Development and pre-evaluation of a “diagnurse” mobile app to support nurses in clinical diagnosis using the addie model

ABSTRACT Healthcare workers are increasingly utilising cutting-edge technology, including mobile apps, to enhance patient health care and ensure efficient professional performance. The aim

of this study was to design, develop and evaluate an educational mobile app dedicated towards being employed by nursing students and practicing nurses to support the clinical assessment of a

patient’s health condition in nursing care. In order to develop the mobile app, the Analysis, Design, Development, Implementation and Evaluation (ADDIE) model was employed. Between 2022 and

2023, a “Diagnostic Nurse” mobile app was developed in the “Android Application Package (APK).” The app’s usability was tested in the laboratory by 20 participants. Three methods were

employed in the study, that is, an eye-tracking technique, a qualitative evaluation and a quantitative evaluation. According to the System Usability Scale (SUS), the app test score for the

nursing student group was assessed as 83.3 ± 8.9, and for the practicing nursing group, this was 84 ± 12.7. These results indicate that the mobile app’s is highly usable. The app received

high ratings in the “user-friendliness”, “ease-of-use”, and “user satisfaction” categories. The “DiagNurse” app makes it easier to learn how to conduct a clinical assessment of a patient’s

condition in nursing care, resulting in better information acquisition, assessment accuracy and speed. Given the low cost of the app development and the ADDIE model on which it is based, the

app may be beneficial to nursing students, practicing nurses and other health-care professionals and students. SIMILAR CONTENT BEING VIEWED BY OTHERS USABILITY OF A MOBILE APPLICATION FOR

HEALTH PROFESSIONALS IN HOME CARE SERVICES: A USER-CENTERED APPROACH Article Open access 14 February 2023 MOBILE APP VALIDATION: A DIGITAL HEALTH SCORECARD APPROACH Article Open access 15

July 2021 MOBILE DEVICE USE AMONG EMERGENCY DEPARTMENT HEALTHCARE PROFESSIONALS: PREVALENCE, UTILIZATION AND ATTITUDES Article Open access 21 January 2021 INTRODUCTION In order to enhance

patient care, the global healthcare environment is increasingly utilising cutting-edge technology, such as mobile apps1. As a result of the growth of the Internet and the widespread use of

smartphones, numerous educational programs can be accessed through mobile apps2. Hence, many apps have been developed and made available for educational and therapeutic healthcare purposes.

Mobile apps can be used at any time and in any place, thus allowing users to quickly and easily access the required information, and at the same time, enhancing engagement and participation

in the app’s content3. A user simply needs to have an app-enabled smartphone to install an app. It is estimated that over 318,500 health-related mobile apps are launched globally each year,

and this figure is increasing year by year4. Several mobile apps for nurses and nursing students have been developed in recent years. The main aim of educational health-related apps is to

support self-care in patients with chronic diseases conditions like diabetes or hypertension5,6or to help nursing students or practice nurses gain knowledge and skills in clinical settings7.

The majority of these apps are developed on a large scale without an expert evaluation or demonstration of the step-by-step development stages. Adu et al.8stress that there is a knowledge

gap in the current literature regarding the development and design processes of health apps for smartphones, which raises a question about how to use the app effectively. Usability testing,

which is a key part of the application development process, is crucial9. A well-designed and highly usable app has a positive impact on users’ engagement10, whereas a poorly usable app has a

negative impact on efficiency and customer engagement11. Recent studies have shown that there are benefits to applying mobile technology to support nursing students learning and to enhance

their clinical competencies12. Studies reveal that students’ clinical decision-making and patient care abilities are improved when readily available electronic resources are accessed on

mobile devices13, and that using mobile technology amplifies nursing students’ learning and performance in clinical settings14. According to one study, mobile devices equipped with a

literature search function assisted students in a nursing research theory class in engaging with the material by organising course ideas and facilitating discussion with their peers15.

O’Connor et al.16 particularly demonstrated that using mobile devices speeds up self-regulated learning and boosts learning motivation among nursing students. In this study, the students

utilized tablets and smartphones with educational apps installed that provided them with access to medical dictionaries, medication guides, calculators and other tools during their clinical

training. Thanks to these tools, the students were able to increase their knowledge and confidence while simultaneously reducing their anxiety levels regarding their clinical experience. Lee

et al.17 carried out a systematic review on mobile technology use in nursing education. The research results suggest that having access to clinical and pharmacological information through

mobile devices improves student performance within clinical settings. In addition, having access to smartphone apps may boost not only the clinical knowledge and skills of nursing students,

but also their motivation and satisfaction. In turn, Gallegos et al.18 demonstrated that students perceive the use of mobile technology as a way to minimize off-task activities, enhance

communication with teachers and peers, solve problems in the classes, and gain skills and confidence related to their education and development. Patient health assessment is of key

importance in providing effective, accurate and safe nursing care in clinical settings. Direct health assessment, i.e., a detailed and comprehensive medical history taking and physical

examination, is one component of the conceptual and theoretical framework for evaluating patient’s health. The other component is indirect health assessment, which is the integration of

various parameters and indicators using measurement scales in the determination of the patient’s physical, mental and social state in order to diagnose disorders within these areas and

support clinical decision-making19. One of the key competencies is the ability to fully assess a patient’s condition, since a lack of this skill or a misjudgment may result in a failure to

recognise a patient’s health deterioration or to take the appropriate nursing actions, thus endangering that patient’s safety and severely affecting his or her health20,21. However, due to

the complexity and variability of health situations in different patient groups, performing a thorough patient health assessment can be difficult for students and inexperienced nurses22.

Therefore, in order to fully ascertain the patient’s health condition, the nurse should be equipped with appropriate measuring instrumentation, as measurements without standardised

assessment tools are based on subjective evaluations. Standardised measurement tools, in contrast to intuitive processes, can provide objectivity, quantification, communication, and have a

positive relationship with economic factors23. Measurement-based care in nursing entails administering scales on a systematic basis to assess symptoms and reported complaints, and then using

the results to make effective clinical decisions. A systematic review of fifty-one publications from randomised and controlled trials revealed that utilizing structured scales (with good

psychometric properties) to evaluate symptoms reported by patients while tracking treatment and care led to noticeably greater improvements in the clinical state of the patients. In

addition, measurement-based care may be implemented on a large scale and is widely accepted by both patients and healthcare providers24. It is important, however, that such measurement tools

should be universal and versatile in order to truly determine both the patient’s health condition and their surrounding environment. In long-term care, quality tools like these enable

healthcare workers, including nurses, to evaluate the effects of their interventions in terms of disease management, care outcomes, as well as long-term patient functioning25. This paper

aims to describe the process of developing the “Diagnostic Nurse” educational mobile app for practicing nurses and nursing students using the ADDIE (Analyse, Design, Develop, Implement,

Evaluate) model. METHODS DESIGN AND STAGES Between August 2022 and December 2023, tutors and nursing students that are also members of the Student Research Association at the Department of

Family and Geriatric Nursing, Faculty of Health Sciences, Medical University, Lublin, Poland, developed and pre-evaluated the “Diagnostic Nurse” mobile app (“DiagNurse”). With regard to this

endeavour, the Ministry of Science and Higher Education provided co-financing as part of the „Studenckie koła naukowe tworzą innowacje” program [“_Student research groups create

innovations_”], which allowed the project to be implemented (contract number: SKN/SP/535770/2022). The ADDIE (Analyse, Design, Develop, Implement, Evaluate) model was employed to develop the

“DiagNurse” educational mobile app. The ADDIE model is a tried-and-true method for transferring information in adult learning that is applied to create multimedia instructional content26.

The model is used to implement educational tools in a systematic manner27. It should be noted that the ADDIE model is not strictly based on a step-by-step linear sequence, with various steps

comprising each phase. When individual stages are completed, the subsequent phase begins. Figure 1 shows the application of the ADDIE model in the development of the ‘Diagnostic Nurse’

mobile app. The ADDIE model was selected since it gives the opportunity for several design revisions and allows each stage to be developed thoroughly. MOBILE APP DEVELOPMENT PROCESS

ACCORDING TO THE ADDIE MODEL PHASE 1: ANALYSIS (A) A patient-centred and user-centred approach was adopted during the analysis phase of the mobile app design28. The adoption of a patient-

and user-centred approach to technology design is undoubtedly an important factor in increasing the likelihood of a match between people and technology29. Patient-centred care coordination

involves not only centring the coordinated process around the preferences, needs and values of the patient, but also enhancing the patient’s involvement and participation in the coordination

of their care and the care provided by their caretakers. There is a growing trend of mobile apps being offered that are designed to involve patients in various aspects of managing their own

care. However, little research has been conducted to determine how much these apps’ developers use human factor approaches and methodologies during the design, development and assessment

phases. Establishing and ensuring a good fit between the intended users and the technology will result in the app being usable, accessible and useful30. In order to identify potential

solutions that would meet the app’s purpose, a needs analysis and review of current Polish-language mobile apps were carried out to enhance nursing competencies in assessing a patient’s

health condition in clinical diagnosis. The holistic, patient-centred approach takes into account all aspects of holistic patient functioning as determinants of patient assessment in

clinical practice. The phase consisted of three stages: * STAGE A1: REVIEW OF AVAILABLE MOBILE APPS. The Play online store (which provides mobile apps for mobile phones with the Android

operating system) was searched for currently available apps using a search engine and the following keywords: “nurse”, “nursing” and “patient care” and “patient health assessment”, “physical

examination”, “measurement scales”, “patient health assessment scales”. The inclusion criteria were as follows: 1) a Polish language app, 2) Android-available app, 3) a dedicated nursing

mobile app, 4) a mobile health app for patient-centred care. The exclusion criteria were as follows: 1) apps not available in Polish, and 2) apps not aimed at enhancing competences related

to patient care (for instance, nursing calendars). Three authors independently selected mobile apps considered to be of merit and created a list. * STAGE A2: ANALYSIS OF THE EDUCATIONAL

REQUIREMENTS OF THE APPLICATION. Between 16th and 30th August 2022, we held three online meetings on the MS TEEMS platform with two nursing university teachers, three nursing academics,

several practicing nurses and nine nursing students from undergraduate and graduate programs. During the meeting, we demonstrated the variety of dedicated nursing apps that are available in

Polish and then we led a discussion. The analysis of the available apps identified in stage A1, and the discussion held thereafter, made it possible to identify the subject area of the apps

and pre-determine their content. A summary was written following each meeting, and the results from the previous session were given before the next meeting began. * STAGE A3: LITERATURE

REVIEW - SEARCHING FOR MEASUREMENT SCALES AND QUESTIONNAIRES.In order to identify measurement scales and questionnaires useful in the assessment of patient’s health condition in nursing

care, the project team (four tutors and nine students) searched for medical research databases and categorised the publications based on the functions and dysfunctions of various human body

systems. The inclusion criteria were as follows: (1) a scale or questionnaire translated into Polish; (2) a scale or questionnaire useful in the assessment of a patient’s health condition

for nursing care; and (3) a scale or questionnaire helpful for nurses in light of the applicable Polish nursing laws allowing them to practice as nurses. In accordance with Polish law

regarding nurses’ professional rights, a database of scales, questionnaires and measuring instruments was developed based upon the current literature. These tools are helpful for clinical

patient health assessment, health condition monitoring, care planning, and nursing advice (including online consultation)31. PHASE 2: DESIGN (DS) At this stage, the researchers focused on

the mobile app’s conceptual design, which includes the environment and functions of the app, as well as how well it can meet the needs of nursing students and practicing nurses. They also

selected patient health assessment scales and questionnaires useful for nursing care. The phase consisted of two stages: * STAGE DS1: MOBILE APP STRUCTURE AND FUNCTIONALITY. During this

stage, a conceptual design for the structure and functionality was developed, including the interface layout, main menu and sub-menus. We made an effort to take into account ease-of-use and

good readability when designing the mobile app. Practicing and student nurses and project team members participated in this step, just like in the preceding stage. We also collaborated with

a software engineer and a graphic designer. The mobile app terms and conditions and its logo were created during this stage. * STAGE DS2: SELECTION OF MEASUREMENT SCALES AND QUESTIONNAIRES,

AND THEIR CLASSIFICATION BY ASSESSMENT AREA. All of the collected scales and measurement questionnaires, i.e., a total of 285 instruments, were presented during the first project team

meeting. Following a discussion of each group of scales, a brainstorming session was held to address the arguments for and against the inclusion of individual available assessment tools in

the educational package. A list of all the scales that were included in the database for the mobile app was prepared during the second meeting. PHASE 3: DEVELOPMENT (DV) In collaboration

with the software developer, decisions regarding the operating system, programming language, download and installation process, and privacy policy were made during this phase. The

development phase (phase DV1) lasted from 1st April 2023 to 15th July 2023. PHASE 4: IMPLEMENTATION (I) * STAGE I1: ACCEPTANCE AND RELEASE OF THE MOBILE APP. The software developer team

delivered the developed “Diagnostic Nurse” mobile app during this stage. Following the acceptance of the prototype, the project team uploaded it to google.play as a trial version. Between

15th July and 15th August 2023, the project team conducted a functionality testing of the app prototype. In order to promote the developed mobile app, staff and students of the Faculty of

Health Sciences at the Medical University of Lublin received informational leaflets encouraging them to download and install the app. Information about the location where the app can be

downloaded was also included in the leaflets. In addition, the mobile app was promoted on social media by the Department of Family and Geriatric Nursing students who are also members of the

Student Research Association. PHASE 5: EVALUATION (E) The testing phase is critical to ensuring that the mobile app functions properly and is user-friendly for the target group. There are

two types of evaluation in the ADDIE model, that is formative and summative26. Formative evaluation involves testing the product before it is fully implemented. The “Diagnostic Nurse” mobile

app underwent a formative evaluation that began with the analysis phase and moved through the ADDIE model’s phases, with a separate evaluation procedure for each phase. In contrast, the

summative evaluation included an eye-tracking testing, a qualitative evaluation of the application (focus group interviews), and a quantitative evaluation (questionnaires). * STAGE E1:

INTERFACE TESTING.The eye-tracking technique, which involves tracking the test subjects’ eye movements while using the mobile app, was employed to evaluate the quality of the “DiagNurse” app

interface. The eye tracker records eye movements (saccades), stops (fixation duration), blinks and also the pupil diameter variations over time. Eye-tracking enables determining which

design elements, for how long, and in what order, attract users’ attention. The eye-tracking technique is non-invasive and takes place under normal computer operating conditions. It provides

information about an IT system’s usability that as obtained through user experimentation and statistical post-processing32. Before eye-tracking testing commenced, the following activities

were completed: study participants, i.e., potential users of the application (individuals), and testing scenarios were defined; the testing environment was prepared; the software was

installed on the laboratory equipment; the testing scenarios were verified by experts; and a detailed testing schedule was planned. > The participants were recruited through purposive 

sampling. For the > purpose of sampling, we created a recruitment post on the fan page > of the Student Research Association at the Department of Family and > Geriatric Nursing with

 a link to register participants for the > testing by filling out the online survey. Two research groups took > part in the study: study group 1 (SG1) practicing nurses and study > 

group 2 (SG2) nursing students. The inclusion criteria for the SG1 > group included: (1) a practicing nurse licensed to practice as a > nurse in Poland, (2) a professionally active 

nurse, and (3) informed > consent to participate in the study. The inclusion criteria for the > SG2 group included: (1) a nursing student and (2) informed consent > to participate 

in the study. A total of 22 people registered for the > survey online, but due to the specified time limit, two people opted > out as they had other plans on the survey date and could 

not attend. > A homogeneous user group of six individuals with characteristics > similar to those of potential app users is adequate for usability > testing of the mobile app 

interface. Two research groups > participated in the study: study group 1 (SG1) practicing nurses and > study group 2 (SG2) nursing students. Each group consisted of ten > 

participants to ensure the study’s safety and to improve the > results. >  > For the GS1 study group, the following ways of interaction with the > app were noted: (1) adds a new 

patient and health assessment result, > (2) monitors and assesses the patient’s health condition based on > the recorded examination (examination review). For the GS2 study > group,

 the following ways of interaction with the app were noted: > (1) uses a guide to measurement scales and questionnaires, and (2) > monitors and assesses the patient’s health condition 

based on the > recorded examination (examination review). As a result, the > following testing scenarios were created: (1) adds a new patient and > health assessment results, (2) 

assesses the patient’s health > condition scenario for practicing nurses, (3) uses a guide to > measurement scales and questionnaires and (4) assesses a patient’s > health condition

 scenario for nurses. An exercise scenario was > created in order to acquaint respondents with the survey prior to > their participation. The survey was conducted in the Laboratory of

> Motion Analysis and Ergonomics of Interfaces, Department of Computer > Science, Faculty of Electrical Engineering and Computer Science, > Lublin University of Technology, Lublin, 

Poland. The testing room > was provided with adequate lighting. Every participant was given a > chair with adjustable seat to ensure a correct posture. In addition, > a moderator 

was present during the survey to explain the details to > participants and to ensure that the test was performed properly. The > following equipment was used in the study: MOTOROLA 

Moto G73 5G > smartphone, Pupil Invisible eye-tracking glasses, OnePlus 8 > smartphone recording module, Pupil Cloud online platform and Acer > Nitro 5 AMD laptop. The survey was 

conducted on 26th, 27th, 30th and > 31st October 2023, with five participants per day. * STAGE E2: QUALITATIVE EVALUATION. The focus group interview (FGI) took place immediately after the

eye-tracking testing. DEVELOPMENT OF INTERVIEW QUESTIONS We conducted the FGI interviews based on Breen’s guidelines33. Breen’s guidelines include practical guidance for each stage of the

FGI. In this study, an interview guide was prepared. In doing so, the research team created draft questions based on the literature review and pre-interview discussions. The key interview

questions are summarised in Table 1. INTERVIEW PROCEDURE The interviews were conducted using the following procedure: PREPARATION The FGIs were conducted in a quiet, separated room in the

Laboratory of Motion Analysis and Ergonomics of Interfaces, Department of Computer Science, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Lublin,

Poland. The facilitator, assistant and note-taker arrived in the interview room thirty minutes before the FGI participants’ arrival in order to set up the recording equipment and prepare the

seats. So as to ease the mood and give participants time to take advantage of the proffered food and beverage offerings, prior to the FGI interview, the researchers made these available.

Upon arrival, the participants were given informational sheets by the researchers, who also provided a thorough verbal explanation of the study’s purpose, methodology, as well as data

management and erasure. Following this, the participants were asked to sign a written consent form. Before beginning the discussion, the researchers reviewed the participants’ general

characteristics. The interview was conducted in small groups ranging between four and five persons. This allowed the participants to freely express their opinions and comments. INTRODUCTION

One of the researchers was the moderator of the interviews. Following the moderator’s explanation to the participants that all information collected during the discussion would only be used

for research, upon receipt of their consent to record, a portable recorder was turned on. DISCUSSION In accordance with the prepared interview questions, the moderator introduced the

subjects and created an atmosphere that encouraged open discussion among the participants. The interviews continued until data saturation was achieved (i.e., no new content or statements

were provided), which took about 1–1.5 h. The moderator ensured that every participant had enough time and equal chance to speak during the interview. The facilitator/observer also

encouraged everyone to participate in the interview by using non-verbal communication such as smiling and nodding. WRAP-UP/SUMMARY The content of the interview was checked based on the

responses and the participants could add their own comments. In addition, after the interview, the researchers thanked the participants and informed them that, if necessary, more interviews

would be conducted. DATA ANALYSIS Data was analysed using thematic analysis34 to identify patterns or major themes and to reflect the experiences of the participants. Firstly, one research

assistant transcribed the recorded interviews, and the principal investigator then double-checked the transcription for accuracy. Secondly, in order to fully comprehend the interview

content, the transcripts were read several times, and significant statements (i.e., sentences as the unit of analysis) were highlighted for each key question. Thirdly, the principal

investigator categorised the key content of significant statements/expressions and organised them into larger groups. After having removed repetitions, the researcher restated the statements

in an abstract and generalised manner. Fourthly, the researcher created themes, thematic groups and categories from the structured meanings that were derived from meaningful statements.

Finally, the basic thematic structure was defined by integrating the common elements of the experiments. PREPARATION OF RESEARCHERS The researchers have between 15 and 34 years of clinical

experience in a tertiary hospital and are currently lecturing at a nursing school in Poland. All researchers had completed postgraduate courses on qualitative research, have participated in

numerous conferences and seminars on the subject, and have conducted qualitative research at some point in the past. RIGOUR OF THE STUDY In order to improve the study’s qualitative rigour,

the four criteria proposed by Lincoln and Guba35 were followed: credibility, fittingness, auditability and confirmability. All researchers listened to the recordings multiple times and

compared them with the transcripts to ensure credibility and prevent omissions. If there was any inaccuracy in the transcript, the researcher verified the content with the participant to

assure the credibility of the data. In order to ensure fittingness, we chose participants that were appropriate for the study’s objectives and conducted the FGIs until data saturation was

achieved. With regard to auditability, all researchers conducted a thorough review of the transcripts and analysis to determine the findings’ confirmability. Subsequently, a second

qualitative research expert was tasked with reviewing the study. Confirmability was ensured by recording the entire data collection process and saving the interview recordings and

transcriptions in order to make it possible for any researchers to have access to the data at any time. * STAGE E3: QUANTITATIVE EVALUATION.The author’s questionnaire and a standardised tool

were utilised to conduct a quantitative evaluation. The standardised tool employed in the study was the System Usability Scale (SUS) in Polish36. Borkowska & Jach adapted the SUS scale

into Polish. Their study results show that the scale in Polish has good reliability (Cronbach’s alpha of 0.805) and sufficient validity36. The scale measures the usability of different goods

and services. The advantage of the System Usability Scale (SUS) is that it allows for evaluating a wide variety of products and services, hardware, software or mobile apps37. The

questionnaire includes ten statements (5 positive and 5 negative), and the respondent must rate each statement on a Likert scale ranging from “strongly agree” to “strongly disagree”. Based

on 5,000 individual SUS assessments and 446 study results, Sauro and Lewis38 determined that the value of 68 (± 12.5) is a mean SUS score. Therefore, the expected value of the SUS normal

distribution is 68 (± 12.5). The app’s user friendliness, ease-of-use, and user satisfaction were evaluated by way of use of the author’s questionnaire. In order to assess whether the app is

user-friendly, the participants had to respond to the following statement: “I believe that the app’s user friendliness is”: “terrible”, “poor”, “average”, “good” and “very good”. Then the

respondents had to rate the “difficulty/ease of use of the app” as: “very difficult”, “difficult”, “fairly easy’”, “easy” and “very easy”. In order to gauge user satisfaction, the following

questions were asked: “Are the features provided by the app satisfactory?” The possible answers were: “unsatisfactory”, “problematic”, “difficult to determine”, “satisfactory” and “fully

satisfactory”. Every response received a score between 1 and 5, and the total score for each question was the mean of the surveyed groups. ETHICS APPROVAL The research involving human

subjects was approved by the Bioethics Committee at the Medical University of Lublin (approval number: KE-0254/191/09/2023). The research was carried out in accordance with local law and

institutional requirements. Participating students and practicing nurses gave written informed consent to take part in this study. RESULTS RESULTS OF THE ANALYSIS PHASE RESULTS OF STAGE A1.

A total of 14 mobile apps dedicated to nurses were identified, with the content covering various areas of usefulness in patient care (Table 2). Based upon a review of currently available

mobile apps, it was concluded that there are no apps that enhance nurses’ ability to properly and thoroughly assess a patient’s health condition. In addition, these apps were found to the

aimed at both nurses and other medical professionals, and their content significantly exceeds the competencies of nurses provided for by Polish law. For instance, the “DrWidget CalcMed”

mobile app includes 62 medical calculators for calculating various parameters, whereas the “DrWidget Normy i Skale” mobile app contains 125 tabs that offer guidance for interpreting

laboratory results (70% of all tabs) and scales for assessing a patient’s health condition (30% of all tabs). The review of nurse-specific mobile apps for assessing a patient’s health

condition revealed that a mobile app is required to support nursing students and practicing nurses in evaluating a patient’s condition for nursing care planning. RESULTS OF STAGE A2. An

overview of the needs analysis for the mobile app’s educational scope is presented in Table 3. Following the meetings, it was decided to name the app “Diagnostic Nurse” and include scales

and questionnaires to evaluate patients’ health conditions for clinical assessment and nursing care planning. RESULTS OF STAGE A3. This stage ended with the development of a paper guide

containing 241 patient health assessment scales and questionnaires divided into 21 sections: General patient health assessment, Anthropometric measurement, Pain assessment, Consciousness

assessment, Cardiovascular system, Respiratory system, Gastrointestinal system, Nervous system, Swallowing disorders, Genitourinary system, Musculoskeletal system, Skin, Comprehensive

geriatric assessment, Mental state - well-being assessment, Mental state - stress assessment, Mental state - aggression and anger assessment, Mental state - anxiety and depression

assessment, Mental state - addiction assessment, Mental state - suicide risk, Fatigue, and Professional and family/social status. RESULTS OF THE DESIGN PHASE RESULTS OF STAGE DS1. We started

by creating the logo, user terms and conditions, structure, and features of the mobile app, as well as its login page and main menu (Fig. 2). After having installed and launched the app,

the user must read the terms and conditions. The user must then click the “I agree to the terms and conditions” button to indicate that he or she has accepted them. The user is then

transferred to a log-in page, where he or she must provide his or her email address, full name and the university name or place of employment. The confirmation of the user’s login to the

mobile app requires clicking the link sent to the indicated email address. The main menu contains three tabs: Patient Health Assessment Tools (after clicking on this tab, the user is

directed to scales and questionnaires arranged in order by assessment area), Patient List (the user may add patients and assign assessment results, thus allowing the patient’s health

condition to be monitored over time), and A-Z Guide (the tab contains all of the assessment scales and questionnaires arranged in alphabetical order). The interactive assessment tool unrolls

when the user clicks on the assessment areas in the sub-menu. RESULTS OF STAGE DS2. During the second stage of this phase, after discussions and agreement, students and university teachers

selected 241 scales from the measurement scales and questionnaires collected during the analysis phase. These scales were then divided into individual assessment areas (Table S1). RESULTS OF

THE DEVELOPMENT PHASE RESULTS OF STAGE DV1. The mobile app was developed in the “Android Application Package (apk)” format, which allows it to be downloaded onto mobile devices. Diagnostic

scales are stored in JavaScript Object Notation (JSON) format. JSON allows large amounts of data to be combined in a chunk of text and to be sent along to other services. Due to the JSON

file’s appropriate data structure, scales can be dynamically loaded and the associated UI objects can be generated from them. The user interface consists of graphical elements that

facilitate interaction and data presentation. These components are employed to create objects, adjust their parameters such as text, colour, and size, and respond to user interactions, such

as when a button is clicked to perform a particular action. The “Diagnostic Nurse” mobile app for Android was developed using Android Studio and the Kotlin programming language. The Kotlin

programming language is an officially supported language for Android. For Android apps, Kotlin is a popular option since it offers expressive syntax, type-safe builders and full Java

interoperability. An SQLite database is exploited to store patient information and assessment results obtained through scales or questionnaires. This is a lightweight, embedded database,

suitable for storing local data in mobile apps. In order to ensure data privacy, all actions performed in the app with a user name and password are comprehensively encrypted and are not

saved on the server. The app’s three main functionalities can be accessed from the home page (Fig. 3): * Patient Health Assessment Tools - provide access to a list of selected scales,

diagnostic tests and standardised clinical measurement tools (Fig. 3: D, E, F), * Patient List - allows the user to display a list of patients, add or delete patients, view a register of

completed examinations and add further examinations for a selected patient (Fig. 3: G, H), * A-Z Guide - provides access to detailed information on the scales, diagnostic tests and

standardised clinical measurement tools used in the app (Fig. 3: I). RESULTS OF THE IMPLEMENTATION PHASE RESULTS OF STAGE I1. The “DiagNurse” app had 154 registered users seven days after it

was released on the Play store, and 476 users after 14 days. The above number of users could be reached by publishing social media posts and distributing information leaflets (Figure S1).

RESULTS OF THE EVALUATION PHASE RESULTS OF STAGE E1. The user interface testing through eye-tracking technique involved twenty participants. Both the SG1 and SG2 groups consisted of women

only. The mean age of the practicing nurses (SG1) in the study was 32.8 (± 14.6) years and the mean length of employment as a nurse was 10 (± 12.7) years. In turn, the students in the SG2

group had a mean age of 20.8 (± 2.4) and varied in terms of study years and levels. Each eye-tracking testing resulted in a video recording that showed fixations, saccades and the

participant’s point of focus superimposed over the scene being viewed. Throughout the study, the participant concentrated on a smartphone with the “Diagnostic Nurse” app running and a

scenario in a paper form. The fixations were visualised as different-sized, numbered circles. Fixation circle size corresponds to the fixation duration. Saccades are straight lines that

connect consecutive fixations. In turn, the large, red and non-sizing circle denotes current gaze location (Fig. 4). Using the Pupil Cloud platform, all research video recordings were

subjected to time-lapse analysis. Excerpts that indicated possible user issues were selected. The following major issues with the app interface were identified by the eye-tracking testing,

including their severity: * Selection of an incorrect test. Figure 4A is a screenshot of the scanpath that indicates the participant’s difficulties in selecting the appropriate scale from a

list of several scales and tests that were completed during the previous examination and saved in the app to assess the patient’s health condition. The user goes through the list and

consequently makes the wrong decision by selecting the incorrect test. As a result, the user must return to the patient list and repeat the entire process to select the correct test. This

minor problem results from a lack of experience with the mobile app. * Incorrect field design. Figure 4B depicts an excerpt from the scanpath that shows the actions of a user attempting to

obtain additional information after pressing a finger in the box where the results are displayed. Since the result display field has a button-like appearance, the user assumes that there is

more detailed information there. This problem is minor. * Small font size and difficulties in reading the information. Figure 4C shows how the user attempts to read the generally presented

interpretation of the result. A high number of small fixations and short saccades within a small area indicates that the user has difficulties in reading the test results. Figure 4D

illustrates how a user scrolls through the tool names from top to bottom to find the Boston Carpal Tunnel Syndrome Questionnaire. Test, scale, and questionnaire names are typically very long

as they are also written in English and include explanations of English-language abbreviations. This makes it challenging for users to locate a particular tool. The participants have to put

a lot of effort into searching, going through each tool’s name one by one. Figure 4E depicts a search for full data about the scale in the A-Z Guide tab. These are presented as text

documents with graphics and tables. Due to the size of these documents, fonts are extremely small, requiring users to enlarge tool descriptions and conduct time-consuming searches. The

problem is of little importance. * Date format (year/month/day) increasing the user’s effort. Figure 4F shows that the user spends a significant amount of time locating relevant studies

arranged in order by the date they were performed. This is because the DATE FORMAT begins with the year. This format requires more cognitive work and lengthens the scanpath. The problem is

major and requires modification of the interface. RESULTS OF STAGE E2. The participants in the focus group interview shared their opinions about the interface. The application interface was

well-received by all participants. Sample comments were as follows: * “The app interface is clear, simple, minimalist” (in a positive sense) (SG 1-S4). * ”The interface colour (blue) has

positive associations with the nursing profession.” (SG 2 –P7). The “Diagnostic Nurse” app’s value in nursing practice was greatly appreciated by the participants. All users correctly

recognized the purpose of the app. Sample comments were as follows: * “Wherever a nurse practices, whether in a hospital or at the patient’s home, the app makes it possible to gather several

scales and assessment questionnaires in one location.” (SG 2-P10). * It is more environmentally friendly to use the app instead of scales and questionnaires in a paper form. (SG 1-S 6) *

”The app gathers the necessary content in one location, reducing the need to search the Internet.” (SG 1-S9). The “Diagnostic Nurse” app’s intuitiveness and ergonomics in nursing practice

were also highly regarded by the participants: * “Almost immediately after having been installed on the phone, the app can be used effortlessly and without any training.” (SG 1-S3). * ”I

instantly knew what to do when I started using the app, as if I have already known it.” (SG 2-P5). * ”The app contains specialised terminology that is useful in nursing practice.” (SG 2-P8).

* ”The app is user-friendly and appears to be bug-free.” (SG 2-P1). RESULTS OF STAGE E3. The quantitative evaluation utilizing the SUS questionnaire yielded very positive results regarding

the app’s usability, with GS1 rating it at 83.3 (± 8.9) and GS2 at 84 (± 12.7). According to the results, the mobile app is highly usable. Table 4 displays the results of the author’s

questionnaire evaluation of user friendliness, ease-of-use, and user satisfaction. Both study groups rated the “Diagnostic Nurse” mobile app positively. DISCUSSION This study employed the

ADDIE model to describe the phases of development of the “Diagnostic Nurse” educational mobile app, which is dedicated to Poland’s practicing nurses and nursing students. The main aim of the

app is to facilitate the clinical assessment of a patient’s health condition through scales and measurement tools. Berking et al.39 recommend the ADDIE model as the most general, universal,

and simple tool. To the best of the authors’ knowledge, this is the first mobile app using the Polish language offering a great number of scales and assessment instruments to facilitate

patient health assessment. Additionally, this is the first app that was developed in an interdisciplinary research team in cooperation with students, and was created in a systematic and

transparent manner, with empirical and theoretical data documented. As a result, we anticipate that our app will assist practicing nurses and nursing students in Poland in assessing a

patient’s health condition and planning nursing interventions. The ICT use can enhance the learning process by fostering learner autonomy and collaborative knowledge construction, and

encouraging the development of concepts for skill development across a range of subject areas, including nursing40. Since the traditional teaching model has weaknesses when it comes to the

student’s active acquisition of knowledge, new technologies must be introduced in the educational system to ensure a more coherent learning process41. It should be noted that the use of

digital tools in patient care improves communication, makes care more accessible, and increases patient satisfaction42. According to studies by Yalcinkaya et al.43 and Özkütük et

al.44nursing students are prepared to exploit mobile technology in their learning process. A similar trend is evident in practicing nurses45. Thape et al.46adds that nurses, as compared to

physicians, express greater willingness about using digital tools in patient care. The lack of willingness to use digital health tools appears to be impacted by concerns about the loss of

patient’s autonomy, patient privacy, data security and unauthorised use47,48. Therefore, implementing digital learning resources early in the higher education system and providing practical

use will support the development of positive attitudes, as well as useful skills and competencies for employing digital resources in patient care. The “Diagnostic Nurse” app is an excellent

example of a digital health tool that can shape positive attitudes. Matthew et al.49 emphasize that ongoing end-user participation is required for a successful mobile application design and

development process. The communication between end users and software development engineers allows for a better understanding of the context of the mobile app being developed and ensures

that users’ needs are met. In addition, it is possible to determine beforehand the precise hardware and software resources that are deemed acceptable, preferred, and in accordance with

users’ needs. The project team that designed the “DiagNurse” mobile app was multidisciplinary and included engineers, practicing nurses, academics and nursing students. The end users’

suggestions allowed us to develop functionalities that met their expectations. All of the meetings held during the “Design” phase helped end users and engineers communicate more effectively.

As it turned out in the subsequent stages, the interdisciplinary team’s collaboration was advantageous to both parties and the mobile app fulfilled end users’ expectations. According to the

current literature, a variety of usability evaluation methods (UEMs) should be employed in the process of developing and testing mobile health apps, as this enables the identification of

issues related to the user-system interaction50. The UEM allows for the identification of the issues that need improvement51. The eye-tracking technique for user interface testing revealed

that the application needed to be slightly improved. A lack of experience with the mobile app was the cause of some of the mishandled instructions during the scenarios, such as selecting the

incorrect assessment tool. However, other detected errors have been fixed in the updated version of the app, including incorrect field design, too-small fonts, and date formats that

required more effort from the user. This can be regarded as a success, most likely as a result of the interdisciplinary team’s effective collaboration. Taking the above into consideration,

it can be concluded that the “Diagnostic Nurse” mobile app is extremely valuable based on the end-users’ feedback from both the focus group interviews and the questionnaire analysis. During

the focus group interviews, users were satisfied with the mobile app and stated that they would recommend this app to other healthcare workers. In addition, based on the Bangor et al.

interpretation of the SUS questionnaire results52, , the mobile app can be categorised as having an excellent usability level. The “Diagnostic Nurse” mobile app development stages and the

UEM results indicate that the product meets requirements and can be released and promoted among larger end user group. We intend to develop a website that provides details about our mobile

app, as well as to send out information about this product to nursing organisations and universities of nursing education, requesting that they disseminate information regarding the

“DiagNurse” app and promote its practical application. In the subsequent stage, we plan to send out survey questionnaires to app users via email, asking them to rate this digital health tool

in a randomized follow-up survey. While developing the Diagnostic Nurse mobile app, we encountered a few challenges, but they turned out to be minor due to the well-planned subsequent

phases of the app development through the ADDIE model. The first issue occurred while searching for patient assessment scales and questionnaires. Many of the assessment scales and

questionnaires were not translated into Polish and/or lacked reliable validation data. As a result, we decided that any tools that have not been adopted into Polish would not be included in

our app. The subsequent challenge was the project’s limited funding, which prevented us from developing the mobile app for both Android and iOS, forcing us to choose only one system. We

chose Android for our mobile app since it is more widely used by Polish smartphone users. As indicated above, the funding for the project allowed for the app development. The project is

completed, and the final version of the app is now available to users for free. Since we do not have any more funding, we are unable to expand the app by including more assessment scales and

questionnaires. We intend to gain more funds in the future to enhance our product. Our study has several limitations. Firstly, due to the small sample size, participants in a usability

testing may not be representative of the target population of app users. However, according to some research, large samples are not required in usability testing since this does not improve

the inference of the results obtained. As a result, the number of participants in the usability testing of the “Diagnostic Nurse” mobile app may be adequate to identify usability issues that

may arise during regular use53. Secondly, the app was only available for Android, which automatically excluded all of the iOS (Apple) users. A future study may address these issues.

CONCLUSIONS Digital health tools specifically designed for practicing nurses and nursing students have been developed in recent years. Our study provides a comprehensive description of the

steps involved in the development of the “Diagnostic Nurse” mobile app. The app offers convenient access to measurement scales and questionnaires that can assist Poland’s practicing nurses

and nursing students in enhancing their competencies in clinical assessment of a patient’s health condition. The usability testing demonstrated that the app was highly recognised by end

users. Future research should compare how using the Diagnostic Nurse mobile app affects the convenience of clinical assessment between the experimental and control groups. DATA AVAILABILITY

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studies: a practitioner’s guide. _J. Usability Stud._ 5 (1), 34–45 (2009). Google Scholar  Download references FUNDING With regard to this endeavour, the Ministry of Science and Higher

Education provided co-financing as part of the „Studenckie koła naukowe tworzą innowacje” program [“_Student research groups create innovations_”], which allowed the project to be

implemented (contract number: SKN/SP/535770/2022). Open access funding provided by the Medical University of Lublin, Poland. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of

Family and Geriatric Nursing, Medical University of Lublin, Lublin, Poland Grzegorz Józef Nowicki & Barbara Ślusarska * Student Research Association at the Department of Family and

Geriatric Nursing, Medical University of Lublin, Lublin, Poland Wiktoria Mazurek, Alicja Waśkowicz, Ewa Kowalczyk & Julia Kozioł * Department of Computer ScienceFaculty of Electrical

Engineering and Computer Science, Lublin University of Technology, Lublin, Poland Marek Miłosz & Mariusz Dzieńkowski Authors * Grzegorz Józef Nowicki View author publications You can

also search for this author inPubMed Google Scholar * Wiktoria Mazurek View author publications You can also search for this author inPubMed Google Scholar * Alicja Waśkowicz View author

publications You can also search for this author inPubMed Google Scholar * Ewa Kowalczyk View author publications You can also search for this author inPubMed Google Scholar * Julia Kozioł

View author publications You can also search for this author inPubMed Google Scholar * Marek Miłosz View author publications You can also search for this author inPubMed Google Scholar *

Mariusz Dzieńkowski View author publications You can also search for this author inPubMed Google Scholar * Barbara Ślusarska View author publications You can also search for this author

inPubMed Google Scholar CONTRIBUTIONS G.J.N.: Conceptualization, methodology, formal analysis, funding acquisition, project administration, writing—original draft preparation, writing—review

and editing and visualization; W.M.: Conceptualization, resources and data curation; A.W.: Conceptualization, resources and data curation; E.K.: Conceptualization, resources and data

curation; J.K.: Conceptualization, resources and data curation; M.M.: Methodology, formal analysis and writing-review and editing; M.D.: Methodology, formal analysis and writing-review and

editing; B.Ś.: Conceptualization, methodology, formal analysis, funding acquisition, project administration, writing-review and editing and supervision. CORRESPONDING AUTHOR Correspondence

to Grzegorz Józef Nowicki. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ETHICAL APPROVAL The study was conducted according to the guidelines of The

Declaration of Helsinki, and approved by the the Bioethics Committee at the Medical University of Lublin (approval number: KE-0254/191/09/2023). The research was carried out in accordance

with local law and institutional requirements. Participating students and practicing nurses gave written informed consent to take part in this study. ADDITIONAL INFORMATION PUBLISHER’S NOTE

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ABOUT THIS ARTICLE CITE THIS ARTICLE Nowicki, G.J., Mazurek, W., Waśkowicz, A. _et al._ Development and pre-evaluation of a “DiagNurse” mobile app to support nurses in clinical diagnosis

using the ADDIE model. _Sci Rep_ 14, 29765 (2024). https://doi.org/10.1038/s41598-024-81813-0 Download citation * Received: 21 February 2024 * Accepted: 29 November 2024 * Published: 30

November 2024 * DOI: https://doi.org/10.1038/s41598-024-81813-0 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a

shareable link is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * Mobile application * Nursing

students * Nurses * Patients * Clinical assessment * ADDIE model