Table 1.
GP nurse characteristics at baseline
| Characteristicsa |
All-SES implementation strategy n = 13 |
SES-sens implementation strategy n = 9 |
|
|---|---|---|---|
| Sociodemographic and work experience | |||
| Gender | female | 12 (92%) | 7 (78%) |
| male | 1 (8%) | 2 (22%) | |
| Age (in years) | 44.4 (9.9) | 48.0 (12.8) | |
| Education level | Non-academic | 8 (62%) | 7 (78%) |
| Academic | 5 (39%) | 2 (22%) | |
| Working hours (per week) | 27.0 (5.8) | 29.2 (7.2) | |
| Number of years’ experience in mental health services | 11.2 (9.6) | 18.1 (7.5) | |
| Number of years’ experience as a GP nurse | 4.3 (2.9) | 5.0 (2.3) | |
| How often have you referred patients to online self-help? | Often/ very often | 7 (54%) | 5 (56%) |
| Experience with guiding patients using online self-help | Quite a lot/ a lot | 3 (23%) | 2 (22%) |
| Internet skill level | Good/ very good | 9 (69%) | 5 (56%) |
| Expectations about guiding patients with a lower SES (using online self-help) | |||
| I feel capable of guiding patients with a lower SES level | Agree/completely agree | 10 (77%) | 6 (67%) |
| I expect that online guided self-help interventions can be effective for patients with a lower SES-level | Agree/completely agree | 6 (46%) | 4 (44%) |
| Online guided self-help interventions are only suitable for motivated patients | Agree/completely agree | 9 (69%) | 9 (100%) |
| I feel capable of guiding patients with a lower SES to use online self-help interventions | Agree/completely agree | 9 (69%) | 4 (44%) |
| UTAUT implementation factors | |||
| Performance expectancy | scale 4–20 | 6.2 (2.2) | 7.1 (2.2) |
| Effort expectancy | scale 4–20 | 9.8 (1.5) | 8.9 (2.1) |
| Social influence | scale 4–20 | 9.5 (1.8) | 9.7 (2.6) |
| Facilitating conditions | scale 4–20 | 7.6 (2.9) | 7.3 (2.5) |
| Attitude towards using technology | scale 4–20 | 7.2 (2.0) | 8.3 (1.7) |
| Self-efficacy in using technology | scale 2–10 | 3.8 (1.3) | 3.9 (1.5) |
| Intent to offer the online CDMIs | scale 1–5 | 1.2 (0.6) | 1.1 (0.3) |
* Percentages may not add up to 100% due to rounding. a Data are mean values (SD) or n (%)