Detect-S: an mHealth application to assist health professionals to identify suicide risk in hospitalized patients

Abstract Introduction Suicide is a serious public health problem that affects the whole world. This study describes development of the prototype for an mHealth application (app) intended to assist healthcare professionals to identify suicide risk in hospitalized patients and reports on testing of the app by some of these professionals, conducted to confirm its functionality. Method This is applied exploratory research into use of Information Technology within the healthcare field, based on application prototyping for mobile devices. The research was conducted at the Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA) from 2017 to 2019. Six healthcare professionals, one data scientist, and three undergraduate students in Biomedical Informatics took part in the study. All research participants signed the free and informed consent form. Results The main findings show that the development team created a prototype named Detect-S, which became a cross-platform application (iOS and Android) offering 16 functions. Conclusion It can be concluded that Detect-S has the potential to be a positive technological instrument that can be tested in a hospital setting to assist healthcare professionals to identify and manage patients with at risk of suicide.


Introduction
Suicide is understood as intentional and conscious self-inflicted actions intended to result in death. 1 In turn, suicidality refers to a wider concept that comprises various aspects of suicidal behavior, such as thinking of dying or killing oneself, suicidal plans, attempts, and completion of suicide. 2 Approximately 800 thousand people die each year all over the globe due to this phenomenon, which represents one death every 35 seconds. 3 In 2012, suicide accounted for 1.4% of all deaths in the world, being the 15th most common cause of death among the general population and the 2nd most common among people between 15 and 29 years old. 4 The complexity of suicidality and its multiple causative factors may result in suicide being attempted in different environments, both private and public, and even inside hospitals. 5 When suicide happens in a hospital setting, it does not solely impact on the victim and their family but also, and inevitably, on the healthcare professionals routinely active in that individual's care -since these professionals are prone to facing such situations in the course of their jobs. 6 Suicide episodes among hospitalized patients may also lead healthcare professionals to develop burnout syndrome and even depression, which cause higher rates of both absenteeism and presenteeism. 7 However, even within a relatively controlled environment -as it is intended that hospitals should be -suicide is still difficult to prevent. Therefore, earlier identification of suicide ideation among hospitalized patients is also a key factor for preserving healthcare professionals' mental health, while enabling effective preventative interventions targeting suicidal attempts and their outcomes.
Technological advances can contribute to clinical assessment of patients at risk of suicide. These technological aspects may contribute to improving the care provided by healthcare professionals to their patients. A variety of software and applications are being used to help with diagnosis of diseases and to improve people's health. In this context, an application to assist with the early identification of suicide risk among hospitalized patients was developed.
Software is classified as an 'intangible' product, in which the main input is knowledge applied by specialized professionals and in which creativity and intellectual capacity allow development of adequate solutions for specific objectives. Its main feature is its flexibility, which has been incorporated into applications adapted to the needs of information management. 8 Use of new technologies in the health field (e.g. mobile platforms) may contribute to making access to information simpler and more dynamic, 9 allowing its applicability in a variety of settings and situations. The term "mobile-health" or "mHealth" was created by the professionals were asked to test the application in order to verify its functionality.

Type of study
The study design is applied exploratory research investigating use of Information Technology in healthcare.
The method employed was application prototyping for mobile devices. The systems development life cycle was used to develop the mobile app, which means that a series of phases were used, such as: requirement definition, analysis, design, development, testing, and prototyping. 10 A new score scale for suicide risk assessment was created in order to be incorporated into the software.
It is intended that the score will be tested in loco using the app, in a process that will be described in a future article. In this paper, besides the prototyping process, development of the new score scale will also be briefly described.

Setting
The prototype was developed and tested at Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), between 2017 and 2019.

Participants
The following participants took part in this research:

Suicidality Detection Score Scale (Detect-S)
First, we conducted a systematic literature review, 11 based on Prisma principles, 12 with the objective of identifying the most cited instruments for suicide risk assessment in the literature. scale, which is a more complete instrument and will be tested in the hospital environment by health professionals using mobile devices. That application will be described in a future article, with the objective of verifying whether Detect-S constitutes an instrument that is applicable in hospital settings and comparing it with instruments already used in hospitals to assess suicide. The Detect-S scale questionnaire was adapted to be used as an application for mobile devices.
The software resulting from the Detect-S scale was installed on the healthcare professionals'/researchers' mobile devices (cell phones or tablets) to evaluate its functionality, in order to obtain views and opinions that would be different from the developers'.
In the app, after suicidality and suicide risk have been assessed using the Detect-S scale, alerts are displayed on the screen indicating the priority for intervention for the patient assessed. Intervention priorities are coded using the same colors used in the Manchester Triage System (MTS) 15 : no risk -blue, low risk -green, moderate risk -yellow, and high risk -red.

Development of the Detect-S mHealth Application
The stages of development of the prototype will be presented below.

Functional) and analysis
The functional requirements (RF) incorporated into the application are listed in Table 1.
A few non-functional requirements (RNF) are also listed in Table 2.

Application development
The Ionic Cordova programming framework was used to develop the project. This program enables quick development, creation of a clear and functional design, and use of cross-platforms apps based on a single source

Outcomes
Some interfaces linked to provision of the functional requirements presented in Table 1 are described in this section, corresponding to the prototype developed.

Welcome interface
The 'home' interface contains the following

Patients interface
The 'patients list' interface lists all individuals who have been added and either have already answered or will answer the questionnaire. The professional using the app can expand patient information for each name by clicking on the 'access' option. This screen also provides the 'add new patient' (+ symbol) option, which enables the professional to access the 'register new patient' interface. This interface covers functional requirements RF1 and RF4.

Professional interface
The 'professional' interface shows details of each professional registered on the system. The name of the professional whose information is being accessed is shown on the upper part of the interface. This encompasses functional requirement RF14.

Questionnaire interface
The 'questionnaire' interface is made available after a professional has been linked to the application. This  Figure 1 shows all of the application interfaces.

Prototype trial by the developers
The prototype developers were: 1 Psychiatrist,  Table 3. Table 3 showed that 4 out of 6 (67%) healthcare professionals who used the Detect-S app considered its use was excellent; 3 out of 6 (50%) thought the design

RNF01
Safely store data on the device to be analyzed later.

RNF02
The software interface must have graphical elements displayed with wide dimensions and clear symbols, to minimize the risk of mistakes and misunderstanding. Usability

RNF03
The system will be accessible through an offline application.

RNF04
The system will respond appropriately. Its interface must be adaptable to different interface sizes.

RNF05
The prototype will have satisfactory performance to reduce awkward situations for users.
Performance RNF = non-functional requirements.  was excellent; 3 out of 6 (50%) said the questions were excellent; 4 out of 6 (67%) classified its sensitivity as excellent; 2 out of 6 (33%) rated its specificity as excellent, and 3 out of 6 (50%) rated the product's reliability as excellent.
One MHealth technologies are constantly present in the daily lives of healthcare professionals. 18 Therefore, creation and development of this prototype tends to add value to this healthcare context.

Discussion
Based on the results obtained in this study, the Detect-S app is considered to be a promising tool to enhance the healthcare professionals' practice, especially in hospital settings.
There are also other apps: Samaritans Radar, developed by the charity organization Samaritans for Twitter users, warns if an individual who follows a profile on the site intends to commit suicide. The Samaritans Radar software uses an algorithm for detecting keywords and phrases that signal this state, such as "tired of being alone," "I hate myself," "depressed," "help me," and "I need to talk to someone." Users who have signed up to participate in the initiative will receive an email alert when someone makes this type of statement. 19 Another application used is ADDS -Support for the

Future prospects
It is intended that the Detect-S scale will be validated and the Detect-S app tested in a hospital setting in a future article, in which the app will be used to assess risk of suicide with the scale. This is expected to assist healthcare professionals to customize care for the patients according to messages and suggestions displayed by the software after scores have been calculated.
It is hoped that this study will inspire further research and creation of other products to help healthcare professionals with their practice in relation to suicide and suicidality, emphasizing the importance of mHealth technologies in this context.

Conclusion
This application can be considered an innovative and technological solution to help healthcare professionals detect suicide risk among hospitalized patients early.
This mHealth prototype was sent to the Innovations As a future prospect, now that the application is complete, administration of Detect-S in hospitalized patients will be addressed in another article.