Introduction
Radiotherapy is a common treatment for cancer. However, although radiotherapy is a highly effective treatment, it can also damage normal tissue, leading to side effects. Therefore, the provision of supportive care during treatment and beyond is essential to enable patients to manage and minimise these side effects, enhance their overall well-being and improve their quality of life [Reference Berman, Laird, Minton, Monnery, Ahamed and Boland1].
Supportive care for patients undergoing radiotherapy is commonly delivered through treatment review clinics overseen by a collaborative team of experts. These clinics allow patients to discuss their disease progress and physical and emotional well-being with healthcare professionals. Nevertheless, these review clinics are not without their limitations. However, the scheduled intervals for these clinics may miss the rapid changes in disease progression and side effects that can occur after treatment. Moreover, the constrained time slots allocated to each patient by clinicians could result in hurried appointments, potentially depriving patients of the comprehensive attention they require to address their concerns. As a result, during these review clinics, the treatment-related side effects are often under-reported, and some important supportive care needs of the patients remain unrecognised [Reference Paterson, Jensen, Jensen and Nabi2,Reference Hart, Crawford-Williams, Crichton, Yee, Smith and Koczwara3]. In order to address these issues, several oncology centres are now introducing mobile health (mHealth) technologies to support patients during treatment and beyond.
mHealth involves using mobile devices such as smartphones, tablets, wearable devices, and other wireless technologies to deliver healthcare-related services [Reference Aljedaani and Babar4]. Although a wide range of mHealth technologies are available on the market, until recently, very few applications have been available for patients receiving radiotherapy. However, the coronavirus pandemic has increased the reliance on telemedicine and mHealth technologies to provide follow-up services to mitigate the spread of the disease [Reference Piras, Venuti, D’aviero, Cusumano, Pergolizzi and Daidone5]. As a result, in response to the pandemic, several radiotherapy equipment manufacturers have now integrated mHealth solutions within their radiotherapy workflows, while some other oncology centres have developed their own solutions [6–Reference Sundberg, Wengström, Blomberg, Hälleberg-Nyman, Frank and Langius-Eklöf10]. These mHealth applications can be easily installed on patients’ mobile phones and serve as platforms to deliver information, facilitate the reporting of electronic patient-reported outcome measures (ePROMS), offer symptom feedback, conduct video conferencing and manage appointments effectively. Studies have shown that ePROMS could be used to facilitate the collection of structured data on the treatment-related side effects experienced by the patient [Reference Holch, Absolom, Henry, Walker, Gibson and Hudson9,Reference Sundberg, Wengström, Blomberg, Hälleberg-Nyman, Frank and Langius-Eklöf10]. This data could then be used to enhance symptom monitoring, offer timely interventions and conduct long-term data analytics to improve patient care.
However, although mHealth technologies can empower patients to take charge of their health and facilitate the delivery of personalised care, they are not without their limitations [Reference Aljedaani and Babar4,Reference Janssen, Shafie, Ruder, Buergy and Scafa8,Reference El Shafie, Weber, Bougatf, Sprave, Oetzel and Huber11,Reference Hauth, Bizu, App, Lautenbacher, Tenev and Bitzer12]. It is important to note that some patients, particularly the elderly and those from a low socio-economic and educational background, may not have access to this technology and/or may lack the knowledge to use it [Reference Aljedaani and Babar4,Reference Frutos, Descalzo, Colussi, Rapisarda, Plazzotta and Luna13]. Therefore, full reliance on this technology can create a digital divide that may exclude some populations from benefiting fully. Additionally, the accuracy of health measurements and data collected through mobile apps can vary due to device quality and user input errors. Data security and privacy concerns are also prominent, as sensitive health information transmitted through these apps could be vulnerable to breaches. The effectiveness of mHealth interventions also relies heavily on user engagement and motivation, which can decline over time and can vary widely among patients [Reference Lau, Mitchell and Faulkner14]. Finally, the absence of in-person interaction might hinder the establishment of a strong patient–provider relationship, potentially affecting the quality of care.
The successful and equitable integration of mHealth technologies within healthcare depends on developing services to meet the distinct needs of the patient population [Reference Aljedaani and Babar4]. Although several studies assessed the feasibility of introducing this technology in clinical practice, research examining the patients’ perception of the benefits of introducing a mHealth service designed specifically to support patients undergoing radiotherapy remains limited. Furthermore, the absence of such a service in Malta underscores the necessity to evaluate the patient’s perspective on the feasibility of implementing this technology within the local oncology setting to supplement the current supportive care services provided at the local oncology centre. Therefore, this study aimed to make use of a questionnaire to assess the patients’ perspectives on the use of mobile applications for the provision of supportive care in radiotherapy.
Methodology
Research design
This study employed a descriptive, cross-sectional, non-experimental and quantitative research design using a self-designed questionnaire.
Ethical considerations
Ethical approval was sought and acquired from the University Research Ethics Committee (UREC) of the University of Malta (FHS-2022-00178).
Data collection tool
The data collection tool consisted of an adaptation of a pre-existing questionnaire designed by El Shafie et al. [Reference El Shafie, Weber, Bougatf, Sprave, Oetzel and Huber11]. Several changes were made to the questionnaire to align better with the aim of the study and the local oncology setting (Supplementary Data 1). The questionnaire consisted of five sections. The initial section enquired about the demographics of the participating patients. Subsequently, the second section delved into the utilisation of smartphone technology among patients. The third section aimed to gain insights into the adoption of smartphone technology for health-related purposes. The fourth segment further probed into the participants’ technical familiarity with smartphone usage. Finally, the concluding section employed a Likert scale ranging from 1 (not useful) to 5 (very useful) to gauge the perceived efficacy of distinct mHealth features that could be used to support patients during their treatment. In order to make it easier for the participants to visualise the application, some print screens of a prototype radiotherapy mobile application were included in this section. The last section of the questionnaire enquired about other issues related to the deployment of this service, including security issues, use of data for research purposes, side effects reporting frequency and preferred communication methods with healthcare professionals. The final questionnaire was also translated into the Maltese language.
The questionnaire was tested for content validity to ensure the relevance of the questions in relation to the aims and objectives of the study. Four experts in the field (three radiographers and one lecturer) were asked to rate the relevance and clarity of each question using a Likert scale of 1 (not relevant / not clear) to 4 (very relevant / very clear). In addition, the experts were asked to provide suggestions to improve the questionnaire. The content validity index (CVI) was calculated by summing up the number of experts who rated the question as relevant or clear (rating 3 or 4) divided by the total number of experts [Reference Zamanzadeh, Ghahramanian, Rassouli, Abbaszadeh, Alavi-Majd and Nikanfar15]. The average CVI for the tool was then calculated. The average CVI for the tool was 0·97. However, based on the feedback obtained from the four experts, three questions were reworded to improve clarity.
Data collection process
All new patients having treatment at the radiotherapy department between February 2023 and March 2023 were invited to complete the questionnaire by a radiographer while waiting for one of their radiotherapy appointments. The patients willing to participate in this study were provided with a paper copy of the questionnaire. We opted for a paper format of the questionnaire instead of electronic to enhance the response rate, as it was considered more convenient for patients to complete while waiting for treatment. Moreover, we believed that patients who can use electronic tools were more likely to have favourable opinions on mHealth. This raised the concern that employing an electronic tool could potentially introduce bias to the research findings.
Data analysis
The Statistical Package for Social Science (SPSS) version 23 was used for statistical analysis. The Chi-square test was used to assess the association between the demographic variables (gender, age group and level of education) and categorical variables, while the Kruskal–Wallis test was used to evaluate the impact of the demographic variables on the continuous variables. For all statistical tests, a p-value below 0·05 was deemed statistically significant.
Results
Characteristics of the participants
During the 6-week data collection period, 150 new patients received treatment at the local oncology hospital and were invited by intermediaries to participate in the study. Out of these patients, 39 (26%) responded to the questionnaire. The demographic characteristics of the participants are summarised in Table 1. The male-to-female ratio of the whole cohort was about 5:3. The majority of the participants were aged between the 66 to 75 years category (n = 14, 35·9%) and the 56 to 65 years category (n = 12, 30·8%), which reflects the typical incidence of cancer within the general Maltese population. The most common educational level achieved by the participants was post-secondary (n = 14, 35·9%). The prostate was the most common area of treatment among participants (n = 16, 41%), while brain (n = 2, 5·1%) and gynaecological cancers were the least common (n = 2, 5·1%).
Characteristics of the participants
* indicates statistically significant.
Most participants (n = 32, 82·1%) owned a smartphone device. Although patients above 75 years old were less likely to own a smartphone, the difference was not statistically significant. However, patients with higher educational levels were significantly more likely to own a smartphone.
Habits of smartphone usage
Table 2 summarises the habits of smartphone usage. The Android operating system was the most commonly used system (n = 26, 81·3%), followed by the iPhone (n = 5, 15·6%). Of the 32 patients who owned a smartphone, 20 (62·5%) used WIFI and mobile data connections.
Habits of smartphone usage amongst the participants who owned a smartphone (n = 32)
Most patients were also regular users and generally checked their smartphones for notifications at least once every 2 h (n = 13, 40·6%) or more frequently (n = 14, 43·8%). Only five (15·7%) patients checked their smartphones once every 12 h or once every 2 days. Most patients used their mobile phones as a means of communication, using either voice calls (n = 15, 46·9%) or instant messaging (n = 17, 53·1%).
Some of the participants (n = 14, 43·8%) were already using some mHealth applications on their smartphones mainly for fitness purposes (n = 8, 25·0%), in conjunction with a smartwatch (n = 2, 6·3%) or to remind them to take medications (n = 3, 9·4%).
Knowledge and willingness to get support while using the smartphone
The majority of the participants who owned a smartphone (n = 32) rated their smartphone skills as basic (n = 14, 43·8%) or average (n = 9, 28·1%). Only one of the smartphone owners stated that they could not use it (n = 1, 3·1%). The rest of the smartphone owners rated their skills as either advanced (n = 3, 9·4%) or above average (n = 4, 12·5%). Only one (3·1%) of the smartphone users stated that they were not willing to ask for help to make use of the radiotherapy application.
Out of the seven participants who did not own smartphones, all of them mentioned their inability to use such devices. However, among these individuals, five expressed their willingness to seek help from a family member or friend to access the radiotherapy application. In contrast, two participants mentioned their reluctance to ask for assistance, and one of them specifically noted that they found none of the smartphone features to be useful.
Gender had no impact on the mean usability and assistance score. However, patients with a higher educational background encountered less difficulty using a smartphone (p = 0·015), and older patients tended to need more assistance using a smartphone (p = 0·039) (Table 3).
Mean ± standard deviation score for the perceived ability and need for assistance using a smartphone. The usability was rated using a score of 1 to 5, whereby 1 indicates ‘no skills’ and 5 indicates ‘advanced skills’. Similarly, the need for assistance was rated using a score of 1 to 5, whereby 1 indicates ‘never’ and 5 indicates ‘always’
* p < 0·05.
Readiness to use a mHealth application throughout their radiotherapy (questions 16 to 22)
Irrespective of whether or not they owned a smartphone, the majority of the participants (79·5%, n = 31) found the introduction of a mobile app as an additional supportive care tool during their treatment and beyond as helpful or very helpful, while the remaining 20·5% (n = 8) stated that they were not sure. Gender (p = 0·017), age (p = 0·468) and level of education (p = 0·302) had no impact on the perceived usefulness of introducing a radiotherapy app. The participants were also asked to rate the usefulness of specific mHealth features commonly used on oncology apps using a scale of 1 ‘Not useful’ to 5, ‘Extremely useful’. As shown in Table 4, all features received a mean score of 3 or higher. The ‘alert my doctor when experiencing severe side effects’ feature received the highest score, while the ‘communicating with my doctor via video conferencing’ received the lowest score. However, the response for the latter feature also had the largest standard deviation, indicating that the perceived usefulness of this feature varied widely.
Mean rating score for the proposed radiotherapy app features whereby a score of 1 indicates not useful and a score of 5 indicates extremely useful
Practical issues related to the deployment of this service
The majority of the participants (n = 24, 61·5%) were willing to ask for help if they encountered difficulty using the app, while only three (7·7%) participants stated that they would not be willing to ask for help. The rest of the participants (n = 12, 30·1%) stated that they do not need assistance to use mobile apps.
The participants’ preferred frequency to respond to app-based inquiries about their well-being or general symptoms varied, with 35·9% (n = 14) willing to do so weekly, 23·1% (n = 9) on alternate days, 12·8% (n = 5) daily, 12·8% (n = 5) at the beginning and end of therapy or every other day, and 15·4% (n = 6) as required. In case the physician noted that they were experiencing severe side effects based on their submitted reports, the majority (n = 30, 76·9%) of the patients stated that they preferred to be contacted via phone. A small number of participants wanted to be contacted via email (n = 2, 5·1%), text message (n = 2, 5·1%) or through the app (n = 4, 10·3%).
The majority (n = 35, 89·7%) of the patients agreed to have their anonymised data collected through this app to be used for research purposes. Concerns regarding data security were voiced by 51·3% (n = 20) of patients. The remaining 20·5% of patients (n = 8) were undecided, and 28·2% (n = 11) stated they had no reservations.
Discussion
The successful and equitable integration of mHealth technologies within healthcare relies on the creation of tailored services that effectively address the unique requirements of the patient population [Reference Frutos, Descalzo, Colussi, Rapisarda, Plazzotta and Luna13]. Therefore, in this study, we have explored the feasibility of developing a mHealth app to address the supportive care needs of cancer patients undergoing radiotherapy treatment in Malta.
Access to mobile technology is a key factor that makes the usability of mHealth apps feasible. Traditionally, age used to be seen as a barrier to accessing smartphone technology [Reference Beneito-Montagut, Rosales and Fernández-Ardèvol16]. In recent years, the use of smartphone technology has increased significantly across all age groups, including the elderly population [Reference Vulpe and Crăciun17]. Our findings indicate that although the ownership of smartphones decreased with age, the difference was not statistically significant. Consistent with previous studies, patients with higher education levels were significantly more likely to own smartphone technology and encountered less difficulty using a smartphone [Reference Frutos, Descalzo, Colussi, Rapisarda, Plazzotta and Luna13,Reference Vo, Auroy and Sarradon-Eck18]. However, in contrast with the findings of El Shafie et al. [Reference El Shafie, Weber, Bougatf, Sprave, Oetzel and Huber11] in our study, the influence of education on smartphone ownership appears to outweigh that of age. The use of smartphones amongst the elderly population varies widely across countries [Reference Beneito-Montagut, Rosales and Fernández-Ardèvol16]. Apart from sociodemographic factors, cultural factors, social networks and national policies were also found to have a big impact on engagement with digital technology [Reference Beneito-Montagut, Rosales and Fernández-Ardèvol16,Reference Vulpe and Crăciun17]. Therefore, the deployment of mHealth services should be adapted according to the specific needs of the population being targeted. It is important to note that even when patients have the technology and knowledge to use smartphones, they may lack the necessary health literacy or physical abilities to understand medical content. However, in contrast to traditional information methods like leaflets, mobile technology offers adaptability to cater to diverse user needs. For instance, multimedia elements can be integrated to accommodate patients with challenges such as low literacy, visual impairment or hearing difficulties [Reference Ownby, Acevedo, Waldrop-Valverde and Woodruff19]. Furthermore, mobile technology allows for on-demand information delivery, ensuring users can access relevant and current information precisely when they require it. As a result, this technology has the potential to improve access to medical information among patients with low health literacy.
In our study, the majority of the respondents had access to smartphones. However, their perceived ability to use the technology, as well as the smartphone features used, varied widely. Most patients used their smartphones as a communication tool and checked their smartphones regularly for notifications. Regular use of smartphone technology is essential for medical staff to reach patients via this technology. It is important to note that most of the respondents owned either a smartphone based on standard operating systems such as Android or iPhone; they were not heavy app users and generally made use of apps that could run smoothly, even on older phones. Elderly patients may find it harder to remain up-to-date with the latest smartphone technology. Therefore, the design of the mHealth app should kept as simple as possible and should be based on a text service and make minimal use of data to ensure that it can run smoothly even on older devices. Alternatively, access to the mHealth app could be offered through a browser that can be accessed on mobile phones.
An important finding of the study was that most of the respondents who did not own a smartphone still displayed a keen interest in utilising the radiotherapy app. Similarly to the study of El Shafie et al., individuals who lacked smartphone ownership in our research were willing to seek assistance in gaining access to this technology, thus highlighting the need to involve caregivers to aid patients unable to utilise the app independently [Reference El Shafie, Weber, Bougatf, Sprave, Oetzel and Huber11]. On the whole, these findings are encouraging, as they show that the use of mobile apps does not exclude individuals who lack access or knowledge of such technology. Nevertheless, not all patients have a readily available social support network. Thus, it is important to emphasise that this technology should complement rather than replace traditional services. Healthcare professionals should empower patients to make informed choices about the use of mHealth services. Moreover, healthcare professionals should offer training to ensure that patients understand the importance of safeguarding their personal data. It is ultimately up to the patient to decide with whom they want to share their medical information. As shown by Vulpe et al. [Reference Vulpe and Crăciun17], the use of mobile phones is becoming more established, even among older people. In the near future, almost all elderly patients will have access to technology. The demand for mHealth services amongst the population is expected to increase as patients are increasingly more willing to manage their health and are now demanding more efficient access to healthcare resources. Not surprisingly, some patients in our study were already using several mHealth technologies aimed at maintaining a healthy lifestyle.
Since there is currently no mobile application designed for radiotherapy purposes available locally, we designed some wireframes to illustrate the various features of a radiotherapy application. Among the app’s features, ‘alert my doctor when experiencing severe symptoms’ and ‘appointment management’ were identified as the most useful. On the contrary, the videoconferencing feature received the lowest rating despite the fact that participant opinions on this aspect varied widely. Likewise, the inclination to report side effects varied significantly among participants. Numerous studies have shown that while patients might display initial interest in utilising an app, their engagement tends to diminish over time as their health improves and the need to use the app wanes [Reference Lau, Mitchell and Faulkner14,Reference Gebert, Schindel, Frick, Schenk and Grittner20,Reference Amagai, Pila, Kaat, Nowinski and Gershon21]. These findings underscore the necessity of creating an adaptable application that caters to the unique needs of each patient while also emphasising the importance of fostering patient engagement in the app’s design and functionality [Reference Vo, Auroy and Sarradon-Eck18]. Most respondents preferred to be contacted via phone in case the doctor noted that they were experiencing severe side effects from the reports provided. This finding underscores the importance of maintaining human communication channels alongside technological solutions to ensure optimal patient care and response during critical situations.
Another notable discovery was that not all patients expressed willingness to share their data for research purposes. Similarly to the study of Vo et al. [Reference Vo, Auroy and Sarradon-Eck18], the patients in this study also reported that they had some reservations about the security of this app. Therefore, the app design should also address these security concerns to safeguard patient data and thus increase the level of trust and, ultimately, user engagement.
The study has some limitations that have to be acknowledged. The short data collection period available for this study and the low response rate limited the sample size of our study and ultimately limited the generalisability of our research findings. Furthermore, the small sample size may have led to the exclusion of viewpoints from patients, particularly those with lower levels of education who might have been less inclined to participate in the questionnaire. Lastly, despite the provision of print screens illustrating the technology’s appearance, it is important to note the patients did not have first-hand experience with the technology. Consequently, further research is necessary to evaluate the service’s feasibility following the deployment of the mobile app. As the digital divide among different age groups is expected to continue to decrease in the coming years, further research is required to assess the long-term impact of this application.
Conclusion
Overall, the findings indicate that most of the patients included in this study have access to mobile technology and are willing to use the mobile app as an additional supportive care tool. Nonetheless, the diversity of patient perspectives regarding the technology underscores the importance of developing a mobile app that can be easily tailored to meet individual patient needs.
Supplementary material
To view supplementary material for this article, please visit https://doi.org/10.1017/S1460396923000407.
Acknowledgements
The authors would like to thank all the professionals who gave their invaluable support during data collection, without whom this study could not have been completed. Gratitude goes to Prof. Liberato Camilleri for his guidance in the statistical analysis of data. The authors also would like to thank Mr. Vimalesan Murugesan, Ms. Clarissa Borg and Ms. Claire Farrugia for providing print screens of their prototype radiotherapy application and for reviewing the questionnaire.
Author contributions
Ms. Maria Stella Sammut conceived the study protocol collected the data, analysed the data and wrote the manuscript.
Dr. Susan Mercieca supervised the project and edited the final manuscript.
Financial support
This research received no specific grant from any funding agency, commercial or not-for-profit sectors.
Competing interests
The authors have no conflict of interest to declare.
