Effect of smartphone location on pharmacy students’ attention and working memory
Data files
Jun 25, 2022 version files 55.10 KB
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Data.csv
42.88 KB
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README_Datadocx.docx
12.21 KB
Feb 23, 2024 version files 8.74 KB
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All_data.csv
6.38 KB
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README.md
2.36 KB
Abstract
Objectives: Smartphone use has become ubiquitous worldwide. Despite smartphone-related convenience, smartphone use has raised concerns regarding addiction among university undergraduates. This study aimed to examine the effect of smartphone location, such as desk, bag, and another room, on working memory, based on electroencephalography parameters, in pharmacy students.
Key findings: Thirty-six students were enrolled in the study. Smartphone location had no effect on electroencephalography outcomes and working memory. Partial correlation coefficients between alpha and beta and between theta and alpha values were statistically significant when the smartphone was on the desk (r = 0.869, p < 0.0001; r = 0.887, p < 0.0001; respectively), however, those between alpha and beta values were not statistically significant when the smartphone was in the bag and outside the room.
Conclusions: Smartphone locations did not affect either electroencephalography or working memory findings. Smartphones located in the bag and outside the room seemed to influence students’ concentration on the task, but this effect did not affect working memory.
README: Effect of smartphone location on pharmacy students’ attention and working memory
Author(s)
Naoto Nakagawa, Pharm.D., Ph.D.
School of Pharmaceutical Sciences, Ohu University, Koriyama, Fukushima, Japan
31-1 Misumido, Tomita-machi, Koriyama, Fukushima 963-8611, Japan
Email: n-nakagawa@pha.ohu-u.ac.jp
Keita Odanaka, Ph.D.; School of Pharmaceutical Sciences, Ohu University, Koriyama, Fukushima, Japan
Hiroshi Ohara, Ph.D.; School of Pharmaceutical Sciences, Ohu University, Koriyama, Fukushima, Japan
Toshinori Ito; School of Pharmaceutical Sciences, Ohu University, Koriyama, Fukushima, Japan
Shigeki Kisara, Ph.D.; School of Pharmaceutical Sciences, Ohu University, Koriyama, Fukushima, Japan
Kitae Ito, Ph.D.; School of Pharmaceutical Sciences, Ohu University, Koriyama, Fukushima, Japan
File list: All data
File descriptions
Details for: All data
The file is a table to analyze for all data
Format(s): .csv
Dimensions: 37 rows x 33 columns
Variables:
* Student: Sophomore or Freshman
* No: Number
* Sex F/M: f=female, m=male
* Line use: unit is min/day
* Phone use: unit is min/day
* Instagram use: unit is min/day
* Facebook use: unit is min/day
* Google use: unit is min/day
* Yahoo use: unit is min/day
* Music application use: unit is min/day
* GPA: Grade point average
* Dependence score : 0 to 84
* Alpha_Intervention.1: unit is microV
* Alpha_Intervention.2: unit is microV
* Alpha_Intervention.3: unit is microV
* beta_Intervention 1: unit is microV
* beta_Intervention 2: unit is microV
* beta_Intervention 3: unit is microV
* theta_ Intervention 1: unit is microV
* theta_ Intervention 2: unit is microV
* theta_ Intervention 3: unit is microV
* Span score_Intervention 1:
* Span score_Intervention 2
* Span score_Intervention 3
* Memory correct_Intervention 1: 0 to 1 (0% to 100%)
* Memory correct_Intervention 2: 0 to 1 (0% to 100%)
* Memory correct_Intervention 3: 0 to 1 (0% to 100%)
* Operation correct_Intervention 1: 0 to 1 (0% to 100%)
* Operation correct_Intervention 2: 0 to 1 (0% to 100%)
* Operation correct_Intervention 3: 0 to 1 (0% to 100%)
* Response time1: unit is milliseconds
* Response time2: unit is milliseconds
* Response time3: unit is milliseconds
Row 34 has some blank cells because the student did not record the time.
Methods
The effects of smartphone use on pharmacy students’ attention and working memory were examined using electroencephalography measurements obtained during a specific task. We also examined associations among electroencephalography variables (theta, alpha, and beta waves), working memory, correct memory, correct operation, response time, smartphone dependency questionnaire score, grade point average, average daily phone use, Line use, Instagram use, Facebook use, Google use, Yahoo use, and music application use. Partial correlation coefficients were calculated for these variables.