Mobile Phone Usage and Awareness of Health Related Issues Among the Male Science Students
Bibliographic record
Abstract
The objective of this study was to understand the usage pattern of mobile phones nowadays by the male science students and to check whether they are aware of the fact that the various risk factors associated to their health are these cellular phones only. Cell phones are considered to be one of the most speedily emerging technologies in the human race especially in younger generation within a short span of time. Youth is more inclined towards using mobile phones for activities other than communication than older generation because in adolescent stage, people are more susceptible to changing fashion trends and style, building them more Tech savvy which creates certain behavioral disorders. The fame of the cell phones is followed by an alarm towards the detrimental effects of cell phone radiation. Fatigue, headache, decreased concentration and local irritation and burning are the major effects of excessive usage of cell phones, as stated by various researches. A descriptive survey design was used to extract answers to the questionnaires administrated to 10th, 11th and 12th standard male science students in the Kanpur city, Uttar Pradesh, a state in India. Opinion of 30 skilled physicians in the field of ENT, cardiology and IVF specialists were also taken. Data was analyzed using the Statistical Package for Social Sciences (SPSS). The study concludes that the use of mobile phones is quite common among the science students besides considering it as a status symbol; they treat it as their necessity of life. The crucial role played by parents, schools and the publicity due to advertisements gives a push to such adoption behavior. Key words: Mobile phones; Science students; Health; Parents
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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 | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".