Effect of Early Introduction of Lectures on OTC Medicine Including TV Commercials and a Case Conference on Learning Motivation and Professional Sense among Freshmen Pharmacy Students
Bibliographic record
Abstract
We gave a lecture on over-the-counter (OTC) medicines to freshmen pharmacy students as early as possible to enhance their professional sense and their learning motivation.The impact of the lecture was reinforced through the use of television commercials and a case conference.In addition,questionnaires were given to the 182 students who attended the lecture before and after it,and the responses of the 170 students who fully completed the questionnaires were analyzed.The following results were obtained.For the students who had bought OTC medicines in the past,the package was the most important factor in selecting the medicine.As a result of the lecture,the number of students who wanted help from a pharmacist in selection increased.Of the 166 students who had used OTC medicines in the past,152 had read package inserts.After the lecture,all students said that the package insert should be read before using OTC medicines.Attending the lecture also increased the number of students who considered it important to read the major items of the package insert,such as“Ingredient and amount”and“Drug characteristics”.The lecture also increased students’interest in the pharmacist dealing with OTC medicines about 1.8-fold.In addition,most students were satisfied with the lecture and it stimulated their interest in learning more about OTC medicines.In conclusion,we felt that the lecture had been useful in enhancing professional sense among freshmen pharmacy students as well as their motivation to learn about OTC medicines.
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 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".