Background and rationale

Professional organizations worldwide are increasingly recognizing the importance of investing in quality assurance measures aligning closely with international standards that emphasize not only the quality of products and services [1], but also the quality of work life (QoWL) [2]. The role of workplace strategies, processes, and environment has been proven in stimulating employee job satisfaction, well-being, organizational effectiveness and overall productivity [3,4]. By adhering to stringent quality assurance directives, professional organizations strive to ensure that workplaces prioritize factors such as ergonomic design, adequate rest intervals, and access to healthcare services, all of which are essential components of promoting a healthy and sustainable work environment [5]. Work-related musculoskeletal disorders are the most common occupational disorders worldwide [6]. Neck pain (NP) is a major health problem in office workers with a one-year prevalence of 58% among data processing workers, and 33% among other office workers in the UK [7], and of 69% in Belgium [8]. Office workers have been reported to have a higher incidence of chronic pain and transition to persistent or recurrent NP over a one-year period [9]. This disorder is responsible of disability, impaired quality of life (QoL) and QoWL, with a great socioeconomic burden [10,11]. Recognizing the prevalence and the burden of this issue in modern office settings, professional organizations are implementing targeted strategies to address concerns and provide necessary support. These interventions may include ergonomic measures to optimize workstation setups, regular breaks, educational initiatives, and exercises [12].

A considerable number of studies focusing on the effects of exercise for NP in office workers have been conducted [13,14]. The evaluation of the effectiveness of various therapeutic interventions in and out the workplace, aiming to prevent or alleviate NP has been reported, including proprioceptive exercises, stretching, and dynamic-resisted strengthening exercises [15–17]. Until early June 2025, best evidence suggests that self-management for NP is recommended to include education and reassurance along with regular exercise and advice to maintain daily activities [18,19]. It has been proven that self-exercises focusing on strength and endurance training, as well as self-mobilization, were effective in reducing pain and improving function and QoL in NP patients [20]. Adherence to rehabilitation self-exercises poses a significant challenge in managing NP [21]. Patients often struggle to consistently follow prescribed exercise regimens due to factors such as lack of motivation, forgetfulness, or the perceived complexity of the exercises [22]. This non-adherence can hinder the effectiveness of rehabilitation programs and impede patients’ progress toward recovery [22]. Recognizing the need for innovative solutions, a growing interest is in incorporating new tools, such as artificial intelligence (AI) embedded smartphone application (app), into rehabilitation strategies [23]. These apps offer a promising avenue to enhance adherence by providing personalized and interactive exercise programs [24]. They represent a mode of information delivery that is suited to the information technology literate population who are familiar with and frequent users of information technology devices [25], and can be particularly useful in a working population where it may be difficult to find time to attend physiotherapy or educational sessions. While previous studies have explored the effectiveness of self-directed exercises for NP [20], some have made a direct comparison between traditional self-directed methods and smartphone-guided interventions [26]. Notably, a pilot randomized experiment comparing posture correction exercises from brochures and neck workouts from apps was carried out by Lee et al. [26]. The aforementioned study was constrained, nevertheless, by its small sample size (n = 20) and the absence of follow-up evaluations for primary and secondary outcomes, which were only assessed at baseline and just after the intervention [26].

Smartphone-guided exercises offer a potential solution by providing personalized guidance, real-time feedback, and increased motivation, which may lead to improved adherence and clinical outcomes. Thus, the use of a smartphone app to deliver a self-managed exercise and education program for office workers with chronic NP may be effective, demonstrating organizations commitment to safeguarding the health, QoL and QoWL of workers in today’s (i.e., June 2025) digitally driven workplaces.

Objective

The objective of this study is to explore the differences in self-management using two workplace-based interventions: a smartphone app consisting of personalized neck exercises compared to conventional approach (i.e., self-exercises program on paper) in chronic NP office workers. We hypothesize that a smartphone app offering personalized neck exercises will provide superior immediate and short-term improvements in pain relief, functional ability, and QoL for office workers with chronic NP compared to conventional self-rehabilitation methods. Additionally, this approach is anticipated to address the challenge of adherence to self-exercise routines in managing this chronic condition.

Trial design

A single blinded two-armed randomized controlled trial will be conducted. Participants will be assigned randomly to either the interventional group (IG), utilizing the smartphone app, or the control group (CG).

Fig 1 details the schedule of enrolment (Recommendation for interventional Trials).

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Fig 1. Participants timeline: schedule of enrolment, interventions, and assessments (Recommendation for interventional Trials (SPIRIT)).

SF12: Short form-12. W: Week.

https://doi.org/10.1371/journal.pone.0329863.g001

Fig 2 lists the flowchart of the study design according to “consolidated standards of reporting trials” guidelines [27].

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Fig 2. CONSORT (consolidated standards of reporting trials) follow diagram of the progress through the phases of a parallel-randomised trial of two groups. app: Application.

NDI: Neck disability index. PI-NRS: Pain intensity number rating scale. QoL: Quality of life. SF12: Short form 12.

https://doi.org/10.1371/journal.pone.0329863.g002

Study setting

The study will be conducted at the University of Monastir (Tunisia). The latter is a public administration having 70 office workers, with an average (minimum-maximum) age of 45 (30–63) years, possessing an average work tenure of 15 years, engaging in eight hours of desk and computer work daily, five days a week.

Recruitment

To recruit participants for the trial, a comprehensive digital survey will be distributed to office workers to identify individuals experiencing NP from September 1 to October 30, 2025. The survey clearly explains the trial and its objectives and expresses that all information will be analyzed with strict respect to anonymity, confidentiality, and medical secrecy. By ticking a checkbox, individuals will express their voluntary commitment to join the study, and will have access to questions identifying general information (e.g., age, sex, comorbidities, work seniority, average number of daily hours spent in front of computer); the existence of NP, duration of symptoms, pain intensity, which will be evaluated via a pain intensity number rating scale (PI-NRS), medication (e.g., pain killers, physiotherapy). Individuals identified as potentially suffering from this condition will subsequently be invited to undergo a thorough physical examination by a specialist in the field (SS in the authors’ list) to confirm the diagnosis.

Eligibility criteria

Inclusion criteria will be the presence of a chronic NP lasting for more than three months, and a PI-NRS pain level at baseline assessment ≥ 3. Non-inclusion criteria will be acute NP, specific causes of NP (e.g., chronic inflammatory diseases), spine trauma or surgery, cervical radiculopathy or myelopathy, and physical therapy treatments in the last six months before baseline assessment.

Informed consent

One researcher (SS in the authors’ list) will obtain written informed consents from all eligible participants before allocation. Participants will be clearly informed about the study aims and potential benefits, and that they will be free to withdraw the study at any point with no need to give any specific reason for that. They will be asked if they agree to the use of their data. This trial does not involve collecting biological specimens for storage.

Intervention

Intervention description.

All participants of the IG and the CG will receive an educational session explaining the intervention details and an initial training session on how to perform exercises along with advices on proper position and ergonomics to be applied during daily work (i.e., ensure your workstation setup promotes good posture, with the monitor at eye level and the keyboard and mouse positioned close to your body; take regular breaks from sitting, standing, or staring at screens to stretch and move around). Participants will be instructed to carry out exercises at the same time daily, three to five days per week for 12 weeks.

For the CG, the rehabilitation program is delivered on a paper sheet containing pictures of exercises with a written explanation in French language with the number of sets and repetitions. Participants assigned to the IG will use the smartphone app. The latter includes the rehabilitation program with a detailed explanation in French language with the number of sets and repetitions.

Based on the findings of some papers [13,14], which focused on the effectiveness of exercise interventions for office workers with NP, we selected sets of self-exercise program with detailed explanation suitable for this population (Table 1).

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Table 1. Neck self-exercises program.

https://doi.org/10.1371/journal.pone.0329863.t001

Description of the developed smartphone app

The smartphone app is designed using Android Studio and Flutter. It integrates advanced features, including an intuitive interface and an easy-to-use solution for all users (i.e., patients and healthcare professionals). Each participant in the IG will receive a code and password to log into the app and to register some general information such as age and sex. All assigned authentications will be recorded in a database created by Firebase. The app features several integrated modules:

1. (i) Basic information about NP and ergonomic advice on proper neck position during daily work,
2. (ii) Series of evaluation questions including pain assessment (PI-NRS) and the impact of NP on participant’s daily functioning,
3. (iii) Appropriate sets of exercises with videos and instructions,
4. (iv) Daily reminder feature to prompt users to engage in their prescribed exercises consistently, and
5. (v) Evaluation report providing feedback on user’s state and tracking their adherence.

To record participants’ engagement with the program, adherence will be monitored using a user activation tracking system assessing the frequency and duration of app use. The application is linked to the Cloud and Firebase tool enabling the therapist to visualize participants’ results in a graphical form. Exercises included are automatically adapted at each use of the app according to the participant’s condition and evolution. Indeed, the app is designed to analyze the data collected before each use from the evaluation questions based on an AI algorithm and to provide personalized exercise recommendations. To monitor and ensure participant engagement, app usage analytics will be utilized to track interaction patterns and identify any drop-offs in usage. Participants will also have access to technical support to troubleshoot any issues with the app, ensuring minimal disruption. Additionally, scheduled check-ins with participants will be conducted to address potential barriers to engagement and encourage continued adherence to the intervention protocol.

The diagram block (Fig 3) illustrates the app, which is composed of distinct therapist and participant interfaces.

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Fig 3. Smartphone application diagram block.

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Criteria for discontinuing or modifying allocated interventions

Any requests from potential participants to discontinue participation in the intervention or follow-up will be accommodated without requiring any explanations.

Strategies to improve adherence to interventions

Participants of both groups will receive a daily notification on their mobile phone to maximize adherence. Participants using the Smartphone app will have access to relevant information, previously described (e.g., participant evolution) to encourage them to continue with the proposed protocol.

Relevant concomitant care permitted or prohibited during the trial

Participants will not be allowed to participate in other trials during the study period. They will be asked not to receive any extra intervention for NP during the intervention period including physiotherapy. They will be instructed to avoid using pain medication; however, if they will do, they will be asked to report the type and frequency of usage. The frequency of pain medication use before and after the intervention will be tracked to offer a more detailed understanding of pain relief and the effectiveness of the intervention.

Outcomes

The main outcome measure is pain intensity, evaluated according to the PI-NRS [28–30]. The latter is a commonly used tool to measure a person’s pain intensity [28–30]. It is simple, quick, and widely accepted in both clinical and research settings [28–30]. Participants will be asked to indicate their current level of pain on a line from 0 (no pain) to 10 (unbearable pain) [28–30].

Secondary outcome measures are function (i.e., neck disability index (NDI)), QoL and participants’ adherence to self-exercises. The French validated version of the NDI will be used to assess the impact of NP on individual’s daily functioning [31]. The scale consists of a set of questions addressing various aspects of NP and its influence on activities such as personal care, lifting, reading, working, and recreation. Participants will be asked to rate their level of disability or limitation on a scale for each activity. The total score provides a quantitative measure of the perceived disability associated with NP, with higher scores indicating greater impairment [32]. The French validated version of the short form 12 (SF-12) will be used to measure health-related QoL. The SF-12 is a shorter version of the short form 36, which assesses an individual’s physical and mental well-being. The SF-12 is often utilized in health research, clinical practice, and population health studies [33,34]. Adherence will be measured via two methods. First, it will be evaluated using a frequency-based response scale (i.e., never, seldom, often, almost always, and always) adapted from the adherence scale of Sluijs et al. [35]. Adherence will then be treated as a dichotomous variable (i.e., adherent or not adherent), participants who will report “always” or “almost always” will be considered adherent [21]. Second, adherence will be measured based on the frequency of exercise sessions completed. Participants who engage in exercises three or more times per week will be categorized as demonstrating “full adherence” whereas those who exercise twice per week or less will be considered to exhibit “partial adherence”. These combined methods ensure a comprehensive evaluation of adherence, capturing both self-reported behavior and objective frequency of exercise.

Participant timeline

Participants will be assessed at 4 and 12 weeks. A schematic diagram for participants’ timeline is shown in Fig 1.

Sample size

The null hypothesis [36] was H₀: m₁ = m₂, and the alternative hypothesis was H_a: m₁ = m₂ + d, where “d” is the difference between two means and n₁ and n₂ are the sample sizes for the interventional and control groups, such N = n₁+ n₂. The sample size was estimated using the following predictive equation [36]: , where

• “n” is the number of participants;
• “Z_1-α/2” is the normal deviate at a level of significance (type I error at 2-sided = 1.96 at 5% level of significance);
• “Z_1-β” is the normal deviate at 1-β% power with β% of type II error (0.84 at 80% statistical power);
• “d” is the expected difference between average changes of PI-NRS from two groups; and
• “s” is the common variance (standard deviation) of PI-NRS means of two groups. “s” was calculated according to the following formula [36]: .

“d” and “s” values were obtained from a previous South Korean study [37] including 34 patients (17 in the IG and 17 in the CG). The patients in the IG performed exercises using a video-based app system, whereas those in the CG performed exercises using an image- and text- based printout [37]. In-home training was implemented for six weeks in both groups [37]. The NP intensity was measured before and after the intervention via the PI-NRS. Kim and Shin [37] reported that within both groups, the PI-NRS improved significantly after the intervention. At the end of the intervention, PI-NRS’ changes (expressed as means ± standard deviation) for the IG and CG were 2.23 ± 1.85 and 1.65 ± 1.26, respectively (“d” is therefore equal to 0.58 (0.58 = 2.23 - 1.65). Based on the aforementioned study [37], where n₁ = 17, n₂ = 17, s₁ = 1.85, s₂ = 1.26, “s²” is equal to 2.51 [2.51= [(17-1) x 1.85² + (17-1) x 1.26²]/(17 + 17-2)].

The injection of the aforementioned data in the predictive equation gave a sample size of 117 participants. However, since our study involves a finite population (i.e., a population with a limited number of participant), a correction was applied to the sample size [36]. The number of participants to be included after correction is given by the formula , where “ n’ ” represents the corrected sample size, “ N ” is the size of the finite population (which is 70 office workers in our study), and “ n ” is the sample size calculated from the standard formula (n = 117). Therefore, the corrected minimum sample size (n’) is equal to 44 participants [44 = (70 x 117)/(70 + 117)]. Assuming a 10% absence during the end of the intervention period, 50 participants (25 in each group) were determined to be the amended sample size [50 = 44/ (1–0.1)].

Methods: Assignment of interventions

Methods: Data collection, management, and analysis

Data management

All participants will be assigned a study identification code linked to their personal information that will be stored in a protected database accessible only to the principal investigator (SS in the authors’ list).

Statistical methods

All data will be analyzed using SPSS version 23. The Shapiro-Wilk test will evaluate the normal distribution of quantitative data. If the distribution will be normal and the variances are equal, the quantitative data will be reported as mean ± standard deviation, and 95% confidence interval. Otherwise, data will be expressed as median (interquartile range). Categorical data will be expressed in percentage frequencies. The between-group differences in the mean changes of the outcome measures (PI-NRS, NDI, SF-12, adherence) after intervention will be calculated using repeated measures mixed models with participants from the IG as random effect, and group (IG or CG) and time (baseline, four weeks, and 12 weeks) as fixed effects, and with adjustments for baseline imbalance. The Spearman rank test or Pearson product-moment correlation coefficient analysis will be used to analyze the associations between clinical data and mean changes in the outcome measures. Two-sided statistical significance is set at a p value < 0.05.

Oversight and monitoring

Ethics and dissemination

Study limitations

A notable limitation of this study could be its relatively brief follow-up period of 12 weeks. Extending the follow-up duration could offer greater insights into efficacy and participant adherence over a longer period. Subsequent studies should take this into account to comprehensively assess effectiveness and participant commitment over extended periods. Another limitation is the potential bias introduced by varying levels of participants’ familiarity with mobile apps and technology literacy, which could influence adherence rates. Future studies should consider stratifying participants by technology proficiency or providing standardized training to minimize these biases. Additionally, the assessment of the cost-effectiveness of the intervention proposed in this study will not be undertaken.