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There is currently an increased interest in and acceptance of technology-enabled mental health care. To adequately harness this opportunity, it is critical that the design and development of digital mental health technologies be informed by the needs and preferences of end users. Despite young people and clinicians being the predominant users of such technologies, few studies have examined their perspectives on different digital mental health technologies.
This study aims to understand the technologies that young people have access to and use in their everyday lives and what applications of these technologies they are interested in to support their mental health. The study also explores the technologies that youth mental health clinicians currently use within their practice and what applications of these technologies they are interested in to support their clients’ mental health.
Youth mental health service users (aged 12-25 years) from both primary and specialist services, young people from the general population (aged 16-25 years), and youth mental health clinicians completed a web-based survey exploring technology ownership, use of, and interest levels in using different digital interventions to support their mental health or that of their clients.
A total of 588 young people and 73 youth mental health clinicians completed the survey. Smartphone ownership or private access among young people within mental health services and the general population was universal (611/617, 99%), with high levels of access to computers and social media. Youth technology use was frequent, with 63.3% (387/611) using smartphones several times an hour. Clinicians reported using smartphones (61/76, 80%) and video chat (69/76, 91%) commonly in clinical practice and found them to be helpful. Approximately 50% (296/609) of the young people used mental health apps, which was significantly less than the clinicians (
Technology access is pervasive among young people within and outside of youth mental health services; clinicians are already using technology to support clinical care, and there is widespread interest in digital mental health technologies among these groups of end users. These findings provide important insights into the perspectives of young people and clinicians regarding the value of digital mental health interventions in supporting youth mental health.
Digital mental health interventions (DMHIs) are interventions that use technologies, such as smartphones, smartwatches, or computer programs, to provide information, support, or treatment for mental health, most commonly using the internet [
The role of technology in supporting mental health was made starkly clear by the global COVID-19 pandemic. During this time, many nations became reliant on technology-enabled service delivery to provide mental health care at a distance [
Despite the potential of DMHIs, a lack of long-term engagement has often been reported. This is true both in clinical trials [
A shift toward practices that prioritize the needs and preferences of young people as end users is required to ensure that DMHIs are engaging and fit for purpose [
The study was approved by the Melbourne University human research ethics committee (approval numbers 2057299 and 2056793) and the Melbourne Health human research ethics committee (reference number QA2020096) and complied with the Declaration of Helsinki.
Young people and mental health clinicians completed a web-based survey as part of the BRACE project, which examined the effects of COVID-19 on the mental health and well-being of young people living in Australia, telehealth service quality, and the potential of technology to support youth mental health care. Data collection for the project occurred during and immediately after Australian Federal and State government–mandated lockdown restrictions (
This study reports primary findings on access to technologies and the use of and interest in different technologies for mental health support among young people and clinicians. Young people, aged between 12 and 25 years, were recruited through 2 sources. As part of a larger survey on social media and self-harm, the survey was advertised to the general population of young people aged 16 to 25 years on social media between June and October 2020. Young people who had scheduled an appointment between March 23, 2020, and August 7, 2020, at Australian primary (headspace) or specialist youth mental health services in Victoria or Queensland were also sent an SMS text message invitation to complete the survey. In Australia, headspace is the leading primary youth mental health service funded by the Australian Federal Government via the Primary Health Networks to provide early intervention for young people aged 12 to 25 years with mild to moderate and high-prevalence mental health conditions [
All participants completed the web-based survey using Qualtrics XM (Qualtrics). In the general population, after clicking the survey link, interested potential participants were screened for eligibility (aged between 16 and 25 years and residing in Australia). The survey was conducted on June 11, 2020, and was open for approximately 4 months. Eligible young people (aged 12-25 years) from 4 primary headspace services in Victoria were identified via the appointment calendars of the participating services. On May 28, 2020, an anonymous web-based survey link was sent via SMS text message to all those with appointments, and a reminder SMS text message was sent 2 weeks later. Young people from specialist services in Victoria and Queensland were provided the link by SMS text message, email, or letter between May 28 and June 11 (Victoria) and July 28 and August 7 (Queensland). Using a clinical staff email list, clinicians were sent a link to the anonymous web-based survey on May 10, 2020 (Victoria), and July 13, 2020 (Queensland), and given approximately 2 weeks to complete it.
In consultation with young people, the surveys were created specifically for the BRACE project, with young people and clinician surveys covering identical themes. Measures related to this study aimed to understand (1) access to and use of technology for mental health and (2) levels of interest in technologies to support mental health care among young people and clinicians.
Technology access and use were explored by asking young people if they owned or had private access to various technologies, ranging from smartphones and laptops to social media and gaming consoles. Those who indicated that they had access to the technology were asked how often they used it on a Likert scale ranging from
The level of interest in using 20 different technologies commonly used to support mental health was measured on a 5-point Likert scale ranging from
All quantitative items were measured on Likert scales, with anchors varying depending on the question, as specified in the results. A full copy of the survey is provided in
The Patient Health Questionnaire-4 [
Quantitative data were analyzed using descriptive statistics in SPSS (version 22.0, IBM). Owing to the focus of the paper, the survey was considered complete if participants responded to the technology interest items; however, all available data were reported, and pairwise analyses were performed. Owing to this, and as survey items were not mandatory, the sample size varied between analyses and is reported where it differed. Chi-square statistics were used to examine differences among participant groups (young people from the general population, young people from primary mental health services, young people from specialist mental health services, and clinicians) and the use of apps for mental health. To gain an indication of participants’ overall interest in technology to support mental health, overall interest in technology was calculated as the mean of an individual’s interest scores across the 20 technology types. Kruskal-Wallis tests with Bonferroni-corrected follow-up contrasts were used to examine differences among participant groups in terms of overall interest in using technology to support mental health. Similar technologies were grouped to examine differences among participant groups concerning interest in technology types. The following seven groups were formed by the research team based on the original 20 technology items:
Web-based self-help (web-based therapy, mental health websites, and web-based employment support)
Mobile self-help (apps to support mental health, apps to track mental health, and wearables to track mental health such as smartwatches)
Telehealth (video chat with clinician, telephone with clinician, texting with clinician, and mental health support lines)
Blended therapy (blended therapy and sharing mental health information with clinicians on the web)
Social media (secure social media to connect with young people about mental health and social media to connect with clinicians about mental health)
Immersive technologies (VR for mental health strategies, augmented reality for mental health strategies, VR with clinicians, and virtual worlds for mental health groups)
Interactive technologies (chatbots for mental health support and digital games for mental health support)
Within primary care services, an SMS text message link to the survey was sent to 1868 young people, 308 (16.49%) of whom responded to the survey, and of the 308 respondents, 229 (74.4%) completed it. Within specialist services, the survey was distributed to approximately 650 young people, of whom 59 (9.1%) responded, and of these 59 respondents, 53 (90%) completed it. The survey was also advertised on social media, and of the 693 people who clicked the link, 498 (71.9%) provided consent and were eligible, and of those who were eligible, 306 (61.4%) completed the survey items reported in this study. Finally, of the approximately 370 clinicians who received the survey link, 92 (25%) initiated the survey, and of those 92 clinicians, 73 (79%) completed it. The final sample comprised 73 clinicians across specialist and primary services and 588 young people (age range 12-25 years) from primary care, specialist services, and the general population. Demographic characteristics of the youth sample are shown in
Characteristics of young people from the general population, primary services, and specialist services (N=588).
Characteristics | General population (n=306) | Primary services (n=229) | Specialist services (n=53) | ||||
Age (years), mean (SD) | 21.20 (2.90) | 18.77 (3.48) | 21.08 (2.54) | ||||
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Female | 222 (72.5) | 142 (62.0) | 26 (49) | |||
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Male | 58 (19) | 63 (27.5) | 26 (49) | |||
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Transgender | 1 (0.3) | 10 (4.4) | 0 (0) | |||
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Nonbinary | 14 (4.6) | 7 (3.1) | 1 (2) | |||
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Unspecified | 11 (3.6) | 7 (3.1) | 0 (0) | |||
Aboriginal or Torres Strait Islander | 6 (2) | 4 (1.7) | 1 (2) | ||||
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Living with parents, caregivers, or siblings | 201 (65.7) | 191 (83.4) | 39 (74) | |||
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Living with friends | 29 (9.5) | 3 (1.3) | 0 (0) | |||
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Living with romantic partner | 30 (9.8) | 11 (4.8) | 0 (0) | |||
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Living in shared accommodation | 23 (7.5) | 9 (3.9) | 5 (9) | |||
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Living alone | 23 (7.5) | 14 (6.1) | 4 (8) | |||
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Homeless or couch surfing | 0 (0) | 1 (0.4) | 3 (6) | |||
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ACTa | 11 (2.4) | 0 (0) | 0 (0) | |||
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New South Wales | 31 (10.1) | 0 (0) | 0 (0) | |||
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Northern Territory | 1 (0.2) | 0 (0) | 0 (0) | |||
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Queensland | 16 (5.2) | 0 (0) | 16 (30) | |||
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South Australia | 10 (3.3) | 0 (0) | 0 (0) | |||
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Tasmania | 17 (5.6) | 0 (0) | 0 (0) | |||
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Victoria | 211 (69.0) | 229 (100) | 37 (70) | |||
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Western Australia | 9 (2.9) | 0 (0) | 0 (0) | |||
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Full-time student | 182 (59.5) | 126 (55.0) | 13 (25) | |||
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Part-time student | 35 (11.4) | 15 (6.6) | 3 (6) | |||
Hours of study each week, mean (SD) | 24.98 (12.22) | 22.14 (17.96) | 16.43 (8.77) | ||||
Full-time paid employment, n (%) | 54 (17.6) | 13 (5.7) | 3 (6) | ||||
Part-time paid employment, n (%) | 103 (33.7) | 34 (14.8) | 9 (17) | ||||
Hours of work each week, mean (SD) | 23.35 (13.33) | 19.72 (12.75) | 24.02 (11.68) | ||||
Unpaid worker as a parent or carer, n (%) | 6 (2.0) | 1 (0.4) | 1 (2) | ||||
Currently unemployed, n (%) | 43 (14.1) | 72 (31.4) | 30 (57) | ||||
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Potential clinical depression | 133 (43.5) | 69 (62.7) | 30 (57) | |||
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Potential clinical anxiety | 152 (49.7) | 65 (59.1) | 31 (60) |
aACT: Australian Capital Territory.
bCategories are not mutually exclusive.
cPatient Health Questionnaire-2 and Generalized Anxiety Disorder-2.
dA score of ≥3 on the 2-item depression and anxiety screening measures indicates probable depressive or anxiety disorder (n=110).
Young people’s access to different technologies is displayed in
A comparison of access to different technologies among young people from the general population, primary services, and specialist services and use of technology for clinical care among clinicians (N=693).
Technologies | Young people from the general population (n=327), n (%) | Young people from primary services (n=236), n (%) | Young people from specialist services (n=54), n (%) | Clinicians (n=76), n (%) | |
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321 (98.2) | 236 (100) | 54 (100) | 61 (80) | |
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iPhone | 233 (71.2) | 145 (61.4) | 29 (54) | —a |
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Android | 88 (26.9) | 91 (38.5) | 25 (46) | — |
Social media | 316 (96.6) | 222 (94.1) | 46 (85) | 4 (5) | |
Instant messenger | 313 (95.7) | 215 (91.1) | 46 (85) | 7 (9) | |
Laptop | 306 (93.6) | 197 (83.5) | 37 (69) | 55 (72) | |
Video chat | 286 (87.4) | 185 (78.4) | 44 (81) | 69 (91) | |
Gaming console | 153 (46.8) | 152 (64.4) | 40 (74) | 1 (1) | |
Tablet | 117 (35.8) | 84 (35.6) | 15 (28) | 27 (36) | |
Wearables | 92 (28.1) | 43 (18.2) | 9 (17) | 3 (4) | |
Desktop | 80 (24.5) | 66 (28) | 16 (30) | 43 (57) | |
Landline | 75 (22.9) | 57 (24.1) | 13 (24) | 33 (43) | |
Virtual reality | 18 (5.5) | 9 (3.8) | 5 (9) | 1 (1) |
aData not available.
Young people’s average frequency of use across technologies that they have access to (as presented in
The proportion of clinicians who used different technologies in their clinical work is presented in
Clinicians’ perceived helpfulness of different technologies that they have used within clinical care (as presented in
Approximately half of all participants (347/670, 51.8%) had used a mental health app themselves (young people: 296/609, 48.6%) or recommended one to their clients (clinicians: 51/61, 84%). A chi-square test for independence indicated a significant difference between participant groups and the use of apps for mental health (
Young people’s use of smartphone apps and clinicians’ use or recommendations of smartphone apps for clients (N=670).
Participant groups | Used or recommended apps for mental health, n (%) | Most commonly used or recommended apps |
Young people from the general population (n=319) | 162 (50.8) | Smiling Mind, Headspace, Calm, and Calm harm |
Young people from primary services (n=236) | 111 (47) | Headspace, Smiling Mind, Calm, and Daylio |
Young people from specialist services (n=54) | 23 (43) | Calm, Headspace, Daylio, Smiling Mind, and YouTube |
Clinicians (n=61) | 51 (84) | Smiling Mind, BeyondNow, Headspace, and Calm |
Overall, most young people from services (specialist services and primary care) reported that using apps to support their mental health was helpful or very helpful (82/132, 62.1%). Approximately 20.5% (27/132) neutral and 17.4% (23/132) reported apps to be unhelpful. Similarly, on average, young people from the general population found apps to be somewhat helpful (124/161, 77%). Approximately 13% (21/161) found them unhelpful. The vast majority of clinicians (45/48, 93.8%) felt that the apps were helpful to their clients.
Young people’s and clinicians’ interest in different technologies to support mental health is presented in
The average level of interest in different technological approaches to support mental health across the 4 participant groups: young people general population (n=306), young people primary services (n=229), young people specialist services (n=53), and clinicians (n=73). AR: augmented reality; MH: mental health; SM: social media; VR: virtual reality; YP: young people.
Similar technology types were then grouped to observe the patterns of interest more clearly between the participant groups (
Technology interest for mental health may be influenced by the respondents’ familiarity with the technology. A Mann-Whitney
Level of interest in each of the participant groups for different categories of mental health technology.
This study examined the access and use of digital technologies among young people from youth mental health services and the general population, as well as the interest in digital technology use for supporting mental health care among young people and clinicians. The findings indicate that young people had widespread access to technologies, with 99% (611/617) having access to a smartphone and 63.3% (387/611) using it on average every hour. Clinicians reported similarly high rates of technology use to support their clinical care, with 91% (69/76) reporting the use of video chat, 80% (61/76) reporting the use of smartphones, and most finding common technologies such as laptops and the internet helpful or very helpful. Approximately 50% (296/609) of young people from within services and the general population reported using smartphone apps to support their mental health, and 84% (51/61) of the clinicians reported recommending them to their clients. Apps were reported to be helpful by 62.1% (82/132) of young people within services and 77% (124/161) in the general population. The vast majority of clinicians (45/48, 94%) found apps helpful for their clients. Levels of interest varied across different technologies for supporting youth mental health, although 100% (73/73) of clinicians were at least slightly interested in technology to support their clients’ mental health, and 88% (520/591) of the young people were interested in technology. There were particularly high rates of interest among young people in self-help tools such as smartphone apps, web-based therapies, and technologies integrated with routine care (
Rates of access to technology were high across young people from within and outside of youth mental health services, with 98% to 100% of those surveyed having access to an internet-enabled device such as a smartphone or computer. Furthermore, young people reported very frequent use of these technologies throughout their daily lives, averaging several times an hour for smartphones. This is in line with prior research showing access rates between 95% and 99% in youth populations within high-income countries [
Overall, 88% (520/591) of young people reported at least some interest in technologies to support their mental health and well-being, and this did not differ depending on whether they were using youth mental health services. However, the patterns of interest appeared to differ across groups. Although all young people showed high levels of interest in self-help technologies, particularly smartphone apps and web-based therapy, those from within the services were most interested in technologies that worked alongside a clinician, including blended therapies and telehealth. This highlights the perceived need among young people for technologies to support care delivery, a finding supported by research indicating that DMHIs are the most effective and engaging when used in conjunction with human support [
Clinicians also endorsed high rates of interest in recommending a wide range of digital technologies to support youth mental health, with 100% (73/73) reporting at least some interest. Patterns of interest appeared to map well with young people, primarily for video calls, self-help apps, and web-based therapy. The most consistently endorsed technology across young people and clinicians was websites providing web-based therapy or mental health information and smartphone apps to track and support mental health. Indeed, 40% (29/73) of the clinicians were
In contrast, clinicians and young people were relatively less interested in automated therapies, such as chatbots, and technologies that made use of platforms that were infrequently accessed and used, such as VR. Although this may represent genuinely lower levels of interest in these technologies, it is also possible that this reflects a lack of familiarity and experience with their use for mental health treatment. Indeed, people tend to hold less positive attitudes and are less likely to adopt technologies with which they are less familiar [
Clinicians also reported frequently using technology to support their practice, with 91% (69/76) using video chat, 80% (61/76) using smartphones, and >80% finding these helpful. Furthermore, overall, clinician interest in recommending digital technologies to support youth mental health was significantly higher than young people’s interest in using them (although both groups displayed high levels of interest). This finding is consistent with prior results from the BRACE survey, showing that 98% of youth mental health clinicians endorsed the ongoing use of telehealth beyond the COVID-19 pandemic [
Half of the young people reported using smartphone apps for their mental health, and 84% (51/61) of the clinicians had recommended them to their clients, with most finding these helpful. This difference between young people and clinicians was statistically significant, indicating that although apps may be commonly recommended by clinicians, this does not correspond directly with uptake by young people. Given that young people have high levels of exposure to digital technologies within their everyday lives [
Notably, the apps most commonly used by clinicians and young people were those with significant market dominance. A recent app store review by Lau et al [
Although this study has a number of strengths, including its large sample of young people across the spectrum of need for care, the inclusion of clinicians as important additional stakeholders and end users of DMHIs, as well as the depth of the survey regarding different DMHIs, the findings should be interpreted with knowledge of study limitations. First, data were collected via technology; thus, respondents likely represent a sample of digitally enabled young people, and only a proportion of young people responded to the survey. A range of demographic factors such as income and education may have influenced young people’s access to, and beliefs about, technology; however, this information was not captured in this study. Importantly, particular populations of young people, such as those from culturally and linguistically diverse or low socioeconomic backgrounds, who may have a greater need for mental health care, may not be well represented in this survey because of lower rates of technology access in these populations. This was highlighted in another report from the BRACE survey as a primary consideration among clinicians regarding the suitability of DMHIs for some young people [
Second, we cannot guarantee that young people from the general population were not users of services or did not experience mental health issues. Indeed, the high rates of depression and anxiety reported in our general population sample indicate a potential need for care. However, we did not ask participants about their help seeking. Notably, these levels of mental health concerns match those of surveys conducted on the general Australian youth population during the pandemic, supporting the representativeness of the sample [
Finally, Australia is a high-income country with mental health services supported by government funding. Youth mental health services are free for young people, although capacity limitations and geographical barriers limit access to them. These results may not be generalizable to countries with more limited youth mental health services, in which the demand for and interest in DMHIs may be higher [
The global pandemic has brought forth a critical juncture in developing a new system of digitally enabled care that is aligned with the needs of those it intends to support. These findings provide valuable insights into the perspectives of clinicians and young people as end users of digital mental health technologies and provide a compelling case for further development and expansion of technologies to enhance youth mental health care.
Full survey on digital mental health use and interest among young people and clinicians.
digital mental health intervention
General Anxiety Disorder-2
Patient Health Questionnaire-2
virtual reality
The authors would like to thank Brendan Pawsey, Irene Opasinov, Steve Hackett, Andrea Mulaimovic, Arianne Wright, Eleanor Bailey, Jo Robinson, Alex Boland, and Veronica Curtin for their assistance with recruitment. The authors are also grateful to the young people and clinical staff who gave their time to complete the survey. This work was supported by Future Generation Global and a Victorian Government Innovation Grant.
None declared.