Abstract
Background: Digital health technologies (DHTs) for psychosis have been developed and tested rapidly in recent years. However, research examining mental health professionals’ views on the use of DHTs for people with psychosis is limited. Given the increased accessibility and availability of DHTs for psychosis, an up-to-date understanding of staff perception of DHTs for psychosis is warranted.
Objective: In this study, we aimed to investigate mental health professionals’ usage of technology and their perception of service users’ technology usage; their views toward the use of DHTs for psychosis, including their concerns; and barriers for implementing DHTs in a mental health setting.
Methods: Two cross-sectional surveys were distributed to mental health care staff who had experience of working with individuals experiencing psychosis in the United Kingdom. Survey 1 (from April 2018 to September 2020) was distributed to 3 local UK National Health Service (NHS) trusts in Northwest England; survey 2 was administered nationally across 31 UK NHS trusts or health boards (from November 2022 to March 2024). The COVID-19 pandemic occurred between the 2 survey periods. Data were analyzed descriptively.
Results: A total of 155 and 352 participants completed surveys 1 and 2, respectively. Staff reported high levels of technology ownership and usage in both surveys. In general, staff expressed positive views regarding the use of DHTs for psychosis; however, barriers and concerns, including affordability, digital literacy, and potential negative effects on service users’ mental health, were also reported. We did not find notable changes in terms of staff use of digital technology in clinical practice over time.
Conclusions: Staff sampled from a broad and diverse range expressed consistent optimism about the potential implementation of DHTs in practice, though they also noted some concerns regarding safety and access. While the COVID-19 pandemic is frequently regarded as a catalyst for the adoption of digital health care tools, the sustainability of this transition from traditional to digital health care appeared to be suboptimal. To address staff concerns regarding safety and potentially facilitate the implementation of DHTs, systematic evaluation of adverse effects of using DHTs and dissemination of evidence are needed. Organizational support and training should be offered to staff to help address barriers and increase confidence in recommending and using DHTs with service users.
doi:10.2196/68362
Keywords
Introduction
Psychosis usually occurs in late adolescence or early adulthood and can have significant personal, family, social, and economic consequences [-]. The duration of untreated psychosis is associated with a range of negative clinical and functional outcomes; therefore, timely access to evidence-based interventions is crucial [-]. Early intervention services (EIS) have been established in many countries to reduce treatment delay and improve outcomes for people who have experienced a first episode of psychosis [,]. Despite evidence for the effectiveness and cost-effectiveness of EIS, there are still challenges for implementing and accessing such services [,]. Digital health technologies (DHTs) to support people who experience psychosis have been developed and tested rapidly in recent years []. DHTs hold the potential to scale up mental health care and provide timely access to evidence-based intervention and management options, which could help reduce duration of untreated psychosis [], prevent relapse [], and facilitate self-management in near real-time []. A variety of digital technologies, including smartphone apps, virtual reality, and websites, have been used as tools for digital interventions and remote symptom monitoring [,]. Large-scale randomized controlled trials are beginning to demonstrate the efficacy of digital interventions for psychosis [-], moving the field on from early phase feasibility studies.
As the frontline of service provision, staff attitudes and knowledge are crucial for the successful development and implementation of DHTs []. Previous studies exploring staff views of digital mental have found staff were interested in using DHTs to provide care and some staff were already using digital technologies to support clinical care [-]. However, given the increased accessibility and availability of DHTs [], an up-to-date understanding of staff perceptions, views and attitudes toward the use of DHTs in the context of working with people with psychosis is warranted. Furthermore, although the transition to telehealth and digital health was accelerated by the COVID-19 pandemic due to the associated social distancing restrictions [,], the maintained implementation of DHTs in clinical practice beyond this period is limited. For example, the 2022 European Psychiatric Association survey on digitalization found that remote mental health services were not part of standard care in half (51.43%) of the 35 European countries surveyed, and over one-third (37.14%) of the respondents reported that no legislative regulation was in place in their countries [,]. In addition, studies focusing on staff usage of DHTs in psychosis services postpandemic are lacking.
In this paper, we report findings from 2 surveys: survey 1 (from April 2018 to September 2020) was distributed to 3 local UK NHS (National Health Service) trusts; survey 2 was administered nationally across 31 UK NHS trusts or health boards (from November 2022 to March 2024). Our aims were to understand mental health professionals’ use of technology and their perception of service users’ technology usage, their views toward the use of DHTs for psychosis, including their concerns, and barriers for implementing DHTs in a mental health setting. Although not the primary aim of this study, we conducted a narrative exploration of the differences between staff responses from the 2 surveys to gain a deeper understanding of the implementation of DHTs in clinical practice postpandemic. A timeline of the survey recruitments and COVID-19 waves in the United Kingdom is shown in Figure S1 in .
Methods
Participants
We surveyed mental health staff working in the UK National Health Service (NHS) in both surveys. Eligibility criteria were health care professionals working within an NHS service providing mental health support to people who experience psychosis or severe mental health problems, aged 18 years or older, and had the ability to provide informed consent. Participants not sufficiently fluent in English to complete the survey were excluded from participation. Potential participants completed screening questions in the survey to assess their eligibility. Survey 1 was disseminated in 3 mental health trusts in the Northwest of England; survey 2 was distributed in 31 NHS mental health trusts or health boards across England and Scotland (Glasgow; Edinburg).
Data Collection
Survey 1 was developed by the research team based on findings obtained in reviewing literature and focus groups with staff working in EIS [,]. The survey included questions about staff perceptions of service user technology usage and engagement, and their views toward use DHTs in the context of working with and supporting psychosis service users. Survey completion time was approximately 8 minutes. Participants were asked to complete either an online or paper-based version of the survey; the online version delivered using the REDCap (Research Electronic Data Capture) [,] platform. Survey 1 was disseminated from April 2018 to September 2020 (ie, before and during COVID-19 pandemic wave 1).
Survey 2 was conducted from November 2022 to March 2024 (ie, post COVID-19 pandemic). The survey was adapted from survey 1 and extended to collect data about staff views on digital remote monitoring technologies (reported in a separate paper; Zhang et al, unpublished data, March 2025). Therefore, this survey was longer than survey 1 and took approximately 20‐30 minutes to complete. Demographic information, data on technology ownership rates, usage in clinical practice, and staff perspectives on the use of digital health tools were collected. Participants had the option to complete an online or paper copy of the questionnaire. The online survey was conducted using the Qualtrics (Silver Lake) platform []. For participants using a paper copy, a study pack with a paper survey and return postage-paid envelope was sent. Once the paper copy was returned, the answers were entered manually into the Qualtrics database. The surveys are shown in Tables S1 and S2 in .
Data Analysis
Descriptive statistics, including frequencies and percentages, and data visualization, were performed using R program (R Foundation for Statistical Computing) [] to analyze quantitative data. The proportion of missing rates for each question were summarized and reported in the results. Free-text answers were summarized narratively using Nvivo (version 12, Lumivero) []. As we recruited different cohorts across the 2 surveys (ie, a regional and national sample) and used slightly different questionnaire versions (ie, survey 2 was adapted and updated from survey 1), no inferential statistical analysis was performed to determine the statistical significance of the differences between the 2 surveys.
Ethical Considerations
The participant information sheet with the study information and consent form were embedded in the survey. Data were anonymized. Survey 1 was approved by the West of Scotland Research Ethics Committee 4 (17/WS/0221), and survey 2 was approved by the Northwest-Greater Manchester West Research Ethics Committee (22/NW/0246). Participants had the chance to enter a £20 (approximately US $25) prize draw to thank them for their time.
Results
Participant Characteristics
A total of 155 and 352 participants completed survey 1 and 2, respectively. A summary of participant demographic characteristics is presented in 
Table 1. In survey 1, median participant age was 39 (IQR 32‐47) years. The median time (years) working in current role was 3 (IQR 1‐8) years. Most participants were female (119/155, 76.77%), White (137/155, 88.39%), and had completed postgraduate level education (106/155, 68.39%). Overall, 40% (62/155) of participants were working in EIS. Participant job roles included mental health nurse (32/155, 20.65%), care coordinator (24/155, 15.48%), and psychologist (21/155, 13.55%).
| Characteristics | Survey 1 (n=155) | Survey 2 (n=352) |
| Age, median (IQR) | 39 (32‐47) | 40 (31‐50) |
| Gender, n (%) | ||
| 119 (76.77) | 244 (69.32) | |
| 36 (23.23) | 102 (28.98) | |
| —a | 1 (0.28) | |
| — | 5 (1.42) | |
| Ethnicity, n (%) | ||
| 11 (7.1) | 45 (12.78) | |
| 3 (1.94) | 20 (5.68) | |
| 137 (88.39) | 276 (78.4) | |
| 2 (1.29) | 5 (1.42) | |
| 1 (0.64) | 4 (1.13) | |
| 1 (0.64) | 2 (0.57) | |
| Service, n (%) | ||
| 7 (4.52) | — | |
| 10 (6.45) | 119 (33.81) | |
| 62 (40) | 82 (23.3) | |
| 9 (5.8) | — | |
| 41 (26.45) | 8 (2.27) | |
| 6 (3.87) | 63 (17.9) | |
| 13 (8.39) | — | |
| — | 3 (0.85) | |
| — | 77 (21.88) | |
| 7 (4.52) | — | |
| Education, n (%) | ||
| 3 (1.94) | 7 (1.99) | |
| — | 41 (11.65) | |
| — | 6 (1.7) | |
| 4 (2.58) | — | |
| 5 (3.22) | — | |
| 36 (23.22) | 129 (36.65) | |
| 106 (68.39) | 165 (46.87) | |
| — | 1 (0.28) | |
| 1 (0.65) | — | |
| Job title, n (%) | ||
| 24 (15.48) | — | |
| 10 (6.45) | 37 (10.51) | |
| 13 (8.39) | 13 (3.69) | |
| 32 (20.65) | 99 (28.12) | |
| 12 (7.74) | 11 (3.12) | |
| 21 (13.55) | 54 (15.34) | |
| 11 (7.1) | 50 (14.2) | |
| 1 (0.64) | — | |
| 7 (4.52) | 28 (7.95) | |
| — | 7 (1.99) | |
| — | 9 (2.56) | |
| 23 (14.84) | 43 (12.22) | |
| 1 (0.64) | 1 (0.28) | |
| Years working in current role, median (IQR) | 3 (1–8) | 4 (1.5‐10) |
| Regions, n (%) | ||
| — | 5 (1.42) | |
| 155 (100) | 68 (19.32) | |
| — | 55 (15.63) | |
| — | 34 (9.66) | |
| — | 2 (0.57) | |
| — | 69 (19.6) | |
| — | 16 (4.55) | |
| — | 47 (13.35) | |
| — | 40 (11.36) | |
| — | 1 (0.28) | |
| — | 15 (4.26) | |
a Not available.
Participants from survey 2 had a median age of 40 (IQR 31‐50) years and a median time working of 4 (IQR 1.5‐10) years in their current role. Most responders were female (244/352, 69.32%) and White (276/352, 78.41%). Around a third held a university bachelor’s degree (129/352, 36.65%), worked in a community mental health team (119/352, 33.81%), and practiced as a mental health nurse (99/352, 28.12%).
Staff Technology Usage
As shown in Table 2, technology usage rates among survey 1 participants were high, with almost all participants reporting using the internet (147/155, 94.84%) and a personal smartphone (135/155, 87.1%) in their daily life. Wearable technology use was less common, with less than a quarter of respondents reporting using a fitness tracker (36/155, 23.23%) and only a few using a smartwatch (18/155, 11.61%). In the work environment, most respondents indicated using a desktop computer (110/155, 70.97%) and mobile phone (102/155, 65.81%). Smartphones were used by 56.77% (88/155) participants in a work context. Tablet computers were used less compared with other types of technologies; only one third of respondents reported using a tablet in the context of their clinical work (51/155, 32.9%).
| Technology | Yes, n (%) | No, n (%) | Missing, n (%) |
| Personal use | |||
| 147 (94.84) | 1 (0.65) | 7 (4.52) | |
| 135 (87.10) | 10 (6.45) | 10 (6.45) | |
| 123 (79.35) | 21 (13.55) | 11 (7.10) | |
| 116 (74.84) | 24 (15.48) | 15 (9.68) | |
| 100 (64.52) | 38 (24.52) | 17 (10.97) | |
| 76 (49.03) | 58 (37.42) | 21 (13.55) | |
| 36 (23.23) | 93 (60.00) | 26 (16.77) | |
| 36 (23.23) | 93 (60.00) | 26 (16.77) | |
| 18 (11.61) | 109 (70.32) | 28 (18.06) | |
| Professional use | |||
| 110 (70.97) | 28 (18.06) | 17 (10.97) | |
| 102 (65.81) | 41 (26.45) | 12 (7.74) | |
| 92 (59.35) | 45 (29.03) | 18 (11.61) | |
| 88 (56.77) | 50 (32.26) | 17 (10.97) | |
| 51 (32.90) | 85 (54.84) | 19 (12.26) | |
In survey 2, as shown in (Figure S2 in ), more than half respondents used a smartphone in their clinical practice (184/352, 52.27%) with a fairly even split of Android (101/352, 28.7%) and iPhone users (94/352, 26.7%). Only 20.17% (71/352) and 7.39% (26/352) of participants respectively used tablets and wearable devices in their clinical work. Notably, nearly 40% (140/352) of participants indicated not using any digital technology in the context of their clinical practice.
Participants’ responses in survey 1 about their attitudes toward digital technologies both in general and in the context of their clinical work are presented in Table 3. Generally, participants reported having a positive attitude toward digital technologies both from a personal perspective and in the context of their clinical work in EIS. Specifically, over half of the responders endorsed “agree” or “strongly agree” to the statement they are “enthusiastic about digital devices” (86/155, 55.48%), and most participants reported that technology could play a positive role in mental health services in the future (134/155, 86.45%). Only a few participants (28/155, 18.71%) expressed negative attitudes toward digital devices in general, reporting that technology is frustrating for them.
| Statement | Strongly disagree, n (%) | Disagree, n (%) | Neutral, n (%) | Agree, n (%) | Strongly agree, n (%) | Missing, n (%) |
| I am enthusiastic about electronics and digital devices | 5 (3.23) | 11 (7.1) | 50 (32.26) | 57 (36.77) | 29 (18.71) | 3 (1.94) |
| I frequently look for new software or apps | 12 (7.74) | 43 (27.74) | 43 (27.74) | 43 (27.74) | 11 (7.1) | 3 (1.94) |
| My friends would describe me as “into” the latest technology | 40 (25.81) | 57 (36.77) | 33 (21.29) | 17 (10.97) | 5 (3.23) | 3 (1.94) |
| Technology could play a positive role in mental health services in the future | 1 (0.65) | 3 (1.94) | 14 (9.03) | 101 (65.16) | 33 (21.29) | 3 (1.94) |
| For me, technology is frustrating | 17 (10.97) | 60 (38.71) | 46 (29.68) | 23 (14.84) | 6 (3.87) | 3 (1.94) |
Staff Perception of Service Users’ Technology Use
We asked survey 1 participants to estimate service users’ technology ownership rate in percentile based on their clinical experience (
Figure 1). Most staff respondents estimated that the percentage of the service users they work with who owned a mobile phone or smartphone ranged between 75%‐99%. In contrast, most staff responders estimated that the percentage of the service users they work with who owned a smartwatch and an activity tracker fell between 1%‐24%.
In survey 2, around 70% of participants (254/352, 72.1%) estimated 25%‐50% of service users on their caseload would use DHTs to support their mental health (Figure S3 in ). Furthermore, over half of participants (186/352, 52.8%) reported that at least 1 service user on their caseload was currently using DHTs. Of those using DHTs, staff said that service users they were working with mostly used smartphones (155/186, 83.3%) to support their mental health, followed by wearable devices (65/186, 35%) and tablets (57/186, 30.6%).
In survey 1, staff perceived barriers for service users with psychosis to own or use a mobile phone are shown in Table 4. Primary barriers were “struggling to afford phones or smartphones” (112/155, 72.26%) and “paranoia or suspiciousness about mobile phones” (101/155, 65.16%). Four additional barriers were identified from free-text responses: “struggling to afford internet, data, or Wi-Fi,” “risk of selling phones,“ “willingness to use phones,” and “restriction of accessing mobile phones in ward or prison.” Survey 2 participants reported the barriers for service users they work with to use DHTs in the free-text question, including “inability to own or use a digital device,” “paranoid beliefs about digital devices,” and “being older.“ A full list is shown in Table S3 in .
| Barrier | Yes, n (%) | No, n (%) | Missing, n (%) |
| Struggling to afford mobile phones or smartphones | 112 (72.26) | 33 (21.29) | 10 (6.45) |
| Paranoia or suspiciousness about mobile phones | 101 (65.16) | 44 (28.39) | 10 (6.45) |
| Damage of mobile phones | 86 (55.48) | 59 (38.06) | 10 (6.45) |
| Loss of mobile phones | 81 (52.26) | 64 (41.29) | 10 (6.45) |
| Technology use skills | 74 (47.74) | 71 (45.81) | 10 (6.45) |
Using Digital Health Technologies in Clinical Practice
We asked survey 1 participants to indicate their usage of common resources, both digital and nondigital forms, in their appointments with service users (Table S4 in ). Many staff reported they had recommended digital resources to service users they worked with, such as online written information (120/155, 77.42%) or videos (85/155, 54.84%) about mental health. Paper-based approaches were also popular amongst staff, with 72.9% (113/155) of respondents having used paper-based symptom monitoring recorded by service users and 59.35% (92/155) having used paper-based between session therapy homework sheets.
As shown in Table S5 in , participants frequently recommended digital technologies for self-management purposes, with the top recommendations including “listening to music or audio files via a smartphone to distract from voices or intrusive thoughts” (129/155, 83.23%), “using a calendar or set alarms or reminders for appointments” (127/155, 81.94%), and “setting alarms or reminders to help with medication management” (114/155, 73.55%). In contrast, symptom monitoring by a paper diary (126/155, 81.29%) was more popular than digital approaches to tracking symptoms (smartphone app: 45/155, 29.03%; website: 22/155, 14.19%). Nonetheless, most respondents were at the very least considering recommending digital symptom monitoring to service users. For example, only about 30% (45/155, 29.03%) of participants indicated they had recommended using a smartphone app to track symptoms, while around 60% (95/155, 61.29%) said they were considering recommending it. Regarding staff preferences for receiving the data from patient-generated symptom reporting through apps, half of the staff (78/155, 50.32%) wanted service users to take the data to appointments, and nearly a third (42/155, 27.1%) accepted the automatic transfer of data from apps to the care team. However, 12.26% (19/155) of respondents indicated they do not want to receive such information at all. When asked whether staff had ever recommended an app to a service user for their mental health, 79.35% (123/155) respondents said they had, whereas 43.87% (68/155) staff had recommended at least 1 app for service users to use for their physical health.
Table S6 in shows staff perceptions of the potential advantages of mental health apps. The most endorsed advantage was the “opportunity to increase understanding about symptoms and experiences” (127/155, 81.93%), followed by “opportunity for service users to take up-to-date records of symptoms and experiences to clinicians” (123/155, 79.36%), and “ability to access an app at any time and in any location” (123/155, 79.36%). Regarding barriers to staff recommending using a mental health app to service users (Table S7 in ), the foremost barrier reported was “service users feeling suspicious or paranoid about using smartphones and apps” (99/155, 63.87%).
We asked survey 2 participants whether they considered smartphones, tablets, and wearable devices to be useful additions for supporting their clinical practice (Figure S4 in ); the top rated digital devices were iPad (175/352, 49.7%), wearable devices (141/352, 40.1%), Android tablet (117/352, 33.2%), and iPhone (117/352, 33.2%). Among the 11 common features afforded by DHT to support service users, the top features rated by staff based on their perceived usefulness (all options were by more than half of respondents) were the “ability to get appointment reminders” (335/352, 95.2%), “monitoring sleep” (308/352, 87.5%) and “physical activity” (284/352 80.7%), the “ability to track mental health symptoms” (278/352, 79%), and using a “diary function” (to log thoughts and feelings (277/352, 78.7%; Table 5). Staff said that the most useful apps for service users’ mental health care were mental health apps (323/352, 91.8%), sleeping apps (322/352, 91.5%), and mindfulness apps (314/352, 89.2%; Figure S5 in ).
| Items | Ranking | Participants, n (%) |
| Ability to get appointment reminders | 1 | 335 (95.2) |
| Monitor sleep | 2 | 308 (87.5) |
| Monitor physical activity | 3 | 284 (80.7) |
| Ability to track mental health symptoms | 4 | 278 (79.) |
| Diary function (ability to log thoughts and feelings in a diary) | 5 | 277 (78.7) |
| Access to information/education/support | 6 | 263 (74.7) |
| Ability to get information about their mental health problem | 7 | 259 (73.6) |
| Ability to discuss data logged by an app with their clinician | 8 | 246 (69.9) |
| Ability to self-manage | 8 | 246 (69.9) |
| Ability to complete outcome measures remotely | 9 | 237 (67.3) |
| Ability to share data logged by an app with a trusted friend/carer/relative for support | 10 | 215 (61.1) |
| Monitor other health-related activities | 11 | 198 (56.2) |
| Other | —a | 29 (8.24) |
| Digital technology does not offer any benefits to service users | — | 5 (1.42) |
a Not available.
Discussion
Principal Findings
We describe the findings of 2 surveys to explore staff usage of and views on implementing DHTs in clinical practice. Survey 1 recruited a regional sample based in the northwest of England; Survey 2 reached a national sample across the United Kingdom. Both surveys recruited a sample with a median age of around 40 years old, more females than other genders, more White than other ethnicity groups, and more practiced as a nurse or a psychologist than other mental health professionals. However, in survey 2, there was a larger proportion of participants working at a community mental health team, and a smaller proportion achieved a postgraduate level of education compared with survey 1.
Staff reported fairly high levels of use of digital technologies in a clinical context in both surveys, with more than half of participants reporting using a smartphone in the context of their clinical practice (Survey 1: 56.77%; Survey 2: 52.27%). Furthermore, a significant proportion of staff expressed positive attitudes toward using digital technologies in mental health care delivery and identified themselves as generally enthusiastic about technology in the Survey 1 (55.48%). Given that staff attitudes toward DHTs and their digital technology literacy have been shown to influence the adoption of DHTs in clinical practice [,], our finding of largely positive attitudes suggests that staff could become key points of contact and ambassadors for DHT implementation within EIS pathways. This is also consistent with findings from previous qualitative studies, which suggest that the more clinicians understand how to use technology and feel comfortable using it, the more likely they will be to use it in clinical practice [].
Of note, in both surveys, staff members’ estimates of service user ownership rates varied depending on device type. Specifically, staff estimated that wearable device ownership was substantially lower than smartphone ownership amongst service users with early psychosis (survey 1: smartphone 75%‐99% vs wearables 1%‐24%; survey 2: smartphone 83.3% vs wearables 35%). A similar pattern was observed in previous research on staff members’ own digital technology ownership conducted in other countries (eg, Australia [] and China []). Bell et al [] reported that clinicians who provided youth mental health care in Australia had higher usage rates of video chat and smartphones compared with wearables, social media, or virtual reality. Zhang et al [] found that mental health staff in China were less aware of virtual reality and artificial intelligence–based interventions than social media, smartphone app, or internet-based interventions. These findings suggest that different types of digital technologies may require different implementation strategies. As the field progresses toward integrating various technologies (eg, passive sensing and smartphones for time-sensitive interventions), a lack of awareness and access to these “newer” technologies may hinder adoption. Therefore, implementation strategies might need to include providing devices such as fitness trackers [].
Barriers and concerns to implementing DHTs were captured in both surveys and were consistent with the broader literature on barriers to implementation of DHTs, including symptoms of psychosis preventing engagement with DHTs, service user lack of motivation to use DHTs, and digital poverty []. Participants from both surveys expressed concerns that using such technologies could contribute to potential negative effects on service users’ mental health (eg, increased paranoia, suspiciousness, depression, or anxiety). These concerns may be related to the association between problematic use of digital technologies and mental health [,]. Although adverse events related to paranoia are generally rare [], some clinical trials on digital mental health interventions for psychosis have reported adverse events in participants who experienced distress related to the technology used [,]. These findings highlight the urgent need for systematic evaluations and reporting of adverse effects of DHTs to fully understand their safety [,].
Although, as mentioned above, the usage of DHTs in clinical practice was not extensive, both surveys showed some DHT implementations in clinical practice. Many respondents from survey 1 reported using digital approaches to support the delivery of mental and physical health care support to service users. This included online videos (54.84%), written information (77.42%), and recommending relevant apps, such as those for tracking symptoms through smartphone apps (29.03%). Participants from survey 2 indicated that appointment reminders (95.2%), and monitoring sleep (87.5%), physical activities (80.7%) and mental health symptoms (79%) would be the most useful features of DHTs for mental health care. These findings are in line with survey studies conducted with staff working with young people [] and individuals diagnosed with bipolar disorder [], highlighting that mental health practitioners are interested in using DHTs in clinical care across various mental health settings.
The COVID-19 pandemic is often considered an accelerator for the adoption of digital health care [] , with increased technology use in clinical practice during social distancing restrictions (eg, appointments through video calls) [,]. By comparing the findings of the 2 surveys, we found that this shift might have not been maintained among staff working in services that support service users with psychosis. For example, smartphones and tablets were reported to be used by 56.77% and 32.9% of participants in clinical practice in survey 1, respectively, but no increase was observed in survey 2 (smartphone 52.27% and tablet 20.17%). This echoes findings from recent reviews, which indicated that although staff across the globe had adopted telehealth during the pandemic, feedback and willingness to continue postpandemic have been mixed; the rates of telehealth use declined once restrictions loosened [,]. One explanation might be that the pandemic only resulted in staff using remote care temporarily to manage social distancing restrictions but did not form a “new norm” for integrating DHTs in their clinical practice []. In addition, lack of organizational support, such as financial support and necessary infrastructure to support digital tools, may also contribute to the drop in rates of use postpandemic [,]. This finding underscores that certain barriers may have persisted despite the widespread transition to telehealth and digital health. Continuous efforts are required to further understand the barriers and facilitators for implementing DHTs in psychosis services in the post-pandemic era.
Strengths and Limitations
One strength of this study is that survey 2 reached a national sample, enabling us to gain a broader understanding beyond the local sample captured in Survey 1. In addition, by comparing and contrasting the 2 survey results, it brings insights on the potential impact COVID-19 pandemic had on staff use of, and views about, DHTs for psychosis care. There are some limitations. First, the online surveys might have attracted participants who are more familiar with and supportive of digital technologies compared with their counterparts. Second, both surveys recruited a convenience sample. As such, we cannot guarantee that participants are fully representative of all staff working in secondary care mental health settings. Third, the 2 surveys recruited different samples and used different measurements, precluding statistical comparison of the results.
Conclusion
This study found that most staff working with individuals experiencing psychosis were familiar with digital technology, both personally and professionally. They expressed positive attitudes toward implementing DHTs in practice. However, concerns regarding the safety of using DHTs were reported. To further develop and implement DHTs, a systematic evaluation of their adverse effects is needed to address safety concerns. In addition, providing comprehensive training is essential to ensure that staff are well-equipped to adopt evidence-based tools to support service users with psychosis and to enhance their confidence in using these technologies. Furthermore, it is imperative to address organizational barriers, such as funding and IT infrastructure, in the postpandemic era, despite the acceleration of adoption of DHTs during the COVID-19 pandemic. Furthermore, it is crucial to conduct further studies with service users directly to explore the readiness, acceptability and adoption of digital health interventions as part of their health care journey.
Acknowledgments
We acknowledge and thank the participants who took part in the study, the Expert Reference Group who provided extensive input on the survey design, and Rose Dickin and Rosa Pitts who assisted with data collection and data management. We thank the kind assistance of the individuals within the respective National Health Service (NHS) services. This project was funded by the research professorship NIHR300794 from the National Institute for Health and Care Research (NIHR; Prof Bucci) and as part of a Medical Research Council grant (MR/ P026664/1). This research was also supported by the NIHR Biomedical Research Center (NIHR203308). There was no editorial direction or censorship from the study funder or the study sponsor. The study funder and study sponsor had no role in the study design, data collection, data analysis, data interpretation, or writing the report. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.
Data Availability
The dataset generated in this study may be made available from the corresponding author on reasonable request.
Authors' Contributions
XZ contributed to writing – review and editing, writing – original draft, visualization, formal analysis, investigation, data curation, and project administration. NB managed writing – review and editing, conceptualization, investigation, and project administration. DDB handled writing – review and editing, investigation, and project administration. CR managed writing – review and editing, conceptualization, investigation, and project administration. EE contributed to writing – review and editing. SB handled writing – review and editing, validation, supervision, resources, project administration, conceptualization, investigation, funding acquisition, and data curation.
Conflicts of Interest
SB is a cofounder of CareLoop Health Ltd, a spin-out company from the University of Manchester that develops and markets digital therapeutics for schizophrenia and a digital screening app for postnatal depression. All other authors declare no conflicts of interest.
References
- Hert MD, Correll CU, Bobes J, et al. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry. Feb 2011;10(1):52-77. [CrossRef] [Medline]
- Hjorthøj C, Stürup AE, McGrath JJ, Nordentoft M. Years of potential life lost and life expectancy in schizophrenia: a systematic review and meta-analysis. Lancet Psychiatry. Apr 2017;4(4):295-301. [CrossRef] [Medline]
- Rössler W, Salize HJ, van Os J, Riecher-Rössler A. Size of burden of schizophrenia and psychotic disorders. Eur Neuropsychopharmacol. Aug 2005;15(4):399-409. [CrossRef] [Medline]
- Marshall M, Lewis S, Lockwood A, Drake R, Jones P, Croudace T. Association between duration of untreated psychosis and outcome in cohorts of first-episode patients: a systematic review. Arch Gen Psychiatry. Sep 2005;62(9):975-983. [CrossRef] [Medline]
- Perkins DO, Gu H, Boteva K, Lieberman JA. Relationship between duration of untreated psychosis and outcome in first-episode schizophrenia: a critical review and meta-analysis. Am J Psychiatry. Oct 2005;162(10):1785-1804. [CrossRef] [Medline]
- Sullivan SA, Carroll R, Peters TJ, et al. Duration of untreated psychosis and clinical outcomes of first episode psychosis: an observational and an instrumental variables analysis. Early Interv Psychiatry. Aug 2019;13(4):841-847. [CrossRef] [Medline]
- Malla A, McGorry P. Early intervention in psychosis in young people: a population and public health perspective. Am J Public Health. Jun 2019;109(S3):S181-S184. [CrossRef] [Medline]
- Srihari VH, Keshavan MS. Early intervention services for schizophrenia: looking back and looking ahead. Schizophr Bull. May 7, 2022;48(3):544-550. [CrossRef] [Medline]
- Csillag C, Nordentoft M, Mizuno M, et al. Early intervention in psychosis: from clinical intervention to health system implementation. Early Interv Psychiatry. Aug 2018;12(4):757-764. [CrossRef] [Medline]
- McGorry PD, Ratheesh A, O’Donoghue B. Early intervention-an implementation challenge for 21st century mental health care. JAMA Psychiatry. Jun 1, 2018;75(6):545-546. [CrossRef] [Medline]
- Torous J, Bucci S, Bell IH, et al. The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry. Oct 2021;20(3):318-335. [CrossRef] [Medline]
- Niendam TA, Loewy R, Savill M, et al. Effect of technology-enhanced screening in addition to standard targeted clinician education on the duration of untreated psychosis: a cluster randomized clinical trial. JAMA Psychiatry. Feb 1, 2023;80(2):119-126. [CrossRef] [Medline]
- Eisner E, Bucci S, Berry N, Emsley R, Barrowclough C, Drake RJ. Feasibility of using a smartphone app to assess early signs, basic symptoms and psychotic symptoms over six months: a preliminary report. Schizophr Res. Jun 2019;208:105-113. [CrossRef] [Medline]
- Lewis S, Ainsworth J, Sanders C, et al. Smartphone-enhanced symptom management in psychosis: open, randomized controlled trial. J Med Internet Res. Aug 13, 2020;22(8):e17019. [CrossRef] [Medline]
- Clarke S, Hanna D, Mulholland C, Shannon C, Urquhart C. A systematic review and meta-analysis of digital health technologies effects on psychotic symptoms in adults with psychosis. Psychosis. Oct 2, 2019;11(4):362-373. [CrossRef]
- Song M, Song YM. Randomized controlled trials of digital mental health interventions on patients with schizophrenia spectrum disorder: a systematic review. Telemed J E Health. Jun 2023;29(6):798-812. [CrossRef] [Medline]
- Alvarez-Jimenez M, Koval P, Schmaal L, et al. The Horyzons project: a randomized controlled trial of a novel online social therapy to maintain treatment effects from specialist first-episode psychosis services. World Psychiatry. Jun 2021;20(2):233-243. [CrossRef] [Medline]
- Freeman D, Lambe S, Kabir T, et al. Automated virtual reality therapy to treat agoraphobic avoidance and distress in patients with psychosis (gameChange): a multicentre, parallel-group, single-blind, randomised, controlled trial in England with mediation and moderation analyses. Lancet Psychiatry. May 2022;9(5):375-388. [CrossRef] [Medline]
- Garety P, Ward T, Emsley R, et al. Effects of slowMo, a blended digital therapy targeting reasoning, on paranoia among people with psychosis: a randomized clinical trial. JAMA Psychiatry. Jul 1, 2021;78(7):714-725. [CrossRef] [Medline]
- Gumley AI, Bradstreet S, Ainsworth J, et al. The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia. Lancet Psychiatry. Jun 2022;9(6):477-486. [CrossRef] [Medline]
- Berry N, Machin M, Ainsworth J, et al. Developing a theory-informed smartphone app for early psychosis: learning points from a multidisciplinary collaboration. Front Psychiatry. 2020;11:602861. [CrossRef] [Medline]
- Bell IH, Thompson A, Valentine L, Adams S, Alvarez-Jimenez M, Nicholas J. Ownership, use of, and interest in digital mental health technologies among clinicians and young people across a spectrum of clinical care needs: cross-sectional survey. JMIR Ment Health. May 11, 2022;9(5):e30716. [CrossRef] [Medline]
- Morton E, Torous J, Murray G, Michalak EE. Using apps for bipolar disorder - an online survey of healthcare provider perspectives and practices. J Psychiatr Res. May 2021;137:22-28. [CrossRef] [Medline]
- Sawyer C, Hassan L, Sainsbury J, et al. Using digital technology to promote physical health in mental healthcare: a sequential mixed‐methods study of clinicians’ views. Early Intervention Psych. Feb 2024;18(2):140-152. [CrossRef]
- Zhang X, Lewis S, Chen X, Berry N, Bucci S. Mental health professionals views and the impact of COVID-19 pandemic on implementing digital mental health in China: a nationwide survey study. Internet Interv. Dec 2022;30:100576. [CrossRef] [Medline]
- Kwon S, Firth J, Joshi D, Torous J. Accessibility and availability of smartphone apps for schizophrenia. Schizophr. Nov 16, 2022;8(1):98. [CrossRef]
- Kinoshita S, Cortright K, Crawford A, et al. Changes in telepsychiatry regulations during the COVID-19 pandemic: 17 countries and regions’ approaches to an evolving healthcare landscape. Psychol Med. Oct 2022;52(13):2606-2613. [CrossRef]
- Torous J, Jän Myrick K, Rauseo-Ricupero N, Firth J. Digital mental health and COVID-19: using technology today to accelerate the curve on access and quality tomorrow. JMIR Ment Health. Mar 26, 2020;7(3):e18848. [CrossRef] [Medline]
- Kalman JL, Burkhardt G, Samochowiec J, et al. Digitalising mental health care: practical recommendations from the European Psychiatric Association. Eur Psychiatry. Dec 13, 2023;67(1):e4. [CrossRef] [Medline]
- The EPA survey on digitalization: status quo and expectations of telepsychiatry in the member states of the European Psychiatric Association. European Psychiatric Association. 2022. URL: https://www.europsy.net/app/uploads/2023/05/EPA-Survey-on-Digitalization_NPAs.pdf [Accessed 2025-03-10]
- Bucci S, Barrowclough C, Ainsworth J, et al. Actissist: proof-of-concept trial of a theory-driven digital intervention for psychosis. Schizophr Bull. Aug 20, 2018;44(5):1070-1080. [CrossRef] [Medline]
- Bucci S, Berry N, Morris R, et al. “They Are Not Hard-to-Reach Clients. We Have Just Got Hard-to-Reach Services.” Staff views of digital health tools in specialist mental health services. Front Psychiatry. 2019;10:344. [CrossRef] [Medline]
- Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. Jul 2019;95:103208. [CrossRef] [Medline]
- Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. Apr 2009;42(2):377-381. [CrossRef] [Medline]
- Qualtrics. 2024. URL: https://www.qualtrics.com [Accessed 2025-03-25]
- The R project for statistical computing. R. 2021. URL: https://www.R-project.org/ [Accessed 2025-03-25]
- QSR International Pty Ltd. NVivo (version 12). 2018. URL: https://lumivero.com/ [Accessed 2022-01-24]
- Smith KA, Blease C, Faurholt-Jepsen M, et al. Digital mental health: challenges and next steps. BMJ Ment Health. Feb 2023;26(1):e300670. [CrossRef]
- Smith KA, Hardy A, Vinnikova A, et al. Digital mental health for schizophrenia and other severe mental illnesses: an international consensus on current challenges and potential solutions. JMIR Ment Health. May 8, 2024;11:e57155. [CrossRef] [Medline]
- Rodriguez-Villa E, Rozatkar AR, Kumar M, et al. Cross cultural and global uses of a digital mental health app: results of focus groups with clinicians, patients and family members in India and the United States. Glob Ment Health (Camb). 2021;8:e30. [CrossRef] [Medline]
- Godoe P, Johansen TS. Understanding adoption of new technologies. J Eur Psychol Stud. 2012;3. [CrossRef]
- Eisner E, Faulkner S, Allan S, et al. Barriers and facilitators of user engagement with digital mental health interventions for people with psychosis or bipolar disorder: systematic review and best-fit framework synthesis. JMIR Ment Health. Jan 20, 2025;12:e65246. [CrossRef] [Medline]
- Odgers CL, Jensen MR. Annual research review: adolescent mental health in the digital age: facts, fears, and future directions. J Child Psychol Psychiatry. Mar 2020;61(3):336-348. [CrossRef] [Medline]
- Valkenburg PM, Meier A, Beyens I. Social media use and its impact on adolescent mental health: an umbrella review of the evidence. Curr Opin Psychol. Apr 2022;44:58-68. [CrossRef] [Medline]
- Ben-Zeev D, Scherer EA, Gottlieb JD, et al. mHealth for schizophrenia: patient engagement with a mobile phone intervention following hospital discharge. JMIR Ment Health. Jul 27, 2016;3(3):e34. [CrossRef] [Medline]
- Bonet L, Torous J, Arce D, Blanquer I, Sanjuan J. ReMindCare app for early psychosis: pragmatic real world intervention and usability study. JMIR Mhealth Uhealth. Nov 6, 2020;8(11):e22997. [CrossRef] [Medline]
- Allan S, Ward T, Eisner E, et al. Adverse events reporting in digital interventions evaluations for psychosis: a systematic literature search and individual level content analysis of adverse event reports. Schizophr Bull. Nov 8, 2024;50(6):1436-1455. [CrossRef] [Medline]
- Eisner E, Richardson C, Thomas N, et al. Measurement of adverse events in studies of digital health interventions for psychosis: guidance and recommendations based on a literature search and framework analysis of standard operating procedures. Schizophr Bull. Nov 8, 2024;50(6):1456-1470. [CrossRef] [Medline]
- Sounderajah V, Clarke J, Yalamanchili S, et al. A national survey assessing public readiness for digital health strategies against COVID-19 within the United Kingdom. Sci Rep. Mar 16, 2021;11(1). [CrossRef]
- Sheehan R, Dalton-Locke C, Ali A, Vera San Juan N, Totsika V, Hassiotis A. Effects of the COVID-19 pandemic on mental healthcare and services: results of a UK survey of front-line staff working with people with intellectual disability and/or autism. BJPsych Bull. Aug 2022;46(4):201-207. [CrossRef]
- Appleton R, Williams J, Vera San Juan N, et al. Implementation, adoption, and perceptions of telemental health during the COVID-19 pandemic: systematic review. J Med Internet Res. Dec 9, 2021;23(12):e31746. [CrossRef] [Medline]
- Witteveen AB, Young S, Cuijpers P, et al. Remote mental health care interventions during the COVID-19 pandemic: an umbrella review. Behav Res Ther. Dec 2022;159:104226. [CrossRef] [Medline]
- Hughes G, Moore L, Maniatopoulos G, et al. Theorising the shift to video consulting in the UK during the COVID-19 pandemic: analysis of a mixed methods study using practice theory. Soc Sci Med. Oct 2022;311:115368. [CrossRef] [Medline]
- Rogan J, Bucci S, Firth J. Health care professionals’ views on the use of passive sensing, AI, and machine learning in mental health care: systematic review with meta-synthesis. JMIR Ment Health. Jan 23, 2024;11:e49577. [CrossRef] [Medline]
- Torous J. Hybrid and virtual care: interest outstrips infrastructure. NEJM Catalyst. Jan 15, 2025;6(2). [CrossRef]
Abbreviations
| DHT: digital health technology |
| EIS: early intervention services |
| NHS: National Health Service |
| NIHR: National Institute for Health and Care Research |
| REDCap: Research Electronic Data Capture |
Edited by John Torous; submitted 04.11.24; peer-reviewed by Bryan Hartzler, Wilson Tumuhimbise; final revised version received 27.01.25; accepted 30.01.25; published 31.03.25.
Copyright© Xiaolong Zhang, Natalie Berry, Daniela Di Basilio, Cara Richardson, Emily Eisner, Sandra Bucci. Originally published in JMIR Mental Health (https://mental.jmir.org), 31.3.2025.
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