Name
Abstract | ||
|---|---|---|
It is very important to identify mental health problems early and efficiently, but traditional method relies on face-to-face communication which suffers from the limitations in practice. This study aimed to propose an innovative method of detecting mental health problems via web use behaviors. 102 graduates were administrated by SCL-90 questionnaire to get their actual mental health status with 10 dimensions, and their web use behaviors were acquired from Internet access log recorded on the gateway. A computational model for predicting scores on each SCL-90 dimension was built based on web use behaviors. Results indicated that the value of Pearson Correlation Coefficient between predicted scores and actual scores on each dimension ranged from 0.49 to 0.65, and the value of Relative Absolute Error (RAE) ranged from 75% to 89%. It suggests that it is efficient and valid to identify mental health status through web use behaviors, which would improve the performance of mental health care services in the future. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-319-02753-1_35 | Brain and Health Informatics |
Keywords | Field | DocType |
computational model,graduates,mental health status,web use behaviors | Social psychology,Pearson product-moment correlation coefficient,Default gateway,Mental health,Internet access,Medicine,Applied psychology | Conference |
Volume | Issue | ISSN |
8211 LNAI | null | 16113349 |
Citations | PageRank | References |
1 | 0.36 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ang Li | 1 | 42 | 5.37 |
| Fan Zhang | 2 | 42 | 7.62 |
| Tingshao Zhu | 3 | 192 | 33.61 |