Mobile Mental Health Applications
Smartphone-based psychological interventions give mental health professionals a unique opportunity to expand the availability and quality of mental health care provision to the wider population. A World Health Organization (WHO) survey of 15,000 mobile health applications reported that 29% of them focussed specifically on mental health issues – mainly treatment, crisis intervention, prevention, diagnosis, and post-treatment patient control (Chandrashekar, 2018).
When compared to traditional therapy, mental health applications (MHapps) offer a cost-effective and scalable solution for treating psychological problems and psychiatric disorders. Moreover, a 2010 survey showed that up to 76% of respondents reacted positively to the opportunity to monitor mental health using MHapps, but only if the application was free (Proudfoot et al., 2010). MHapps can reduce some other barriers associated with traditional therapy (discomfort in new situations, stigma connected to mental health problems) and offer an alternative to individual therapy or group sessions (Kovandžić et al., 2011).
This relatively new fusion of mobile application technology and psychological interventions has showed promising results in alleviating symptoms of depression and anxiety (Bakker et al., 2018; Firth et al., 2017a; Firth et al., 2017b; Ly et al., 2015), schizophrenia (Ben-Zeev et.al., 2014; Firth & Torous, 2015), and borderline personality disorder (Rizvi et al., 2011). Additionally, these applications offer alternative ways to enhance mindfulness (Howells, Ivtzan, & Eiora-Orosa, 2014), self-awareness (Morris et al., 2010), and a positive body perception associated with self-worth (Rodgers et al., 2018). Despite mobile applications being effective in treating psychological problems, the academic research mostly focuses on the features and usability of MHapps.
Qualitative studies often focus on user recommendations about technical aspects of MHapps. These insights are mostly tied to barriers (Peng et al., 2016), ease of use (Alqahtani & Orji, 2020), accessibility (Marshall, Dunstan, & Bartik, 2019), psychoeducation (Zhang et al., 2019), personalization (Peng et al., 2016), tracking and monitoring (Widnall et al., 2020), credibility - research-based and safe interventions (Alqahtani & Orji, 2020), goal setting (Chiauzzi, & Newell, 2019), reminders (Widnall et al., 2020), privacy, and esthetics (Schueller et al., 2018). Interestingly, similar conclusions could be found in studies of clinical patients with different diagnoses. Bipolar disorders subjects praised helpful content, supportive environment, and ease of use, psychoeducation, including daily routine (goal settings), sleep control (tracking), social aspects (community), avoidance of stimuli, and insight into illness (psychoeducation) (Nicholas, et al., 2017; Switsers et al., 2018). Moreover, similar themes emerged in a study of physicians, and their patients with depression (Patoz et al., 2021).
The results from qualitative studies often serve as a basis for theoretical frameworks and guidelines for mental health app development. For example, Chandrashekar (2018) reviewed wide variety of studies dealing with MHapps and recommended focussing on four areas of development when designing an MHapp: (1) High patient engagement, (2) Simple UI and UX, (3) transdiagnostic capabilities, and (4) self-monitoring features. Engagement can be improved by employing real-time engagement, notifications, and gamified interactions. Simple UI and UX can be achieved through the use of pictures rather than text, short sentences, and inclusive language, which reduce users’ cognitive load. Transdiagnostic apps may help to raise treatment efficacy by reducing the need to interact with multiple apps. Lastly, self-monitoring of moods, thoughts, behaviors, or actions has been shown to improve emotional self-awareness and, as a result, ease anxiety, depression, and substance abuse symptoms.
Similarly, Gorini et al. (2018) developed the P5 approach to MHapps design, which is predictive, personalized, preventive, participatory, and psycho-cognitive. Here predictive refers to data collection on the patient’s current psychological state. Personalization is achieved through tailoring the application to the patient’s individual characteristics. Prevention is about long-term patient monitoring and the ability to provide timely preventive interventions when needed. It is participatory in the sense that the users are active decision-makers who can benefit from patient-doctor and peer communication features. Finally, it is psycho-cognitive in the sense that the personalization is based on the patient’s psychological characteristics, cognitive abilities, and life experiences.
Recommendations by Gorini et al. (2018) and Chandrashekar (2018) stem from numbers of previous studies and literature reviews of academic papers focused on MHapps in combination with mobile applications (e.g. Bakker et al., 2016). Most of the empirical studies and theoretical models focus on the technical aspect of mobile applications. Unfortunately, they fail to report experiences' and the impact on the life of individuals on an emotional, behavioral, and cognitive level. Understanding individual experiences is crucial when accessing the impact of Mhapps on its users as they might have positive, but also negative consequences for its users. Current study to fill this science gap and analyze MHapps experience more deeply from a psychological perspective. Participants were and asked about the type of the application, functionality, recommendations for future app development, but added the layer of a more psychological perspective – the impact on life (emotional, cognitive, and behavioral). The specific questions targeted at emotions, cognitions, and behaviours are based on the previous study assessing the effectiveness of an intervention (Halamova et al., 2018).