Resident Use of the Internet, E-Mail, and Personal Electronics in the Care of Surgical Patients
Bibliographic record
Abstract
BACKGROUND: The use of smartphones, e-mail, and the Internet has affected virtually all areas of patient care. Current university and hospital policies concerning the use of devices may be incongruent with day-to-day patient care. PURPOSE: The goal was to assess the current usage patterns of the Internet, e-mail, and personal electronics for clinical purposes by surgical residents as well as their communication habits and preferences. Also assessed was residents' knowledge regarding the institutional policies surrounding these issues. METHODS: Surgical residents (n = 294) at a large teaching institution were surveyed regarding their knowledge of university policies as well as daily use of various communication technologies. Communication preferences were determined using theoretical clinical scenarios. RESULTS: Our survey with a response rate of 54.7% (n = 161) revealed that 93.8% of participants indicated daily Internet use for clinical duties. Most respondents (72%) were either completely unaware of the existence of guidelines for its use or aware but had no familiarity with their content. Use of e-mail for clinical duties was common (85%), and 74% of the respondents rated e-mail as "very important" or "extremely important" for patient care. Everyone who responded had a mobile phone with 98.7% being "smartphones," which the majority (82.9%) stated was "very important" or "extremely important" for patient care. Text messaging was the primary communication method for 57.8% of respondents. The traditional paging system was the primary communication method for only 1.3% of respondents and the preferred method for none. CONCLUSIONS: Daily use of technology is the norm among residents; however, knowledge of university guidelines was exceedingly low. Residents need better education regarding current guidelines. Current guidelines do not reflect current clinical practice. Hospitals should consider abandoning the traditional paging system and consider facilitating better use of residents' mobile phones.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".