Introduction
The aging population is a global phenomenon, and addressing the needs arising from it is one of the most pressing concerns in today’s world [1]. Periodic censuses from the Iranian Statistics Center indicate that the elderly population has increased at twice the rate of the overall population over the past 60 years. According to the latest official statistics from the National Statistics Center of Iran in 2018, the elderly population in Guilan City, Iran, exceeds the national average, constituting approximately 13.25% of the total population [5]. Sleep disorders are prevalent issues that significantly affect the quality of life for the elderly. Sleep hygiene training, which aims to modify beliefs and habits related to sleep, is a non-pharmacological approach to treating these disorders [11]. The use of mobile phones represents a cost-effective and efficient method to promote self-care among patients [9]. This study investigates the effect of sleep health education delivered via a mobile application on the sleep quality of elderly individuals covered by the national pension fund in Rasht City, Iran, in 2022.

Methods & Materials 
This semi-experimental study was conducted in two phases. Initially, 330 elderly individuals were recruited, and their sleep quality was assessed using a designated tool. Subsequently, 96 individuals with low sleep quality were randomly divided into two groups of 48 subjects, namely an intervention group and a control group. The inclusion criteria were having 60 years of age or higher, not suffering from substance abuse disorders, membership in the Rasht State Pension Fund, possessing minimum literacy, and having the ability to communicate through sight and hearing. Meanwhile, the exclusion criteria in the first phase included incomplete or improperly completed questionnaires. 
The data collection tool comprised a two-part questionnaire, including personal-social information and the Pittsburgh sleep quality index (PSQI). The Pittsburgh sleep quality index includes seven scales measuring subjective sleep quality, sleep onset delay, sleep duration, sleep adequacy, sleep disorders, use of sleeping medications, and daily functioning disorders [26]. The intervention group received training on using the mobile-based sleep health educational application during two face-to-face sessions and was instructed to implement its programs daily for four weeks. A training booklet related to the application was also provided. The researcher followed up by phone twice a week. After four weeks, the sleep quality questionnaire was completed again for both groups, and after the research was completed, the educational application and sleep health educational booklet were provided to the control group. Data analysis included the Chi-square tests and the 1-way analysis of variance to compare baseline characteristics between groups, paired t-tests for within-group comparisons, and analysis of covariance (multivariate analysis of covariance) to compare means between groups post-intervention. The data were analyzed using the SPSS software, version 24, considering a significance level of 0.05.

Results
The results indicated that the average age of elderly participants was 68.98±6.52 years, with a majority being female (60.1%), married (83.3%), living in urban areas (91.5%), and possessing a university education (52%). The mean sleep quality score for the elderly was 5.37±3.88, influenced by various factors, including gender, education level, marital status, living arrangements, underlying health conditions, and employment status (P≤0.05). Among various aspects of sleep quality, sleep onset delay and use of sleep medications were identified as having the most and least issues, respectively. The comparison of changes in sleep quality domains between the two groups revealed significant differences in mental quality of sleep, sleep onset delay, sleep duration, use of sleeping pills, and daily dysfunction (P>0.100). The control group did not exhibit significant changes in these areas. Intra-group comparisons showed significant improvements in the intervention group across all areas except for sleep duration (P=0.830). Conversely, the control group showed no significant changes or, if any, an increase in sleep quality scores. In the control group, only the sleep disorder (P=0.100) and sleep efficiency (P=0.024) domains showed a statistically significant decline. Comparing the sleep quality score before and after the intervention and the changes in the two groups shows no statistically significant difference between the two groups before the intervention (P=0.997); however, after the intervention, there was a significant difference (P<0.001). The mean and median scores of sleep quality in the control group were higher than in the intervention group.
Also, the changes in sleep quality scores from before to after were significant between the two groups (P<0.001). The decreasing changes in the mean and median of the intervention group were significantly higher than the control group. Also, in the comparison between the two groups, sleep quality scores decreased significantly from before to after in the intervention group (P<0.001); nevertheless, these changes were not significant in the control group (P=649) (Table 1).


Notably, after the intervention, 96% of the control group reported poor sleep quality, while only 43% of the intervention group did. Multivariate analysis of covariance analysis indicated that sleep hygiene education significantly improved sleep quality across all areas, except for sleep efficiency (P≥0.05).

Conclusion
Sleep health education utilizing accessible and practical methods enhances the sleep quality of the elderly.  The global proliferation of mobile phone technology has been accompanied by the development of educational applications that enhance health education and self-care. This method offers the benefits of increasing access to educational, self-care, and medical services quickly and simply. Mobile applications are particularly important for the elderly, who may be more vulnerable and have limited mobility. Although the number of studies in this field remains limited, existing research, including this study, demonstrates promising results regarding mobile phone-based interventions aimed at improving sleep quality among the elderly. These findings support the use of such interventions to alleviate insomnia symptoms in elderly individuals who cannot access face-to-face interventions. Given the high prevalence of sleep disorders and their associated complications in this demographic, this model is recommended as a non-pharmacological treatment for managing sleep disorders, targeting healthcare workers, the elderly, and their caregivers.

Ethical Considerations
Compliance with ethical guidelines
This study was approved by the Research Ethics Committee of Guilan University of Medical Sciences (Code: IR.GUMS.REC.1401.322) and Iranian Registry of Clinical Trials (IRCT) (Code: IRCT20220926056042N1).

Funding
This article was extracted from the master’s thesis of Hananeh Rahimi in community health nursing funded by Guilan University of Medical Sciences and was done with the financial support of the Research Vice-Chancellor of this university.

Authors' contributions
Study design and investigation: Shahla Asiri, Hananeh Rahimi, and Negar Pourvakhshoori; Data analysis: Ehsan Kazemnejad; original draft preparation: Negar Pourvakhshoori; Review and editing: Shahla Asiri

Conflicts of interest
The authors declared no conflict of interest.

Acknowledgments
The authors thank all participants in this research for their cooperation.


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