The Effect of a Supportive-Educational Intervention through Virtual Social Networks on Sleep quality of Patients with Cancer

doi:10.21203/rs.3.rs-2495234/v1

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The Effect of a Supportive-Educational Intervention through Virtual Social Networks on Sleep quality of Patients with Cancer

https://doi.org/10.21203/rs.3.rs-2495234/v1

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Purpose

Sleep disturbances are very common among cancer patients, and they need more support in this regard. More access to technology has provided opportunities to use virtual teaching methods to train and support cancer patients. This study aimed to investigate the effect of supportive-educational intervention (SEI) through virtual social networks (VSNs) on the sleep quality and the severity of insomnia of cancer patients.

Methods

The study was conducted on 66 patients with cancer, intervention (n = 33) and control (n = 33) groups(CONSORT). Intervention group received supportive-educational intervention on sleep for two months through virtual social networks(VSNs). All participants completed the Pittsburgh Sleep Quality Index and insomnia severity index(ISI) before, and after the intervention.

Results

The mean scores of sleep quality (p = .001) and insomnia severity (p = .001) in the intervention group had a statistical significant decrease. Moreover, quality, latency, duration, efficiency, disturbances of sleep, and daytime dysfunction showed significant improvement in the intervention group, every two times after the intervention (P < .05). However, the participants’ sleep quality deteriorated progressively in the control group (p = .001).

Conclusions

Supportive-Educational Intervention(SEI) through VSNs can be an effective method to improve the sleep quality and decrease insomnia severity of patients with cancer.

Trial registration number: IRCT20220528055007N1

Date of registration: 2022-08-31(retrospectively registered)

Sleep Quality

Cancer

Virtual Training

Supportive Care

Chemotherapy is one of the common cancer treatments, which has a wide range of physical and psychological side effects[1]. Sleep problems, among other problems, are widespread and troublesome in cancer patients, especially in patients undergoing chemotherapy[2]. Sleeping is a biological need and is regarded as a vital health component. Poor or reduced quality of sleep will impact different biological clocks, which may eventually stop working. Poor sleep quality will also have a broad, negative impact on cognitive and physiological functions; patients' quality of life may therefore be severely affected[3, 4]. Since sleep disorders have a negative effect on the production of immune cells that play an essential role in the immune system, proper sleep is critical for patients, especially patients with specific diseases and cancer, to facilitate immune activity in the fight against cancer cells[5]. There are a variety of causes in the cancer care chain for insomnia[6]. Insomnia exacerbates other complications and affects the quality of life dimensions[2, 7].

In the study of Echchikhi, cancer patients reported that insomnia resulted in 41% fatigue, 53% decreased mental abilities, 39% adverse effects on interpersonal communication, and 74% decreased quality of life among them[8]. Sleep disorders in these patients lead to excessive daytime sleepiness and impaired function.In the Jaumally study, daily fatigue (94%), daily naps (81%), and excessive daytime sleepiness (69%) were reported as the most common symptoms in cancer patients[9].

Despite the high prevalence of sleep disorder in cancer patients and its effect on their quality of life, it has been of less attention compared to other symptoms[8]. Most patients do not seek help for insomnia since they believe that it is a temporary result of treatment and do not report it to a nurse or doctor[10]. Some of them seek the advice of healthcare providers and use sleeping pills as the only solution to insomnia[11]. About 75% of people use medications for insomnia, which are associated with potential side effects[10, 11]. Pharmacological interventions are more commonly used for sleep disorders in cancer patients than non-pharmacological interventions[2].

In addition to pharmacological interventions, non-pharmacological nursing interventions, such as education and patient support, are necessary to improve the sleep quality of these patients[2] Patient education is a process designed to facilitate learning and improve health outcomes. Patient education has many benefits, including increased knowledge, quality of life, and self-care, for patients and provides proper health practice[12]. Supportive care is defined as those services provided to prevent and manage the side effects of cancer and its treatment from the time of cancer diagnosis, treatment, and after[13]. A supportive education system is used in patients who can perform self-care activities. In this system, nurses have a crucial role in educating, guiding, and supporting patients[14]. self-care measures are effective in improving the physical and mental conditions of cancer patients under chemotherapy and play an important role in improving patients’ life quality[15].

Based on Orem’s nursing theory, self-care is considered as activities that people engage in to maintain, restore or improve their health. Orem defined three nursing systems including wholly compensatory, partially compensatory, and supportive-educative systems. The nurse’s roles in the supportive educational system are taken when the patient is ready to learn something, but he/she cannot do it without help and guidance[16].

Virtual Social Network(VSN) seems to be a good opportunity to support patients, decrease health care costs and the number of patients’ visits, improve access to supportive care, and reduce the pressure on health systems and health care providers (HCP) during the pandemic [17]. The ease of access and extensive capabilities of mobile devices, including services based on VSNs, make them excellent tools for planning, implementing, evaluating health interventions, educating, and supporting patients in the health system as well as patients with cancer[18.19.20]. This method is able to remove the obstacles of traditional and face-to-face education during the COVID- 19 pandemic and maintaining a safe environment for patients and HCP[21].

VSNs provide the ability to send a variety of text, audio, and educational videos at any time and place (19), as long as needed, and are able to support patients by establishing online communication between the HCP and the patient, which is led to better disease management[22]. In this method, home care services, supportive and palliative care including spiritual care, and even end-of-life care can be provided as much as possible for patients during the Covid-19 pandemic [23].

According to the above-mentioned descriptions this study was conducted to determine the effect of the supportive-educational intervention(SEI) through virtual social networks on sleep quality of patients with Cancer.

Design

The randomized clinical trial estimated the appropriate sample to be at least 33 samples in each group (Fig. 1). Based on a previous study as a guide[24], by taking into account the 10% attrition rate through using the sample size formula for comparing two means with a type I error of 0.05 and a power of 0.80(Fig. 1). Formulas for determining the sample size are a minimum criterion, and the number of samples in each group can be increased depending on the project feasibility without imposing more cost on the study. Thus, in this study, we decided to add seven samples in each group to the specified minimum number of samples, which is not a problem in terms of methodology.

Data Collection

According to the inclusion criteria, 80 patients were finally included in the study using the available sampling method. The inclusion criteria were the age range between 25–65 years, definitive diagnosis of Gastrointestinal Cancer(GIC) (esophagus, stomach, liver, pancreas, and colorectal), undergoing chemotherapy, cancer for at least two months, cancer awareness, smartphone availability, reading and writing ability, absence of mental illnesses and underlying diseases causing sleep disorders, no drug addiction, and get a score above 5 from the Pittsburgh Questionnaire and a score above the median of one of the Insomnia Severity Index(ISI) questionnaires. Unwillingness of participants to continue participate in the study, lack of access to the participants for any reason, and missing the smartphone were the exclusion criteria. Participants were randomly assigned into intervention (A) or control (B) group through block randomization with a block size of four. Sampling and block randomization was continued until 40 patients were allocated to each group by researcher.

The tools used to collect data were a demographic questionnaire and the Pittsburgh Sleep Quality Index (PSQI) and the Insomnia Severity Index (ISI). PSQI assesses sleep quality during the past month. It has 19 items under seven components of subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The items 1 to 4 are short-answer questions, and the items 5–9 are scored on a four-point Likert scale. The score of each scale ranges between 0 and 3 (indicating a normal state, a minor problem, a moderate problem, and a severe problem, respectively). The total score of the seven components is between 0 and 21. A score of 5 and higher shows a major sleep disorder, and higher scores indicate lower sleep quality[25]. In a study, it was found that PSQI in cancer patients had acceptable psychometric properties of internal consistency with a Cronbach’s alpha coefficient of 0.77 and discriminative and construct validity[26].

Insomnia Severity Index (ISI), a commonly utilized seven-item psychometrically validated instrument for rating insomnia and recommended for use in cancer trials. 32 Items are rated on a scale of 0 to 4, with higher summed scores (0 to 28) indicating worse insomnia[27].

The participants were recruited from a tertiary cancer hospital. The participants in the research were assured that their information would be protected. Oral informed consent was obtained from the study participants. The questionnaires were completed before the intervention in both groups. Participants in the intervention group were contacted through a virtual social network allowing users to send and receive texts, photos, videos, and audio. The intervention group received supportive training messages on sleep in addition to routine care. The content of the messages was developed as a protocol based on the latest investigations and textbooks on cancer nursing and supportive care and was approved by the oncology department. The messages, including explanations about insomnia management, sleep quality, and strategies to improve sleep quality (sleep health, nutritional advice, place and time of sleep, relaxation techniques, and stress and anxiety management), were sent to the intervention group in two to three text messages with related pictures and audio and video files (8 am to 8 pm) every day for one month. The participants were asked to send the message "the message was read" to the researcher. If the message were not read for more than 24 hours, a reminder message would be sent. To ensure that educational content was understood, the participants were asked two to three questions at the end of each week to obtain feedback. The participants' questions were also answered. After finishing the intervention, the participants were asked to review the sent messages and report their sleep quality for one month. To support the participants, they were constantly monitored and encouraged to perform training. Also, they were referred to a psychologist or psychiatrist if needed. The control group received routine care. Immediately and one month after the intervention, the participants in both groups completed the PSQI, ISI questionnaires as the follow-up process. At the end of the research process, an educational booklet containing the presented content on the social network was given to both groups.

A total of 105 patients with cancer were screened for eligibility, of which 25 patients did not meet the inclusion criteria, 5 refused to participate in the study because they were not interested, and 9 passed away during the study. In total, 66 patients participated in the study.

normality distribution was studied using the Kolmogorov-Smirnov test. In cases of, parametric tests (ANOVA with repeated measure), and in cases of non-normal distribution, non-parametric tests (Mann Whitney, Wilcoxon, and Friedman) were used.

The study finished with 66 patients (33 in each group). There were no statistically significant differences between the groups concerning participants' demographic characteristics (p > .05) (Table 1).

Sleep quality

The total sleep quality score before the intervention showed no significant difference between the two groups (p = .259). Immediately and one month after the intervention, the mean total score of sleep quality was lower in the intervention group than in the control group, and the Mann-Whitney test results showed a statistically significant difference between the groups (p = .008 and p = .001, respectively). The Friedman test results showed significant changes in the score of sleep quality, which increased in the control group and decreased in the intervention group (p = .001 and p = .001, respectively) (Table 2). Analysis of variance with repeated measures showed that the intervention significantly affected the total score mean of sleep quality in terms of time and groups under study (p = 0.001) (Table 2).

Table 2

Mean Score of Sleep Quality in the Intervention and Control Groups
Time	Intervention Group	Control Group	P-value
	Mean SD	Mean SD
Before intervention Immediately After intervention One-month After intervention P-value	15.18 2.983 12.57 3.437 9.48 3.052 .001^b	14.392.474 14.662.495 15.78 2.803 .001^b	.259^a .008^a .001^a .001^c

^a Mann–Whitney U-test.

^b Friedman test.

^c ANOVA with repeated measure test.

The mean total score of sleep quality in the intervention group decreased immediately and one month after the intervention compared to before the intervention. Moreover, the sleep quality score was lower one month after the intervention compared to immediately after the intervention. The Wilcoxon test results showed significant changes (p = .001). In the control group, the mean total score of sleep quality after the intervention did not show a significant difference compared to before the intervention (p > .05). The Wilcoxon test results showed a significant increase in the score of sleep quality one month after the intervention compared to immediately after the intervention (p = .001). In other words, progressive and significant improvement in sleep quality was observed in the intervention group, while progressive and significant deterioration was observed in the control group. The Wilcoxon test results as a significant level in the intervention and control groups are shown in Table 3.

Table 3

Wilcoxon's Paired Comparison of (PSQI (in the Intervention and Control Groups
	Intervention	Control
Time	Immediately One month After After intervention intervention	Immediately One month After After intervention intervention
Before intervention One-month after intervention	.001^a .001^a ---- .001^a	.457^a .001^a ---- .001^a

^a Wilcoxon test.

There was no significant difference between the two groups before the intervention regarding the sleep quality components (p > .05). The scores of the subjective sleep quality, sleep latency, and sleep duration components significantly decreased in the intervention group immediately after the intervention compared to before the intervention (P < .05). However, no other components significantly changed in the intervention group immediately after the intervention compared to before the intervention (P > .05). One month later, the scores of all the sleep quality components, except for the use of sleeping medication component, were significantly lower in the intervention group than in the control group (P < .05).

The results of analysis of variance with repeated measures showed that the intervention had a significant effect on the mean scores of all the components, except for the use of sleeping medication component, in terms of time and groups under study (P < .05).

The Friedman test results indicated that the scores of all the sleep quality components decreased in the intervention group; however, changes in the use of sleeping medication component were not significant in this group (P > .05). The Friedman test results also revealed an increase in the scores of all the sleep quality components in the control group, although only significant in the subjective sleep quality and daytime dysfunction components (P < .05). The most remarkable changes in the intervention group under SEI were found in subjective sleep quality followed by sleep efficiency.

Insomnia severity

Insomnia severity score before the intervention did not show a significant difference between the two groups (p = .1). Immediately and one month after the intervention, the mean score of insomnia severity in the intervention group was lower than the control group and the results of t-test and Mann-Whitney test showed a statistically significant difference between the groups (p = .027 and p = .001), respectively.

The results of Friedman test showed significant changes in insomnia severity score in the intervention group but no significant changes were observed in the control group (P = .001 and p = .438 respectively). Analysis of variance with repeated measures showed that the intervention had a significant effect on the mean score of insomnia severity in terms of time and groups (p = 0.047) (Table 4).

Table 4

The Score Mean of Insomnia Severity Index in the Intervention and Control Groups
Time	Intervention Group	Control Group	P-value
	Mean SD	Mean SD
Before Immediately After One- month After P-value	19.45 3.55 15.75 3.73 13.33 4.69 .001^b	17.873.83 17.96 4.17 18.21 4.64 .438 ^b	.10 ^a .027 ^c .001^a .047 ^d

^a Mann–Whitney U-test.

^b Friedman test.

^c T test.

The mean score of insomnia severity in the intervention group decreased immediately and one month after the intervention compared to before the intervention. Also, the score of insomnia severity was lower one month after the intervention than immediately after the intervention. The results of Wilcoxon test showed significant changes (p = 0.001). In the control group, the results of Wilcoxon test did not show statistically significant changes in insomnia severity scores (p > 0.05). In other words, in the intervention group, a progressive and significant improvement in insomnia severity was observed. The Wilcoxon test results as a significant level in the intervention and control groups are shown in Table 5.

Table 5

Wilcoxon's Paired Comparison of (ISI) in the Intervention and Control Groups
	Intervention	Control
Time	Immediately One month after after intervention intervention	Immediately One month after after intervention intervention
Before intervention One-month After intervention	.001^a .001^a ---- .001^a	.932^a .429^a ---- .522^a

^a Wilcoxon test.

The present study aimed to investigate the effect of SEI through VSNs on the sleep of cancer patients. The results showed that SEI based on VSNs could improve the sleep quality, insomnia in cancer patients. These findings were in line with the results found in the subsequent studies. Studies showed that the instructions of sleep health in the chemotherapy protocol had positive effects on the sleep and the patients' fatigue level[29, 30].

Peoples et al. indicated that sleep-related training improved insomnia in cancer survivors and decreased their depression[27]. The above studies showed that poor sleep in cancer patients could be improved with sleep training intervention.

In the present study, increasing information about non-pharmacological methods has led to improved sleep quality, insomnia and patients have paid more attention to the importance of sleep, insomnia complications, non-pharmacological strategies, and such points. Improving the quality of night sleep can reduce daily sleepiness and improve quality of life. Increasing awareness is effective in adopting healthy behaviors. Another possible reason for improved sleep quality, insomnia is the collaborative and comprehensive nature of the educational content that considers different aspects of sleep, and the role of nurses can be influential in this regard.

The findings showed that sleep quality got deteriorated in the control group. It can also be stated that other symptoms associated with insomnia, over time, exacerbate each other's defective cycle and lead to more negative effects on patients' sleep quality, which can have adverse effects on quality of life if appropriate measures are not taken. However, the results of other studies showed that newly diagnosed patients had more sleep problems due to new exposure to chemotherapy and anxiety of cancer diagnosis[31], which is inconsistent with the results of the present study.

In the present study, the improvement in sleep quality in the intervention group was stable until follow-up (one month after the intervention). In the study of Nakase-Richardson et al., the results were not sustainable in the follow-up process[32], which is inconsistent with the results of this study. Progressive improvement of sleep quality in the intervention group and the sustainability of the results can be considered the results of the supports provided for the patients in the form of follow-up, encouraging the patients, and dynamic communication with the patients.

Various studies have reported that nurses' training and support can improve health outcomes and empower patients in self-care and disease management[15.33.34]. Moreover, training with support and telephone follow-up is more effective than training alone[32]. However, the post-intervention sleep quality scores in the present study are still within the range of poor sleep quality; sleep quality improvement one month after the intervention and support is significant and considerable.

Various studies support the benefits of mobile-based interventions and distance learning in improving health outcomes in the health system[19, 35.36].

None of the conducted interventions on sleep in cancer patients focused on SEI through VSNs. Using social media in the present study made it possible to send health and supportive advice and dynamic communication with the patients on sleep in a multimedia manner, which can be regarded as the causes of the effectiveness of the intervention. Patients may forget the health education after face-to-face or telephone training, resulting in decreased training effectiveness over time.

While, another reason for the sustainability of the intervention is that the educational content, patients' questions, and the provided answers are stored on social networks, and patients can access them at any time and place and even long after the training.

In a review, Rathnayake et al. reported that medical health applications were a good source of education and support for family caregivers of people with dementia[37]. The findings of the Khairkhah and et. al study showed that face-to-face lymphedema self-management education was more effective than virtual education on patients' quality of life[38].

Cancer patients face many challenges and need continuous training and support to manage their conditions. Virtual learning can be considered as an appropriate and efficient method to train these patients. This method provides more flexibility for the patients who feel stressed in tedious treatment sessions and have limitations to attend training classes due to their physical conditions. The patients constantly receive information, and there is no interference with their treatment, rest, and living conditions. Reducing direct and indirect treatment costs, the number of visits to medical centers, and reducing the workload of medical staff are other advantages of this supportive training method.

Studies revealed the effectiveness of virtual learning on improving health outcomes in different issues, as consistent with the present study results, and the viability of using this technology in health promotion strategies[6, 19]. The results of a review showed that social media can be used by people and patients to increase knowledge and improve health outcome[39].

Cancer is one of the most critical challenges facing patients and healthcare professionals (HCPs) in the COVID-19 pandemic. Patients undergoing chemotherapy and survivors are more likely to be affected by adverse consequences due to weak immune system[21]. Therefore, considering the need for continuous training and support during the disease and especially cancer, as well as regarding the context of the COVID-19 pandemic, it is essential to choose the appropriate training method for these patients, and it is recommended to use the virtual space for training and meet these patients' needs in order to reduce the referral to high-risk places and medical centers.

In the follow-up process, there was a more significant difference between the two groups, and the intervention improved all sleep quality components, except the use of sleeping medication. It shows that training and support can lead to behavior change, but it needs more time to practice and stabilize health behaviors to make the right behaviors a habit. This finding was consistent with the results of Shafaat et al.'s study, which supports the effect of time on the effectiveness of training and behavior change [24].

The most remarkable improvement was observed in subjective sleep quality followed by sleep efficiency after the intervention. The component of the sleeping medication use increased in the control group while it decreased in the intervention group, although the differences were not statistically significant. Therefore, it is suggested to conduct further longitudinal studies with continuous courses of SEI. Based on the findings of this study, SEI via VSNs can be considered one of the effective methods for providing sleep supportive care to cancer patients.

This study was conducted in only one city and only consisted of patients with GIC receiving chemotherapy. Therefore, findings may not be generalizable to patients with other types of cancer and treatment. Further studies are needed to evaluate the effects of SEI via VSNs on the sleep quality of patients with different types of cancer in different societies and the management of other symptoms in cancer patients.

SEI using VSNs can be considered as an effective non-pharmacologic intervention to promote GIC patients' sleep quality. Accordingly, policymakers are suggested to develop this method, especially in the COVID-19 pandemic, to support highly vulnerable cancer patients. Nurses can extend their roles in supporting patients with cancer and take a helpful step toward increasing sleep quality among patients with sleep difficulties. Therefore, the development of such interventions is recommended.

Acknowledgments: This study was financially supported by the Deputy of Research and Technology of Arak University of Medical Sciences (Ethics Approval code: IR.ARAKMU.REC.1398.116). The authors would like to express their deepest gratitude for the support. The authors would also like to thank the participants for their time and participation.

Funding: This study was financially supported by the Deputy of Research and Technology of Arak University of Medical Sciences (Ethics Approval code: IR.ARAKMU.REC.1398.116). The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests: The authors have no relevant financial or non-financial interests to disclose.

Author contributions statements:

Elahe Sarlak: Data gathering, Investigation, Software, Writing- Original draft preparation, Reviewing and Editing.

Nazi Nejat: Conceptualization, Methodology, Supervision, Writing, Reviewing and Editing.

Rahmatollah. Moradzadeh: Methodology, Statistical Analysis, Reviewing and Editing.

Jamshid. Ansari: Methodology, Reviewing and Editing.

Data Availability: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Ethics approval: This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Arak University of medical science (Date: 28/07/2019/ Ethics Approval code: IR.ARAKMU.REC.1398.116).

Consent to participate: Informed consent was obtained from all individual participants included in the study.

Ji YB, Bo CL, Xue XJ, et al(2017) Association of inflammatory cytokines with the symptom cluster of pain, fatigue, depression, and sleep disturbance in Chinese patients with cancer. Journal of Pain and Symptom Management 54(6):843–852.
Song J, Choi-kwon S(2019) Factors affecting sleep disturbances in hospitalized patients with colorectal cancer undergoing chemotherapy: a retrospective study. Korean Journal of Adult Nursing 31(1):100–108.
Aguilar-Arnal L, Sassone-Corsi P(2015) Chromatin landscape and circadian dynamics: Spatial and temporal organization of clock transcription. Proceedings of the National Academy of Sciences 112(22):6863–6870.
Dickerson S. S, Connors L. M, Fayad A, et al(2014). Sleep–wake disturbances in cancer patients: narrative review of literature focusing on improving quality of life outcomes. Nature and science of sleep 6:85.
Giffoni F.A.d.O(2020). SLEEP AND IMMUNITY. Amadeus International Multidisciplinary Journal 5(9):144–151.
Ancoli-Israel S(2015) Sleep disturbances in cancer: a review. Sleep Medicine Researchn6(2):45–49.
Dambrosio N.M, Mazanec, P(2013). “Nurse, I Can’t Sleep!”: Approaches to Management of Insomnia in Oncology Patients. Journal of Hospice & Palliative Nursing 15(5):267–275.
Echchikhi Y, El-Abbassi S, Touil A, et al(2017). Sleep disorders and sleep quality in Moroccan adult patients with cancer during treatment. J Cancer Sci Ther 9:637–643.
Jaumally B. A, Das A, Cassell N. C, et al(2021). Excessive daytime sleepiness in cancer patients. Sleep Breath 25(2):1063–1067.
Dozeman E, Verdonck-de Leeuw I. M, Savard J, et al(2017). Guided web-based intervention for insomnia targeting breast cancer patients: feasibility and effect. Internet interventions 9:1–6.
Valente S(2015). Evaluating and managing insomnia: non-pharmacological treatments. J Sleep Disord Ther 4(2):189.
Flanders S. A(2018). Effective patient education: Evidence and common sense. Medsurg Nursing 27(1):55–58.
Multinational Association of Supportive Care(2020). Available from. https://www.mascc.org/ Retrieved Accessed 5 April 2020.
Wanchai A, Armer J. M(2018). Promoting self-care capabilities of patients: nurses’ roles. Nurs Health Care 7(4):1–3.
Wang Z, Yin G, Jia R(2019). Impacts of self-care education on adverse events and mental health related quality of life in breast cancer patients under chemotherapy. Complementary therapies in Medicine 1;43:165–9.
Aligood MA(2017). Nursing theorists and their1 works. 9th ed. US: Elsevier.
Al-Shamsi HO, Alhazzani W, Alhuraiji A, Coomes EA, Chemaly RF, Almuhanna M, et al(2020). A Practical Approach to the Management of Cancer Patients During the Novel Coronavirus Disease 2019 (COVID19) Pandemic: An International Collaborative Group. Oncologist 25(6):936–45.
Cherrez Ojeda I, Vanegas E, Torres M, Calderon JC, Calero E, Cherrez A, et al(2018).Ecuadorian Cancer Patients’ Preference for Information and Communication Technologies: Cross-Sectional Study. J Med Internet Res 20(2). 50.
Pereira A. A. C, Destro J. R, Bernuci M. P, et al(2020). Effects of a whatsapp-delivered education intervention to enhance breast cancer knowledge in women: mixed-methods study. JMIR mHealth and uHealth 8(7):1–16
Jongerius C, Russo S, Mazzocco K, et al(2019). tested Mobile apps for breast cancer care: systematic review. JMIR mHealth and uHealth 7(2):1–15.
Lambertini M, Toss A, Passaro A, et al(2020). Cancer care during the spread of coronavirus disease 2019 (COVID-19) in Italy: young oncologists’ perspective. ESMO open 5(2):1–4.
Sharifian R, Fallahnejad E, Niknam F(2016). The Importance of Internetbased Educational and Clinical Interventions and Social Networks in Pregnant Women. Women’s Health Bulletin 4(2).
Schoenmaekers J, Hendriks LEL, van den Beuken-van Everdingen, Marieke HJ(2020). Palliative Care for Cancer Patients During the COVID-19 Pandemic, With Special Focus on Lung Cancer. Front Oncol 10:1405.
Shafaat N, Makvand H. S, REZAIE A. M(2017). Effectiveness of Multi-components Cognitive-behavioral Therapy on Insomnia Intensity and Quality of sleep among Breast Cancer Patients after Surgery. Research in Psychological Health 11(2):82–91.
Khosravi A, Emamian MH, Hashemi H, Fotouhi A(2021). Components of Pittsburgh Sleep Quality Index in Iranian adult population: an item response theory model. Sleep medicine 3:1–8.
Al Maqbali M, Hughes C, Gracey J, et al(2020). Validation of the Pittsburgh sleep quality index (PSQI) with Arabic cancer patients. Sleep and Biological Rhythms 18(3):217–223.
Peoples A. R, Garland S. N, Pigeon W. R, et al(2019). Cognitive behavioral therapy for insomnia reduces depression in cancer survivors. Journal of Clinical Sleep Medicine 15(1):129–137.
Gasparro R, Calabria E, Coppola N, et al(2021). Sleep Disorders and Psychological Profile in Oral Cancer Survivors: A Case-Control Clinical Study Cancers 13(8):1855.
ELmetwaly A. A. M, Mohamed E. M. H, Abou Elmaati H. M. B, et al(2019). Sleep Hygiene: Improving Sleep Quality and Fatigue for Patients Receiving Chemotherapy. American Journal of Nursing Research 7(6):1078–1085.
Zengin L, Aylaz R(2019). The effects of sleep hygiene education and reflexology on sleep quality and fatigue in patients receiving chemotherapy. European journal of cancer care 28(3).
Chen M. L, Yu C. T, Yang C. H(2008). Sleep disturbances and quality of life in lung cancer patients undergoing chemotherapy. Lung Cancer 62(3):391–400.
Nakase-Richardson R, Vuletic S, Bell K. R, et al(2016). Telephone problem-solving treatment improves sleep quality in service members with combat-related mild traumatic brain injury: results from a randomized clinical trial. Journal of head trauma rehabilitation 31(2):147–157.
Wasalamah B, Alim S, Widyandana D(2022). Supportive Educative Nursing Intervention (SENI) as Intervention in Enhancing Self-Efficacy among Hemodialysis Patients. Journal of Health Sciences and Medical Development 1(1):1–11.
Pourfallahi M, Gholami M, Tarrahi M. J, et al(2020). The effect of informational-emotional support program on illness perceptions and emotional coping of cancer patients undergoing chemotherapy. Supportive Care in Cancer 28(2):485–495.
Uppu P, Manickavasagam M, Jagadeesh NS, Babu KR(2021). Efficacy of Mobile Phone Technology for Managing Side Effects Associated with Chemotherapy among Cancer Patients: A Systematic Review and Meta-Analysis. Indian Journal of Medical and Paediatric Oncology 42(06):518–27.
Sarbaz M, Monazah FM, Eslami S, Kimiafar K, Baigi SF(2022). Effect of Mobile Health Interventions for Side Effects Management in Patients Undergoing Chemotherapy: A Systematic Review. Health Policy and Technology 11(4).
Rathnayake S, Jones C, Calleja P, et al(2019). Family carers' perspectives of managing activities of daily living and use of mHealth applications in dementia care: a qualitative study. Journal of clinical nursing 28(23–24):4460–4470.
Kheirkhah M, Haghighat S, OMIDI Z(2021). Comparing the Effect of In-Person and Virtual Lymphedema Self-management Education on Quality of Life of Women with Breast Cancer: A Randomized Clinical Trial. Iranian quarterly journal of breast disease 13(4):9–22.
Farsi D, Martinez-Menchaca H. R, Ahmed M, et al(2022). Social media and health care (part II): narrative review of social media use by patients. Journal of Medical Internet Research 24(1):1–16.

Table 1 is available in the Supplementary Files section.

No competing interests reported.

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The Effect of a Supportive-Educational Intervention through Virtual Social Networks on Sleep quality of Patients with Cancer

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