Exploration of stress, burnout and technostress levels in teachers. Prediction of their resilience levels using an artificial neuronal network (ANN) (Record no. 194417)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 01726nam a22001937a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250117164632.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250117b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | LDD |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Pagan-Garbin, Ines |
| 245 ## - TITLE STATEMENT | |
| Title | Exploration of stress, burnout and technostress levels in teachers. Prediction of their resilience levels using an artificial neuronal network (ANN) |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Elsevier, 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Other physical details | p. 1-11 |
| 490 ## - Journal | |
| Journal | An International Journal Of Research And Studies |
| Volume/sequential designation | Vol. 148 |
| 500 ## - GENERAL NOTE | |
| General note | This study explores stress, burnout syndrome, resilience, and technostress in 168 teachers in Region of Murcia. The general objective was to predict the teacher's resilience levels, as well as analyse the relationship between the variables under study and see the influence of age and gender. The results achieved showed statistically significant relationships in the correlational analysis between stress, technostress, emotional exhaustion, and depersonalisation. Analyses on resilience showed a significant and negative relationship with factors the factors above, but a positive and statistically significant relationship with personal accomplishment. Also, we found age effects on technostress and stress. Furthermore, an artificial neural network (ANN) was created, obtaining a model with a capacity to predict resilience levels in an 86.7% of cases. Personal accomplishment is the most relevant factor to predict resilience levels in teachers, although stress, age and gender are also important. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Artificial Intelligence |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Mendez, Inmaculada |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Link text | click here to access online |
| Uniform Resource Identifier | <a href="https://www.sciencedirect.com/science/article/pii/S0742051X2400249X">https://www.sciencedirect.com/science/article/pii/S0742051X2400249X</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Article |
| Date last seen | Total checkouts | Price effective from | Koha item type | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Withdrawn status | Home library | Current library | Date acquired |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 01/17/2025 | 01/17/2025 | Article | Dewey Decimal Classification | Library and Documentation Division NCERT | Library and Documentation Division NCERT | 01/17/2025 |
