Introduction
Cancer continues to be a significant global health concern, with its prevalence steadily increasing worldwide [1]. Gynecologic cancers, encompassing malignancies of the uterus, ovaries, cervix, vagina, and vulva, represent approximately 20% of diagnosed cancers in women [2, 3]. Gynecologic cancers accounted for 1,398,600 new cases, representing 7.29% of all new cancer cases worldwide in 2020 [4]. Advancements in cancer detection and treatment have considerably increased the lifespan of cancer patients. However, their quality of life has not improved to a similar degree [5].
Gynecologic cancer patients experience various complications during the disease process, including fatigue, immune system suppression, pain, nausea, sleep disturbances, vaginal discomfort, changes in bowel and bladder function, menopausal symptoms, sexual dysfunction, and early menopause. Additionally, they face challenges such as coping with cancer, the shock of diagnosis, fear of disease recurrence, reactions from their families and friends and suicidal ideation. These factors can lead to high levels of anxiety in these patients and may contribute to reduced quality of life [6‐14]. Up to one-third of patients diagnosed with cancer report significant anxiety symptoms. This anxiety is linked to ineffective coping strategies, reduced adherence to treatment, and increased utilization of healthcare services [15‐17]. Anxiety among cancer patients can lead to sleep disturbances, hinder treatment progress, and ultimately, alongside disease-related complications and treatment approaches, can diminish their overall quality of life [18‐24]. Von Gruenigen et al. reported that individuals with cancer experience decreased quality of life in physical, functional, and emotional dimensions [25]. Research has shown that individuals diagnosed with gynecologic cancers have a lower quality of life and higher levels of anxiety. Although previous studies have explored interventions targeting quality of life and anxiety in gynecologic cancer patients, these challenges remain unresolved [7, 26‐30]. Consequently, it is essential for nurses to embrace their role in offering support by engaging in effective communication with patients and providing them with the vital knowledge and training needed to enhance the quality of life for women facing cancer [31].
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One promising approach to enhance patients’ quality of life and provide effective education is through the utilization of nursing theories and models. The continuous care model, which emphasizes ongoing education and care, was introduced and evaluated by Dr. Ahmadi in 2001 [23]. This model includes four stages: familiarization, sensitization, control, and evaluation [32]. The primary goal of the continuous care model is to establish a flexible, dynamic, and continuous care connection between nurses and patients, aiming to improve patient well-being, which is in line with the complexities of chronic diseases [33, 34].
The geographical distance of many cancer patients from treatment facilities poses barriers to receiving continuous care, leading to more frequent trips for medical services and simultaneously increasing costs, pain, and discomfort. Limited access to health-related information and healthcare providers can result in unfavorable treatment outcomes, increased psychological distress, reduced quality of life, and compromised physical functioning among patients [35‐37]. Hence, the implementation of the mobile application-based continuous care model may be effective in enhancing quality of life and addressing the challenges encountered by these patients. Online interventions have become increasingly recognized as effective strategies for improving health outcomes in patients with gynecological cancer [38]. Moreover, patients who are well informed and actively engage in their own care tend to receive better treatment. Additionally, lifestyle changes can improve quality of life and lower the chances of cancer recurrence for survivors of gynecological cancers [39, 40]. This study’s merits include reducing unnecessary in-person visits to healthcare establishments, saving time for both patients and medical staff, fostering effective patient‒nurse communication through App feedback, enabling round-the-clock inquiries, convenient access to care details, and the possibility of reviewing education. Given the scant attention given to gynecologic cancers in previous studies and the absence of positive outcomes from interventions targeting quality of life and anxiety among gynecologic cancer patients and the lack of an association or support group for patients diagnosed with gynecological cancers in the setting in which the study was conducted, this research aims to explore the impact of the mobile application-based continuous care model on the quality of life and anxiety levels of gynecologic cancer patients receiving care at the medical facilities of Shahrekord University of Medical Sciences in 2023. We hypothesized that the implementation of a continuous care model utilizing a smartphone application would significantly increase quality of life and lead to a substantial reduction in anxiety levels in gynecologic cancer patients compared with those receiving only routine care.
Methods
Study design
we conducted a two-group pre/posttest randomized controlled trial evaluating the impact of a continuous care model utilizing a smartphone application on quality of life and anxiety levels among gynecologic cancer patients. The study was conducted on 70 patients referred to educational and therapeutic centers affiliated with the Shahrekord University of Medical Sciences (oncologist clinics and two university-affiliated hospitals named Kashani and Hajar hospitals in Shahrekord, Iran) from February 2024 to July 2024. The study was approved by the ethics committee of Shahrekord University of Medical Sciences, with the ethics code IR.SKUMS.REC.1402.135. To register this research as a clinical trial in the Clinical Trial Registration Center of Iran, the code IRCT20231107059977N1 was obtained. The study has been reported in line with the Consolidated Standards of Reporting Trials (CONSORT) Guidelines to structure the methods and reporting of the results [41].
Sample size calculation, sample randomization and blindness
The study sample size according to a similar study [42], with α = 0.05, β = 0.2 and a dropout rate of 20%, was estimated to be 35 patients in each group. The final adjusted sample size for our study was 70 in total. Patients were randomly assigned to the intervention (n = 35) or control (n = 35) group via web-based Research Randomizer Software. In this software, a number from 1 to 10 was generated each time; if an odd number was produced, the patient was placed in the intervention group, and if an even number was generated, the patient was placed in the control group. As the interventions in the two groups could not be fully blinded, this study was a single-blind randomized controlled trial. While the patients and the investigator were aware of group allocation due to the educational nature of the intervention (i.e., they knew whether they received the App), all outcome assessors and data analysts remained blinded to the group allocation.
$$\:N=\frac{({{S}_{1}}^{2}+{{S}_{2}}^{2}){({Z}_{1-\frac{\alpha\:}{2}}+{Z}_{1-\beta\:})}^{2}}{{({\mu\:}_{1}-{\mu\:}_{2})}^{2}}=\frac{(286.96+400){(1.96+0.84)}^{2}}{192.65}=27.95$$
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In the second month of the intervention, one patient from the intervention group unfortunately passed away, and another patient from the control group was removed because of noncompliance with questionnaire completion. As a result, 68 patients remained in the groups.
Participants and settings
The inclusion criteria were willingness to participate; suffering from gynecologic cancers (recently diagnosed by a specialist); aged 18–68 years; the ability to perform personal tasks independently; the ability to use smartphones; having an Android smartphone; having internet access; the absence of cognitive, psychological, hearing, and vision disorders; having no history of other cancers; proficiency in reading and writing in the Persian language; and the possibility of communicating with the patient after discharge. The exclusion criteria were unwillingness to continue cooperating, incomplete attendance in educational interventions (using the application less than twice a week), incomplete questionnaires, use of other care programs outside of the study, severe disease complications, development of other cancers or psychological disorders and patient death. In the recruitment process of the study, 95 patients did not meet the eligibility criteria, while 47 patients declined to participate.
We recruited a total of 21 patients from oncologist clinics, which primarily provided limited educational services, focusing mainly on consultations with oncologists, prescription of medications, and administration of chemotherapy. Additionally, we collected data from 24 patients at Kashani Hospital and 23 patients at Hajar Hospital in Shahrekord, Iran. These hospitals included oncology and surgical wards from which participants were recruited. At these facilities, patients received medications and chemotherapy, along with daily visits. While nurses occasionally provided brief oral educational sessions when time permitted, there was no established program for patient education at these hospitals.
Data collection
The data collection tools used consisted of a demographic questionnaire, the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30), and the Spielberger State-Trait Anxiety Inventory (STAI). Data were collected through questionnaires, which were completed before, immediately after, and two months after the intervention for both groups.
Measurement
Demographic information questionnaire
The demographic information questionnaire included age, marital status, number of children, education level, occupation, time spent from diagnosis, and living in a city or village.
EORTC Core Quality of Life Questionnaire (EORTC QLQ-C30)
The EORTC QLQ-C30 is a 30-item questionnaire that measures quality of life in 5 dimensions of functional dimensions, including physical functioning, role functioning, emotional functioning, cognitive functioning, and social functioning, as well as 9 symptom domains, including fatigue, pain, nausea and vomiting, dyspnea, diarrhea, constipation, insomnia, appetite loss, and financial difficulties resulting from the disease, and a general quality of life dimension [43]. Each dimension is scored on a scale from 0 to 100. Higher scores in the functional and general quality of life dimensions indicate better performance or better quality of life. In the symptom domain, a higher score indicates a greater presence of that symptom or problem. The reliability and validity of the Persian version of the QLQ-C30 questionnaire have been examined in previous studies. Saffari et al. (2005) conducted a study on 132 patients and reported that most domains had adequate reliability, with Cronbach’s alpha coefficients exceeding 70%, and that all multi-item dimensions had good validity [44].
Spielberger state-trait anxiety inventory (STAI)
The STAI is a 40-item self-report instrument that measures adult anxiety. The STAI comprises two 20-item subscales, state and trait anxiety. The state anxiety subscale evaluates the current anxiety status, whereas the trait anxiety subscale assesses how individuals generally and usually feel [45]. Each item is scored on a 4-point Likert scale, resulting in a total subscale score of 20–80, with higher scores denoting higher anxiety levels [46]. This questionnaire was introduced by Spielberger et al. in 1970. An overall median Cronbach’s alpha of 0.86–0.92 confirmed the internal consistency of this instrument in normative samples [47]. A reliability coefficient of 0.89 to 0.90 was reported in the literature for the STAI-T, and 0.86 to 0.95 was reported for the STAI-S in diverse populations and cultures. A Cronbach’s alpha of 0.886 for trait anxiety and 0.846 for state anxiety also confirmed the internal consistency of the Persian version of the STAI [47, 48]. In 1993, Panahi Shahri examined the psychometric properties of this questionnaire in a population in Iran and obtained a correlation coefficient of 0.76 for the state anxiety scale, as well as a reported alpha coefficient of 0.90 for the state anxiety scale [49]. In the study conducted by Setareh and colleagues to determine the validity of the Persian Spielberger anxiety questionnaire, the content validity method was used, and the reliability was determined via Cronbach’s alpha method, with a value of 0.91 obtained [50].
Study procedure
The study involved two phases: (1) development of the smartphone application and (2) execution of the intervention.
The first phase: development of the smartphone application
In the initial phase of the study, we gathered educational material tailored for patients with gynecological cancers by examining relevant textbooks and literature and the website of the American Cancer Society [51]. This material was then reviewed and endorsed by a team of experts, including nursing faculty members, oncology specialists, psychologists, and sports physiology graduates. They assessed the content on the basis of its relevance, necessity, usefulness, and effectiveness. The educational material was refined on the basis of their feedback and ultimately approved before being passed on to the software engineer.
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To create the application, a collaborative meeting involving the software engineer, researcher, advisor, and consulting professors was held. They discussed the expectations and desired features of the application. After the initial version of the application was evaluated and adjusted by the research team in a subsequent meeting, the final version of the mobile application named “Shafayar”, which means something that helps to cure the disease, was developed and reapproved. The application was subsequently tested by experts in programming and information technology, along with academic faculty members, to assess its practical functionality. Following their input and necessary adjustments, the final version of the application was completed.
The mobile application was designed to be user friendly, allowing for both online and offline use. Its main menu featured options for profile information, entering clinical data, receiving weekly patient status reports, accessing an online clinic for virtual consultations with nurses, and a relaxation section with calming music, yoga videos, and meditation guides. Users can easily interact with the researcher through a message box icon. There was a search box to quickly find specific information in the app. On the homepage, educational content was divided into sections covering topics such as chemotherapy, common patient queries, the introduction of different gynecological cancers and their care, gratitude practices, yoga, meditation, and lifestyle tips. These sections provide detailed information on cancer symptoms, risk factors, diagnostic methods, treatment procedures, and practical advice for managing various symptoms and side effects. The content was presented in different forms, including images, animations, audio files and video clips. The participants in the intervention group were given a link to download the application onto their mobile phones. A tutorial guide video was sent to patients after installation. Upon logging in with a unique username and password, users had immediate access to all educational resources. The application facilitated communication with healthcare providers during interventions and encouraged patients to submit their weekly reports through the app. Researchers could track user activity and App usage statistics for research purposes through the management panel. Usage statistics were monitored to ensure adherence to the intervention.
The second phase: execution of the intervention
In the second phase of the study, detailed explanations of the research goals were provided to individuals, and their written informed consent was obtained if they were willing to participate. Written consent was obtained from all patients. The intervention consisted of a continuous care model implemented through a mobile phone application for the intervention group, in addition to usual care. The control group received only the usual care, which includes the standard support provided by nurses throughout hospitalization and prior to discharge. This standard care comprises comprehensive health assessments and routine oral education. Although Hajar and Kashani Hospitals had a designated unit for patient education, its effectiveness was limited. Patients occasionally received outreach calls to discuss their condition, but such instances were neither common nor systematically applied to all patients. Additionally, in oncologist clinics, nursing education was lacking, with a primary focus on consultations with oncologists, medication prescriptions, and chemotherapy administration. The questionnaires were completed online with a link sent to patients. The intervention group received a continuous care model via a mobile application. However, the control group only received routine care. The continuous care model is a nursing care model that was first developed by Ahmadi et al. in Iran in 2001. This model consists of four steps: orientation, sensitization, control, and evaluation [33].
The orientation stage involved explaining study goals, setting expectations for nurses and caregivers, explaining study protocols, involving patients and their families in care, and emphasizing the importance of continuous cooperation. A private 30–45 min session was held with each patient and her family to identify the patients’ problems and to motivate them to continue the cooperation until the end of the study. The mobile App was installed in this session, and necessary instructions were provided alongside addressing any queries or concerns. Patients were reminded to use the program at least twice a week. Additional guidance was offered to ensure that patients could use all the features effectively. In this session, patients completed questionnaires. The sensitization stage included nursing interventions administered over eight weeks through the mobile application, requiring patients to engage with the content at least twice weekly. This stage focused on understanding the disease, its constraints, explaining disease complications, and the importance of treatment adherence and explaining the problems caused by the lack of attention to the goals and instructions. The control stage focused on evaluating and maintaining care. Continuous counseling was provided, and patient status was monitored weekly through a dedicated section in the app. Communication with nurses was facilitated through messaging and online clinic features. Researchers’ contact information was available for patient inquiries. During the evaluation stage, the impact of the interventions and follow-ups was assessed via online quality of life and anxiety questionnaires immediately and two months after the intervention. The control group also completed the questionnaires online at both time points.
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Statistical analysis
The data were analyzed via SPSS 24 software, descriptive statistical parameters (frequency, mean, standard deviation) and inferential statistical tests, including the chi-square test, independent samples t test, analysis of covariance, and repeated-measures ANOVA. The normality of the data was assessed via the Kolmogorov‒Smirnov test. This test revealed a normal distribution for all outcome measures. The mean scores between the intervention and control groups were compared before the intervention via an independent samples t test, and to compare the mean scores between the intervention and control groups immediately and two months after the intervention, analysis of covariance was utilized. The statistical assumption of analysis of covariance is that the covariates are correlated with the dependent variable. The demographic or clinical variables (including age and cancer type) were not added as covariates because no associations were found between these variables and the primary outcome. Furthermore, two-way repeated-measures ANOVA was used to examine the effects of time in each group. P values less than 0.05 were considered significant for all tests.
Results
In the first phase, the mobile App was designed according to the experts’ comments, with all the features to meet the requirements of the patients. In the second phase, the results indicated that there were no significant intergroup differences in the demographics, type of gynecologic cancer or time spent from diagnosis (all P > 0.05); these items are presented in Table 1. The results of between-group and within-group comparisons of the mean scores of quality of life before, after, and two months after the intervention are presented in Table 2. No significant differences in quality of life (P = 0.608) were detected between the intervention and control groups before the intervention. The results of covariance analysis revealed a significant difference between the two groups regarding the mean quality of life score immediately after and two months after the intervention. Repeated-measures ANOVA was used to compare the mean scores of quality of life in each group. The results of between-group and within-group comparisons of the mean scores of state anxiety and trait anxiety before, after, and two months after the intervention are presented in Table 3. No significant differences between the intervention and control groups were discovered for state anxiety (p = 0.689) or trait anxiety (P = 0.841) before the intervention. The results of covariance analysis revealed significant differences between the two groups regarding the mean scores of state anxiety and trait anxiety immediately after and two months after the intervention. Repeated-measures ANOVA was used to compare the mean scores of state anxiety and trait anxiety in each group.
Table 1
Sociodemographic and clinical characteristics of the participants
Characteristics | Intervention (n = 34) | Control (n = 34) | P |
|---|---|---|---|
Age (year) | 49.41 ± 8.80 | 50.26 ± 13.64 | 0.76* |
18–28 | N = 0 (0%) | N = 4 (11.76%) | 0.111** |
29–38 | N = 3 (8.82%) | N = 1 (2.94%) | |
39–48 | N = 14 (41.17%) | N = 8 (23.52%) | |
49–58 | N = 10 (29.41%) | N = 10 (29.41%) | |
59–68 | N = 7 (20.58%) | N = 11 (32.35%) | |
Time spent after diagnosis (month) | 6.50 ± 3.077 | 6.91 ± 3.545 | 0.611* |
Educational background | 0.735** | ||
Reading and writing skills (basic literacy) | 8 (23.5%) | 11 (32.4%) | |
Below Diploma | 8 (23.5%) | 9 (26.5%) | |
Diploma | 12 (35.3%) | 8 (23.5%) | |
University education | 6 (17.6%) | 6 (17.6%) | |
Type of cancer | 0.635** | ||
Ovarian cancer | 22 (64.7%) | 19 (55.9%) | |
Cervical Cancer | 1 (2.9%) | 2 (5.9%) | |
Uterus cancer | 10 (29.4%) | 13 (38.2%) | |
Vaginal cancer | 1 (2.9%) | 0 (0.0%) | |
Marital status | 0.535** | ||
Single | 1 (2.9%) | 3 (8.8%) | |
Married | 29 (85.3%) | 24 (70.6%) | |
Divorced | 1 (2.9%) | 2(5.9%) | |
The widow | 3 (8.8%) | 5 (14.7%) | |
Occupation | 26.23 ± 6.65 | 25.21 ± 5.54 | 0.634** |
Nongovernment job | 2 (5.9%) | 0 (0.0%) | |
Retired | 1 (2.9%) | 2 (5.9%) | |
Housewife | 29 (85.3%%) | 29 (85.3%%) | |
Employee | 2 (5.9%) | 3 (8.8%) | |
Residence | 0.791** | ||
Village | 9 (26.5%) | 11(32.4%) | |
City | 25 (73.5%) | 23(67.6%) |
Table 2
Comparison of the mean scores of quality of life before, after and two months after the intervention between groups and within groups
Variable | Groups | Before the intervention Mean ± SD | After the intervention Mean ± SD | 2 months after the intervention Mean ± SD | P value Within groups |
|---|---|---|---|---|---|
Quality of life | Control | 71.09 ± 17.37 | 16.62 ± 62.41 | 13.71 ± 62.43 | 0.021** |
Intervention | 68.90 ± 17.50 | 16.79 ± 73.78 | 9.90 ± 80.61 | 0.006** | |
P value between groups | 0.608* | 0.04# | < 0.001# | ------- | |
Effect size | ---------- | 0.120# | 0.371# | -------- | |
F | ---------- | 8.841 | 38.273 | -------- | |
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Table 3
Comparison of the mean scores of quality of life before, after and two months after the intervention between groups and within groups
Variable | Groups | Before the intervention Mean ± SD | After the intervention Mean ± SD | 2 months after the intervention Mean ± SD | P value Within groups |
|---|---|---|---|---|---|
State anxiety | Control | 50.23 ± 13.99 | 57.41 ± 12.72 | 61.82 ± 10.78 | < 0.001** |
Intervention | 51.64 ± 14.97 | 47.23 ± 12.38 | 40.20 ± 11.70 | 0.005** | |
P value between groups | 0.689* | 0.001# | < 0.001# | ------ | |
Effect size | ---------- | 0.150# | 0.500# | -------- | |
F | ---------- | 11.482 | 64.995 | -------- | |
Trait anxiety | Control | 50.61 ± 13.85 | 58.88 ± 12.21 | 61.11 ± 10.70 | 0.001** |
Intervention | 49.91 ± 14.96 | 47.79 ± 13.66 | 39.82 ± 10.28 | 0.006** | |
P value between groups | 0.841* | 0.001# | < 0.001# | ------ | |
Effect size | ---------- | 0.161# | 0.521# | -------- | |
F | ---------- | 12.492 | 70.711 | -------- | |
Discussion
This randomized controlled study demonstrated that implementing the continuous care model through a mobile application led to increased quality of life and reduced anxiety levels among gynecologic cancer patients. The intervention group showed notable improvements in average anxiety and quality of life scores postintervention and at the two-month follow-up. As the control group did not experience any reduction in anxiety or improvement in quality of life, these positive changes are credited to the impact of the mobile phone-based continuous care model. These findings are consistent with previous research highlighting the benefits of educational interventions for cancer patients, delivered through various formats including group sessions, in-person meetings, or video formats [52‐54].
The integration of mobile applications into healthcare has fundamentally transformed the relationship between patients and their care providers, especially for individuals suffering from gynecologic cancer [55]. The user-friendly design of the “Shafayar” App empowers patients by allowing them to easily navigate educational materials, care guidelines, and support resources. This enhances their understanding of medical conditions and encourages active participation in their care, positively affecting their overall well-being. A significant feature of the app is the direct communication option with nurses, which reduces barriers to care. Patients can ask questions about treatments or report symptoms without the logistical challenges of in-person visits. This continuous access fosters a supportive environment, enabling prompt responses to patient concerns and enhancing treatment adherence. Moreover, the ability to communicate easily with healthcare providers alleviates feelings of isolation and provides reassurance in challenging times [56‐58]. Gynecologic cancer patients often face numerous uncertainties, ranging from potential side effects of treatment to emotional challenges [59]. This tailored approach effectively addresses uncertainty related to treatment and side effects which are common sources of anxiety for cancer patients [60]. Rapid symptom reporting plays an essential role in alleviating concerns, correlating with improved psychological outcomes, in line with findings from Petzel et al. [61]. Having nurses readily available creates a comforting sense of safety, as assistance is just a message away. Timely interactions can diminish feelings of helplessness, fostering a more positive emotional state [38, 62]. Furthermore, research underscores that effective communication with healthcare providers is strongly linked to improved health outcomes and reduced anxiety among cancer patients [63, 64]. By facilitating ongoing dialog between patients and healthcare professionals, the mobile application not only enhances the quality of care but also fosters a therapeutic alliance that is beneficial for building psychological resilience. In essence, this technology represents a meaningful advancement in patient care, offering hope and support to those navigating the complexities of gynecologic cancer [38, 64, 65].
Research has indicated that the services offered through mobile applications, along with seamless communication with nurses, have played a crucial role in improving the quality of life of patients and reducing their anxiety levels [66‐68]. Patients diagnosed with cancer are found to be interested in the use of mobile technologies to manage their illness. The literature emphasizes the potential of smartphones in enhancing patients’ emotional well-being and quality of life [69, 70]. Patients diagnosed with cancer can take part in interventions remotely through platforms such as mobile devices. A pilot study conducted by Lengacher et al. demonstrated the effectiveness of a 6-week mobile mindfulness program, which included yoga, meditation, and body scanning, in reducing stress, anxiety, and depression in breast cancer survivors while also improving their overall quality of life. This program was found to be acceptable and feasible because of its positive impact on participants’ psychophysical symptoms. These findings align with those of the current study, which also incorporates yoga and meditation in the “Shafayar” application to improve anxiety and quality of life [71].
Previous studies have demonstrated that the use of mobile applications is effective in improving the quality of life of ovarian cancer patients [66], the quality of life of breast cancer patients [42, 72], the quality of life of gynecologic cancer patients [68, 73], the anxiety of breast cancer patients [74] and the stress of women with breast cancer [71]. These findings are consistent with those of the present study, indicating the positive impact of application-based interventions on reducing anxiety levels and enhancing quality of life in cancer patients. Lin et al., similarly noted that mobile health interventions significantly enhanced patient outcomes [73]. Consistent with the findings of Song et al. [55], our study demonstrated a significant increase in quality of life among these patients. However, unlike Salvetti et al. [75], who reported no significant increase in quality of life, our intervention indicated a marked increase in quality of life scores following the eight-week intervention. This discrepancy may be attributed to several factors, including variations in the duration of the interventions, the nature of the educational materials provided, or differences in participant engagement across various studies. Zhu et al. reported that an electronic support program through a mobile application was effective in improving self-efficacy and quality of life during chemotherapy but had no role in reducing anxiety or depression [76]. These findings are consistent with those of the present study in terms of quality of life improvement but differ in anxiety scores, possibly due to variations in questionnaire completion times. The prolonged presence of chemotherapy-related side effects and the discontinuation of educational interventions during this period may have influenced the lack of anxiety reduction. Furthermore, the study by Zhu et al. did not evaluate the patient’s utilization of the application, a factor that was examined in the present study. In another study, Kinner et al. revealed that internet-based group intervention enhanced the quality of life of ovarian cancer patients [66]. This study was in line with the current study and demonstrated that application-based support programs are novel approaches to address the gaps in care, which provide an easy and convenient solution for delivering information, communication, and support, thereby enhancing the quality of life of gynecologic cancer patients.
In contrast to previous studies, this study utilized a smartphone application in conjunction with a continuous care model to deliver nursing instructions. Kazemi et al. demonstrated that implementing the continuous care model through a mobile application was effective in improving adherence to treatment and self-efficacy among patients with multiple sclerosis [77]. The continuous care model was also effective in promoting treatment adherence among hemodialysis and myocardial infarction patients [78, 79] and affected lifestyle modifications in patients with Multiple Sclerosis [80].
These results suggest that the integration of mobile applications into patient care not only addresses logistical barriers to healthcare access but also significantly enhances the emotional well-being of patients through informed and supported self-care.
Strengths and limitations
The utilization of a mobile application for implementing the continuous care model has been shown to be a minimally invasive, cost-effective, and user-friendly method. The information available on the application is derived from reliable sources, simplified for patient understanding, and presented through various formats, such as text, images, videos, and animations, to encourage engagement and facilitate learning. Patients using the App have the option to communicate with nurses, ask questions, and submit weekly reports whenever needed. The App also offers a search function for easy access to information, as well as customization options for background color, text size, and font style on the basis of personal preferences. However, the study had several limitations. The participants included only 4 out of 5 types of gynecologic cancers (with vulvar cancer not represented). Another limitation was the exclusion of patients who were not familiar with technology, potentially limiting the broader applicability of the findings. Furthermore, the results might predominantly reflect patients who are highly interested in educational interventions, introducing a positive bias into the study. Another study limitation was the selection of participants within the age range of 18–68 years, thus limiting its applicability in older individuals. Another study limitation was the short follow-up period (two months) due to the limited research time. Further studies with longer follow-ups and larger samples are also recommended in this context.
Conclusions
The findings of the current study demonstrated that the mobile application-based continuous care model effectively reduced anxiety and enhanced the quality of life of patients with gynecologic cancers. The App provides a framework for symptom management and self-care for gynecologic cancer patients and can provide them with accurate information about their illness, which empowers patients to make informed decisions about their health. The App can offer access to counseling services (with nurses) that promote mental well-being and social support among patients and their families. Providing resources on nutrition, exercise, and wellness tailored to the needs of gynecologic cancer patients can help improve quality of life and support overall health during treatment. Nurses can effectively incorporate these App-based programs into standard care, improving health outcomes, patient well-being, and patient satisfaction. The use of mobile applications is essential, particularly when face-to-face interactions are limited by physical or geographic barriers. Moreover, clinic and hospital leaders are recommended to establish centers for delivering mobile application-based education to cancer patients. Further research is recommended using this approach in other cancer types and chronic illnesses.
Acknowledgements
The authors would like to thank all of the patients and health care providers who participated in the study, psychologists, sports physiology graduates, and oncologists.
Declarations
Ethics approval and consent to participate
The study was approved by the ethics committee of Shahrekord University of Medical Sciences, with the ethics code IR.SKUMS.REC.1402.135. The patients were informed about the details and aims of the study. Informed consent was obtained from all the participants, and procedures were conducted according to the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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