The Feasibility of AgileNudge+ Software to Facilitate Positive Behavioral Change: Mixed Methods Design
Bibliographic record
Abstract
BACKGROUND: In today's digital age, web-based apps have become integral to daily life, driving transformative shifts in human behavior. "AgileNudge+" (Indiana University Center for Health Innovation and Implementation Science) is a web-based solution to simplify the process of positive behavior change using nudging as an intervention. By integrating knowledge from behavioral economics with technology, AgileNudge+ organizes multiple steps, simplifies complex tasks, minimizes errors by enhancing user engagement, and provides resources for creating and testing nudge interventions. OBJECTIVE: This paper aimed to outline the design process, methodologies, and usefulness of "AgileNudge+" for the development of evidence-based nudges. It used a mixed methods approach to evaluate the software's interface usability and usefulness for creating and testing nudge interventions. METHODS: AgileNudge+ was developed through iterative processes integrating principles from behavioral economics and user-centered design. The content of AgileNudge+ operationalizes an Agile science-based process to efficiently design, embed, and disseminate evidence-based nudges that encourage positive behavior change without limiting choice. Using a mixed methods approach, we tested AgileNudge+ software's ability to organize and simplify the nudge intervention process, allowing a diverse range of scholars with limited knowledge of Agile science to use nudges. Usability testing assessed the tool's usefulness and interface with a sample of 18 health care professionals, each asked to interact with the software and create a nudge intervention to solve a problem within their professional project's sphere. RESULTS: The study was funded in August 2022, with data collection occurring from June 2023 to July 2024. As of July 2024, we have enrolled 18 participants. Quantitative results found a mean usefulness rating of AgileNudge+ of 3.83 (95% CI 3.00-4.66). Qualitative results highlighted ways to modify the language used in AgileNudge+ to be more comprehensible to a diverse user base and promoted modifications to the software that facilitate real-time assistance and prioritize time efficiency in user interactions. Feedback further supported the positive impact of gamification on participant motivation when using the software. CONCLUSIONS: AgileNudge+ is an effective assistive tool for simplifying the positive behavior change process using nudge interventions, with tailored content and interactions to meet users' needs and demands. Building onto the current design, future iterations of AgileNudge+ will use artificial intelligence to process large volumes of data while reducing the time and mental energy required to scan for existing cognitive biases and nudge prototypes. The software is also being upgraded to build on current gamification efforts, encouraging more sustained motivation by increasing the temporal resolution of the digital interface. These modifications stay true to the agility and user-centered aspects of AgileNudge+, emphasizing the novelty of the constantly evolving software design process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.108 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".