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Does it work? Using a Meta-Impact score to examine global effects in quasi-experimental intervention studies
Nancy Elizabeth Doyle1, Almuth McDowall2, Raymond Randall3
1School of Psychology, City, University of London, London, United Kingdom.
Plos One
|March 17, 2022
Summary
Evaluating workplace interventions is hard due to participant differences. A new Meta-Impact score better shows how individual employees respond to support, supplementing traditional group comparisons.
Area of Science:
- Psychology
- Organizational Behavior
- Intervention Science
Background:
- Evaluating applied psychological interventions presents challenges, often leading to heterogeneity in intervention and control groups.
- Traditional group mean comparisons may obscure individual participant responses to interventions.
- Difficulty in achieving randomisation and matching complicates intervention evaluation.
Purpose of the Study:
- To introduce and evaluate a novel Meta-Impact score for assessing psychological interventions.
- To demonstrate how the Meta-Impact score can highlight person-specific variations in intervention response.
- To provide a supplementary method for applied research requiring personalized impact analysis.
Main Methods:
- Utilized longitudinal studies of coaching interventions for dyslexic employees.
- Described and calculated a Meta-Impact score to analyze intervention effects.
- Compared the Meta-Impact score approach with traditional null hypothesis significance testing.
Main Results:
- The Meta-Impact score effectively highlights individual participant variations in response to interventions.
- This method revealed effects masked by traditional group-wise comparisons.
- Demonstrated the practical utility of the Meta-Impact score in showing intervention effectiveness.
Conclusions:
- The Meta-Impact score offers an incremental supplement to traditional group-based analyses.
- This approach more accurately demonstrates the extent to which an intervention works on an individual level.
- Such personalized impact analysis methods are crucial for applied research, policy, legal, and ethical considerations, especially with small sample sizes.
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