Facilitating In-House Mobile App Development Within Psychiatric Outpatient Services for Patients Diagnosed With Borderline Personality Disorder: Rapid Application Development Approach

BACKGROUND

Mobile app development within mental health is often time- and resource-consuming, challenging the development of mobile apps for psychiatry. There is a continuum of software development methods ranging from linear (waterfall model) to continuous adaption (Scrum). Rapid application development (RAD) is a model that so far has not been applied to psychiatric settings and may have some advantages over other models.

OBJECTIVE

This study aims to explore the utility of the RAD model in developing a mobile app for patients with borderline personality disorder (BPD) in a psychiatric outpatient setting.

METHODS

The 4 phases of the RAD model: (1) requirements planning, (2) user design, (3) construction, and (4) cutover, were applied to develop a mobile app within psychiatric outpatient services for patients diagnosed with BPD.

RESULTS

For the requirements planning phase, a short time frame was selected to minimize the time between product conceptualization and access within a clinical setting. Evidenced-based interactive content already developed was provided by current staff to enhance usability and trustworthiness. For the user design phase, activity with video themes and a discrete number of functions were used to improve the app functionality and graphical user interface. For the construction phase, close collaboration between clinicians, researchers, and software developers yielded a fully functional, in-house-developed app ready to be tested in clinical practice. For the cutover phase, the mobile app was tested successfully with a small number (n=5) of patients with a BPD.

CONCLUSIONS

The RAD model could be meaningfully applied in a psychiatric setting to develop an app for BPD within a relatively short time period from conceptualization to implementation in the clinic. Short time frames and identifying a limited number of stakeholders with relevant skills in-house facilitated the use of this model. Despite some limitations, RAD could be a useful model in the development of apps for clinical populations to enable development and access to evidence-based technology.

Do you Feel it? The Relationship Between the Perceived Team Climate for Innovations and the Experience of Flow and Worry

This paper examines the relationship between the perceived team climate for innovations and the experience of flow and worry and the moderating effect of team size. The research contains a multi-organization dataset with 323 software product development team members. The results show that the perceived climate for innovation is significantly positively related to the experience of flow and worry. However, the findings did not support the moderation with no differences in working in smaller or larger teams. This study indicates that the perceived climate for innovations positively relates to positive and negative individual effects without the importance of team size.

Toward an Economically Optimal Team Design in IT-Related Innovation Projects

Driven by the increased relevance of digitalised and hypercompetitive business environments, companies need to focus on IT-related innovation projects (ITIPs) to guarantee long-term success. Although prior research has illustrated that an appropriate team design can increase project performance, an approach for determining the economically optimal team design from an ex ante perspective is missing. Against this backdrop, we follow analytical modelling research and develop a model that determines the optimal team design for an ITIP by transferring central findings of previous research regarding relevant influencing factors, e.g., team size and academic background diversity, into an ex ante economic evaluation. Thereby, our model allows the comparison of different team designs (i.e., team compositions) with regard to the prospective monetary project performance. Generally, the results show that only about a fifth of the random team designs resulted in a positive profit. In contrast, the well-founded, optimal team designs proposed by our model led to a positive profit in almost 90% of all cases. Regarding the influencing parameters, we observe that team size is the most important factor since a deviation from the optimum has a much more significant effect on the expected profit than do other factors such as work experience. To ensure the real-world fidelity and applicability of our model, we discuss the underlying assumptions with two practitioners. Our contribution is manifold: Inter alia, from an academic perspective, we enhance existing research on team design by converting well-accepted qualitative findings from a frequently investigated field outside business administration (i.e., [social] psychology) into a quantitative model that allows for the ex ante economic evaluation of team design parameters. For practitioners, we provide a model that assists managers in designing ITIP teams that are more likely to deliver desired results. This model enables managers to avoid relying only on gut feeling when designing ITIP teams, as is currently often the case due to a lack of alternative approaches.