Scale Development Guidelines
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Questions and Answers

What is a critical consideration when developing a scale to measure a specific construct?

  • Excluding any items that might overlap with or tap into other related constructs. (correct)
  • Ensuring the scale includes items that measure a broad range of related constructs.
  • Prioritizing items that are applicable to all situations, regardless of the construct's specificity.
  • Including some items that may seem different, but actually tap into the same construct.

Why might certain items on a depression scale, such as those related to somatic symptoms, cause issues when used among people with chronic illnesses?

  • Because those with chronic illnesses do not experience the somatic elements of depression.
  • Because they are not specific enough and will result in lower scores for the depression scale.
  • Because somatic symptoms are exclusive to depression and should be measured regardless of other health conditions.
  • Because they may mistake symptoms of the illness for symptoms of depression, leading to over diagnosis. (correct)

What initial step should a scale developer take before generating an item pool?

  • Clearly articulate and define the purpose of the scale they aim to build. (correct)
  • Decide what statistics will be used to ensure validity
  • Determine if the construct is similar to other constructs within the field.
  • Administer the scale to a small group of people to see their response

In generating an item pool, what should be the primary guide for selecting or creating items?

<p>The specific goals and purpose for which the scale is intended to measure. (C)</p> Signup and view all the answers

When might it be important to include somatic items in a depression measure?

<p>When researchers are specifically interested in the somatic aspects of negative affect. (C)</p> Signup and view all the answers

In the context of scale development, what does it mean for items to 'cross over' into a related construct?

<p>An item meant to assess one construct inadvertently measures another. (D)</p> Signup and view all the answers

According to the content, what is the first step when constructing a measurement scale after clearly defining its purpose?

<p>Generate a large pool of possible items to include in the scale. (A)</p> Signup and view all the answers

Which of the following best describes the relationship between 'barriers' and 'latent variables' in the context of compliance?

<p>Barriers are a category of constructs, where each barrier is associated with a separate latent variable. (A)</p> Signup and view all the answers

Why might items measuring different constructs within the same 'barriers' category not covary as expected?

<p>They are measuring different underlying constructs. (D)</p> Signup and view all the answers

How does the concept of redundancy function in the development of a measurement scale?

<p>Redundancy is a desirable feature, as it captures common content while averaging out the unique aspects of the items. (C)</p> Signup and view all the answers

What is the benefit of using multiple, seemingly redundant items when measuring a phenomenon?

<p>To enhance the representation of the phenomenon through the shared content while minimizing non-essential item specificities. (A)</p> Signup and view all the answers

What type of redundancy does the text suggest as beneficial within a scale?

<p>Redundancy in which items capture the construct of interest. (D)</p> Signup and view all the answers

Why is it recommended to be more inclusive during the early stages of scale development regarding redundancy?

<p>To capture the phenomenon of interest from many unique item manifestations. (B)</p> Signup and view all the answers

How does the use of redundant items impact a scale's reliability?

<p>It increases the reliability of the scale by mitigating the impact of idiosyncratic variations of individual items. (C)</p> Signup and view all the answers

What does the explanation of the 'Spearman-Brown prophecy formula' indicate about the relationship between reliability and the number of items in a scale?

<p>Reliability increases with a larger number of items, all else being equal (A)</p> Signup and view all the answers

What is a primary concern when using a sample where relationships among items differ from the broader population?

<p>Items may have different meanings for the sample than for the general population. (A)</p> Signup and view all the answers

In the context of scale development, what might be reflected by unusual patterns of association among items in a sample?

<p>Shared attributes specific to the sample but rare in the broader community. (D)</p> Signup and view all the answers

If a sample does not understand a key word within a scale's items, how might this affect the scale's performance?

<p>It may obscure how the scale would perform in different contexts. (C)</p> Signup and view all the answers

What does the example of the word 'sick' in the United States and England illustrate?

<p>The same word can have different culturally contextual meanings. (D)</p> Signup and view all the answers

How might a health scale, developed in the United States, perform differently in England when using the word 'ill'?

<p>Items using 'ill' might cluster together distinctly due to its association with nausea. (D)</p> Signup and view all the answers

What is a potential issue that may arise when using the term 'bad blood' in a scale administered in the Southern United States?

<p>The term may be interpreted differently, as a euphemism for venereal disease. (B)</p> Signup and view all the answers

What can be a significant consequence of using an unrepresentative sample in scale development, in terms of the scale structure?

<p>The patterns of covariation among items may be a result of the specific sample used. (B)</p> Signup and view all the answers

When should a researcher exercise great caution while interpreting the findings from a development sample?

<p>When it is suspected that the meanings of items may be interpreted differently in the sample. (B)</p> Signup and view all the answers

What is the primary purpose of including response bias scales in instruments like the MMPI?

<p>To detect patterns of responding that may distort results. (D)</p> Signup and view all the answers

Why should researchers consider including measures of related constructs during the item development phase?

<p>To gather evidence about the scale's construct validity during development. (C)</p> Signup and view all the answers

What is the main reason for using a large sample when administering items in the scale development process?

<p>To reduce the impact of variance related to items, not participants. (D)</p> Signup and view all the answers

What does Nunnally suggest as an adequate sample size for scale development?

<p>Approximately 300 subjects. (B)</p> Signup and view all the answers

What is one potential risk of using a small developmental sample in scale development?

<p>Unstable patterns of item covariation. (D)</p> Signup and view all the answers

If items are selected based on their contribution to alpha in a study, what is a potential problem with using a small developmental sample?

<p>The alpha will be overestimated. (A)</p> Signup and view all the answers

If a researcher is aiming to extract a single scale from a pool of 20 items, what does the content suggest about the required sample size?

<p>A sample size smaller than 300 might be adequate. (A)</p> Signup and view all the answers

What should be the focus of a researcher when determining the sample size for a scale development study?

<p>Obtaining a sample that captures the item variance, not the participant variance. (B)</p> Signup and view all the answers

When a researcher uses a 0-to-100 scale for a two-item questionnaire, what is the primary benefit they are hoping to achieve?

<p>To identify subtle differences in participant responses. (A)</p> Signup and view all the answers

What is a potential drawback of using a large number of response options (e.g., 50) on a questionnaire?

<p>It may result in lower reliability due to participant fatigue or boredom. (D)</p> Signup and view all the answers

When respondents are given a large number of response options, such as 50, which of the following is a common tendency?

<p>They often use only those response options that are multiples of five or ten. (D)</p> Signup and view all the answers

Why might there be no benefit as the scale's variance increases?

<p>The increased variance could be entirely due to random error rather than the phenomenon's true differences. (B)</p> Signup and view all the answers

How can researchers reduce ambiguity when using vague quantity descriptors in options?

<p>By arranging the descriptors in a continuum that implies an ordering of magnitude. (C)</p> Signup and view all the answers

When is it most appropriate to use a simpler binary response format such as 'angry' versus 'not angry'?

<p>When there are a high number of questions in a survey or scale. (C)</p> Signup and view all the answers

What problem can arise when participants are asked to discriminate among vague quantity descriptors like 'few', 'many', and 'several'?

<p>Ambiguity in the terms can interfere with participants' ability to meaningfully differentiate the response options. (B)</p> Signup and view all the answers

What does it mean when a scale has 'false precision'?

<p>The scale's precision suggests differences in measurement where there is no actual difference. (D)</p> Signup and view all the answers

What is the primary goal when evaluating the performance of individual items in a scale?

<p>To achieve high correlation with the true score of the latent variable (D)</p> Signup and view all the answers

How can item reliability be inferred during the evaluation phase?

<p>By examining the correlation matrix of the items (D)</p> Signup and view all the answers

What should be considered if some items have negative correlations with others?

<p>To consider reverse scoring those items (C)</p> Signup and view all the answers

What does high intercorrelation among scale items indicate?

<p>The individual item reliabilities are also high (C)</p> Signup and view all the answers

Which aspect is considered second in importance after item development in the scale development process?

<p>Item evaluation (C)</p> Signup and view all the answers

What methodological approach relates the correlation between any two items to their individual item reliabilities?

<p>Parallel tests (C)</p> Signup and view all the answers

Why might a developer inadvertently create negatively correlated items?

<p>By attempting to combine separately anticipated groups of items (B)</p> Signup and view all the answers

Which quality is paramount when selecting items for a scale?

<p>Items should have high correlations with each other (C)</p> Signup and view all the answers

Flashcards

Construct Specificity

The ability of a scale to measure what it intends to measure, without capturing other related concepts.

Scale Breadth

Scales can measure general concepts like 'anxiety' or specific ones like 'test anxiety'. Choose based on your research goals.

Item Crossover

When items on a scale may unintentionally measure multiple constructs, potentially confusing the results.

Item Selection in Scale Development

It's crucial to ensure scale items reflect the specific purpose of the instrument, aligning with the intended measurement goal.

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Generating an Item Pool

The process of creating a large pool of potential questions or statements that could be used in a scale.

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Choosing Items That Reflect the Scale’s Purpose

Items should be carefully selected or created to align with the specific purpose of the scale, ensuring that they measure the intended concept.

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Response options

The number of options available to a respondent when answering a question in a survey or experiment.

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Respondent discrimination

The level of detail or precision that a respondent can provide in their answer. For example, can they distinguish between 'slightly angry' and 'moderately angry'?

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Scale variance

The ability of a scale to measure meaningful differences in the underlying phenomenon being studied.

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Error variance

Random fluctuations or errors in the data that do not reflect the true underlying phenomenon.

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Scale reliability

The extent to which a scale consistently measures the phenomenon it is intended to measure. It can be affected by factors like fatigue or ambiguity.

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Vague quantity descriptors

The use of vague or imprecise language to describe response options, which can lead to ambiguity and unreliable data.

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Response option arrangement

Using the physical arrangement of response options on a page to guide the respondent's understanding and response. This can help to avoid ambiguity.

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Continuum scale

A type of scale that presents a clear and continuous range of options, making it easier for respondents to understand what is being asked.

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Barriers to compliance

A category of factors that prevent people from participating in a certain action, like getting medical treatment.

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Redundancy in scales

The presence of multiple items in a scale that measure the same underlying concept or construct.

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Benefits of redundancy

Redundancy can be beneficial in scale development, as it allows for more reliable measurement and reduces the impact of random errors in individual items.

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Types of redundancy

While some redundancy is desirable, it should be focused on measuring the core construct, not on incidental aspects of the items.

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Spearman-Brown prophecy formula

The Spearman-Brown prophecy formula illustrates how increasing the number of items in a scale increases its reliability.

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Covariance of different constructs

Items measuring different constructs within the same category (e.g., fear and cost) should not be expected to correlate as strongly as items measuring a single construct.

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Latent variables

Latent variables are underlying concepts that cannot be directly observed, but are inferred from measured variables.

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Redundancy in item development

Items in a scale are expected to be redundant in terms of measuring the underlying construct.

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Non-representative Sample

A sample that does not accurately reflect the characteristics of the population it's supposed to represent. This can lead to skewed results and inaccurate conclusions.

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Item Meaning Variance

When items on a scale have different meanings for people in different groups, leading to inaccurate interpretations of the scale.

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Atypical Item Interrelationships

The patterns of relationships between items on a scale may be unique to the sample and not representative of the broader population.

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Different Causal Structure

The relationships between variables and true scores in a sample may differ from the population, making it difficult to generalize findings.

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Lack of Understanding Key Terms

When a sample doesn't understand key terms used in the scale. This can lead to inaccurate responses and misinterpretations.

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Cultural Variations in Item Meaning

The meaning of items on a scale can vary across different cultures or even regions. This can make it difficult to compare results.

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Consequences of Sample Nonrepresentativeness

The potential for findings from a non-representative sample to be misleading and not generalizable to the wider population.

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Scale Structure

The underlying structure of a scale, revealed through patterns of covariation between items. This structure should be representative of the population.

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Response Bias Scales

A set of items designed to detect response biases, such as faking good or faking bad, in a personality inventory.

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Construct Validity

The extent to which a scale measures the intended construct, relying on evidence from other measures of related concepts.

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Concurrent Measure of Related Constructs

Measuring relevant constructs alongside the main scale to gather validity evidence during scale development.

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Adequate Sample Size

A large enough sample size to reduce the influence of participant differences and ensure stable patterns of item covariation.

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Sampling Items from a Hypothetical Universe

Sampling items from a theoretical pool of potential items, aiming to represent a wide range of the construct.

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Subject Variance

The influence of participant differences on the scale results, especially in smaller samples.

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Item Instability

The tendency of an item to appear as a good indicator of a construct, but later prove unreliable when tested on a different sample.

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Alpha Coefficient

A statistical measure of internal consistency, indicating how well the items in a scale measure the same underlying construct.

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Item Evaluation

In scale development, evaluating individual items to identify the best ones for the final scale, determining their quality and suitability.

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Item Quality

A high correlation between an item and the true score of what it measures, meaning it is measuring the intended concept accurately.

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Intercorrelation of Items

Analyzing how well items are related to each other by examining the correlations between them.

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Reverse Scoring

Adjusting an item's scoring direction to ensure its relationship with other items is consistent. This is often needed when items are worded in opposite directions.

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Negatively Correlated Items

Items that have negative correlations with other items, suggesting they might measure a different concept or be worded incorrectly.

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Item Selection

Focuses on choosing items that accurately reflect the intended purpose and concept of the scale, ensuring all items contribute to measuring the same construct.

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Study Notes

Guidelines in Scale Development

  • Researchers should clearly define what they want to measure. This is crucial at the outset to avoid costly errors later in the process.
  • It's vital to base scales on relevant established social science theories. If extant theory doesn't offer guidance, a new intellectual direction is justified.
  • Specify a preliminary theoretical model to guide scale development. This may encompass a definition of the phenomenon being measured or a description of the relationship to existing constructs.
  • The level of specificity of the construct to be measured alongside tangible criteria is essential and needs to be considered.

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Description

This quiz covers essential guidelines in the development of measurement scales in social science research. It emphasizes the importance of defining what to measure, grounding scales in established theories, and specifying a theoretical model. Understanding these principles is crucial for effective and valid measurement.

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