Related Experiment Video
Updated: Sep 16, 2025

Measuring Engagement of Spectators of Social Digital Games
Published on: July 3, 2021
Evaluating sport-for-development outcome measures used in a living lab setting: Process, improvements, and insights
Bhanu Sharma1, Jackie Robinson2, Benjamin B Arhen2
1Child Health and Exercise Medicine Program, Department of Pediatrics, McMaster University, 1280 Main Street West, Hamilton, ON L8S4L8, Canada; Imaging Research Centre, St. Joseph's Healthcare, Hamilton, ON, Canada; Department of Electrical & Computer Engineering, McMaster University, Hamilton, Canada.
Background:
Sport-for-development (SFD) is an innovative approach utilizing sport to foster positive physical, mental, and social outcomes among children and youth, particularly those from underserved backgrounds. Living labs, which emphasize participant-centered research conducted in natural, real-world environments, present unique challenges for outcome measurement, including reduced control over conditions, variability in participant engagement, and logistical issues that complicate standardized data collection. Further, there are few outcome measures that are developed for SFD measurement in living lab settings. For these reasons, outcome measurement in a living lab setting remains challenging.
Objective:
Our objective was to evaluate a set of outcome measures that have been administered in a living lab setting to better understand their performance, reliability, and areas for improvement.
Methods:
SFD programming was delivered in a living lab setting at a large facility located in an urban center in Toronto, Canada. We evaluated 11, self-reported, Likert-style outcome measures against 8 key metrics used in Classical Test Theory to understand (for example) floor-and-ceiling effects, inter-item correlations, internal consistency, and test-retest reliability. Data were collected from 2019 to 2024 across multiple cohorts aged 6-29 years, involving diverse SFD programs.
Results:
Our analysis of 2656 questionnaire completions demonstrated strengths in data collection, including complete response rates with minimal missing data (91 % of outcome measures met missingness thresholds), yet also highlighted issues primarily related to single-item-endorsement and inter-item correlations (with 38 % and 19 % of outcome measures meeting these thresholds, respectively). These insights prompted iterative improvements to the evaluation tools, such as modifying Likert scale response formats to include more response categories (and thereby reducing the impact of binning of responses).
Conclusions:
Evaluating our outcome measures provided insight into how they can be improved for administration in a living-lab setting. The results emphasize the need for context-appropriate tools to effectively capture nuanced SFD program impacts and underscore the importance of ongoing validation to improve both research quality and practical implementation in living lab environments.
More Related Videos
06:52Behavioral and Locomotor Measurements Using an Open Field Activity Monitoring System for Skeletal Muscle Diseases
Published on: September 29, 2014
10:08Effects of a Novel Neuromuscular Training Intervention on Jump, Sprint, and Change of Direction in Adult Female Soccer Players
Published on: June 10, 2025
Related Concept Videos
Nursing Evaluation
Guidelines for Writing Outcome
Patient outcomes reflect the patient's response to the goal rather than what the nurse aims to achieve. Terminology should be observable and measurable to avoid the reader's interpretation. The desired outcome should be realistic and achievable in the designated care timeframe. Expected outcomes should align with adjunctive therapies. The outcome should enhance care...