InsuOnline, a Serious Game to Teach Insulin Therapy to Primary Care Physicians: Design of the Game and a Randomized Controlled Trial for Educational Validation
Bibliographic record
Abstract
BACKGROUND: Physicians´ lack of knowledge contributes to underuse of insulin and poor glycemic control in adults with diabetes mellitus (DM). Traditional continuing medical education have limited efficacy, and new approaches are required. OBJECTIVE: We report the design of a trial to assess the educational efficacy of InsuOnline, a game for education of primary care physicians (PCPs). The goal of InsuOnline was to improve appropriate initiation and adjustment of insulin for the treatment of DM. InsuOnline was designed to be educationally adequate, self-motivating, and attractive. METHODS: A multidisciplinary team of endocrinologists, experts in medical education, and programmers, was assembled for the design and development of InsuOnline. Currently, we are conducting usability and playability tests, with PCPs and medical students playing the game on a desktop computer. Adjustments will be made based on these results. An unblinded randomized controlled trial with PCPs who work in the city of Londrina, Brazil, will be conducted to assess the educational validity of InsuOnline on the Web. In this trial, 64 PCPs will play InsuOnline, and 64 PCPs will undergo traditional instructional activities (lecture and group discussion). Knowledge on how to initiate and adjust insulin will be assessed by a Web-based multiple choice questionnaire, and attitudes regarding diabetes/insulin will be assessed by Diabetes Attitude Scale 3 at 3 time points-before, immediately after, and 6 months after the intervention. Subjects´ general impressions on the interventions will be assessed by a questionnaire. Software logs will be reviewed. RESULTS: To our knowledge, this is the first research with the aim of assessing the educational efficacy of a computer game for teaching PCPs about insulin therapy in DM. We describe the development criteria used for creating InsuOnline. Evaluation of the game using a randomized controlled trial design will be done in future studies. CONCLUSIONS: We demonstrated that the design and development of a game for PCPs education on insulin is possible with a multidisciplinary team. InsuOnline can be an attractive option for large-scale continuous medical education to help improving PCPs´ knowledge on insulin therapy and potentially improving DM patients´ care. TRIAL REGISTRATION: Clinicaltrials.gov: NCT01759953; http://clinicaltrials.gov/show/NCT01759953 (Archived by WebCite at http://www.webcitation.org/6Dq8Vc7a6).
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".