how to measure impact of change

Introduction

Measuring the impact of changes, whether in software systems, health outcomes, or environmental assessments, is crucial for understanding the effectiveness and consequences of interventions. Various methodologies and tools have been developed to quantify these impacts, each with its own strengths and limitations.

Key Insights

Model-Based Impact Analysis in Software Systems:
- Using model dependencies to measure the impact of changes at the model level can speed up the maintenance process and allow early discovery of critical components before actual code changes are made.
- Empirical studies show that the size of the impact after a single modification ranges between 14% and 38% of the total model size, while multiple modifications range between 30% and 64%.
Sensitivity to Change in Health Status Measures:
- The Oral Health Impact Profile (OHIP) has been shown to be sensitive to changes following clinical interventions, correlating well with changes in denture satisfaction.
- The Stroke Impact Scale (SIS) Version 2.0 is reliable, valid, and sensitive to change, making it a useful tool for assessing recovery in stroke patients.
Environmental Impact Assessment:
- Intervention Analysis (IA) and Before-After, Control-Impact (BACI) are effective methods for assessing environmental impacts by comparing time series data before and after an intervention at impact sites.
- These methods differ in their goals and models of error variance, with IA focusing on specific impact sites and BACI using control sites as covariates to reduce extraneous variance.
Psychometric Characteristics and Reliable Change Parameters:
- The Immediate Postconcussion Assessment and Cognitive Testing (ImPACT) provides reliable change parameters that help in determining deterioration, improvement, and recovery following a concussion.
Integrated Information Retrieval for Change Impact Analysis:
- Combining multiple information retrieval techniques, such as bag-of-words and neural network-based methods, improves the accuracy of change impact analysis in software systems.
- This integrated approach has shown statistically significant improvements in accuracy and F-score values across several open-source systems.
Challenges in Measuring Change in Medical Research:
- There is no consensus on the best strategy for assessing health status change, leading to the development of various indicators, most of which are variations of the Effect Size (ES) concept.
- Accurate interpretation of change scores requires detailed baseline information and an understanding of what these changes mean for specific sub-groups of patients.

Conclusion

Measuring the impact of changes is a multifaceted task that varies across different fields. In software systems, model-based and integrated information retrieval approaches provide early and accurate impact assessments. In health outcomes, tools like OHIP and SIS are sensitive to changes and useful for clinical research. Environmental impact assessments benefit from methods like IA and BACI, which effectively compare pre- and post-intervention data. Despite the challenges in medical research, understanding and interpreting change scores remain crucial for accurate assessments.

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How to measure impact of change

Summary

Introduction

Key Insights

Conclusion

Sources and full results

Toward automatically quantifying the impact of a change in systems

The proposed model-based impact analysis approach automatically measures the expected impact of changes in state-based systems, allowing early discovery of critical components before applying changes at the code level.

An assessment of sensitivity to change of the Oral Health Impact Profile in a clinical trial.

The Oral Health Impact Profile (OHIP) shows good sensitivity to change after clinical intervention, but this property is not improved by using statement weights.

TEMPORAL AND SPATIAL VARIATION IN ENVIRONMENTAL IMPACT ASSESSMENT

Intervention Analysis and Before-After, Control-Impact methods are effective for assessing local environmental impacts, while IVRS estimates error variance by comparing sites rather than time.

Interpreting Change on ImPACT Following Sport Concussion

ImPACT 2.0 is a reliable tool for assessing cognitive changes in athletes after a concussion, providing more precise determinations of deterioration, improvement, and recovery.

An Integrated Model for Information Retrieval Based Change Impact Analysis

Our integrated approach combining bag-of-words and neural network techniques significantly improves change impact analysis accuracy compared to individual methods.

On the Measurement of Change in Medical Research

Measurement of change in medical research requires understanding what changes mean for specific sub-groups of patients and incorporating baseline information for accurate interpretation.

The stroke impact scale version 2.0. Evaluation of reliability, validity, and sensitivity to change.

The Stroke Impact Scale (SIS) Version 2.0 is a reliable, valid, and sensitive stroke-specific outcome measure that is responsive to change and can be used in clinical research.

The Autism Impact Measure (AIM): Examination of Sensitivity to Change

The Autism Impact Measure (AIM) effectively detects short-term improvements in children with ASD across symptom domains and is sensitive to change across different treatments.

Assessing change in quality of life using the Oral Health Impact Profile.

Oral health-related quality of life measures capture both improvement and deterioration, creating new complexities for conceptualizing and analyzing change in longitudinal studies.

Social impact measurement in social entrepreneurial organizations

Social impact measurement in social entrepreneurial organizations needs improvement, considering sustainability, added value, and scalability, while considering psychological impact on clients.

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