| Title |
To use or not to use? Compulsive behavior and its role in smartphone addiction
|
|---|---|
| Published in |
Translational Psychiatry, February 2017
|
| DOI | 10.1038/tp.2017.1 |
| Pubmed ID | |
| Authors |
Y-H Lin, Y-C Lin, S-H Lin, Y-H Lee, P-H Lin, C-L Chiang, L-R Chang, C C H Yang, T B J Kuo |
| Abstract |
Global smartphone penetration has led to unprecedented addictive behaviors. To develop a smartphone use/non-use pattern by mobile application (App) in order to identify problematic smartphone use, a total of 79 college students were monitored by the App for 1 month. The App-generated parameters included the daily use/non-use frequency, the total duration and the daily median of the duration per epoch. We introduced two other parameters, the root mean square of the successive differences (RMSSD) and the Similarity Index, in order to explore the similarity in use and non-use between participants. The non-use frequency, non-use duration and non-use-median parameters were able to significantly predict problematic smartphone use. A lower value for the RMSSD and Similarity Index, which represent a higher use/non-use similarity, were also associated with the problematic smartphone use. The use/non-use similarity is able to predict problematic smartphone use and reach beyond just determining whether a person shows excessive use. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 50% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 151 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 14% |
| Student > Bachelor | 21 | 14% |
| Student > Master | 19 | 13% |
| Researcher | 9 | 6% |
| Student > Doctoral Student | 6 | 4% |
| Other | 27 | 18% |
| Unknown | 48 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 27 | 18% |
| Social Sciences | 12 | 8% |
| Medicine and Dentistry | 11 | 7% |
| Computer Science | 10 | 7% |
| Business, Management and Accounting | 6 | 4% |
| Other | 32 | 21% |
| Unknown | 53 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 March 2017.
All research outputs
#13,878,354
of 24,224,854 outputs
Outputs from Translational Psychiatry
#2,236
of 3,474 outputs
Outputs of similar age
#211,282
of 436,006 outputs
Outputs of similar age from Translational Psychiatry
#58
of 85 outputs
Altmetric has tracked 24,224,854 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.