Extracting more information from behaviour checklists by using components of mean based scores

Area of Science:

• Psychology
• Developmental Psychology
• Behavioral Science

Background:

• Behavioral checklists commonly use sum scores for outcome measurement.
• This approach may obscure important nuances in behavioral data.
• A need exists for more refined methods to analyze behavioral data.

Purpose of the Study:

• To propose and validate the use of mean scores over sum scores for behavior checklist analysis.
• To introduce a method for decomposing mean scores into range and intensity measures.
• To demonstrate the utility of this decomposition technique using real-world data.

Main Methods:

• Utilized mean scores for analyzing behavior checklist data.
• Developed a decomposition method yielding a 'range' measure (proportion of positive scores) and an 'intensity index' (proportion of scores above a threshold).
• Applied these methods to Developmental Behaviour Checklist (DBC) data from the Australian Child to Adult Development Study.

Main Results:

• Low mean scores in individuals with profound intellectual disability reflect a narrow range of behaviors, not low intensity.
• Analysis of change over time indicates that both range and intensity of behaviors evolve with age.
• The decomposition technique effectively differentiates contributions of range and intensity to overall mean scores.

Conclusions:

• Mean scores provide a more informative outcome measure than sum scores for behavior checklists.
• Decomposing mean scores into range and intensity offers deeper insights into behavioral patterns.
• This methodology is applicable to various behavior checklists with different response scales.