| Literature DB >> 31763990 |
Gwendolyn Mayer1, Nadine Gronewold1, Simone Alvarez2, Bastian Bruns1, Thomas Hilbel3, Jobst-Hendrik Schultz1.
Abstract
BACKGROUND: The acceptability of electronic mental (e-mental) health apps has already been studied. However, the attitudes of medical experts, students, and patients taking into account their knowledge of and previous experiences with e-mental health apps have not been investigated.Entities:
Keywords: acceptance; depression; eHealth; expectation; experts; interventions; mHealth; patients; risk; students; telehealth; telemedicine
Year: 2019 PMID: 31763990 PMCID: PMC6902133 DOI: 10.2196/14018
Source DB: PubMed Journal: JMIR Ment Health ISSN: 2368-7959
Descriptive statistics of the study sample (N=269).
| Characteristics | Participants, n (%) | |
| Age (years), mean (SD) | 37.39 (14.14) | |
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| Female | 173 (64.31) |
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| Male | 96 (35.69) |
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| Other | 0 (0) |
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| German | 251 (93.31) |
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| Other | 18 (0.69) |
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| Single | 158 (58.74) |
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| Married | 86 (31.97) |
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| Separated | 4 (1.49) |
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| Divorced | 14 (5.20) |
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| Widowed | 1 (0.37) |
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| Other | 5 (1.86) |
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| Missing | 1 (0.37) |
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| General medical practitioner | 7 (6.73) |
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| Specialist in internal medicine | 23 (22.12) |
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| Specialist in psychosomatics | 12 (11.54) |
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| Specialist in psychiatry | 9 (8.65) |
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| Specialist in psychotherapy | 6 (5.77) |
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| Physician (total) | 43 (41.35) |
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| Psychological psychotherapist | 33 (31.73) |
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| Psychotherapist in training | 16 (15.38) |
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| Nurse | 13 (12.50) |
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| Experts (total) | 104 (100) |
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| Medicine | 54 (67.50) |
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| Psychology | 28 (35.00) |
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| Students (total) | 80 (100) |
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| Patient of the University Hospital Heidelberg | 41 (48.24) |
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| Patient recruited via the internet | 44 (51.76) |
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| Patients (total) | 85 (100) |
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| Still in school | 1 (1.18) |
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| Secondary school | 13 (15.29) |
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| Secondary high school | 24 (28.24) |
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| Higher school certificate | 26 (30.59) |
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| Study exam | 18 (21.18) |
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| Other | 3 (3.53) |
aMultiple choice possible.
Items of the section “Attitudes towards e-mental health apps” sorted by issues.
| Issue and item | Type | ||
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| Which of the following apps do you know? (list) | Multiple choice | |
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| Which of the following apps did you already try? (list) | Multiple choice | |
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| How do you rate your experiences? | 5-point Likert scalea | |
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| What do you think in general of e-mental health apps? | Rank order (ordinal) | |
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| Do you think, that e-mental health apps will gain importance in the future? | 5-point Likert scalea | |
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| Which positive aspects do you see regarding e-mental health apps? | Open-text field | |
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| What functions or properties would you like to have in an ideal e-mental health app? (8 sub items) | 5-point Likert scalea | |
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| Further functions or properties | Open-text field | |
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| What would stop you from using an e-mental health app? | Open-text field | |
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| What risks do you see in e-mental health apps? (4 sub items) | 5-point Likert scalea | |
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| Further risks | Open-text field | |
aRange: –2 to +2.
Results for the question, “Which of the following apps do you know?”
| App | Experts (n=54), n | Students (n=16), n | Patients (n=58), n | Total (N=128), n (%) |
| ARYA | 2 | 1 | 4 | 7 (5.47) |
| DepressionsCoach (TK) | 14 | 4 | 9 | 27 (21.0) |
| Deprexis24 | 16 | 0 | 3 | 19 (14.84) |
| Human Progress | 0 | 3 | 2 | 5 (3.91) |
| Meplus | 0 | 0 | 1 | 1 (0.78) |
| Minddistrict | 2 | 0 | 2 | 4 (3.13) |
| Moodgym | 5 | 0 | 4 | 9 (7.03) |
| Moodpath | 1 | 2 | 11 | 14 (10.94) |
| MyTherapy | 2 | 4 | 7 | 13 (10.16) |
| Novego | 0 | 0 | 1 | 1 (0.78) |
| Selfapy | 5 | 2 | 3 | 10 (7.81) |
| Others | 7 | 0 | 11 | 18 (14.10) |
Results for the question, “What do you think in general of e-mental health apps?”
| Response | Experts (n=104), n | Students (n=80), n | Patients (n=85), n | Total (N=269), n (%) |
| I think, there's great potential in the development. | 22 | 15 | 16 | 53 (19.70) |
| I'm basically in favour of the development. | 49 | 35 | 30 | 114 (42.38) |
| I'm in favour of the development of health apps, but not for mental disorders. | 1 | 10 | 9 | 20 (7.43) |
| I am sceptical about the development. | 25 | 16 | 24 | 65 (24.16) |
| I am concerned about the development. | 6 | 4 | 2 | 12 (4.46) |
| Not answered | 1 | 0 | 4 | 5 (1.86) |
Results for the question, “What functions or properties would you expect in an ideal e-mental health app?” (for all: min=–2, max=2).
| Item | Participants (N=269), n (%) | Mean (SD) | 95% CI |
| It should be changeable and adaptable by me. | 267 (99.26) | 0.66 (1.14) | 0.52-0.80 |
| It should not cost much. | 266 (98.88) | 1.05 (1.06) | 0.92-1.18 |
| It should be covered by the health insurance. | 266 (98.88) | 0.67 (1.20) | 0.52-0.81 |
| The purpose of the exercises should be clear and concise. | 267 (98.26) | 1.61 (0.68) | 1.53-1.69 |
| It should be clear who designed the app. | 268 (99.63) | 1.04 (1.14) | 0.90-1.18 |
| There should be scientific evidence of efficacy. | 268 (99.63) | 1.21 (0.92) | 1.10-1.32 |
| The design should be appealing. | 268 (99.63) | 1.13 (0.91) | 1.02-1.24 |
| Privacy should be respected. | 268 (99.63) | 1.85 (0.59) | 1.78-1.93 |
Matrix of components after varimax-rotation (the rotation is converged in 5 iterations; method of extraction: main component analysis).
| Component | Transparency | Costs | Design/customizability |
| It should be clear who designed the app. | 0.72 | –0.17 | –0.08 |
| There should be scientific evidence of efficacy. | 0.70 | 0.03 | 0.03 |
| Privacy should be respected. | 0.62 | 0.16 | 0.10 |
| The purpose of the exercises should be clear and concise. | 0.54 | 0.40 | 0.12 |
| It should be covered by the health insurance. | 0.11 | 0.71 | 0.25 |
| It should not cost much. | –0.05 | 0.79 | –0.18 |
| The design should be appealing. | 0.42 | 0.26 | –0.56 |
| It should be changeable and adaptable by me. | 0.25 | 0.18 | 0.77 |
| Eigenvalue | 2.18 | 1.22 | 1.01 |
| Percentage of total variance | 27.27 | 15.25 | 12.56 |
| Total variance | —a | —a | 55.09b |
aNot applicable.
bDeviations due to rounding.
Results for the question, “What risks do you see in e-mental health apps?” (for all: min=–2, max=2).
| Item | Participants, n (%) | Mean (SD) | 95% CI | |
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| Experts | 103 (99.04) | –0.01 (1.04) | –0.21 to 0.19 |
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| Students | 79 (98.75) | 0.47 (0.92) | 0.26 to 0.67 |
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| Patients | 82 (96.47) | 0.41 (1.12) | 0.17 to 0.66 |
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| Total | 264 (98.14) | 0.27 (1.05) | 0.14 to 0.39 |
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| Experts | 103 (99.04) | –0.50 (0.96) | –0.68 to –0.31 |
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| Students | 79 (98.75) | –0.46 (0.95) | –0.67 to –0.24 |
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| Patients | 81 (95.29) | –0.47 (1.21) | –0.74 to –0.20 |
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| Total | 263 (97.77) | –0.48 (1.03) | –0.60 to –0.35 |
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| Experts | 104 (100.00) | –0.16 (1.32) | –0.42 to 0.09 |
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| Students | 79 (98.75) | –0.25 (1.21) | –0.53 to 0.02 |
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| Patients | 83 (97.65) | –0.31 (1.42) | –0.62 to 0.00 |
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| Total | 266 (98.88) | –0.24 (1.32) | –0.40 to –0.08 |
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| Experts | 104 (100.00) | 0.91 (1.04) | 0.71 to 1.12 |
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| Students | 79 (98.75) | 0.73 (1.11) | 0.49 to 0.98 |
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| Patients | 83 (97.65) | 0.88 (1.13) | 0.63 to 1.13 |
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| Total | 266 (98.88) | 0.85 (1.09) | 0.72 to 0.98 |