Table 3.
Research coding results included in meta-analysis.
| Research | Sample size | Age stage | Mental health problem | Technology type | Intervention duration | g (95% CI) |
|---|---|---|---|---|---|---|
| Anttila2021 | 82 | J | D | A | LI | 0.045 |
| Jones2020 | 35 | S | D | A | LI | 0.192 |
| kor2023 | 1,670 | J | M | A | LI | 0.142 |
| nicoll2022 | 17 | S | D | C | SI | 0.005 |
| Pavarini2023 | 100 | S | M | T | SI | 1.316 |
| Ruggiero2015 | 2,000 | S | D | R | LI | 0.192 |
| Stasiak2014 | 34 | S | D | A | LI | 0.52 |
| Stewart2017 | 15 | P | B | T | SI | 0.786 |
| Topooco2019 | 70 | S | D | T | LI | 0.893 |
| Zepeda2023 | 27 | J | C | T | SI | 0.379 |
A, App software; B, Bullying (including cyberbullying, school bullying); C, Chatbot; M, Mental health issues caused by COVID-19; D, Depression; J, Junior high school; P, Primary school; S, Senior high school; T, Telemedicine; LI, Long-term intervention; SI, Short-term intervention.