Internet and Social Media use among Pharmacists in a state in Nigeria
Bibliographic record
Abstract
Objectives: This study determined the use of internet and social media by pharmacists in Delta State as well as their experiences with the internet and patients.
 Method: This was achieved through the use of a 32 item, structured questionnaire, pretested and administered to 100 pharmacists attending the quarterly meeting of Pharmaceutical Society of Nigeria in Abraka, Delta State. Use of internet and social media were evaluated by Chi square analysis, using SPSS 20. At 95% confidence interval, a 2-tailed, P- value less than 0.05 was considered significant.
 Results: Of 100 questionnaires administered, 81 were returned, giving a response rate of 81%. Majorities (29.6%) were aged 30-39 years, there were more males (54.3%) than females, one third (39.5%) had been in practice for 1-10 years. Nearly half (48.1%) were in community practice, more than half (56.8%) were practicing in Asaba. Majority (61.7%) used electronic communication for professional services; a quarter (27.2%) used email to communicate with their patients. Whatsapp was 3.5%, text messaging and Face book were 1.2% each. Significant differences were found in their online activities. Reasons for not communicating online included respondents not being computer literate (9.9%), irregular power supply in location (9.9%), lack of time (2.5%).
 Conclusion: Internet use among respondents in the study area was poor, with those practicing in urban capital using the internet most. There is need to encourage greater internet use among pharmacists because of the obvious benefits to patient care.
 Keywords: Internet use, pharmacists, social media
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".