Table 3.
Fitted SARIMA models and excess suicides by Twitter content category, 2016–2018 (1096 days), United States.
| Content category | Raw association (only controlled for total tweets) |
Adjusted for all other categories and total tweets |
||
|---|---|---|---|---|
| Estimate (SE) | p | Estimate (SE) | p | |
| Awareness | −0.002 (0.06) | 0.98 | −0.025 (0.06) | 0.67 |
| Prevention | −0.08 (0.05) | 0.092 | −0.11 (0.05) | 0.038 |
| Coping | −0.14 (0.26) | 0.60 | −0.18 (.25) | 0.47 |
| Suicidal ideation / attempt without coping | 0.052 (0.20) | 0.80 | −0.011 (0.20) | 0.96 |
| Suicide case | −0.045 (0.05) | 0.33 | −0.078 (0.05) | 0.11 |
| Total tweets | 4.9 × 10−5 (2.6 × 10−5) | 0.059 | 6.4 × 10−5 (2.6 × 10−5) | 0.015 |
SARIMAL Seasonal Autoregressive Integrated Moving Average; SE: standard error.
The time series (1 January 2016 to 31 December 2018) data were checked for additive and innovative outliers and level shifts. There were no outliers. A SARIMA(2,0,1)(1,0,1) model, stationary R² = 0.39, Box-Ljung-Q = 19.32, df = 13, p = 0.11, was fitted to the data. The final multivariate model was a SARIMA(2,0,1)(1,0,1) model, stationary R² = 0.40, Box-Ljung-Q = 15.72, df = 13, p = 0.27.
Suicide deaths were defined by International Classification of Diseases, 10th Revision (ICD-10) underlying cause of death codes X60–X84, Y87.0 and U03. The bold value indicates the significant p < .05.