measurable terms.","mcqOptions":[{"text":"They must operationalise it in measurable terms.","correct":true,"explanation":"Because anxiety cannot be observed directly, researchers must operationalise it by defining a measurable indicator, such as a questionnaire score or observed behaviour."},{"text":"They must standardise it across all participants.","correct":false,"explanation":"Standardisation ensures that all participants experience the same procedure, but researchers must first operationalise anxiety by specifying how the unseen construct will be measured."},{"text":"They must randomise it into experimental groups.","correct":false,"explanation":"Random allocation reduces participant differences between conditions, but it does not define anxiety. Researchers must first operationalise the construct in measurable terms."},{"text":"They must replicate it under controlled conditions.","correct":false,"explanation":"Replication assesses whether findings can be reproduced after a study has been designed. Before collecting data, researchers must operationalise anxiety in measurable terms."}]},{"id":"543492a6-baae-4e59-94e1-d0a7c1959967","cardType":"cloze","points":null,"front":"Reliability asks [ ]; validity asks [ ].","back":"Reliability asks is the measurement consistent?; validity asks is it measuring the intended construct?.","mcqOptions":[{"text":"Reliability asks is the measurement consistent?; validity asks is it measuring the intended construct?.","correct":true,"explanation":"Reliability concerns whether a measure produces consistent results, while validity concerns whether it genuinely measures the psychological construct it was designed to assess."},{"text":"Reliability asks is it measuring the intended construct?; validity asks is the measurement consistent?.","correct":false,"explanation":"The two concepts have been reversed: consistency is the central concern of reliability, whereas measuring the intended construct is the central concern of validity."},{"text":"Reliability asks is the measurement accurate?; validity asks is it consistent over time?.","correct":false,"explanation":"Accuracy alone is not the defining question for reliability, and consistency over time is a form of reliability. Validity instead asks whether the intended construct is measured."},{"text":"Reliability asks does it generalise beyond the study?; validity asks is the same result repeated?.","correct":false,"explanation":"Generalisability concerns external validity, while obtaining the same result repeatedly concerns reliability. Reliability asks about consistency, and validity asks whether the intended construct is measured."}]},{"id":"19bc52a0-1680-430e-9044-ea486ec2b248","cardType":"basic","points":2,"front":"A stress measure gives consistent scores but actually measures revision time. What is the problem?","back":"It has weak validity: it measures revision time, not stress.","mcqOptions":[{"text":"It has weak validity: it measures revision time, not stress.","correct":true,"explanation":"Although the measure is reliable because its scores are consistent, it lacks validity because revision time does not accurately represent the intended construct of stress."},{"text":"It has weak reliability: its scores are inconsistent across repeated tests.","correct":false,"explanation":"Consistent scores indicate strong rather than weak reliability. The problem is weak validity because the measure captures revision time instead of the intended construct of stress."},{"text":"It has weak ecological validity: the task is unlike real-life stress.","correct":false,"explanation":"Ecological validity concerns whether findings generalise to everyday settings, not whether a measure represents its intended construct. Measuring revision time instead of stress shows weak validity."},{"text":"It has weak internal validity: an extraneous variable caused the scores.","correct":false,"explanation":"Internal validity concerns whether the independent variable caused the dependent variable in an experiment. Here, the problem is measurement validity because revision time is not stress."}]},{"id":"4a62b3a0-f265-4d14-aa55-9e7cb4896a7d","cardType":"basic","points":1,"front":"An experiment really shows that the IV caused the DV. Which validity is high?","back":"Internal validity.","mcqOptions":[{"text":"Internal validity.","correct":true,"explanation":"Internal validity is high when researchers can confidently conclude that manipulation of the independent variable caused the observed change in the dependent variable."},{"text":"External validity.","correct":false,"explanation":"External validity concerns whether findings generalise beyond the study. Demonstrating that the independent variable caused the dependent variable specifically indicates high internal validity."},{"text":"Ecological validity.","correct":false,"explanation":"Ecological validity concerns generalisation to natural, everyday settings. A secure causal link between the independent and dependent variables instead demonstrates internal validity."},{"text":"Temporal validity.","correct":false,"explanation":"Temporal validity concerns whether findings generalise to other historical periods. Establishing that the independent variable caused the dependent variable demonstrates internal validity."}]},{"id":"5cfe0971-dd63-46db-a517-78c694e15f5f","cardType":"basic","points":1,"front":"Findings generalise beyond the study to other settings, times, people or tasks. Which validity is supported?","back":"External validity.","mcqOptions":[{"text":"External validity.","correct":true,"explanation":"External validity is the extent to which findings can be generalised beyond the original study across settings, historical periods, populations and tasks."},{"text":"Internal validity.","correct":false,"explanation":"Internal validity concerns whether the independent variable caused the dependent variable within the study. Generalisation to other contexts and populations concerns external validity."},{"text":"Face validity.","correct":false,"explanation":"Face validity judges whether a measure appears appropriate on the surface. Broad generalisation across settings, times, people and tasks demonstrates external validity."},{"text":"Concurrent validity.","correct":false,"explanation":"Concurrent validity compares a new measure with an established measure taken at the same time. Generalisation beyond the original study concerns external validity."}]},{"id":"867ffac5-9920-4f07-b6c9-8decd6263a56","cardType":"cloze","points":null,"front":"Ecological and temporal validity are both types of [ ].","back":"Ecological and temporal validity are both types of external validity.","mcqOptions":[{"text":"external validity","correct":true,"explanation":"External validity concerns generalisation beyond the original study. Ecological validity covers other settings, while temporal validity covers other times or historical periods."},{"text":"internal validity","correct":false,"explanation":"Internal validity concerns whether a study supports a causal conclusion without confounding variables. Ecological and temporal validity are instead forms of external validity."},{"text":"face validity","correct":false,"explanation":"Face validity concerns whether a measure appears to assess its intended construct. Ecological and temporal validity both concern generalisation, making them types of external validity."},{"text":"criterion validity","correct":false,"explanation":"Criterion validity assesses agreement with an independent outcome or established criterion. Ecological and temporal validity address generalisation beyond a study, so they are types of external validity."}]},{"id":"1f03b8b3-6123-4d22-bb7b-3554abf141a8","cardType":"basic","points":1,"front":"A questionnaire appears on the surface to measure social anxiety. Which validity type is being judged?","back":"Face validity.","mcqOptions":[{"text":"Face validity.","correct":true,"explanation":"Face validity is judged from whether a measure appears, at surface level, to assess its intended construct, such as social anxiety."},{"text":"Content validity.","correct":false,"explanation":"Content validity examines whether a measure adequately represents the full range of the construct. A surface-level judgement about appearance specifically concerns face validity."},{"text":"Concurrent validity.","correct":false,"explanation":"Concurrent validity is established by correlating a new measure with an accepted measure administered at the same time. Surface appearance is judged using face validity."},{"text":"Construct validity.","correct":false,"explanation":"Construct validity is broader evidence that a measure genuinely represents its theoretical construct. Judging only whether the questionnaire appears appropriate concerns face validity."}]},{"id":"1b6f6e59-4c6c-4181-94bb-3f82eca02dcd","cardType":"basic","points":1,"front":"How is face validity usually assessed?","back":"By inspection of whether the measure seems appropriate.","mcqOptions":[{"text":"By inspection of whether the measure seems appropriate.","correct":true,"explanation":"Face validity is judged by inspecting the measure and deciding whether, on the surface, it appears to measure the intended concept appropriately."},{"text":"By calculation of whether the measure produces significant results.","correct":false,"explanation":"Statistical significance concerns whether an observed result is likely under the null hypothesis. Face validity is assessed by inspecting whether the measure appears appropriate."},{"text":"By repetition of whether the measure produces consistent results.","correct":false,"explanation":"Repeating a measure assesses reliability, which concerns consistency rather than validity. Face validity is assessed by inspecting whether the measure appears to measure the intended concept."},{"text":"By comparison of whether the measure correlates with a criterion.","correct":false,"explanation":"Correlation with an established criterion assesses concurrent validity, not face validity. Face validity is usually assessed through inspection of whether the measure seems appropriate."}]},{"id":"cc4f070f-eaba-4931-82bd-4dc9144977d3","cardType":"basic","points":2,"front":"If a measure’s aim is too obvious, what participant effect may reduce validity?","back":"Demand characteristics: participants change behaviour after guessing the aim.","mcqOptions":[{"text":"Demand characteristics: participants change behaviour after guessing the aim.","correct":true,"explanation":"When participants work out the study’s aim, they may deliberately or unconsciously alter their behaviour, so the results no longer reflect their natural responses."},{"text":"Order effects: participants change behaviour because of fatigue or practice.","correct":false,"explanation":"Order effects arise from fatigue or practice in repeated-measures research, not from identifying the study’s aim. Guessing the aim can produce demand characteristics."},{"text":"Participant attrition: participants leave before the research is completed.","correct":false,"explanation":"Participant attrition means individuals withdraw from a study, which may bias the remaining sample. An obvious aim instead risks demand characteristics as participants alter their behaviour."},{"text":"Investigator effects: researchers unintentionally influence participants’ behaviour.","correct":false,"explanation":"Investigator effects result from a researcher’s behaviour or expectations influencing participants. When participants alter behaviour because they have guessed the aim, demand characteristics are occurring."}]},{"id":"da16c845-2b0f-4838-b175-aef85bf6f59c","cardType":"cloze","points":null,"front":"Concurrent validity compares a new measure with an established [ ] at roughly the [ ].","back":"Concurrent validity compares a new measure with an established criterion at roughly the same time.","mcqOptions":[{"text":"Concurrent validity compares a new measure with an established criterion at roughly the same time.","correct":true,"explanation":"Concurrent validity is established when scores from a new measure correspond with an accepted criterion measured at approximately the same time."},{"text":"Concurrent validity compares a new measure with an established hypothesis at roughly the same time.","correct":false,"explanation":"A hypothesis is a testable prediction, not an established standard for comparison. Concurrent validity compares the new measure with an established criterion at roughly the same time."},{"text":"Concurrent validity compares a new measure with an established criterion at roughly the later time.","correct":false,"explanation":"Comparison with a future outcome concerns predictive validity. Concurrent validity requires the new measure and the established criterion to be assessed at roughly the same time."},{"text":"Concurrent validity compares a new measure with an established observation at roughly the earlier time.","correct":false,"explanation":"Concurrent validity does not compare the measure with any earlier observation. It requires comparison with an established criterion assessed at roughly the same time."}]},{"id":"1c81dcef-531b-478e-96b2-b2c9096b6b3a","cardType":"basic","points":2,"front":"In concurrent validity, what if the observed correlation exceeds the critical value?","back":"Reject $H_0$; evidence supports concurrent validity.","mcqOptions":[{"text":"Reject $H_0$; evidence supports concurrent validity.","correct":true,"explanation":"A correlation exceeding the critical value is statistically significant, so the null hypothesis of no association is rejected and the result supports concurrent validity."},{"text":"Accept $H_0$; evidence supports concurrent validity.","correct":false,"explanation":"Accepting the null hypothesis would mean treating the correlation as non-significant, which cannot support concurrent validity. Exceeding the critical value means rejecting $H_0$."},{"text":"Reject $H_0$; evidence supports ecological validity.","correct":false,"explanation":"A significant correlation with an established criterion supports concurrent validity, not generalisation to everyday settings and behaviour, which concerns ecological validity."},{"text":"Retain $H_0$; evidence rejects concurrent validity.","correct":false,"explanation":"The null hypothesis is retained when the observed correlation does not reach the critical value. Exceeding that value requires rejecting $H_0$ and supports concurrent validity."}]},{"id":"b12b0876-3ac7-44bb-ad83-638a8b73ef14","cardType":"basic","points":1,"front":"Which correlation test suits interval or ratio data meeting parametric assumptions?","back":"Pearson’s r.","mcqOptions":[{"text":"Pearson’s r.","correct":true,"explanation":"Pearson’s r tests the strength and direction of a linear correlation between interval or ratio variables when the relevant parametric assumptions are met."},{"text":"Spearman’s rho.","correct":false,"explanation":"Spearman’s rho is a non-parametric correlation test suited to ordinal, ranked or non-normal data. Suitable interval or ratio data meeting parametric assumptions require Pearson’s r."},{"text":"Wilcoxon’s T.","correct":false,"explanation":"Wilcoxon’s T tests a difference between two related sets of scores rather than a correlation. Pearson’s r is appropriate for parametric interval or ratio data."},{"text":"Mann-Whitney’s U.","correct":false,"explanation":"Mann-Whitney’s U tests a difference between two independent groups using non-parametric data. Pearson’s r tests correlation for suitable interval or ratio data."}]},{"id":"beedc5dc-b54a-4c89-9de9-134f800092d5","cardType":"basic","points":1,"front":"Which correlation test suits ordinal, ranked or non-normal data?","back":"Spearman’s rho.","mcqOptions":[{"text":"Spearman’s rho.","correct":true,"explanation":"Spearman’s rho is a non-parametric test of correlation, making it suitable when data are ordinal, converted into ranks or do not meet normality assumptions."},{"text":"Pearson’s r.","correct":false,"explanation":"Pearson’s r is a parametric correlation test generally requiring interval or ratio data and relevant assumptions. Ordinal, ranked or non-normal data require Spearman’s rho."},{"text":"Wilcoxon’s T.","correct":false,"explanation":"Wilcoxon’s T is a non-parametric test of difference for related data, not a test of correlation. Spearman’s rho is used for ranked or ordinal correlations."},{"text":"Chi-squared.","correct":false,"explanation":"Chi-squared examines associations or differences involving categorical frequencies, rather than correlations between ranked scores. Spearman’s rho suits ordinal, ranked or non-normal data."}]},{"id":"e1fb6126-bbf0-49da-96a3-ac3e408e0a4a","cardType":"basic","points":1,"front":"Give one reason a significant correlation does not prove a new measure is valid.","back":"The criterion may be flawed.","mcqOptions":[{"text":"The criterion may be flawed.","correct":true,"explanation":"A strong correlation only shows agreement with the chosen criterion. If that criterion is itself invalid or inaccurate, matching it does not establish the new measure’s validity."},{"text":"The new measure may be reliable.","correct":false,"explanation":"Reliability means a measure produces consistent results and does not undermine evidence of validity. The real concern is that a flawed criterion could create misleading validation."},{"text":"The sample may be representative.","correct":false,"explanation":"A representative sample strengthens generalisability rather than explaining why the correlation fails to establish validity. A significant relationship is unconvincing if the criterion itself is flawed."},{"text":"The scores may be normally distributed.","correct":false,"explanation":"Normally distributed scores help satisfy assumptions for Pearson’s r but do not invalidate a significant correlation. Validity remains uncertain if the established criterion is flawed."}]},{"id":"ba302793-6f36-4baa-9979-2e69a363f80b","cardType":"cloze","points":null,"front":"Ecological validity concerns generalising findings to [ ] and [ ].","back":"Ecological validity concerns generalising findings to real-life settings and everyday behaviour.","mcqOptions":[{"text":"Ecological validity concerns generalising findings to real-life settings and everyday behaviour.","correct":true,"explanation":"Ecological validity concerns whether research findings apply beyond the study itself, particularly to situations and behaviour encountered in ordinary, real-world life."},{"text":"Ecological validity concerns generalising findings to laboratory settings and everyday behaviour.","correct":false,"explanation":"Laboratory settings are controlled research environments rather than the real-world contexts central to ecological validity. Findings must generalise to real-life settings and everyday behaviour."},{"text":"Ecological validity concerns generalising findings to real-life settings and physiological responses.","correct":false,"explanation":"Physiological responses are a type of measurement, not the broader target of ecological generalisation. Ecological validity concerns applying findings to real-life settings and everyday behaviour."},{"text":"Ecological validity concerns generalising findings to controlled settings and artificial behaviour.","correct":false,"explanation":"Controlled settings and artificial behaviour are features that may reduce ecological validity. High ecological validity involves generalisation to real-life settings and everyday behaviour."}]},{"id":"ef1c69a0-9b2b-42fa-9b09-383709caa1f9","cardType":"basic","points":2,"front":"Why might a highly controlled lab task have lower ecological validity?","back":"The task may be artificial, limiting real-life generalisation.","mcqOptions":[{"text":"The task may be artificial, limiting real-life generalisation.","correct":true,"explanation":"Lab experiments often use tightly controlled, artificial tasks, so behaviour may not reflect what people do in everyday settings. That limits ecological validity, which concerns real-life generalisation."},{"text":"The sample may be biased, limiting population generalisation.","correct":false,"explanation":"A biased sample affects population validity rather than ecological validity. The issue with a highly controlled lab task is that the task may be artificial, limiting real-life generalisation."},{"text":"The procedure may be inconsistent, limiting test-retest reliability.","correct":false,"explanation":"Inconsistent procedures are a reliability problem, not the main ecological validity issue. Lower ecological validity comes from an artificial task that may not generalise to everyday behaviour."},{"text":"The participants may guess the aim, limiting internal validity.","correct":false,"explanation":"Guessing the aim is a demand characteristics issue affecting internal validity. Ecological validity is lower when the task itself is artificial and therefore hard to generalise to real life."}]},{"id":"a539ea67-6f88-495f-ba9e-315baf73c211","cardType":"basic","points":3,"front":"How is mundane realism different from ecological validity?","back":"

Mundane realism: the task resembles real life.
Ecological validity: findings generalise to real life.

","mcqOptions":[{"text":"

Mundane realism: the task resembles real life.
Ecological validity: findings generalise to real life.

","correct":true,"explanation":"Mundane realism is about whether the task looks like everyday activity. Ecological validity is broader: whether the findings can be applied to real-life settings."},{"text":"

Mundane realism: findings generalise to real life.
Ecological validity: the task resembles real life.

","correct":false,"explanation":"This reverses the two terms. Mundane realism concerns how realistic the task appears, while ecological validity concerns whether the findings generalise to real life."},{"text":"

Mundane realism: the sample represents real life.
Ecological validity: participants represent the population.

","correct":false,"explanation":"This confuses both terms with population validity. Mundane realism is about the realism of the task, and ecological validity is about real-life generalisation of findings."},{"text":"

Mundane realism: the study is tightly controlled.
Ecological validity: extraneous variables are controlled.

","correct":false,"explanation":"This describes experimental control, which is linked to internal validity. Mundane realism is task realism, while ecological validity is whether findings generalise to real life."}]},{"id":"a72c37d6-c5f5-4194-b22b-56de51035549","cardType":"cloze","points":null,"front":"Temporal validity is assessed through [ ] over [ ].","back":"Temporal validity is assessed through replication over time.","mcqOptions":[{"text":"Temporal validity is assessed through replication over time.","correct":true,"explanation":"Temporal validity concerns whether findings remain true across historical periods. Replicating research over time shows whether the original conclusions still apply."},{"text":"Temporal validity is assessed through reliability over participants.","correct":false,"explanation":"This confuses temporal validity with consistency across people. Temporal validity is assessed by replication over time to see whether findings still hold in later periods."},{"text":"Temporal validity is assessed through operationalisation over settings.","correct":false,"explanation":"Operationalisation checks whether variables are defined clearly, and settings relate more to ecological validity. Temporal validity is assessed through replication over time."},{"text":"Temporal validity is assessed through sampling over populations.","correct":false,"explanation":"This is a population validity misconception. Temporal validity is about whether findings remain valid across time, so it is assessed through replication over time."}]},{"id":"f610de2c-99d9-445b-b885-605b061f00a6","cardType":"basic","points":2,"front":"Why might Asch’s 1956 conformity findings have lower temporal validity today?","back":"Society has changed since 1956.","mcqOptions":[{"text":"Society has changed since 1956.","correct":true,"explanation":"Temporal validity is reduced when findings may no longer apply because the historical context has changed. Social norms around conformity may differ from those in 1956."},{"text":"The sample was biased in 1956.","correct":false,"explanation":"Sample bias would affect population validity, not temporal validity. Asch’s findings may have lower temporal validity today because society has changed since 1956."},{"text":"The task was artificial in 1956.","correct":false,"explanation":"An artificial task affects ecological validity, not temporal validity. The temporal issue is that society has changed since 1956, so conformity levels may differ today."},{"text":"Statistics have improved since 1956.","correct":false,"explanation":"Better statistical techniques do not explain why the original conformity findings may apply less well now. The temporal validity concern is that society has changed since 1956."}]},{"id":"c76a7c4b-abc7-40bc-b775-cc8d9ee0198e","cardType":"basic","points":1,"front":"How can a researcher make a task itself more ecologically valid?","back":"Use a more realistic task.","mcqOptions":[{"text":"Use a more realistic task.","correct":true,"explanation":"Making the actual task closer to everyday behaviour increases mundane realism and can support ecological validity, because the behaviour studied is less artificial."},{"text":"Use a larger sample.","correct":false,"explanation":"A larger sample may improve representativeness or statistical power, but it does not make the task itself more realistic. Ecological validity of the task improves by using a more realistic task."},{"text":"Use a standardised script.","correct":false,"explanation":"A standardised script improves control and reliability, but it may leave the task just as artificial. To improve the task’s ecological validity, make the task more realistic."},{"text":"Use a double-blind design.","correct":false,"explanation":"A double-blind design reduces researcher and participant expectation effects, which helps internal validity. It does not make the task itself more realistic; that requires a more realistic task."}]},{"id":"bad88778-6414-476d-98a3-53ff87ea19b6","cardType":"basic","points":2,"front":"In observations, what does clear operationalisation of behavioural categories help ensure?","back":"Categories represent the target behaviour.","mcqOptions":[{"text":"Categories represent the target behaviour.","correct":true,"explanation":"Clear operationalisation improves validity by ensuring the behavioural categories actually capture the behaviour the researcher intends to study, rather than a vague or unrelated action."},{"text":"Categories represent the whole population.","correct":false,"explanation":"Representing the whole population is a sampling issue, not a behavioural category issue. Operationalised categories help ensure the observations represent the target behaviour being measured."},{"text":"Categories hide the research hypothesis.","correct":false,"explanation":"Hiding the hypothesis is about reducing demand characteristics or observer expectations. Operationalising behavioural categories helps validity by ensuring categories represent the target behaviour."},{"text":"Categories increase participant confidentiality.","correct":false,"explanation":"Confidentiality is an ethical safeguard, not the purpose of behavioural categories. Clear operationalisation helps ensure the categories represent the target behaviour in the observation."}]},{"id":"4f557875-9e1b-4afb-b81b-494663146a44","cardType":"cloze","points":null,"front":"Triangulation uses more than one [ ] or [ ].","back":"Triangulation uses more than one method or data source.","mcqOptions":[{"text":"Triangulation uses more than one method or data source.","correct":true,"explanation":"Triangulation strengthens validity by comparing evidence from different methods or data sources. If they point to the same conclusion, confidence in the finding increases."},{"text":"Triangulation uses more than one aim or hypothesis.","correct":false,"explanation":"Multiple aims or hypotheses do not provide cross-checking evidence. Triangulation means using more than one method or data source to strengthen validity."},{"text":"Triangulation uses more than one condition or control group.","correct":false,"explanation":"This confuses triangulation with experimental design. Triangulation involves using more than one method or data source, not simply adding conditions or control groups."},{"text":"Triangulation uses more than one mean or standard deviation.","correct":false,"explanation":"Means and standard deviations are descriptive statistics, not sources of evidence. Triangulation uses more than one method or data source to check validity."}]},{"id":"09fba927-5431-42fc-bdc0-0e78d7920e52","cardType":"basic","points":3,"front":"What validity-ethics trade-off occurs when using deception?","back":"

Validity: deception can reduce demand characteristics.
Ethics: it weakens informed consent and requires debriefing.

","mcqOptions":[{"text":"

Validity: deception can reduce demand characteristics.
Ethics: it weakens informed consent and requires debriefing.

","correct":true,"explanation":"Deception may improve validity because participants are less likely to alter behaviour to fit the study aims. Ethically, it limits informed consent, so debriefing is needed afterwards."},{"text":"

Validity: deception can increase demand characteristics.
Ethics: it strengthens informed consent and avoids debriefing.

","correct":false,"explanation":"This reverses the usual trade-off. Deception can reduce demand characteristics, but it weakens informed consent and creates an ethical need for debriefing."},{"text":"

Validity: deception can improve population validity.
Ethics: it mainly protects confidentiality and privacy.

","correct":false,"explanation":"This confuses different issues. Deception targets demand characteristics, not population validity, and its ethical problem is weakened informed consent, requiring debriefing."},{"text":"

Validity: deception can improve test-retest reliability.
Ethics: it removes the need for informed consent.

","correct":false,"explanation":"Deception is not mainly used to improve test-retest reliability. It can reduce demand characteristics, but ethically it weakens informed consent and therefore requires debriefing."}]}]}],"examCountdown":{"examDate":"2027-05-18","paperLabel":"Paper 1"},"heading":"Validity (A-level only)","title":"Validity (A-level only) Flashcards","topbar":{"backHref":"/a-level/psychology/aqa/flashcards"},"topicSidebar":"$L36"}]}],"topicId":"e6bf5c51-43bc-5875-a1b3-a47feb3eb0eb","walled":"$L37"}],"$L38","$L39"]