Technology Trumping Sleep: Impact of Electronic Media and Sleep in Late Adolescent Students
Bibliographic record
Abstract
The purpose of this research study was to explore with what impact evening media use interfered with either schoolwork and/or sufficient healthy sleep. In addition, the study examined with what impact there may be a compromise in students’ ability or aptitude for positive academic success, related to either lack of sleep or electronic media use. The participants were 89 high school and college students, ages 16 through 25, with median age of 18. Research was conducted using a secured online survey tool. Electronic habits, internet and social networking usage, sleep and rise times, daily sleepiness and perceptions were examined. College students were randomly sampled and participated in an in-depth, one-time survey. High school students participated in a weeklong nightly electronic sleep & evening media use survey and journal. Data was obtained from anonymous and coded student responses and student and teacher surveys. The results of the study suggested that healthful adolescent sleep is indeed greatly compromised, during a time when the reverse is vitally important. Of students randomly sampled, all but one student owned a cell phone. In the total study group, a majority were smart phone owner-users (84%). Many high school participants slept with a cell phone or tablet in their bed (72%), and among college participants who regularly slept with cell phone, tablet, or laptop, this rose to 86%. Over half of these students continued to access and use their devices in bed for significant amounts of time prior to sleeping. Many of these even awakened after falling asleep to access or respond to electronic messaging. The research indicated that unhealthy sleep habits may be creating a generation of sleep-deprived individuals who may not be functioning at top capacity. Findings regarding a correlation between lack of sleep and quantified academic success are inconclusive, however, student perceptions indicate that they believe there is a relationship. Findings also suggest that all instructors of late adolescent students aged 16-25 may count on the fact of their student clientele owning and using mobile devices to access internet for social purposes. Students allow their social digital world to impede and compete with their academic time and biological sleep cycle. Instructors would be wise to appropriately channel the digital skills of this new generation of no longer-wired, but now “wi-fied” students. Therefore it is strongly suggested that teachers, parents, and medical personnel adopt and provide healthy guidelines for parents to use with pre-teens and teens, to facilitate and develop in the next generation of students some structure and means of protecting their health in the realms of electronics and sleep.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".