# Smartphone usage habits among french nursing students: A monocentric mixed-methods study

Anaëlle Thebault, Pascale Beloni, Jean Toniolo

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Anaëlle Thebault, Pascale Beloni, Jean Toniolo. Smartphone usage habits among french nursing students: A monocentric mixed-methods study. Archives of Psychiatric Nursing, 2025, 58, pp.151958. 10.1016/j.apnu.2025.151958. hal-05313711

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# Smartphone usage habits among french nursing students: A monocentric mixed-methods study

Anaëlle THEBAULT<sup>a,1</sup>, Pascale BELONI<sup>b,c</sup>, Jean TONIOLO<sup>b,c,*1</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

**Keywords:**

Digital health literacy

Nursing education

Smartphone dependency

Student health

Technology use in nursing

## ABSTRACT

**Background:** Smartphones, first introduced in 1992 in the United States, have evolved into essential communication tools due to their convenience and increasing functionalities. Their widespread use has significantly impacted daily life, leading to various psychological and physical consequences, particularly among young adults. In France, Interministerial Mission to Combat Drugs and Addictive Behavior (MILDECA) reports a high prevalence of intensive smartphone usage among individuals aged 15-24, with many acknowledging their inability to control their screen time. This trend is particularly concerning among nursing students, where excessive smartphone use has been linked to issues such as stress, anxiety, and diminished academic performance. Despite the benefits of smartphones in accessing educational resources, problematic usage remains a growing concern.

This study aimed to describe nursing students' smartphone usage habits, assess addiction and ocular discomfort, and evaluate their knowledge of risks and preventive measures to inform targeted prevention strategies.

**Method:** A cross-sectional, monocentric mixed-methods study was conducted with 50 first- and second-year nursing students. Data were collected through questionnaires assessing smartphone use, addiction, and health impacts, followed by semi-structured interviews with 12 participants. Quantitative and qualitative analyses were performed to explore usage patterns, addiction, and preventive awareness.

**Results:** The average daily smartphone usage was 6 h and 15 min. Of the participants, 86 % showed signs of smartphone addiction, while 66 % exhibited subjective convergence insufficiency, indicating potential ocular discomfort. Although students had some awareness of harmful effects, many struggled to regulate their smartphone use effectively.

**Conclusion:** This study reveals excessive smartphone use among nursing students, contributing to addiction and ocular discomfort. Despite awareness of its negative impacts, students lack effective preventive strategies. Integrating digital health literacy and targeted prevention measures into nursing curricula is essential to address these risks and promote healthier smartphone use.

**Reporting method:** COREQ, STROBE.

## Introduction

Smartphones, first introduced in the United States in 1992, have rapidly become the most important communication tool due to their convenience and accessibility (Bozoglan, 2019). Over the years, their features have evolved significantly, continuously offering new

functionalities, leading to a substantial increase in their usage (Bozoglan, 2019; Herry, 2022; Osorio-Molina et al., 2021). Smartphones are technological devices that have profoundly impacted daily life, altering habits and behaviors. Their utilities and capabilities are expanding. According to recent projections, the number of smartphone users worldwide is expected to reach 7.8 billion by 2028, compared to

<footnote><sup>a</sup> Limoges University, France</footnote>

<footnote><sup>b</sup> Inserm U1094, IRD UMR270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of chronic diseases in tropical zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, France</footnote>

<footnote><sup>c</sup> Département Universitaire de Sciences Infirmières, Faculté de Médecine et Pharmacie, Université de Limoges, France</footnote>

<footnote>* Corresponding author at: CHU de Limoges, 2 Av. Martin Luther King, 87000 Limoges, France.</footnote>

<footnote>E-mail address: jean.toniolo@chu-limoges.fr (J. TONIOLO).</footnote>

<footnote>@Jean_Toniolo (J. TONIOLO)</footnote>

<footnote n="1">¹ These authors contributed equally to this work.</footnote>
6.9 billion in 2023, reflecting the continuous growth in mobile device penetration (Petroc, 2024). However, the problematic use of smartphones among nursing students has raised concerns due to its association with decreased academic performance, increased stress, and reduced attention during clinical placements (Osorio-Molina et al., 2021; Ramjan et al., 2021).

In France, this increase in smartphone usage has been highlighted by the Interministerial Mission to Combat Drugs and Addictive Behavior (MILDECA) Barometer, which assesses screen usage annually (MILDECA, 2021). It has been found that intensive daily users (more than 4 h/day) are twice as prevalent among those aged 15–24 compared to older age groups (MILDECA, 2021). Moreover, 8 out of 10 French individuals acknowledge their inability to control their screen usage, despite being aware of its excessive nature (MILDECA, 2021). The COVID-19 pandemic further disrupted societal habits, necessitating an exponential growth in scientific and digital advancements to reorganize essential daily activities (Serra et al., 2021). Consequently, digital usage became indispensable, with the rise of remote work and e-learning (Alliti et al., 2022; Berdida & Grande, 2023; Elhai et al., 2020).

The increasing use of smartphones has led to numerous psychological and physical consequences. In the short term, it can cause issues such as convergence insufficiency, a condition where the eyes have difficulty working together while focusing on a near object, leading to symptoms like eye strain, headaches, and blurred vision (Vera et al., 2023). In the medium term, prolonged and recurrent use can lead to sleep disorders, concentration difficulties, and addiction (Daei et al., 2019; Lawrenson et al., 2017). In the long term, excessive smartphone use can disrupt circadian rhythms and cause retinal disturbances, posing a significant public health concern (Dufier & Touitou, 2021). This phenomenon is not limited to France; similar trends have been reported among nursing students in countries such as Spain, South Korea, and Turkey, highlighting a global concern that requires further investigation (Demirci et al., 2015; Kim & Park, 2019; Osorio-Molina et al., 2021).

Specifically, for nursing students, excessive smartphone use has been identified as a significant source of distraction, negatively impacting their learning and academic performance. Research indicates that personal smartphone use in clinical and classroom settings can diminish professionalism and increase stress, anxiety, and reduce sleep quality (Ramjan et al., 2021). Smartphone dependency, often leading to addiction, has been associated with lower communication skills and heightened social distress among nursing students (Osorio-Molina et al., 2021). Overuse of smartphones among this population has also been linked to psychological issues, such as increased anxiety, poor sleep quality, and impaired interpersonal relationships, all of which can hinder their overall well-being and academic success (Chandio et al., 2023). However, when used appropriately, smartphones can significantly enhance nursing education by providing immediate access to educational content, clinical guidelines, and evidence-based resources (Koohestani et al., 2018; Lee et al., 2018). This enables students to apply their knowledge in real-time clinical scenarios, thereby enhancing their learning outcomes (Kim & Park, 2019).

The prevalence of smartphone addiction has been documented with varying results across different studies. For instance, research conducted at King Saud University identified that 48 % of the student participants showed signs of smartphone addiction, with higher rates observed among unmarried individuals and those with lower monthly incomes (Aljomaa et al., 2016). Similarly, a study in Tunisia reported that 68.8 % of students were at a high risk of developing smartphone addiction, particularly among cannabis users and students in non-medical fields (Turki et al., 2023). Meta-analytic estimates show that the prevalence of nomophobia, or smartphone addiction, among nursing students is 22 % (CI95% 18 %-26 %), based on a sample of 2780 students (Osorio-Molina et al., 2021). However, in France, there is a lack of specific data regarding smartphone addiction among nursing students.

Despite these concerns, preventive actions related to smartphone use in France are primarily targeted towards children, particularly those

under 12 years old (Tisseron, 2022). For the general population, prevention efforts are focused on the risk of screen addiction, especially concerning recreational use, such as social media and video games (Bozoglan, 2019; Herry, 2022). However, there are no specific campaigns targeting university students, even though they spend significant amounts of time on their smartphones (MILDECA, 2021). Additionally, there is a lack of data regarding the literacy of nursing students on the consequences of smartphone use, as no studies have been published on this topic. Given the harmful effects of excessive screen time on health (Lawrenson et al., 2017; Park et al., 2020; Rahman et al., 2017), it is crucial to develop tailored prevention strategies. The findings of this study could have important implications for the development of targeted interventions in nursing education and for the broader public health strategy addressing smartphone addiction.

During their training in Nursing Schools, nursing students are particularly exposed to a significant number of online courses through digital platforms and extensive resources via the University Library's Digital Workspace, leading to many hours spent daily on their smartphones and computers. This trend is observed across all nursing programs since their integration into universities (Gause et al., 2022). Furthermore, there has been an increase in orthoptic consultations related to intensive screen use since the pandemic (Alliti et al., 2022).

## Study objectives

The primary objective of this study was to describe and understand the smartphone usage habits of nursing students. The secondary objectives were to identify and assess smartphone addiction, determine the presence of subjective convergence insufficiency indicating ocular discomfort, describe students' knowledge regarding appropriate smartphone use and its harmful consequences, and finally, to understand the most consulted preventive measures by this population to define specific prevention actions.

## Methods

We conducted a cross-sectional, descriptive monocentric study using a convergent mixed-methods design (Fetters et al., 2013; Guetterman et al., 2015). The qualitative data were employed to complement and interpret the quantitative findings (Östlund et al., 2011). The study was reported following the COREQ and STROBE guidelines (Tong et al., 2007; Von Elm et al., 2007).

### Study setting and population

Data were collected from May 15, 2023, to June 30, 2023, at the Limoges branch of Nursing School of the Centre Hospitalier de de Haute-Corrèze, affiliated with the Faculty of Medicine at the University of Limoges. Given that this is the first study on the topic, we used an exhaustive convenience sampling method, inviting all eligible nursing students to participate. Our study population included first- and second-year nursing students.

### Inclusion and exclusion criteria

Participants were eligible if they were nursing students over 18 years of age and owned a smartphone. To participate, students were required to give informed consent after receiving an information sheet and oral explanation about the study's objectives. Participants needed to be proficient in reading and writing in French. Exclusion criteria included being under guardianship or curatorship.

### Data collection and analysis

As this was a mixed-methods study, data were collected from two sources: questionnaires developed based on literature review, followed
by semi-structured interviews.

## Quantitative data collection and analysis

All participants completed an anonymous questionnaire administered via KoboCollect. The questionnaire included the following components:

Collection of sociodemographic data, information on visual health consultations, the frequency of such consultations, practitioners consulted, visual anomalies, and optical corrections used, as well as descriptive data on smartphone use based on screen time recorded during the week preceding data collection.

* The PUMPQ (Problematic Use Mobile Phone Questionnaire), to assess smartphone addiction (Lopez-Fernandez et al., 2018).

* The CISS-V15 (Convergence Insufficiency Symptom Survey), to identify subjective convergence insufficiency, potentially indicating eye strain (Rouse et al., 2004). When the subjects are under 21 years old, a score of 16 or higher is indicative of convergence insufficiency; for those 21 and older, a score is considered indicative if it is 21 or higher.

* A non-validated questionnaire based on the literature to evaluate the literacy of nursing students regarding the perceived consequences of intensive smartphone use, the knowledge score was calculated on twenty points.

A significance threshold of 5 % was established for this study. Descriptive statistics were used to describe the population characteristics and the distribution of smartphone usage types. Mean ± standard deviation and/or median [IQR] were reported for continuous variables; frequencies and percentages were reported for categorical variables. Confidence intervals at 95 % were calculated for each outcome measure. The normality of the distribution of continuous variables was assessed using the Shapiro-Wilk test. The PUMPQ and CISS-V15 questionnaires were processed according to the authors' recommendations (Billieux et al., 2008; Mejía & Perez, 2016). All statistical analyses were performed using SPSS 29.

## Qualitative data collection and analysis

To complement the quantitative analyses, individual semi-structured interviews were conducted to explore specific aspects of the studied issue in greater depth. Interviews were conducted by a researcher trained in qualitative research, who also participated in the subsequent data analysis. A senior qualitative researcher was involved in co-analyzing the data, and a third expert was available for triangulation in case of disagreement, although consensus was reached without the need for arbitration.

Interviews were recorded, transcribed in full, and then anonymized in compliance with data protection regulations before the recordings were deleted. The interview guide focused on four main areas: (1) participants' daily smartphone use, (2) their perceptions of smartphone dependency, (3) their knowledge of potential health impacts, and (4) their opinions on existing and potential prevention strategies. Examples of questions included: "Can you describe your typical daily smartphone use, from morning to night?"; "How important is your smartphone to you on a scale from 1 to 10, and why?"; "In what ways do you think your smartphone use affects your physical or mental health?"; "Have you ever tried to reduce or control your smartphone use? If yes, how?"; "What is your perception of smartphone dependency?"; "Have you received any education or prevention messages about the risks of smartphone use?"

The interview guide was discussed and tested with a nursing student before the first interview to ensure clarity and comprehension. Importantly, no modifications to the interview guide were necessary after this testing phase, as the guide was found to be clear and comprehensive. Participants for the interviews were selected through random sampling.

This random selection allowed for the inclusion of diverse perspectives, as similar profiles were present among the study participants, thereby ensuring the exhaustiveness of viewpoints. Data saturation was evaluated based on the redundancy of themes emerging from the interviews and the absence of new ideas being generated in subsequent interviews (Drapeau, 2004). A minimum of 12 interviews were planned (Guest et al., 2006).

The qualitative data were analyzed by two researchers (JT and PB), both experienced in conducting and analyzing qualitative studies. Interviews were transcribed following a floating listening approach and analyzed using thematic analysis, as described by Tuckett (Tuckett, 2005). Themes and sub-themes were initially identified using a deductive approach, followed by an inductive method to ensure the comprehensiveness of the themes (Auerbach & Silverstein, 2003; Carter et al., 2014). The interviews were independently coded using NVivo 11®, and the identified themes were consolidated through regular consensus meetings. The final set of themes was validated by the third expert researcher, ensuring methodological rigor, triangulation, and analytical validity (Carter et al., 2014; Drapeau, 2004).

## Ethical and regulatory considerations

The study received ethical approval from the CHU of Limoges Ethics Committee (N°9-2023-02). To obtain consent, participants were first informed orally, followed by the provision of an information sheet outlining the study's objectives, procedures, expected outcomes, and participant rights. Written informed consent was obtained from all participants.

## Results

### Demographic data

A total of 50 participants were included in this study, with 12 subsequently participating in individual semi-structured interviews. The participants had an average age of 19.6 ± 1.8 years, ranging from 18 to 28 years. Among those who had pursued higher education before beginning their nursing training, four held a State Diploma as a nursing assistant.

Sociodemographic data were obtained through questionnaire analysis, and these data are presented in Table 1.

### Smartphone usage habits

All participants in this study owned a smartphone, with an average ownership duration of 8 ± 2.5 years. Daily usage of smartphones was notably high among participants. For example, participant P1 reported checking their smartphone "every 30 minutes."

On average, students used their phones for six hours per day. Usage was generally higher on weekends than on weekdays. Participant P5 explained, "If I'm not busy, I can spend my whole afternoon on it." However, some participants had lower usage due to being more

<table><caption>**Table 1**
Sociodemographic data.</caption><thead><tr><th>Variable:</th><th></th></tr></thead><tbody><tr><td>- Woman</td><td>46 (92 %)</td></tr><tr><td>School year:</td><td></td></tr><tr><td>- 1st year</td><td>29 (58 %) 21 (42 %)</td></tr><tr><td>- 2nd year</td><td></td></tr><tr><td>Previous education:</td><td></td></tr><tr><td>- High school</td><td>42(96 %) 8 (6 %)</td></tr><tr><td>- University</td><td></td></tr><tr><td>Student work (yes)</td><td>9 (18 %)</td></tr><tr><td>Driving licence (yes)</td><td>37 (74 %)</td></tr><tr><td>n(%)</td><td></td></tr></tbody></table>
occupied; for instance, P7 stated that they did not use their smartphone “for more than two hours a day” when working.

**Table 2** below describes the average daily smartphone usage in minutes and hours for each day of the week, as recorded by the participants' smartphones.

Daily, participants reported using their smartphones from waking up to going to bed. P9 shared, “I wake up, turn off my phone which I use as an alarm, then use it to go to class. Then during classes, at meals or during breaks, and in the evening before going to bed.”

Some participants used their smartphones as an alarm clock and then checked notifications and browsed “social media to see what happened overnight” (P2).

During their commutes to the nursing school (IFSI), some participants used their smartphones while driving. P1 noted, “I use my phone while driving.” In public transport, some listened to music or browsed social media. P2 expressed, “I put on music to get ready and on the bus ride to class; it’s something I do every morning.”

At the training institute during classes, students used their phones for academic purposes, such as conducting research, taking photos of slides, or sharing their internet connection. They also used their smartphones for personal purposes. P3 explained, “Throughout the day, I play games; whether I’m in class or during breaks.”

Between classes, students reported browsing social media, playing games, or watching videos and series. P4 mentioned that it was “a good way to relax.”

However, participants did not regularly use their phones to view e-learning courses, preferring instead to use their computers or tablets. They noted that the screen was “a bit too small, it’s not practical” (P6).

In the evening, participants used their smartphones to browse social media, play games, listen to music, or watch videos, series, or movies. P3, after returning home, stated that they “mainly use it to watch videos and play games, being addicted to video games.”

Some participants also used their smartphones during meals or as a sleep aid. P2 explained that they couldn’t “sleep without noise” and would “put on a series on the phone until falling asleep.” The data collected show the pervasive presence of smartphones in the students’ lives.

The functions of the smartphone and their associated usage frequencies are described in Table 3.

Participants intensively used their smartphones to browse social media and listen to music. P7 mentioned, “I listen to a lot of music, at least 2 hours a day.”

The most frequently used applications were communication and social media apps: 48 participants (96 %) used Instagram, 46 (92 %) had Snapchat, 42 (84 %) sent SMS messages, 38 (76 %) used TikTok, 37 (74 %) had WhatsApp, 36 (72 %) used their smartphones to send emails, 22 (44 %) used Messenger, 21 (42 %) had BeReal, 13 (26 %) used Twitter, and 2 (4 %) had LinkedIn.

Contrary to other participants, P4 did not use social media: “I distance myself from it because I know it’s toxic. One can be heavily influenced and want to mimic certain people.”

During classes, 49 (98 %) students used their phones, while 23 (46 %)

<table><caption>**Table 2**
Time spent by nursing student using the smartphone.</caption><thead><tr><td>Day of the week</td><td>Average time in hours</td></tr></thead><tbody><tr><td>Monday</td><td>6 h25 ± 2 h11</td></tr><tr><td>Tuesday</td><td>6 h26 ± 2 h26</td></tr><tr><td>Wednesday</td><td>5 h54 ± 2 h</td></tr><tr><td>Thursday</td><td>6 h08 ± 2 h16</td></tr><tr><td>Friday</td><td>5 h39 ± 1 h59</td></tr><tr><td>Saturday</td><td>6 h24 ± 2 h52</td></tr><tr><td>Sunday</td><td>6 h43 ± 2 h36</td></tr><tr><td>Average daily duration of use</td><td>6 h15 ± 0 h20</td></tr><tr><td>Average total weekly usage time</td><td>43 h44 ± 0 h53</td></tr><tr><td>m ± SD</td><td></td></tr></tbody></table>

<table><caption>**Table 3**
Type of smartphone use.</caption><thead><tr><td></td><td>Never</td><td>Occasionally</td><td>Daily</td><td>Very often</td></tr></thead><tbody><tr><td>Videos/Films</td><td>6 (12 %)</td><td>17 (34 %)</td><td>14 (28 %)</td><td>13 (26 %)</td></tr><tr><td>Video games</td><td>23 (46 %)</td><td>16 (32 %)</td><td>6 (12 %)</td><td>5 (1 %)</td></tr><tr><td>Social networks</td><td>1 (2 %)</td><td>1 (2 %)</td><td>6 (12 %)</td><td>42 (84 %)</td></tr><tr><td>News</td><td>1 (2 %)</td><td>25 (5 %)</td><td>17 (34 %)</td><td>7 (14 %)</td></tr><tr><td>School</td><td>—</td><td>12 (24 %)</td><td>26 (52 %)</td><td>12 (24 %)</td></tr><tr><td>Photos</td><td>1 (2 %)</td><td>12 (24 %)</td><td>17 (34 %)</td><td>20 (4 %)</td></tr><tr><td>Music</td><td>2 (4 %)</td><td>5 (1 %)</td><td>8 (16 %)</td><td>35 (7 %)</td></tr><tr><td>n (%)</td><td></td><td></td><td></td><td></td></tr></tbody></table>

%) used them during internships: 47 (94 %) used their phones for academic purposes and 44 (88 %) for personal purposes. P8 noted that “sometimes it happens throughout the entire hour of class” for personal use.

### Importance and perception of the smartphone

#### Problematic smartphone use

The PUMPQ scale was administered to participants to quantify problematic smartphone use. The questionnaire results are described in Table 4.

The PUMPQ test results in our study population showed an average score exceeding the reference score for all themes assessed: dangerous behavior, prohibited use, smartphone dependency, and financial problems. This indicates problematic smartphone use within our study population.

Only 7 participants (14 %) had a score below the reference score for smartphone dependency.

Additionally, 27 (54 %) participants exhibited dangerous behavior, 26 (52 %) engaged in prohibited use, and 22 (44 %) experienced financial problems related to phone bills.

#### Perceived importance and representation of the smartphone

During individual interviews, participants were asked to rate the importance of their smartphones on a scale of 1 to 10.

The median perceived importance of the smartphone among the students interviewed was 8/10, with the first quartile at 6.5/10 and the third quartile at 9.5/10.

During the interviews, all participants except one mentioned smartphone dependency. They described it as an essential communication tool, with some even considering it indispensable as it contained “our entire life” (P8). Students explained that its numerous features facilitated daily life activities. P2 stated that “there are a lot of things that would be more difficult to do without it.”

However, according to them, it was primarily social media and video games that caused dependency.

The thematic analysis revealed three interrelated core themes describing smartphone use among nursing students: Perceived functionality: Smartphones were described as essential tools supporting daily life—used for communication (WhatsApp, Snapchat), information retrieval (e.g., medical databases), entertainment (YouTube, TikTok), and organization (alarms, calendars, GPS). This utilitarian perception reinforces daily and continuous engagement.

**Emotional and behavioral dependency:** A large proportion of participants referred to a form of automatic or emotional use. Smartphones were used to combat boredom, reduce anxiety, or feel connected. Many participants used expressions such as “it’s a need”, “when I don’t have it, I feel empty” (P1, P8), suggesting habitual, compulsive patterns of use. Some even acknowledged symptoms of irritation or frustration when interrupted (P3).

**Negative consequences:** Students frequently reported symptoms including visual fatigue, concentration difficulties, disrupted sleep, and mental overload. Some participants expressed guilt about the time lost due to smartphone use and described feelings of detachment from reality
<table><caption>**Table 4**
Results of PUMPQ questionnaire.</caption><thead><tr><th></th><th>Quite a lot</th><th>Somewhat well</th><th>Somewhat badly</th><th>Not at all</th></tr></thead><tbody><tr><td>Use in prohibited areas</td><td>14 (27 %)</td><td>18 (35 %)</td><td>10 (19 %)</td><td>8 (16 %)</td></tr><tr><td>Easy to spend the day without a phone</td><td>7 (13 %)</td><td>18 (35 %)</td><td>14 (27 %)</td><td>11 (22 %)</td></tr><tr><td>Telephone bill: important place</td><td>2 (4 %)</td><td>6 (11 %)</td><td>10 (19 %)</td><td>32 (64 %)</td></tr><tr><td>Phone while driving</td><td>7 (13 %)</td><td>8 (16 %)</td><td>7 (13 %)</td><td>28 (54 %)</td></tr><tr><td>Don't pay attention to phone expenses</td><td>11 (21 %)</td><td>2 (4 %)</td><td>4 (8 %)</td><td>33 (63 %)</td></tr><tr><td>Difficult not to use the phone</td><td>16 (32 %)</td><td>18 (35 %)</td><td>10 (19 %)</td><td>6 (11 %)</td></tr><tr><td>No use of phone in library</td><td>6 (11 %)</td><td>12 (23 %)</td><td>16 (32 %)</td><td>16 (32 %)</td></tr><tr><td>Easy to do without phone</td><td>4 (8 %)</td><td>18 (36 %)</td><td>17 (35 %)</td><td>11 (21 %)</td></tr><tr><td>Phone expenses prevent certain purchases</td><td>1 (2 %)</td><td>1 (2 %)</td><td>4 (8 %)</td><td>43 (86 %)</td></tr><tr><td>Irritated when forced to turn phone off</td><td>3 (6 %)</td><td>8 (16 %)</td><td>11 (21 %)</td><td>28 (54 %)</td></tr><tr><td>Avoid using the phone on the motorway</td><td>29 (56 %)</td><td>6 (12 %)</td><td>6 (12 %)</td><td>9 (17 %)</td></tr><tr><td>Control over telephone expenditure</td><td>32 (61 %)</td><td>5 (1 %)</td><td>5 (10 %)</td><td>8 (15 %)</td></tr><tr><td>Phone in forbidden places</td><td>7 (13 %)</td><td>9 (18 %)</td><td>6 (12 %)</td><td>28 (54 %)</td></tr><tr><td>Difficult financial situations due to telephone expenses</td><td>1 (2 %)</td><td>2 (4 %)</td><td>1 (2 %)</td><td>46 (92 %)</td></tr><tr><td>Wish to reduce the amount of time they use their phone</td><td>14 (27 %)</td><td>24 (46 %)</td><td>6 (12 %)</td><td>6 (12 %)</td></tr><tr><td>Use phone in dangerous situations</td><td>14 (27 %)</td><td>10 (20 %)</td><td>13 (25 %)</td><td>13 (25 %)</td></tr><tr><td>Lost without phone</td><td>10 (20 %)</td><td>18 (35 %)</td><td>12 (23 %)</td><td>10 (20 %)</td></tr><tr><td>Very high telephone bills</td><td>1 (2 %)</td><td>6 (12 %)</td><td>5 (10 %)</td><td>38 (73 %)</td></tr><tr><td>Use phone on public transport: pay attention to volume</td><td>40 (80 %)</td><td>5 (10 %)</td><td>2 (4 %)</td><td>3 (6 %)</td></tr><tr><td>Too much time on the phone</td><td>20 (40 %)</td><td>21 (42 %)</td><td>7 (13 %)</td><td>2 (4 %)</td></tr><tr><td>Manages money spent on phone effectively</td><td>29 (56 %)</td><td>15 (3 %)</td><td>1 (2 %)</td><td>5 (10 %)</td></tr><tr><td>Concerned about the importance of the phone</td><td>10 (20 %)</td><td>16 (32 %)</td><td>13 (25 %)</td><td>11 (21 %)</td></tr><tr><td>When driving: tricky situation because of phone</td><td>5 (10 %)</td><td>4 (8 %)</td><td>10 (20 %)</td><td>31 (62 %)</td></tr><tr><td>Difficulty paying phone bills</td><td>1 (2 %)</td><td>1 (2 %)</td><td>4 (8 %)</td><td>44 (85 %)</td></tr><tr><td>Avoids using phone in quiet places</td><td>18 (35 %)</td><td>13 (26 %)</td><td>9 (17 %)</td><td>10 (20 %)</td></tr><tr><td>Surprised by the size of telephone bills</td><td>-</td><td>1 (2 %)</td><td>4 (8 %)</td><td>45 (90 %)</td></tr><tr><td>Difficult to switch off the phone</td><td>4 (8 %)</td><td>11 (22 %)</td><td>15 (29 %)</td><td>20 (40 %)</td></tr></tbody></table>

<table><caption>**Table 4 (continued)**</caption><thead><tr><th></th><th>Quite a lot</th><th>Somewhat well</th><th>Somewhat badly</th><th>Not at all</th></tr></thead><tbody><tr><td>Borrow money for phone bills</td><td>1 (2 %)</td><td>1 (2 %)</td><td>1 (2 %)</td><td>47 (94 %)</td></tr><tr><td>When driving, using the phone in situations requiring a high level of concentration</td><td>4 (8 %)</td><td>8 (16 %)</td><td>4 (8 %)</td><td>34 (68 %)</td></tr><tr><td>Telephone conversations that last longer than desired</td><td>6 (11 %)</td><td>15 (29 %)</td><td>18 (35 %)</td><td>11 (22 %)</td></tr><tr><td>Average score for dangerous behavior Reference: 8,52 (±3,19)</td><td>9,58</td><td></td><td></td><td></td></tr><tr><td>Average score for prohibited use Reference: 7,68 (+/- 2,56)</td><td>10,56</td><td></td><td></td><td></td></tr><tr><td>Average score for telephone dependency relationship Reference: 12,75 (+/- 4,53)</td><td>16,92</td><td></td><td></td><td></td></tr><tr><td>Average score for financial problems Reference: 21,92 (+/- 6,93)</td><td>22,46</td><td></td><td></td><td></td></tr><tr><td>Smartphone addiction (yes): N (%); moyenne ± SD; médiane [IQR]</td><td>43 (86 %)</td><td></td><td></td><td></td></tr></tbody></table>

or social withdrawal (P6, P8).

These three themes are not isolated but form a self-reinforcing cycle: functional utility leads to regular use, which escalates into emotional dependency, which in turn generates health or cognitive consequences. These consequences often reinforce use through avoidance behaviors or compensation—thus feeding the cycle further.

### Emergent typology of users

To deepen the synthesis, we developed an inductive typology based on participant narratives Table 5). This typology allows a better understanding of user diversity and suggests the need for differentiated prevention strategies.

### Visual health and sleep quality

On average, participants in this study had undergone a visual check-up 1.7 ± 1.6 years ago. However, only five participants had consulted an orthoptist.

Table 6 below describes visual health and the devices used by participants to mitigate the effects of blue light. Additionally, we gathered information on their perceptions of sleep quality.

Anti-blue light systems were used by 26 participants (52 %). Among them, 18 participants (36 %) used photochromic glasses with or without

<table><caption>**Table 5**
Typology of smarphone users.</caption><thead><tr><th>User Type</th><th>Participants</th><th>Dominant Use</th><th>Key Characteristics</th></tr></thead><tbody><tr><td>Functional Users</td><td>P4, P7</td><td>Communication and utility</td><td>Deliberate use, critical of social media, minimal symptoms, low perceived dependency</td></tr><tr><td>Moderate Users</td><td>P5, P10, P11</td><td>Balanced (personal and academic)</td><td>Aware of overuse, employ self-regulation tools (timers, app reorganization)</td></tr><tr><td>Compensatory Users</td><td>P1, P2, P6, P12</td><td>Emotional relief, connection</td><td>Automatic use in idle moments, guilt expressed, difficulty detaching from phone</td></tr><tr><td>At-risk/ Dependent Users</td><td>P3, P8, P9</td><td>Games, social media, emotional regulation</td><td>Strong self-identified dependency, associated psychological or physical symptoms</td></tr></tbody></table>
<table><caption>**Table 6**
Health data.</caption><tbody><tr><td>- Restful sleep (yes)</td><td>28 (56 %)</td></tr><tr><td>- Feeling of sleeping easily (yes)</td><td>25 (50 %)</td></tr><tr><td>Visual inspection less than 3 years old</td><td>33 (66 %)</td></tr><tr><td>Health professional consulted:</td><td></td></tr><tr><td>- Ophthalmologist</td><td>38 (76 %)</td></tr><tr><td>- Optician</td><td>18 (36 %)</td></tr><tr><td>- Orthoptist</td><td>5 (10 %)</td></tr><tr><td>Wearing optical correction:</td><td></td></tr><tr><td>- Wearing glasses</td><td>29 (58 %)</td></tr><tr><td>- Wearing contact lenses</td><td>2 (4 %)</td></tr><tr><td>Ametropia:</td><td></td></tr><tr><td>- Myopia</td><td>8 (16 %)</td></tr><tr><td>- Hyperopia</td><td>13 (26 %)</td></tr><tr><td>- Astigmatism</td><td>14 (28 %)</td></tr><tr><td>Anti-blue light devices:</td><td></td></tr><tr><td>- Wearing photochromic lenses</td><td>24 (48 %)</td></tr><tr><td>- Brightness adjustment and blue light filter on screen</td><td>8 (16 %)</td></tr><tr><td>n (%)</td><td></td></tr></tbody></table>

optical correction and blue light filters, 2 participants (4 %) preferred adding the blue light filter function to their screens, and 6 participants (12 %) used both blue light glasses and the built-in blue light filter on their screens.

The CISS-V15 scale measures subjective visual fatigue and comfort. The results obtained by the participants are described in Table 7. The average score of the participants was 21.8 ± 11.6, revealing subjective convergence insufficiency in 33 participants (66 %).

## Literacy and prevention

A questionnaire was administered to assess participants' knowledge of the effects of excessive smartphone use.

<table><caption>**Table 7**
Results of CISS-V15 questionnaire.</caption><thead><tr><th></th><th>Never</th><th>Not very often</th><th>Sometimes</th><th>Quite often</th><th>Always</th></tr></thead><tbody><tr><td>Headaches</td><td>13 (25 %)</td><td>15 (29 %)</td><td>9 (17 %)</td><td>13 (26 %)</td><td>-</td></tr><tr><td>Difficulty concentrating</td><td>11 (22 %)</td><td>14 (27 %)</td><td>13 (25 %)</td><td>9 (18 %)</td><td>3 (6 %)</td></tr><tr><td>Tired eyes</td><td>6 (12 %)</td><td>8 (16 %)</td><td>20 (40 %)</td><td>11 (22 %)</td><td>5 (10 %)</td></tr><tr><td>Discomfort</td><td>9 (16 %)</td><td>13 (26 %)</td><td>19 (38 %)</td><td>7 (14 %)</td><td>2 (4 %)</td></tr><tr><td>Falling asleep</td><td>18 (36 %)</td><td>13 (26 %)</td><td>8 (16 %)</td><td>4 (8 %)</td><td>7 (14 %)</td></tr><tr><td>Difficulty remembering</td><td>8 (16 %)</td><td>14 (28 %)</td><td>15 (30 %)</td><td>8 (16 %)</td><td>4 (8 %)</td></tr><tr><td>Diplopia</td><td>27 (54 %)</td><td>6 (12 %)</td><td>9 (18 %)</td><td>5 (10 %)</td><td>3 (6 %)</td></tr><tr><td>Moving words</td><td>33 (66 %)</td><td>6 (12 %)</td><td>3 (6 %)</td><td>8 (16 %)</td><td>-</td></tr><tr><td>Slow reading</td><td>18 (36 %)</td><td>10 (20 %)</td><td>11 (22 %)</td><td>4 (8 %)</td><td>7 (14 %)</td></tr><tr><td>Eye pain</td><td>15 (30 %)</td><td>13 (26 %)</td><td>9 (18 %)</td><td>10 (20 %)</td><td>3 (6 %)</td></tr><tr><td>Irritated eyes</td><td>15 (30 %)</td><td>10 (20 %)</td><td>14 (28 %)</td><td>6 (12 %)</td><td>5 (10 %)</td></tr><tr><td>Tightness in the eyes</td><td>15 (30 %)</td><td>10 (20 %)</td><td>14 (28 %)</td><td>9 (18 %)</td><td>2 (4 %)</td></tr><tr><td>Getting lost in the text</td><td>13 (26 %)</td><td>15 (30 %)</td><td>13 (26 %)</td><td>7 (14 %)</td><td>2 (4 %)</td></tr><tr><td>Rereading the same line</td><td>7 (14 %)</td><td>12 (24 %)</td><td>19 (38 %)</td><td>9 (18 %)</td><td>3 (6 %)</td></tr><tr><td>Blurred vision</td><td>16 (32 %)</td><td>16 (32 %)</td><td>13 (26 %)</td><td>2 (4 %)</td><td>3 (6 %)</td></tr><tr><td colspan="6">CISS-V15 Average</td></tr><tr><td colspan="6">Total Score: 21.76 ± 11.6</td></tr><tr><td colspan="6">N (%); mean ± SD</td></tr></tbody></table>

The items in the questionnaire and the correct answers associated with each question are presented in S1 Appendix. A score out of 20 was established to estimate each participant's level of literacy.

All participants interviewed during the qualitative interviews discussed the topic of dependency and how smartphone use had become a real habit. P1 explained that “When we don't have it, we feel empty. We feel the dependency. It's a need, otherwise we get bored.”

Students also mentioned mental and social health issues, including depression, anxiety, sedentary behavior, and loss of time and motivation: “being dependent and spending a lot of time on the phone, we can tell ourselves that we could have done something else. Sometimes I stay on my phone longer than planned” (P8), and the detachment from reality.

P3 explained the emotional impact, saying “as soon as someone takes my phone away or tells me not to be on it, I get angry, upset, and then I'm in a bad mood.”

Many of them talked about the potential effects on vision: headaches and changes in vision with the onset of myopia and retinal damage.

Sleep disorders, including difficulties falling asleep, fatigue, drowsiness, and learning difficulties, were also mentioned. Conversely, P10 felt that using their phone helped them concentrate: “When I play games, it helps me focus better than when I watch the teacher.”

Some participants believed that smartphone use could affect posture because “we have the reflex to bend over, and this creates small traumas” and cause hand issues, including tendinitis, and tendon and finger pain (P6).

Chronic diseases were not mentioned during the interviews.

## Potential restrictions

Initially, the students interviewed mentioned that the acquisition of a first smartphone by young people should be delayed because, according to them, “younger people are using it earlier and earlier” (P11).

To reduce the impact of smartphone use, some participants suggested adjusting the brightness of their smartphones during use or wearing anti-blue light glasses.

It was also suggested to set time limits on usage to reduce exposure time, remove notifications, and regularly change the location of the most used apps to prevent habitual use.

P6 explained, “sometimes I think I should uninstall some apps that don't bring me anything, they make me waste time.”

To avoid spending more time than intended, some participants decided to organize their time better by setting specific schedules for specific tasks and keeping the phone out of reach during activities or in the evening before bed. P11 “doesn't take it and leaves it in the bedroom to avoid using it.”

## Prevention

The results of the questionnaire and interviews show that most participants had not received much prevention on the effects of smartphone use, or had received limited prevention, mainly focused on addiction and social media. They did not find it impactful.

P5 received prevention “in middle and high school about social media and precautions to take, but not really about the effects of the phone.”

## Strengthening prevention

Opinions differed on the need to implement or strengthen prevention related to smartphone use. According to them, it is difficult to change habits, especially when it comes to addiction. “We live connected, so it's very difficult to change routine, but it's necessary to develop prevention because the phone causes a lot of harm” (P6).

They considered the topic of screen use to be sensitive. According to P4, “It's still a very taboo subject, so prevention would be difficult.”
Most participants mentioned the need for prevention aimed at young children: “It’s better to condition them when they’re young, so they grow up with the idea that ‘it’s not good,’ because after that, it’s too late” (P4), or at young parents because new parents expose children to screens a lot to keep them occupied.

P3, however, thought that “prevention among children wouldn’t be effective because they don’t realize and don’t understand.”

Some participants believed that prevention should be done before entering middle school, especially before the age of 10, as children receive phones very early. Furthermore, given the high amount of screen time, regular reminders should be implemented throughout the school years. According to P6, “addictions develop very quickly, so it would be best to have prevention before children get a phone.”

P7 thought that “for adults, it would be better to offer techniques to limit time because some might want to reduce it without knowing how.”

## Form of prevention

Participants believed that the most effective means of prevention would include television, interventions (in schools, universities, etc.), prevention campaigns, posters, internet advertisements, and prevention videos. They also suggested the possibility of using social media for awareness campaigns and using the smartphone to share information. P6 explained that “advertisements on social media could be more viewed because posters are less read by young people.”

To raise awareness among younger audiences, participants proposed conducting interventions in schools because, according to them, human contact enhances understanding. These interventions could take the form of “games and fun activities” (P5). However, “since videos are on a screen, it’s not logical” (P12).

Posters could be displayed “in strategic places like parks, schools, cinemas, pools, libraries, and other public places accessible to children” (P2), but some thought they were less effective.

Some participants suggested that TV ads be broadcast, but they believed that “television is less watched nowadays” (P9).

P3 said that “it would also be necessary to implement psychological follow-ups for all high school students to combat addictions.”

For adults, an email could be sent in the form of a video to raise awareness and enhance understanding “to better comprehend through concrete images” (P9).

Prevention campaigns could also be implemented with striking statistics. P10 believed that “this would help better understand the risks.”.

## Discussion

In modern society, digital screens have become ubiquitous in both work and home environments (Lawrenson et al., 2017). Since the COVID-19 pandemic, online learning has become a standard method of education, and nursing training has not been exempted from this shift (Alliti et al., 2022; Berdida & Grande, 2023). Despite this, our study found that few participants chose to use their smartphones to access online courses. Our findings reveal that all first- and second-year nursing students in the study owned a smartphone, with an average daily usage of 6 h and 15 min ± 21 min. This level of usage exceeds the threshold of intensive daily use defined by the MILDECA, which is more than 4 h per day (MILDECA, 2021). Globally, users spend an average of 145 min per day on social media, approximately 2 h and 30 min (Vera et al., 2023). These results align with our study, where 84 % of participants reported frequent use of social media, particularly among those under 35 years old (De-Sola et al., 2019). These findings are consistent with international data showing high rates of smartphone dependency among university students. For example, studies conducted in South Korea, Spain, and Saudi Arabia report similar patterns of compulsive use, emotional reliance, and interference with daily functioning (Aljomaa et al., 2016; Nikolic et al., 2023). While our sample focused exclusively on nursing students, these parallels suggest that problematic smartphone use may

reflect a broader generational and academic trend, not limited to the nursing field. This highlights the relevance of implementing universal prevention strategies across disciplines, while also considering the specific stressors and clinical contexts of nursing education.

During classes, 98 % of the participants used their phones for either personal or academic purposes. They are aware that their smartphones play a significant role in their lives and that their usage is excessive. Indeed, the MILDECA study also reports that 8 out of 10 individuals admit they do not control their screen usage and spend more time than intended (MILDECA, 2021). These findings are supported by Almutairi’s 2022 study, which shows that 96 % of media usage is for personal purposes (Almutairi et al., 2022). This increased use of social media contributes to dependency and a concerning level of nomophobia among nursing students (Berdida & Grande, 2023). In our study, 86 % of participants exhibited signs of smartphone dependency. Additionally, nearly half demonstrated dangerous behavior, prohibited use, and financial problems linked to smartphone usage. However, few of them take steps to reduce the time they spend on their phones. Similar trends, with lower rates have been observed in international studies, such as the study by Aljomaa et al. (2016) at King Saud University, where 48 % of students exhibited signs of smartphone addiction, highlighting the global nature of this issue (Aljomaa et al., 2016).

Problematic smartphone use has been positively associated with stress, depression, sleep disturbances, and female gender (Lopez-Fernandez et al., 2018). Multiple studies have shown that women tend to exhibit higher levels of smartphone dependency compared to men (Gutiérrez-Puertas et al., 2019). Given that 92 % of our study sample are women, it is logical that similar proportions would be observed in our results.

The most frequently cited negative effects by the participants in our study are dependency and mental health issues. Some participants reported experiencing anxiety, stress, and negative emotional disturbances related to prolonged smartphone use. These results are consistent with Almutairi’s findings (2022) findings, which indicate that individuals with intense usage are more likely to be depressed (Almutairi et al., 2022). Nursing students who are dependent on their smartphones have also reported low self-esteem, increased stress, reduced social support, and decreased sleep quality (Berdida & Grande, 2023).

According to the participants, smartphones also offer significant benefits. This multifunctional device is an important tool for communication, work, and entertainment, providing quick access to information (Berdida & Grande, 2023; Kim & Park, 2019; Serra et al., 2021). Media can facilitate learning by making it more interactive and reflective, thereby enhancing self-efficacy and reducing stress (Cathala & Moorley, 2023). Emerging technologies such as artificial intelligence, augmented reality, and virtual reality are likely to influence future smartphone usage patterns among nursing students (Farghaly Abdelaliem et al., 2023). While these technologies could exacerbate smartphone dependency, they also offer opportunities for enhanced learning experiences through immersive simulations and personalized learning environments (Farghaly Abdelaliem et al., 2023).

Given the current prevalence of screen use, it seems necessary to find an appropriate place for them by integrating them intelligently. Overuse leads to numerous consequences, but appropriate use provides access to a tool that also offers many advantages (Kim & Park, 2019). It is therefore relevant to discuss the role of media in the nursing curriculum (Cathala & Moorley, 2023). Considering all these factors, we must question how to incorporate digital learning methods that use smartphones to diversify and facilitate learning. Training institutes and universities that rely on distance education have become the most affected sectors by screen-induced eye strain. Indeed, our study found that 66 % of participants exhibited subjective convergence insufficiency, necessitating an orthoptic assessment. Yet, only 10 % of participants consult an orthoptist questioning the possible access to care.

Participants in our study suggested that better time management could help them reduce their smartphone usage. Interestingly, while
some students doubted the effectiveness of current prevention strategies, others suggested practical solutions, such as setting time limits and using ergonomic tools, indicating a need for more tailored, student-driven approaches to prevention. In 2022, Alliti proposed integrating courses on the ergonomic use of digital devices into the curriculum and disseminating this information to a broader audience (Alliti et al., 2022). In France, the "Mangerbourger.fr" website offers solutions to reduce screen time, targeting parents (Bouger, 2023). The MILDECA report also provides recommendations for proper use, focusing on children and young people. For adults, the report only suggests physical activity and taking breaks every two hours (MILDECA, 2021). While some studies suggest that primary school children should be prioritized for preventive interventions, most researchers also agree that preventive interventions would be more effective for adolescents, whose values and norms are still developing (Bonnaire et al., 2019). However, only half of the participants in our study believe that strengthening prevention is necessary, despite 86 % of them showing signs of dependency. Many of them believe they know the dangers but are unable to change their habits in this connected world.

These findings suggest a need for integrating smartphone usage guidelines and digital health literacy into the nursing curriculum. Educators should consider not only promoting the pedagogical and clinical benefits of smartphones but also developing targeted strategies to mitigate their negative impacts. This could include specific training modules on screen time regulation, digital self-care, and awareness of the psychological risks associated with overuse. Clinical instructors should also model appropriate smartphone use during placements to reinforce healthy practices. To develop effective prevention strategies, it is crucial to involve key stakeholders—educators, students, families, and public health authorities—in co-designing interventions that address smartphone dependency among nursing students, both at individual and institutional levels.

This study has several strengths, particularly due to its innovative nature. It is the first convergent mixed-methods study to focus on smartphone usage habits among nursing students in France. Beyond providing an initial assessment of smartphone use among nursing students, it also highlights significant concerns regarding student use in general. More than just a diagnosis, it also provides insights into the most effective prevention strategies for this specific population.

However, our study has limitations. Firstly, our sample size is limited, although it is exhaustive. Additionally, 98 % of the participants are women, which may have influenced some results, as women are reported in the literature to be more prone to smartphone dependency. Although women are overrepresented, this is consistent with the demographics of the nursing population, which comprises 88 % women, making our results relevant (Barlet, & Direction de la recherche, des études, de l'évaluation et des statistiques, 2011). To enhance the generalizability of these findings, future studies should replicate this research across multiple nursing schools in different regions of France and in other European countries. A multi-center approach would allow for broader sampling, better gender balance, and the identification of contextual differences in smartphone use among nursing students. Additionally, the self-reported nature of the data may introduce response bias, as participants might underreport their actual smartphone use. Another limitation lies in the use of the CISS-V15 scale, which has not been formally validated in French. However, the translation was carried out by bilingual researchers using a forward-translation approach, with a strong focus on preserving the semantic accuracy of the clinical terminology. Given that the scale assesses concrete clinical signs (e.g., visual fatigue, eye strain, blurred vision), rather than abstract psychological constructs, no significant issues related to cultural or contextual adaptation were identified. Nonetheless, future psychometric validation in a French-speaking population would help confirm the reliability of this version. Also, the PUMPQ scale, which, although specific to our subject, dates back to 2008; its threshold values and items may need updating due to significant technological

advancements in recent years. Nonetheless, it is still used in recent literature in this form. Finally, our study focuses on smartphone use, while other types of screens are also used by our participants and should be considered when evaluating total screen time.

## Conclusion

The smartphone has become an essential tool in our society due to its numerous functionalities. This digital device offers many advantages; however, it also has harmful effects if its use is not regulated. Nursing students have an excessive dependence on smartphones and are aware of it, raising significant public health concerns. The topic of prevention is sensitive within this population. Although students are aware of the short-term effects of smartphone use, they are not sufficiently educated about the long-term risks. Despite their awareness of the risks and acknowledgment of their shortcomings, nursing students doubt the effectiveness of enhanced prevention efforts. Longitudinal studies are needed to assess the long-term impacts of smartphone use on nursing students' health, academic performance, and professional development, especially considering the rapidly changing technological landscape.

## Relevance to practice

This study underscores the widespread use of smartphones among nursing students and its significant implications for both their health and academic performance. With 86 % of participants exhibiting signs of smartphone dependency, the findings highlight an urgent need for integrating digital health literacy into nursing education globally. In an increasingly interconnected world, where digital devices play a crucial role in education and clinical practice, nursing educators must develop targeted interventions that promote healthier usage patterns. Internationally, similar trends have been observed, emphasizing the global relevance of these findings. By incorporating guidelines on ergonomic device use, strategies for managing screen time, and leveraging mobile technology to enhance learning rather than hinder it, nursing programs worldwide can better prepare students for the responsible use of technology. Such initiatives not only aim to improve academic outcomes but also equip future nurses with the skills necessary to navigate the digital landscape effectively and safely in their professional practice.

Supplementary data to this article can be found online at https://doi.org/10.1016/j.apnu.2025.151958.

## CRediT authorship contribution statement

**Anaëlle THEBAULT:** Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Pascale BELONI:** Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Formal analysis, Data curation, Conceptualization. **Jean TONIOLO:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

## Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
## Acknowledgments

We gratefully acknowledge the nursing teachers for their support in setting up this study and sincerely thank all the nursing students who participated.

## References

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