This paper explores adolescents’ (aged 16‐18 years) perspectives of a new, cocreated stepped digital intervention to support sleep hygiene behaviors and well-being. In-depth qualitative interviews were conducted, focusing particularly on a diverse range of adolescents from across the United Kingdom.

Ethics approval for this study was granted by the North-West–Greater Manchester Central Research Ethics Committee (23/NW/0129). All methods were completed in accordance with applicable guidelines and regulations. Participants were informed about this study’s aims and objectives, procedures, their right to withdraw from this study, and how their data would be stored in line with the General Data Protection Regulation in this study’s information sheet. All participants provided verbal informed consent before taking part in a one-to-one qualitative interview. All data were anonymized, and all identifying information was removed. Only the research team had access to deanonymized data, which was stored on secure password-protected servers in accordance with General Data Protection Regulation requirements. In compensation for their time, interview participants were offered a digital voucher of £40 (US $53.93), which was financed through this study’s budget.

Adolescents aged 16‐18 years were recruited to a nonrandomized feasibility trial carried out in collaboration with 33 schools and colleges from across the United Kingdom. Participants were invited to participate if they were aged between 16 and 18 years and owned a smartphone. Those receiving treatment for insomnia or a diagnosed mental health condition were excluded from this study, as they were receiving treatment. Participating schools and colleges received a “welcome pack” on enrolling in this study, featuring a study poster, a digital presentation explaining this study, staff and student information videos, and a document outlining the most effective ways to recruit students. Participants could express their interest in taking part by scanning a QR code or by following a direct link on the poster, presentation, or videos to the participant information sheet and consent form.

On initial sign-up to this study, and at 6 and 12 weeks, participants completed several quantitative measures to assess their levels of insomnia, anxiety, and depression; the Insomnia Severity Index [57-59], and the Hospital Anxiety and Depression Scale [60] or Revised Child Anxiety and Depression Scale [61], for users aged younger than 16 years. These findings are explored in our later papers in this series. Details of the recruitment of participants to the nonrandomized feasibility trial can be found in Multimedia Appendix 1. The focus of this paper is on the qualitative interviews conducted as part of this study, namely participants’ feedback on their use of the cocreated Sleep Solved app.

For the interviews, purposive sampling was used to better reach underserved populations in research. All those who had expressed an interest in being interviewed were purposively sampled based on ethnicity and levels of socioeconomic deprivation. The levels of deprivation were estimated by comparing contributors’ postcodes to the 2019 English indices of deprivation, a relative measure of deprivation for small areas (lower-layer super output areas [LSOAs]) [15,62,63]. To ensure that adolescents from ethnically diverse and disadvantaged backgrounds were well represented, involvement of participants from diverse ethnicities and more socioeconomically disadvantaged areas was prioritized for participant interviews.

Interview participants provided written consent to take part in a one-on-one interview using televideo software. Participants were allocated a unique identification number, and the data were anonymized, whereby all identifying information was removed. Participants were informed about the purpose of this study, the benefits and possible downsides of participating, the apps, what would be required of them, how their data would be stored, and who was funding the research, and had the opportunity to ask questions. Talking with the research team about this study in a one-to-one interview was entirely optional, and only those who consented to be contacted about an interview and for the interview to be recorded were invited to participate. Participants were reminded that they could stop participating at any time, without giving a reason. Names and corresponding identification numbers and consent forms were kept separately and securely on a password-protected server.

A semistructured interview topic guide was used to guide discussions, developed by members of the research team (SEB, MHJ, GT-E, PK, LY, and RM). Open-ended questions explored participants’ reasons for participating, sleep experiences before and after trying the apps offered, as well as their knowledge of sleep hygiene advice and any experiences of sleep advice. Participants were asked about app use, app content, use of social support, and whether they were likely or not to continue to use the app. To ensure relevance of the questions to adolescents, they were further refined after the first 10 interviews for clarity and to capture any new factors. A relationship with participants was not established before the commencement of this study.

Interviews were carried out by televideo between November 2023 and April 2025 by 5 women members of the research team: SEB, GML, PK, SC, and MHJ. All had prior training in and experience of conducting in-depth qualitative interviews. As the team conducting the qualitative interviews was all women, this may have influenced both data collection and analysis. Being of the same shared gender as many of our participants might have influenced rapport, particularly when discussing behaviors around sleep experiences. In line with the approach by Braun and Clarke [64] to inductive thematic analysis, possible biases were considered throughout data collection and analysis, through ongoing group discussion and reflection. Interviews were conducted on televideo, enabling participants to see the characteristics of the interviewer. Interviews were recorded using televideo software, transcribed verbatim, anonymized, and checked for correctness. Each participant was assigned a participant information number. Data collection concluded at 63 interviews, where no additional factors were identified from the data, and a rich awareness of the issues raised had been achieved [65].

Qualitative analysis was conducted iteratively by 3 women members of the research team (SEB, GML, and SC) using a pragmatic inductive thematic analysis approach, a method to identify, analyze, and report patterns within qualitative data [64]. NVivo (version 14; Lumivero), a qualitative data analysis management software, was used to manage the data [65]. All 3 coders had prior training in thematic analysis, coding, advanced use of NVivo software [65], and qualitative research methods. The codes, which were inductively derived from the data by each researcher, rather than any preexisting framework, were combined to form themes, and this process continued until a series of overarching themes or key findings were recognized. Preliminary results and a thematic map were shared and discussed with the wider research team to further refine the themes identified [64]. Any disagreements were discussed with a fourth member of the research team, who has substantial coding and qualitative research experience, in order to achieve thematic validity. Data saturation was considered to have been realized when no further aspects were identified from the data [65]. This was achieved at 55 interviews and continued to 63 participant interviews to ensure that no new ideas were introduced. These results have been reported in line with COREQ (Consolidated Criteria for Reporting Qualitative Research) reporting guidelines (see Checklist 1) [66].

This paper aimed to explore adolescents’ views, expectations, and experiences of Sleep Solved, with a particular focus on members of the underserved populations that it was intended to benefit. The positive experiences of and engagement with Sleep Solved described by this sample of adolescent participants were encouraging, and many reported substantial benefits for their mood and sleep. The methods recommended in the Sleep Solved sleep hacks, including regular sleep and wake times [69], getting up after 20 minutes if unable to sleep (thereby reducing the amount of time spent in bed) [70], progressive muscle relaxation [71,72], and mindfulness meditation [73], are all evidence-based sleep behavior change techniques that have been successfully used in adult populations. From these results, it is clear that Sleep Solved has the potential to be effective in adolescent, underserved, and low SES populations.

Low SES has been linked to significantly poorer user engagement with mHealth apps, including those that target health behaviors [13,33,34]. Most of those interviewed from low SES or underserved groups joined as they experienced poor or irregular sleep. As some had not heard of Sleep Solved or its potential benefits, they were motivated to take part by recommendations from close friends or college staff. The need for trusted authority figures to refer those who may need it to the Sleep Solved app is an important finding, as adolescents experiencing poor sleep or mental health may not always be aware of supportive interventions, or seek them out themselves [74,75]. People are substantially more likely to engage in a digital health intervention when it is recommended to them by a recognized authority figure, such as a trusted friend, health professional, or the government [76-78]. Considering this, and the need for underserved and low SES adolescents to be well supported into the intervention, future referral pathways for Sleep Solved would benefit from being promoted by an authority figure or trusted peer. Research has shown that participants who hold positive expectations about an mHealth intervention are more likely to find the intervention effective and engage more in using the app [79]. Therefore, the need for the potential benefits of Sleep Solved to be framed positively will be crucial for any future rollout.

Overall, the challenges faced by participants from low SES and underserved populations, such as the potential for low literacy levels, lower English language skills, poor reading comprehension, or low health literacy, were well met by the Sleep Solved app. Participants appreciated the accessible, science-based information provided by Sleep Solved, with praise for its readability and ease of understanding. Great care was taken to make Sleep Solved as accessible as possible to users from underserved groups, particularly those with lower literacy levels and lower health literacy [15,16]. Similar research with underserved groups has found that users with low literacy skills can struggle to understand some of the language used in online interventions, even text perceived as “simple” by the research team [80], highlighting the need for effective coproduction at all stages of the research project [15,16]. These efforts to make the app more inclusive, understandable, and easy to use have the added benefit of improving the usability of the app for all participants, not just those who may have difficulties with reading or understanding [80].

The “sleep hacks” provided by Sleep Solved were seen as being more legitimate and trustworthy than the sleep advice they had seen on social media platforms. How adolescents trust health information on social media can be complex [81,82], with many placing more belief in health-related information from legitimate websites, compared to social media or networking sites [82]. Participants in this study also spoke of learning about sleep and sleep-related advice on social media platforms. The quality of health-related information on social media apps used by adolescents in this study is low [83,84]. As promotional materials for the current study made clear that it was being conducted as university research, this may have influenced participants’ positive perceptions of the Sleep Solved app. The advice in Sleep Solved might have therefore been seen as more trustworthy [74], removing the need for users to continuously appraise and monitor the accuracy, relevance, and credibility of the information presented to them.

Gamification, the chance to collect Sleep Stars when using Sleep Solved, was also a popular motivating feature of the app, encouraging friendly competition between users. The results from Sleep Solved are similar to prior research in the area of sleep apps. For example, adolescents using the Sleep Ninja app can work toward a black belt in sleep at the end of a 6-week program [75], whereas users who meet their sleep and wake-up time goals in the Sleep Town app could collect a variety of buildings and coins [76]. Engaging in gamification can enhance feelings of reward and accomplishment when achieving a target behavior, such as keeping to a regular sleep schedule [76,77]. However, much of the existing research in this area is based on the experiences of adults, raising questions about the degree of applicability to adolescents [69]. Factors relating to adolescent sleep discussed previously, such as later circadian rhythms, social pressures, examination stress, and the readiness of phone use, may require more targeted adaptation to better meet the needs of adolescents. Gamification, including engaging in social comparison, rewards, and challenges, may be more engaging, motivating, and interesting for adolescents, but this can vary, and feedback from the adolescents who will be the target users of the app is essential [85-87].

Social relatedness is also an important factor in popular sleep hygiene game designs, such as the use of friending, social prodding, and group quests [88]. While social relatedness was not used directly as a game design feature in Sleep Solved, interviewed participants spoke of a degree of social competitiveness and requested a leaderboard and the ability to form friendship groups in future iterations of the app. In addition, adolescents have previously expressed a preference for gamified elements; self-tracking behaviors that reward progress toward their goals, increasing their motivation to engage with the app and regularly track their progress [78].

Changes to behavior and health, such as those promoted by our Sleep Solved cocreated sleep intervention, can potentially lead to “ripple effects”: outcomes relating to the intervention that were not an explicit goal of the intervention, but that can have a positive impact [89,90]. These positive ripple effects can extend beyond participants themselves to their familial and social domains [89-92]. In addition to their own use of Sleep Solved, participants spoke of sharing the app and the sleep advice contained within with others who had difficulties sleeping, such as family members or friends. This included social connections who would not have met the initial age range (14‐18 y) or inclusion criteria for this study. As numerous participants had observed helpful effects from Sleep Solved, they described sharing the app with others who they felt could benefit from getting better sleep and from following the sleep hacks recommended in the program. Successful social diffusion of mHealth apps has also been seen in other interventions, such as in apps for HIV protection [93]. These findings mirror participants’ recommendations to widen the availability of Sleep Solved, from being available to those aged 14‐18 years to older and younger participants. Other apps that address maladaptive sleep behaviors, such as SHUTi, have been successfully cocreated and culturally tailored to be inclusive and relevant to a range of demographic groups, including American adults [51], Black women [94], those with caring responsibilities [95], older adults [95], and adolescents in the United Kingdom [15].

Although this study took great care to purposively sample adolescents from a variety of ages, genders, ethnicities, and levels of socioeconomic deprivation, our findings will not be reflective of all UK adolescents’ experiences. Although we purposively sampled interviewees who had not engaged with the app, people who had more positive experiences and views of the app will have been more likely to agree to be interviewed. For this reason, while the encouraging views expressed by many of our interviewees provide an indication of the benefits it can provide, particularly for adolescents from underserved and low SES populations, these findings cannot be used to generalize or estimate the likely benefits at a population level. In addition, the reported benefits of the app are subjective; the duration of participants’ sleep was not objectively measured during this study, instead relying on self-reported changes in sleep behavior over time. Future work could mitigate the effects of these limitations. For example, a large randomized controlled trial would mitigate the effects of self-selection bias by randomly selecting participants to take part in the intervention, potentially engaging with users who had fewer positive experiences or who did not engage with the Sleep Solved app. Future mixed methods results, exploring both quantitative and qualitative data, would enable any patterns to be investigated in greater depth.

Many participants expressed a desire to continue using Sleep Solved in the future, even beyond the end of this research study. User enthusiasm for the Sleep Solved app, and participants reporting positive promotion of Sleep Solved to friends and family members, was an unexpected but encouraging finding. Future iterations of Sleep Solved could potentially be tailored to different age ranges, such as versions for children, young adults, or older adults.

This study of Sleep Solved and wider Sleep Well intervention has shown promising results in a varied range of underserved and ethnically diverse adolescents with sleep difficulties from across the United Kingdom. Sleep Solved was perceived as easy to use, with interesting and appealing content that was easy to read and understand. The adaptation of the app for users with low literacy or low health literacy was a well-received and novel finding, highlighting the ability of mHealth apps to be better designed for diverse and underserved populations in research.

Cocreated features of the app, including the science-based sleep hacks and Sleep Stars gamified rewards system, were well-liked by participants, enabling them to better understand the science behind the recommendations and track their progress toward their goals. Participants may require the encouragement of authority figures to take part in Sleep Well, as they may not be aware of or seek out support for their sleep or mental health difficulties. The potential benefits and helpfulness of the app will need to be highlighted for any future implementation in order for participants to form positive expectations about Sleep Solved. Future work, adapting the Sleep Solved app to different age ranges or cultures, inclusion in adolescent health initiatives, or United Kingdom–wide scalable public health strategies may also extend the usefulness of the app, such as rollout across schools, colleges, universities, or inclusion in National Health Service digital health support programs.