15 April 2024 794 words, 4 min. read

Multi-item or single-item scales: How do you choose?

By Pierre-Nicolas Schwab PhD in marketing, director of IntoTheMinds
In this article, I deal with a rather technical but especially important subject in quantitative research: choosing the right measurement scale. I give you 8 points of comparison to make the right choice.

If you are conducting a survey, scales will help you measure variables. A scale is a way of measuring the response to a question. There are 2 families of scales in use: multi-item and single-item. Multi-item scales comprise several questions or items assessing various aspects of the same construct. Single-item scales measure a construct with a single question or item. The choice between these scales affects the research results’ precision, reliability, and applicability. I propose comparing these two scales along 8 important dimensions in this article.

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Multi-item scale Single-item scale
Concreteness of the construct abstract constructs concrete constructs
Dimensionality/complexity multidimensional, moderately complex, unidimensional, or extremely complex
Semantic redundancy low high
Main role of constructing dependent or independent variable moderator or control variable
Desired accuracy high low
Tracking of changes adequate to avoid
Sample population heterogeneous homogeneous
Available sample size large small

To compare the 2 scale types, I propose to analyze 8 dimensions.

Concreteness

Multi-item scale

Several indicators are used to “measure” the various facets of a concept. This minimizes interpretative variance. In this way, a construct can be measured more abstractly.

Single-item scales

These are ideal if you want to conduct a concrete measurement. However, they are only problematic if the construct is simple. My rule is simple: reserve single-item scales for concrete, universally understood constructs.

Dimensionality/complexity

Multi-item scales

Simply put, the more dimensions a construct has, the more important it is to use a multi-item scale. In other words, when the construct is multifaceted, each item will represent a different dimension or aspect.

Single-item scale

By contrast, single-item scales are more suited to unidimensional measurement. As I wrote in the previous paragraph, the single-item scale will be reserved for naturally simple and coherent constructs. I won’t go into the question of representativeness here, but you can easily understand that it’s a challenge. It would help if you made sure that the item used is truly representative of the entire construct. Conduct a literature review and use a confirmed scale to ensure everything runs smoothly. This will help you to avoid headaches.

Semantic redundancy

Multi-item scales

I often tell my colleagues that the most important questions regarding market research deserve to be asked twice. It’s the same with scales, and it’s called semantic redundancy. It is commonly applied to multi-item scales. Its purpose is to enhance measurement reliability.

Single-item scales

Of course, when your scale has only one question (item), it cannot feature semantic redundancy. Therefore, you play a significant role in formulating and interpreting the item. As a result, the reliability of your measurement will depend entirely on a single question.

Asking just one question can also be advantageous when it comes to avoiding fatiguing respondents with a lengthy series of questions. Your dropout rate will be lower as a result.

Main role of the construct

Multi-item scale

Let me get straight to the point. If the construct you want to measure is central to your research project, opt for a multi-item scale. They’re more robust and reliable.

Single-item scales

In my case, I reserve a single-item scale for measuring a construct that is not the main focus of my research. This scale measures a “nice to have,” such as a moderating effect.

Desired precision

Multi-item scales

Multi-item scales offer greater precision. The measurement is conducted on several items, so the average score better reflects reality than a single-item measurement.

Single-item scales

Accuracy is often lower. Nevertheless, it may be sufficient for exploratory research. You should also bear in mind that the accuracy of a single-item scale depends largely on the quality and specificity of the formulation.

Tracking changes

Multi-item scales

Multi-item scales are better suited to tracking changes (over time, for example). Multi-dimensionality is an asset for detecting distinct types of variation. If you want to assess how a perception evolves, try to measure the corresponding construct with a multi-item scale.

Single-item scales

The ability of a single-item scale to conduct tracking change needs to be improved. It is, therefore, best to avoid its use in this particular case.

Population samples

Multi-item scale

I’ve already talked about sampling strategies. Your choice of scale will also depend on them. Multi-item scales are particularly effective when you need to sample a diverse population (e.g., a random sample).

Single-item scales

The simplicity of single-item scales limits their use, but they can be good instruments in simple cases when the population is homogeneous, for example.

The size of available samples

Multi-item scale

If your sample size is large enough, a multi-item scale will enable you to confirm the reliability and factor structure of the measure.

Single-item scales

Single-item scales are preferable when your sample size is limited. As mentioned in other paragraphs, this may be the case for exploratory research.



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