A total of 21 college-aged adults with a history of a trauma exposure that resulted in a hospital visit participated in the study. Participants were 19 years old (mean [SD] 18.8 [0.87]), and the majority were female (16/21, 76%) and White (15/21, 71%). All participants owned a smartphone, primarily iPhones (15/21, 71%). Participants all texted, took pictures, listened to music, downloaded apps, recorded videos, and accessed the Internet on their phones. A majority used their devices to obtain information about physical health (17/21, 81%) and mental health (14/21, 67%). All participants provided verbal consent as the Institutional Review Board did not require written consent. Consent was recorded using a required documentation form.

A development team with expertise in mobile app development, database creation, acute trauma care, and post-trauma mental health care created a prototype app. Design was guided by the Technology Acceptance Model (TAM) [27], which posits that adoption and continued use of software is a function of perceived usefulness and perceived ease of use. Perceived usefulness is the extent that a technology will increase the likelihood of a given outcome. Applied to the current problem, monitoring may improve the likelihood that an individual receives mental health care after a trauma. Perceived ease of use is the extent that minimal effort is needed to use the technology.

A distributed system comprising several major software components was created (Figure 1). The patient-facing component is a mobile app that administers self-report assessments. The system also includes a database and a Web interface for care providers. The Web interface allows providers to manipulate patient data (add new patients, view existing patients, obtain reports of responses provided by patients) and manipulate questions (create, edit, and delete). Creation and modification of questions can be done quickly and efficiently with a series of menus and text fields through the Web portal. Notifications can be assigned to alert the patient to complete an assessment at a specific time or randomly within a pre-specified interval [28]. Notifications are automatically pushed to the mobile app. The following areas were prioritized during the development process.

Standardized tasks took place within a laboratory. To standardize the use of the app, participants were read a script describing a motor vehicle accident that required immediate and sustained medical attention. They were told that this app was being given to them to monitor their recovery after they left the hospital and they were asked to complete a set of self-report assessments in the coming weeks. Participants used the app a total of 5 times, each time progressing further in their recovery. Trained research assistants observed the participants during their interaction with the app and interactions were recorded with a usability mounted camera [31]. They then completed a brief qualitative interview to assess their thoughts on using the app. Videos were reviewed to identify user interaction errors, defined as errors made by the user due to the interface. These include tapping an icon that is not a responsive icon or being unable to determine how to complete a specific task. The university’s Institutional Review Board approved all procedures.

A clinical psychologist analyzed the qualitative data. A constructivist grounded theory approach was used in which comments and interviews were reviewed multiple times, coded, and primary themes were extracted. Themes that were present for more than three cases were retained. Themes that were present in three or fewer cases were reviewed, merged with other themes, or discarded. Coding and thematic analyses were conducted after each wave to determine the point at which saturation had been obtained and when no new bugs were identified. A hierarchical structure in which themes were evaluated as representing perceived usefulness or perceived ease of use was then evaluated to determine the extent that the qualitative data corresponded to the quantitative data. Several passes of the data determined that this structure represented the data well. Matrix analyses combined the quantitative data from the PUEU and the qualitative data from the interview. Triangulation of the mixed-method yielded a high degree of overlap across the quantitative and qualitative data, which adds validity to the conclusions drawn from the qualitative analysis.

Ratings of overall perceived usefulness according to the PUEU suggested that participants thought a mobile monitoring system would be useful in improving post-trauma recovery (mean [SD] 5.14 [1.10]). Participants reported the app would facilitate communication with their provider (mean [SD] 5.81 [1.17]). A substantial portion (11/21, 52%) reported that this app would improve communication above and beyond traditional follow-up methods in the qualitative interview. Participants requested two-way communication with their provider through the app (12/21, 57%). That is, they wanted a provider to give feedback, but the type varied. A portion wanted personalized feedback (6/21, 29%), whereas others preferred a notification that the doctor received or viewed their responses (12/21, 57%). Several (3/21, 14%) recommended the app list contact information for a provider. Last, several participants (5/21, 24%) reported that reminders for intervention (eg, take medication, complete physical therapy) would be helpful.

Participants rated the app as moderately likely to improve their recovery from the traumatic event (mean [SD] 4.42 [1.43]) and thought it would be useful after a trauma (mean [SD] 5.19 [1.47]). A majority thought a monitoring system would be helpful (13/21, 62%), with a portion stating it would indicate their provider cared about their recovery (4/21, 19%). However, several participants voiced concerns that this app would replace face-to-face provider contact (2/21, 10%).

Overall ratings suggested the app was easy to use (mean [SD] 5.92 [1.05]; mean calculated out of 7), easy to learn to use (mean [SD] 6.38 [0.97]), and it would be easy to become skillful with the app (mean [SD] 6.19 [0.98]). Qualitative responses were supportive of these data. Nearly all (19/21, 90%) reported the app was easy to use and they enjoyed the simplicity of the design. Several found the design calming and engaging (5/21, 24%). A substantial majority reported assessments took minimal time to complete and would impose minimal burden (17/21, 81%). Indeed, participants reported they would be willing to answer mean (SD) 2.86 (1.85) question sets per day, mean (SD) 4.90 (2.41) days per week.

Participants had several recommendations to enhance the design and features of the app. Half (11/21, 52%) suggested that personalizing the app would be helpful. Specific recommendations included changing colors, setting backgrounds, and personalizing the question content. Personalized content involved using specific details about the individual (eg, name) and questions about their trauma (eg, “how is the pain in your left leg?”). Second, it was recommended that each question have a free text response option to clarify ratings (7/21, 33%).

Participants reported they wanted the app to provide feedback, including a graph of their responses (10/21, 48%). Participants wanted to receive positive feedback that informed them of areas where they were improving and did not wish to be notified if symptoms were worsening (8/21, 38%). Rather, they preferred that worsening outcomes be reported to their provider and the provider contact them.

The current study obtained important information about user preferences for a monitoring system for mental health symptoms following a trauma. Participants preferred an app that was easy to use, would not impose a significant burden, and was customizable. The findings are consistent with the TAM [27]. Prior work with websites for health care have also shown that ease of use is correlated with sustained use [32]. The app was focused on a single purpose, obtaining self-report data, which allowed participants to respond to 7 questions in less than 30 seconds on average and showed increased willingness to use the app for a sustained period. The speed with which individuals were able to respond suggests that longer question sets are likely to impose minimal burden. Difficulty providing responses may undermine the utility of mobile monitoring apps [33].

Participants were moderately positive that a mobile monitoring app would help their recovery. This is consistent with evidence suggesting that monitoring is helpful in reducing symptoms of PTSD [34] and that interactions via SMS after a trauma are perceived as helpful [35]. To increase perceived helpfulness, participants should be given a rationale as to the benefit of monitoring. In addition, participants should be told how their data will be used if no other feedback mechanism is available.

A key theme was the importance of providing feedback. Participants were unanimous in their request to interact with their provider through the app rather than as a one-way communication tool. Most users wanted immediate feedback from their provider after completing an assessment. An immediate response, however, would be challenging given the burden this would impose on a provider [12]. Rather, a two-tiered feedback method is recommended. The first would involve an immediate response. This could include a graph of responses, positive praise for completing the assessment, or notification that their provider will review their responses. More patient-specific responses may become feasible as the computational power of mobile devices increases. That is, devices may be able to generate a specific response to a patient based on their answers with a more powerful mobile device. The second type of feedback would involve provider interaction at a later point, such as a phone call or session. Interactions with providers should explicitly highlight that the data obtained from the mobile app triggered this contact. Additional work is needed to determine how to best tailor this feedback and use these data in clinical practice.

A related theme was the personalization of the app to the needs of the patient. Personalized feedback is highly relevant to outcomes and sustained use [36,37]. Advanced analytic methods, such as machine learning, may be especially well suited to provide personalized feedback. These methods can use the large quantities of data generated by these apps to provide specific feedback to an individual [38]. For example, a patient with poor sleep, increased arousal, increased pain, and a prescription for narcotic pain medicine may be at risk for substance abuse. The system could use these data to provide very specific questions or information to the individual about their medication use. Such information would then facilitate care interactions. Relatedly, this ability to tailor question content should specifically address the traumatic event that the participant experienced. Rather than using generic language, it would likely be beneficial to ask targeted questions about specific symptoms, injuries, or events that reference the participant’s experience. Such an approach will assure the participant that this app is tailored to their needs. When implemented successfully, this strategy would improve the efficiency and quality of care for patients in settings with considerable clinical demands, such as the emergency department. As an example, a recent study used mobile telehealth to monitor healing after surgery [39]. The system allowed physicians to monitor healing, provide targeted feedback, and eliminate unnecessary follow-up appointments for those healing as expected while spending more time with those who had complications.

Participants provided two areas of caution. First, participants wanted automated feedback to be positive and preferred that negative outcomes trigger a provider touchpoint. Within the context of TAM, it is possible that negative feedback may diminish the perceived usefulness of an app. Those who are not recovering likely do not want feedback reinforcing their lack of progress but rather want intervention. Alternatively, providing positive feedback about their progress may be perceived as encouraging and supportive. Second, participants cautioned that such monitoring systems should not replace interpersonal care. It is unclear if this concern could be addressed by providing a more personalized experience, such as telehealth or telephone sessions, or additional contact from their provider. Wound care after surgery using telehealth reduced the need for in-person follow-ups, which was preferred by patients [39].

Our conclusions should be considered within the context of several limitations. The sample size for the current study was within the recommended size for usability studies [40] but is still relatively small. The current study was conducted within a laboratory setting with patients who had a trauma history but were not currently dealing with the repercussions of their event. As such, the ecological validity of the current study is limited [26]. Additional usability and feasibility testing is needed with a sample of patients who have recently experienced a traumatic event. Such studies should coincide with validation studies in which responses to the surveys administered via the mobile platform are compared with responses to a gold-standard measure. The majority of the participants in the current study were young, White, female, iPhone-owners, which may limit the generalizability of the findings to other populations. Indeed, recent work has highlighted the ethnic, racial, and economic diversity of patients in an acute setting [15], such that evaluation across a more diverse group of participants is warranted. Finally, the current study focused primarily on the use of a mobile app by patients. The current framework, however, involves a provider dashboard that displays results, allows providers to create and edit question sets, and reviews their patient priorities. Additional usability testing is needed to evaluate this component.

The results of this study provide several points of feedback to advance modern methods for monitoring mental health recovery after a trauma. The need for personalized feedback, the type of feedback provided, and how patients view such a system has broad implications for other conditions. These recommendations should guide the refinement of current systems and the development of new strategies that leverage novel technology. Although technology changes rapidly, the principles obtained from this study and related projects are applicable to systems that address mental health. Such work is essential to the development of systems that will be used by patients to improve outcomes.