Abstract
Keywords
Introduction
During the COVID-19 pandemic, educational institutions were shut down worldwide, which impacted over 60% of students and caused a massive disruption of the education system. 1 Studies conducted since the outbreak of the pandemic uncovered a significant elevation of COVID-19-related anxiety among students in European countries.2–6 The COVID19 pandemic is anticipated to result in long-term adverse mental health effects on the population 7 ; therefore, there is an urgent need to support students’ psychological resilience. Psychological resilience refers to adapting successfully in the face of stress or adversity, 8 overcoming daily challenges, coping with stress, and achieving goals despite obstacles. 9 Psychological resilience is an important life skill that remains highly relevant in the post-pandemic era.
Pusey et al. 10 recently reported that interactive technologies could deliver effective resilience interventions in an accessible, cost-effective, and flexible manner. Their scoping review included several types of interactive technologies used in resilience interventions, such as serious video games, virtual reality simulations, social robots, and commercial off-the-shelf video games. Their scoping review did not include mobile applications. However, mobile devices and associated software applications are fast becoming an integral part of health care, if for no other reasons than advantages of access, convenience, and cost.11,12
Mobile applications and medical smartphone apps are being extensively used in the health domain.13,14 As their potential usage scenarios in healthcare continue to expand, there is a concomitant need for open, accessible, and scalable digital tools, as are smartphone mental health apps. 15 According to a recent systematic review of digital mental health interventions 14 smartphone-based interventions were the second most common technology studied in articles included in the review, reported in 27.4% (57/208) of the articles. The focus of mobile health applications seems to be on health behavior change in physical activity, 16 diet, and drug and alcohol use rather than mental health. 17 According to a review conducted by Milne-Ives et al., 18 mental health seems to be the topic receiving the least attention. It is also important to note that most studies on operational mobile mental health apps address major mental health issues while prevention and well-being areas are underdeveloped. 19
A literature review revealed several attempts to develop and validate resilience apps within the last five years; most efforts target adults belonging to specific professional groups.7,20–23 For example, some resilience apps targeted mental health care providers for reducing burnout 21 and, more recently, to support their mental health in the COVID-19 era. 7 Other apps targeted users with significant depression symptoms 23 or targeted military personnel, veterans, and civilian first responders. 22 Only two resilience apps were identified in the literature that targeted youth. The first one focused on youth who experienced sexual violence and had adverse childhood experiences8,24 and the second one focused on student veterans with posttraumatic stress disorder (PTSD).25,26 The effectiveness of these resilience apps was promising through small-scale studies21,24,25 and randomized controlled trials.20,23
Previous research suggests that gamification could increase engagement with mobile prevention interventions. 20 Gamification may have a positive motivational effect compared with other self-guided interventions. 27 Gamification was used extensively for mental health,27–29 for example, in stress management applications.17,30–33 However, only a few studies were found that used gamification to improve resilience in a mobile mental health intervention.20,23,34 These studies had positive findings demonstrating effectiveness but did not address a general population.
Fleming et al. 29 showed that it is feasible to translate traditional theory-based and evidence-based interventions into computer gaming formats. However, most mobile health apps do not have strong theoretical foundations. Only a slim minority of developed apps are theory-based. For example, out of 50 unique apps for health behavioral change tested in the Milne-Ives et al. 18 review, only a few explicitly reported the behavioral change techniques (BCTs) incorporated into the app. None of the resilience apps identified in the literature refers to behavioral change techniques, even though some refer to psychoeducational components20,34 and emotion regulation. 8
In recent years, research interest focused on tools for objectively measuring activity-related parameters and promoting health-related outcomes. 35 The role of the Internet of Things (IoT) is becoming increasingly important in an individual's daily activities. Users have engaged actively with IoT technology through various end-user devices. Smartphones can be used in an IoT setup along with different application categories, one of which is “Personal IoT” where we find an increasing number of applications targeting health and fitness, and helping to solve everyday problems for users. 36 The information gathered from the sensors is then used to draw useful conclusions on the user's activities and/or surroundings; such conclusions may lead to providing recommendations to a person (e.g. a slight change to lifestyle, engagement in physical exercise, etc.). Data that can be passively collected from sensors embedded in modern smartphones, (such as native GPS, and accelerometer), allow for new ways to measure psychological health. For example, data on changes in daily physical activity collected with smartphone GPS and accelerometer technology predict mood states before phone users themselves report mood changes.11,37 Adopting IoT technologies for mental health has been slow 38 ; concerning the use of IoT technology to provide objectively measured personalized health data to users, none of the gamified apps on resilience made use of IoT in general or enabled smartphone sensors in particular.
Our study aimed to address the current and anticipated psychological impact of the COVID-19 pandemic on undergraduate students by designing and developing a mental health mobile app. A few resilience-building apps target specific professional groups’ needs.7,20–23 The resilience app described in this study stands out for several reasons.
Methodology
Design of the Student Stress Resilience prototype
The
The core co-design team initially consisted of three members: two undergraduate students and the first author. The core co-design team identified a selection of relevant gamification elements, based on a literature review focusing specifically on the development of smartphone apps for mental health 39 and on interactive technologies to support emotional resilience. 10 These gamification elements included: system recommendations, the use of smartphone sensors, the allocation of points, competition and collaboration among users, reflection, and goal setting.
As a second step, the gamification elements to be embedded in a gamified app for resilience were presented to 18 students (extended co-design team) who took a course on digital games in the fall semester of 2020. These students participated in a two-hour online, recorded participatory design session which took place during one of the course's regular meetings and was coordinated by the first author of the study. These 18 students evaluated the feasibility of the idea of a gamified app for resilience by providing their input individually to avoid the possibility of influencing each other's perspectives. They were invited to provide their suggestions about additional gamification elements and voice their concerns about the design of the proposed app by answering two open-ended questions. 3
Students’ input was used by the core co-design team for designing the prototype of the app in AdobeXD. The following student-provided suggestions were implemented in the prototype of the app: (a) the inclusion of badges, (b) an anonymous leader board to increase competition among users, (c) the allocation of bonus points for the completion or partial completion of goals, (d) including ways to verify goal completion (through using phone sensors), and (e) the inclusion of a daily challenge (in the form of one daily goal) that can be shared. This user-centered design approach helped to better respond to undergraduates’ self-identified needs at a time of repeated lockdowns due to the pandemic. The details of this participatory design study were recently published. 3
Mobile health apps often lack dynamic features that adapt based on users’ responses.
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The

Screenshot of the Student Stress Resilience prototype showing (a) goal setting, (b) self-reported anxiety symptoms for progress monitoring, (c) leaderboard, points, and ability to share progress on social networks, and (d) progress feedback and badges.
The app leverages gamification and intrinsic motivation to engage users. Users are expected to set one goal to focus on daily; the goal may refer to either studying, engaging in physical exercise, or socializing. As Van Roy and Zaman 45 suggested, to support the user's autonomy, a moderate amount of meaningful options should be provided. These researchers suggested providing users with at least one option that is meaningful and complies with their values while avoiding placing them in a dilemma by offering too many options. 45 Following this gamification heuristic, which is based on self-determination theory the design choice of offering one out of three possible goals to users was made. To support the user's feelings of competence, goals are manageable and perceived as feasible to fulfill. 45 Examples of manageable goals refer to at least 30 min of focused work on a specific assignment (for the goal of studying) or at least 30 min of walking (for the goal of physical exercise) or interacting with three people outside of the household in one day (for the goal of socializing).
Users can monitor their progress in reaching each goal by employing sensors for objective measurements and self-reflecting on their performance at the end of the day. They receive points and badges for completing challenges. To support users’ relatedness, social interaction is facilitated 45 through the users' ability to share their progress with other users. As a first stage what will be shared is a brief text outlining the goal that was achieved, for example, “I’ve completed my physical exercise goal in the SSResilience app.” Sharing results on social media for joint experiences and allowing for social pressure is expected to motivate users. 46
As shown in Figure 1, in the Student Stress Resilience app, five out of eight gamification elements, as defined by Tondello et al., 47 were implemented to increase engagement and acceptability: (1) socialization, including social comparison, competition, leaderboards, and a connection with social networks (Figure 1(c)), (2) risk/reward, through the use of challenges, (3) customization, through the use of points (Figure 1(c)), (4) progression, through progress feedback (Figure 1(d)) on each one of three goals that can be set daily (studying, physical exercise, or socialization), and (5) incentives, through the use of badges (Figure 1(d)).
The design of the SSResilience app is theory-based, as nine behavioral change techniques, as defined by Milne-Ives et al., 18 were used: (a) action planning, (b) feedback on outcomes of behavior, (c) self-monitoring of behavior through reflection, (d) social support, (e) social comparison, (f) prompts/cues, (g) achievements, and (h) incentives.
Mobile health apps often feature dense sections of psychoeducational text that are perceived as not useful.
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As Connolly et al.
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caution: “Mental health researchers are attempting to squeeze complex behavioral therapies into patients’ pockets without adapting them to an app context, and it is often not working.” To overcome this limitation, the app provides specific, brief, and accessible recommendations and resources, including psychological health information from the World Health Organization, to its users using minimal text. An example of psychological health tips is the following: The World Health Organization recommends
1. Know that it is okay to feel how you are feeling, it is normal to experience feelings of sadness, frustration, stress.
2. Maintain a routine: start your day at about the same time each day.
3. Practice good sleep hygiene of 7–9 hours per night.
4. Connect with others by engaging in regular calls with friends and family.
The app also offers other more generic features as it generates reminders at a time chosen by the user to engage, and logs past app use. Overall, it provides a simple and intuitive interface that facilitates interactions, as suggested by Bakker et al. 39
Research questions
The study examined the
The two research questions of the study were:
- RQ1: How do students evaluate the feasibility and acceptance of the - RQ2: How do students evaluate the usability of the
Participants, data collection, and ethical issues
Participants were recruited from the authors’ social and professional networks, and they were asked to voluntarily participate in the study if they satisfied two criteria: (a) they were adults (older than 18 years old) and (b) they had an undergraduate student status. Twenty undergraduate students were invited to participate as part of a class taught by the first author (convenience sampling). The response rate was 100% in the sense that all students who attended the class participated in the study. A total of 60 participants were individually invited by the second author (convenience sampling) who had a student status at the time and contacted his peers who were attending either his university or one of four different universities at the time the research study took place. University affiliation was established because the second author knew the participating students personally. Out of these 60 students, 54 responded positively. Therefore, the response rate for the second author was 90%.
In the first stage of the study, students were informed in writing about the study's objective. The study was conducted according to the World Medical Association Declaration of Helsinki. The study followed American Psychological Association (APA) ethical standards and General Data Protection Regulation (EU) 2016/679 (GDPR) guidelines, and its protocol is in accordance with the University Ethics Committee and with the country's National Bioethics Committee (Approval number: EEBK EΠ 2021.01.218). It meets ethical guidelines, including adherence to the legal requirements of the country where the study was conducted. Participants provided their consent online by selecting boxes indicating that they are adults (older than 18 years old), understand the study's objective, and voluntarily provide anonymous data. At the second stage of the study, participants were asked to follow a link that led them to a working prototype of
Data sources
The questionnaire consisted of a total of 29 questions. Ten of these questions were related to the feasibility and acceptance of the application's design (RQ1), and another 10 were related to its usability evaluation (RQ2). For evaluating feasibility and acceptance an instrument was developed specifically for the needs of this study and it was not validated. For evaluating usability, a highly robust instrument was used (System Usability Scale). 48
The remaining questions were basic demographic questions examining age, gender, previous use of health apps, and frequency of use of health apps. Lastly, a question was included that indicated participants’ interest in trying the application when it would be fully developed.
Feasibility and acceptance were evaluated by asking participants to indicate how useful each specific function of the app would be for supporting resilience. The following question was used: “To what extent do you think the following design functions of the app are useful for supporting resilience during the COVID19 pandemic? Resilience is our ability to manage challenges (e.g., social distancing measures/lockdowns) adaptively.” Participants were asked to evaluate the usefulness of 10 app functions that are shown in Table 1 (in the second column “App functionality”), using a 5-point Likert scale ranging (1 = not at all useful, 2 = slightly useful, 3 = somewhat useful, 4 = very useful, 5 = extremely useful) after testing the app to familiarize themselves with each demonstrated functionality.
Feasibility and acceptance of 10 characteristics of app functionality for supporting resilience.
*NPA: Net Percent Agreement (composite score of 4 = “very useful” and 5 = “extremely useful”).
The usability evaluation was conducted using the System Usability Scale (SUS), 48 a methodology frequently used to evaluate medical apps. 49 SUS was chosen because (a) it is a highly robust and versatile tool for usability professionals, 50 and (b) it allows the comparison of similar systems. The scale included the following 10 items, with responses graded by a 5-point Likert scale ranging from completely disagree to completely agree (Figure 2).

System usability scale (SUS) for the
Data analysis
To analyze the first research question (RQ1), which focused on feasibility and acceptance, descriptive statistics (frequencies, percentages, Mean, SD) were run for all 10 app functions (see Table 1, column “App functions”) separately and using a composite score. A Net Percent Agreement (NPA) was calculated, which consisted of the composite score of participants’ answers of 4 = very useful and 5 = extremely useful.
For the analysis of the second research question (RQ2), which focused on usability, the procedure for calculating usability evaluation scores proposed by the author of the instrument SUS was followed. 48 Specifically, for odd-numbered items, one was subtracted from the user response. For even-numbered items, the user responses were subtracted from 5. This scaled all values from 0 to 4 (with four being the most positive response). The converted responses for each user were added up, and the total was multiplied by 2.5. This converted the range of possible values from 0 to 100 instead of 0 to 40. An average SUS score was calculated for all participants. The SUS score was then converted into a percentile rank and a letter grade from A to F, according to the norms proposed by Sauro. 51
Results
Demographic data
A total of 74 adult participants (44 male and 30 female) with an average age of 22 years old (
RQ1 feasibility and acceptance of the Student Stress Resilience prototype
Regarding the evaluation of
The lowest score was reported for the use of IoT as an objective way to measure and monitor progress, specifically the functionality that refers to the use of a sound sensor (
The vast majority of participants (93.2%, 69/74) stated that they would be interested in trying the application when it is completed, a finding that shows high acceptability. A statistically significant, moderate positive correlation (Pearson's
A statistically significant positive correlation was also found between the overall feasibility evaluation of
Additional analyses were run to examine trends with respect to potential in-group comparisons concerning gender and whether participants were current users of health apps. Concerning gender comparisons, there were no significant differences with respect to the feasibility evaluation of
RQ2 usability evaluation of the Student Stress Resilience prototype
The SUS was utilized to evaluate the application's usability. To provide an answer to RQ2, the average scores of the SUS scale provided by 74 students were calculated. The app received a satisfactory usability score. The raw average SUS score was 72.9, which is in the 70% percentile rank, corresponding to the category “B” of the scale, a result that shows a satisfactory degree of usability.
Figure 3 shows how the percentile ranks (

The raw average system usability scale (SUS) score of the Student Stress Resilience prototype, based on a sample of 74 participants.
Females evaluated the usability of the app (
Discussion
This study described the design of
Previous research suggests that gamification, turning intervention content into a game format, is effective in increasing user intention to use mHealth apps, 52 especially in the healthy and younger groups. 53 Mobile apps using gamification can be a valuable and effective platform for well-being and mental health interventions and may enhance motivation and reduce attrition. 20 Framed as games, apps become potentially powerful tools to promote well-being. 23 Gamified smartphone-based self-help programs and prevention and early-stage mobile interventions for supporting resilience have shown to be effective and engaging for mental health at least for the resilience of significantly depressed individuals 23 of men 34 and of young professionals. 20 The SSResilience app stands out due to its targeted nature, in that it is a gamified mobile prevention intervention addressed to and designed for use by a nonclinical undergraduate student population.
Nowadays, different sensors and IoT devices can readily be used to passively collect various health data—including physical activity, social interaction, sleep, and mobility patterns—and make inferences about mental and physical health.18,54 The potential of using IoT in the context of mental health applications has been hardly harnessed. 38 The IoT promises many benefits to streamlining and enhancing health care delivery to proactively predict health issues. 55 As Kelly et al. 55 noted, IoT can improve the accessibility of preventative public health services but this is still in theory. The smartphone is considered to be at the heart of a growing universe of connected devices and sensors. 36 In this study, the focus was on smartphones which have impressive sensing and processing capabilities that make them an ideal tool for collecting data. This study attempted to take advantage of IoT capabilities that are easily accessible by utilizing smartphone-based sensors in a prevention intervention for a mental health issue.
Mobile applications using smartphone sensors to provide personalized data have been connected with behavioral change, but there is insufficient empirical evidence to verify this connection. The Milne-Ives et al. 18 review found little evidence of changed behavior or health outcomes due to the use of mobile health apps. As Abedtash and Holden 35 put it, it seems that “devices alone or with minimal behavioral change support are insufficient to change health-related outcomes.” This further reinforces the importance of designing evidence-based apps with strong theoretical foundations to examine their impact on adopting and maintaining healthy behaviors. As Hoffmann et al. 30 noted, app designers do not exploit the potential of combining gamification techniques with behavior change theory. The proposed resilience app combines gamification techniques with behavior change theory and IoT functionality and addresses gaps identified in the literature.
The study attempted to examine the feasibility and acceptability of the
Some studies on mental health apps indicate that smartphone devices are a promising self-management tool for mental health, specifically for reducing symptoms of depression57,58 and anxiety. 59 Other studies argue that there remains debate around whether these apps have demonstrated high efficacy 60 and that their effectiveness and potential for sustained use remain uncertain. 40 Developing and evaluating a functional resilience app will shed light on this debate.
Some implications for the design of gamified environments for health can be drawn from this study. The user experience has to be sought and evaluated during the design and development phase of gamified apps with participants representative of the target audience, as shown by Nicolaidou et al. 3 Prototypes of gamified apps that may not be fully functional have to be pilot tested in their targeted environment with their targeted audience to examine feasibility and acceptance of the idea before engaging in full development. This may significantly impact financial investments and reduce the cost of developing features that the targeted audience may not need or value. Integrating IoT technology in gamified apps for health seems to be a promising approach as it may provide data that can be valuable for several stakeholders, including (a) the users themselves, as they can receive personalized recommendations based on their data and changing trends over time, (b) app developers, as they can potentially use these data for app improvement, and (c) researchers, as they can use these data to understand better which behavior change techniques may positively impact user behavior more effectively and efficiently.
Limitations
The study had several limitations. The study did not include testing with a functional app, its sample was small and it was reached using convenience sampling rather than random sampling. The instrument that was used for evaluating the app's feasibility and acceptance was developed specifically for the needs of this study and it was not validated. Participants were self-selected, and only quantitative data were collected to evaluate the prototype's feasibility, acceptance, and usability. These limitations are expected to be addressed in future work.
Future work
Given the study's small sample size with self-selected participants and no testing with a functional app, further investigations can focus on developing a fully functional app followed by a randomized controlled trial. As the evidence base is still uncertain regarding the effectiveness and usability of mobile health apps,
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our future studies will involve users in interacting with the app to evaluate its efficacy. As the overwhelming majority of participants in this study expressed an interest in trying out a functional app, a larger group of interested participants is expected to participate in future studies. Participating students can be divided into experimental and control groups to investigate how their resilience scores change, measured with a validated resilience scale (e.g. CD-RISC)
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when they use the
Findings from trials and user reviews of some commercially available programs suggest that applied gaming approaches can be engaging; however, many analyses do not report engagement or ongoing use.
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Findings of Connolly's et al.
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narrative review that aimed at understanding factors influencing sustained use of mental health apps suggest that for apps to be successful, they must be advantageous over alternative tools, relatively easy to navigate, and aligned with users’ needs, skills, and resources. The proposed
