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Data Validation

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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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Formulating and Validating Nursing Diagnosis II

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Related Experiment Video

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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

[Diagnostic tool for action in partnerships: foundation, development and validation].

Angèle Bilodeau¹, Marilène Galarneau, Michel Fournier

¹Ecole de santé publique, Université de Montréal, Montréal, QC. abilodea@santepub-mtl.qc.ca

Canadian Journal of Public Health = Revue Canadienne De Sante Publique

|September 15, 2011

Summary

Public health partnerships are crucial for addressing social determinants of health. A new validated tool helps evaluate partnership quality and effectiveness, supporting intersectoral collaboration.

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Area of Science:

Public Health
Health Services Research
Organizational Studies

Background:

Intersectoral partnerships are essential for addressing social determinants of health.
A lack of valid evaluation tools hinders the assessment and improvement of these partnerships.
Existing limitations necessitate the development of instruments to measure partnership quality.

Purpose of the Study:

To introduce and validate a new tool for evaluating the quality of intersectoral partnerships.
To provide a method for assessing the effectiveness of collective action within partnerships.
To support public health stakeholders in strengthening collaborative efforts.

Main Methods:

Development of a theoretical model based on case studies of partnership conditions.
Operationalization of theoretical conditions into a series of 18 items with 3 response options each.
Pretesting using cognitive interviewing and verification of construct and ecological validity.

Main Results:

The tool demonstrates sensitivity to judgment variations and good respondent convergence.
It effectively distinguishes between partnerships facing challenges and those meeting conditions.
The tool is suitable for self-evaluation in partnerships beyond simple information exchange.

Conclusions:

The tool's validity is supported by its rigorous validation process and theoretical foundation.
The theoretical model is grounded in literature reviews on partnership functioning and outcomes.
This instrument offers a reliable means to evaluate and enhance intersectoral public health partnerships.