| Literature DB >> 27489204 |
Ines Hungerbuehler1, Leandro Valiengo, Alexandre A Loch, Wulf Rössler, Wagner F Gattaz.
Abstract
BACKGROUND: There is a tremendous opportunity for innovative mental health care solutions such as psychiatric care through videoconferencing to increase the number of people who have access to quality care. However, studies are needed to generate empirical evidence on the use of psychiatric outpatient care via videoconferencing, particularly in low- and middle-income countries and clinically unsupervised settings.Entities:
Keywords: depression; eHealth, videoconferencing; home-care services; mental health; outpatient; psychiatry; telehealth; telemedicine
Year: 2016 PMID: 27489204 PMCID: PMC4989121 DOI: 10.2196/mental.5675
Source DB: PubMed Journal: JMIR Ment Health ISSN: 2368-7959
Baseline characteristics of participants in each treatment arm.
| Baseline Variables | Total (n=107) | VCa(n=53) | F2Fb(n=54) | |
| Age, mean (SDc), year | 35.64 ± 8.33 | 35.42 ± 8.18 | 35.87 ± 8.53 | |
| Female (%) | 76 (71.0%) | 39 (73.6%) | 37 (68.5%) | |
| Brazilian (%) | 103 (96.3%) | 52 (98.1%) | 51 (94.4%) | |
| Marital Status (No., %) | ||||
| Single | 58 (54.2%) | 25 (47.2%) | 33 (61.1%) | |
| Married | 34 (31.8%) | 22 (41.5%) | 12 (22.2%) | |
| Divorced | 13 (12.1%) | 5 (9.4%) | 8 (14.9%) | |
| Widowed | 2 (1.9%) | 1 (1.9%) | 1 (1.9%) | |
| Education (No., %) | ||||
| Primary | 2 (1.9%) | 0 (0.0%) | 2 (3.7%) | |
| Secondary | 30 (28.0%) | 14 (26.4%) | 16 (29.6%) | |
| Higher | 75 (70.1%) | 39 (73.6%) | 36 (66.7%) | |
| Working situation (No., %) | ||||
| Student/Homemaker | 13 (12.1%) | 6 (11.3%) | 3 (5.7%) | |
| Employed | 67 (62.6%) | 32 (60.4%) | 35 (66.0%) | |
| Unemployed | 24 (22.4%) | 11 (20.8%) | 12 (22.6%) | |
| Retired | 1 (0.9%) | 0 (0.0%) | 1 (1.9%) | |
| Other | 10 (9.3%) | 4 (7.5%) | 2 (3.8%) | |
| Severity of depression, mean (SD) | 7.05 ± 3.69 | 7.92 ± 3.59 | 6.19 ± 3.61 | |
| Mental health status, mean (SD) | 127.12 ± 26.37 | 121.25 ± 26.19 | 132.89 ± 25.49 | |
| Medication – multiple choices; No. (%) | ||||
| Antidepressants | 105 (98.1%) | 52 (98.1%) | 53 (98.1%) | |
| Tranquilizers | 29 (27.1%) | 13 (24.5%) | 16 (26.6%) | |
| Mood stabilizers | 2 (1.8%) | 1 (1.9%) | 1 (1.9%) | |
| Antipsychotics | 1 (0.9%) | 1 (1.9%) | 0 (0%) | |
| Other | 7 (6.5%) | 2 (3.8%) | 5 (9.4%) | |
a VC: Videoconferencing.
b F2F: Face-to-face.
c SD: standard deviation
Figure 1Sample flow diagram.
Unadjusted mean scores and standard deviations of outcome measures.
| Measure by Time Point | Score | ||||||
| VCa | F2Fb | Total | |||||
| Mean (SD) | No. | Mean (SD) | No. | Mean (SD) | No. | ||
| HDRSc | |||||||
| Baseline | 7.92 (3.59) | 53 | 6.19 (3.60) | 54 | 7.05 (3.69) | 107 | |
| Follow-up: 6 months | 4.65 (4.13) | 49 | 3.90 (3.88) | 42 | 4.31 (4.01) | 91 | |
| Follow-up: 12 months | 3.42 (3.58) | 45 | 4.45 (4.13) | 40 | 3.90 (3.86) | 85 | |
| MHId | |||||||
| Baseline | 121.25 (26.19) | 53 | 132.89 (25.49) | 54 | 127.12 (26.37) | 107 | |
| Follow-up: 6 months | 123.98 (27.56) | 50 | 117.09 (25.54) | 44 | 120.76 (26.72) | 94 | |
| Follow-up: 12 months | 137.71 (28.88) | 45 | 143.32 (25.07) | 40 | 140.35 (27.14) | 85 | |
| CSQe | |||||||
| Baseline | 27.66 (2.82) | 53 | 28.43(2.61) | 54 | 28.05 (2.73) | 107 | |
| Follow-up: 6 months | 28.24 (3.06) | 50 | 29.45 (2.21) | 44 | 28.81 (2.75) | 94 | |
| Follow-up: 12 months | 27.91 (3.76) | 45 | 29.35 (2.48) | 40 | 28.59 (3.28) | 85 | |
| WAIf | |||||||
| Baseline | 68.90 (12.56) | 52 | 72.11 (10.26) | 54 | 70.54 (11.50) | 106 | |
| Follow-up: 6 months | 63.52 (8.86) | 50 | 64.93 (8.95) | 44 | 64.18 (8.88) | 94 | |
| Follow-up: 12 months | 70.78 (11.96) | 45 | 73.41 (9.18) | 39 | 72.00 (10.78) | 84 | |
a VC: videoconferencing.
b F2F: face-to-face.
c HDRS: Hamilton Depression Rating Scale.
d MHI: Mental Health Inventory.
e CSQ: Client Satisfaction Questionnaire.
fWAI: Working Alliance Inventory.