Designing Emails Aimed at Increasing Family Physicians’ Use of a Web-Based Audit and Feedback Tool to Improve Cancer Screening Rates: Cocreation Process
Bibliographic record
Abstract
BACKGROUND: Providing clinical performance data to health professionals, a process known as audit and feedback, can play an important role in health system improvement. However, audit and feedback tools can only be effective if the targeted health professionals access and actively review their data. Email is used by Cancer Care Ontario, a provincial cancer agency, to promote access to a Web-based audit and feedback tool called the Screening Activity Report (SAR); however, current emails that lack behavior change content have been ineffective at encouraging log-in to the SAR. OBJECTIVE: The objective of our study was to describe the process and experience of developing email content that incorporates user input and behavior change techniques (BCTs) to promote the use of the SAR among Ontario primary care providers. METHODS: Our interdisciplinary research team first identified BCTs shown to be effective in other settings that could be adapted to promote use of the SAR. We then developed draft BCT-informed email content. Next, we conducted cocreation workshops with physicians who had logged in to the SAR more than once over the past year. Participants provided reactions to researcher-developed BCT-informed content and helped to develop an email that they believed would prompt their colleagues to use the SAR. Content from cocreation workshops was brought to focus groups with physicians who had not used the SAR in the past year. We analyzed notes from the cocreation workshops and focus groups to inform decisions about content. Finally, 8 emails were created to test BCT-informed content in a 2×2×2 factorial randomized experiment. RESULTS: We identified 3 key tensions during the development of the email that required us to balance user input with scientific evidence, organizational policies, and our scientific objectives, which are as follows: conflict between user preference and scientific evidence, privacy constraints around personalizing unencrypted emails with performance data, and using cocreation methods in a study with the objective of developing an email that featured BCT-informed content. CONCLUSIONS: Teams tasked with developing content to promote health professional engagement with audit and feedback or other quality improvement tools might consider cocreation processes for developing communications that are informed by both users and BCTs. Teams should be cautious about making decisions solely based on user reactions because what users seem to prefer is not always the same as what works. Furthermore, implementing user recommendations may not always be feasible. Teams may face challenges when using cocreation methods to develop a product with the simultaneous goal of having clearly defined variables to test in later studies. The expected role of users, evidence, and the implementation context all warrant consideration to determine whether and how cocreation methods could help to achieve design and scientific objectives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".