The Science of Diabetes Self-Management and Care 2025, Vol. 51(6) 644–657 © The Author(s) 2025 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/26350106251371082 journals.sagepub.com/home/tde
Abstract
Purpose: The purpose of the study was to evaluate the quality, reliability, and informational adequacy of YouTube videos related to the installation and replacement of continuous glucose monitor (CGM) systems.
Methods: This descriptive and correlational study evaluated 460 videos retrieved using the keywords “CGM installation” and “CGM replacement” and analyzed 35 videos that met the inclusion criteria. Videos were assessed using 3 tools: the DISCERN instrument, the Global Quality Scale (GQS), and the 24-item CGM Informational Survey (CIS) developed by the researchers.
Results: The majority of videos (80%) were user-generated, and only 2.9% were uploaded by health care professionals. The average GQS score was 2.80, DISCERN 34.57, and CIS 11.86, indicating moderate to low quality and informativeness. Video duration showed strong positive correlations with CIS (r = .80), DISCERN (r = .64), and GQS (r = .71) scores (P < .001). Videos with high information scores were significantly longer and more comprehensive than low-scoring ones. No significant correlation was found between follower count and content quality. The most frequently shared YouTube videos were related to the Dexcom CGM System (34.3%) and the FreeStyle Libre CGM System (25.7%).
Conclusions: YouTube videos related to CGM installation and replacement are largely insufficient in terms of medical accuracy and completeness. Given the growing reliance on digital health information, it is essential for health care professionals to produce accurate, standardized, and accessible video content to support safe diabetes self-management and improve public health literacy.
The integration of digital technologies into health care has led to fundamental changes in how individuals access information.1,2 The global accessibility of the Internet has transformed the way the world interacts. The popularity of seeking online health information has steadily increased. Given its ease of access, immediacy, and interactive nature, the Internet has become one of the most popular sources for obtaining health information.3 One of the advantages of the YouTube platform is its global reach and popularity.2 YouTube is the world’s second most popular search engine and social media platform. It has been reported that 80% of people ages 18 to 49 watch videos on YouTube (Google, San Bruno, California) each month, and more than 70% of adults search for healthcare-related information online.4 In 2020, YouTube had more than 2.1 billion users, resulting in over 1 billion hours of video watched daily and more than 500 hours of content uploaded every minute.1 With this surge in video content, YouTube has become a valuable educational resource. It has transformed into a visual model that can be used for instructional purposes, offering both theoretical and practical knowledge. The accessibility and social nature of YouTube make it a powerful tool for influencing individuals’ decisions and supporting their well-being.1
However, YouTube does not consist solely of beneficial content. It also allows the upload of misleading and poor-quality videos.1 Although YouTube’s potential to provide informative health content is widely acknowledged, the Internet generally operates in an unregulated environment. According to YouTube’s terms of service, uploaded content is solely the responsibility of the individual or organization that provides it. This means that false and unreliable health information can spread rapidly on YouTube and other social media platforms without peer review or accountability mechanisms.4 Furthermore, YouTube ranks videos based on popularity, which implies that high-quality content can appear alongside misleading and low-quality videos in search results. Therefore, the quality and reliability of the videos users are primarily exposed to remain uncertain.1
Thanks to its visual and practical content, YouTube can provide accessibility and comprehensibility, particularly for health-related procedures (e.g., device use). One of the most important tools developed for diabetes management is the continuous glucose monitor (CGM) device, which analyzes interstitial fluid every 10 seconds and provides users with an average glucose value every 5 minutes. These continuous measurements offer a more accurate model of daily glucose fluctuations, helping to determine the glycemic impact of food, physical activity, insulin, and various types and doses of medication. This supports improved self-management and avoidance of undetected hypoglycemia.5 CGM devices offer significant benefits, such as reducing A1C levels and improving quality of life.6 Studies have shown that CGMs are cost-effective over a lifetime for both health care systems and patients.7,8 Numerous randomized controlled trials have reported reductions in A1C levels and hypoglycemic episodes with regular CGM use.9-11 Although studies on type 2 diabetes have shown that short-term CGM use does not have a direct effect on A1C improvement, users reported behavioral changes, including increased glucose monitoring, more frequent insulin administration, and overall improvement in diabetes management and quality of life.12 Additionally, CGM usage has been associated with reductions in acute diabetes complications, such as diabetic ketoacidosis, severe hypoglycemia, diabetes-related coma, and hospital admissions due to hypogylcemia and hyperglycemia.13,14 Real-time CGM use has been shown to significantly reduce A1C levels and decrease emergency department visits or hospitalizations due to hypoglycemia.15 Achieving the American Diabetes Association’s target A1C level of 7% is particularly challenging for individuals with type 1 diabetes. Current data suggest that only a small proportion of adults meet this goal.5,16,17 However, CGM use has been shown to increase the time spent in the target glucose range without increasing the risk of hypoglycemia or hyperglycemia.18 Like all adhesive devices worn on the skin, CGM sensors may cause dermatological issues, such as contact dermatitis (both irritant and allergic).16 Certain medications and substances can also interfere with CGM sensor readings. Although various CGM brands provide information about such interactions in their user manuals, additional interactions have been reported postmarket. Substances such as ascorbic acid (vitamin C) and sorbitol may affect CGM readings.5 Although CGMs demonstrate good correlation with plasma glucose levels, there may be delays when glucose levels are rapidly rising or falling. Despite these limitations, CGM devices remain a valuable tool for enhancing the efficacy and safety of treatment in individuals with type 1 diabetes and those with type 2 diabetes on intensive insulin therapy.5 Although structured education on CGM device usage is provided in health care services, individuals with diabetes may attempt to supplement their knowledge through digital platforms due to concerns when initiating device use, forgetting information previously learned, or the complex nature of diabetes management. One study revealed that individuals with type 1 diabetes often lacked adequate training when beginning CGM use and instead turned to online resources to fill these gaps. Most participants reported actively using the Internet to address challenges and information gaps. They particularly cited YouTube videos, Reddit forums, and Facebook groups as sources of information about CGM application, sensor insertion techniques, adhesive use, and managing common device-related issues. This finding demonstrates that CGM users heavily rely not only on official manufacturer training materials and health care provider education but also online resources. Furthermore, participants emphasized that accessing “real user experiences” via social media not only offered technical support but also promoted psychosocial adaptation to device use. These findings highlight the critical importance of the accuracy, timeliness, and adequacy of information obtained from platforms like YouTube during the CGM usage process. In this context, our study, which evaluates the informational adequacy of YouTube videos related to CGM installation and replacement processes, directly addresses this significant gap in the existing literature.19
In recent years, a wide range of video content related to CGM installation and replacement has been shared on the YouTube platform. Inadequate or incorrect information may lead to improper device use or even adverse health outcomes. Therefore, YouTube videos must be systematically evaluated not only in terms of accessibility but also for their informational adequacy and content reliability. This study aims to evaluate and compare the technical content, informativeness, quality, and reliability of YouTube videos related to the installation, replacement, and use of CGM systems. It also seeks to emphasize the need for health care professionals to contribute to digital platforms by producing reliable educational content. The research provides a comprehensive assessment of the resources accessible to individuals with diabetes and their families regarding CGM usage on YouTube.
Research Question 1: What are the technical characteristics, CGM-related information content, reliability, and quality features of YouTube videos on CGM systems?
Research Question 2: Is there a difference between the informativeness of YouTube videos and their reliability and quality scores?
Research Question 3: Is there a difference between DISCERN scores and the informativeness and quality scores of the videos?
Research Question 4: What is the relationship among the CGM-related information scores, technical features, reliability, and quality scores of the videos?
This study employed a descriptive and correlational research design. A descriptive approach was appropriate to systematically examine the content, technical features, and quality of publicly available YouTube videos related to CGM installation and replacement. The correlational component allowed for the assessment of statistical relationships between video characteristics (eg, duration, view count, and like count) and their informativeness, quality, and reliability scores. This design was suitable because the study aimed to analyze existing, naturally occurring digital content without manipulation or experimental control, aligning with the observational nature of videobased health information research.
Between April 1 and April 5, 2025, separate searches were conducted on the YouTube platform (www.youtube.com) using the keywords “CGM device installation” and “CGM device replacement.” Only Turkish-language YouTube videos were selected for evaluation to ensure the accessibility, understandability, and cultural relevance of digital health information for Turkish-speaking individuals with diabetes. Because this population predominantly seeks information in their native language, evaluating non-Turkish content would not have reflected the actual digital resources they use. Furthermore, because health communication practices and the quality of online content vary across cultures, each country or language group should conduct similar evaluations to identify population-specific needs and enhance the quality of digital health education accordingly.
The “relevance” filter was applied during the searches. The relevance filter, which is the default YouTube sorting algorithm, was applied during searches to display videos based on user engagement metrics, such as views, likes, comments, and watch time. This filter prioritizes the most interacted with videos, assuming these are the most visible to typical users. Following the search, videos were screened based on predefined inclusion criteria, which required that the content be in Turkish, focus on the installation or replacement of CGM systems, and be free of unrelated or promotional material. In similar studies in the literature, typically the first 200 videos per keyword were reviewed.20-22 However, to ensure a more comprehensive screening, the first 230 videos for each keyword were included in this study. Because overlapping results may occur despite different keywords, duplicate videos were identified and excluded. Ultimately, out of 460 videos screened, 35 unique Turkish-language videos that met the inclusion criteria were analyzed in detail. These videos included patient experiences, health care professional explanations, product presentations, and setup instructions related to CGM sensor installation and replacement. Videos that did not meet the inclusion criteria were excluded. Specifically, videos were excluded if they were unrelated to CGM systems, contained promotional content or advertisements, were duplicates, or were not in the Turkish language. This study was limited to Turkish-language videos to evaluate the digital health information most accessible and relevant to Turkish-speaking individuals with diabetes. As such, non-Turkish videos were not assessed.
As a result of the screening, 460 videos were evaluated. Of these, 412 were excluded due to not being in Turkish, 5 were unrelated to the topic, 1 focused on an implantable CGM system, 1 presented a developing product, 2 were animations aimed at children, 2 involved CGM usage in animals, and 2 provided training on standard glucose meter use. A total of 35 videos meeting the inclusion criteria were included in the study (Figure 1).
After keyword-based searches, the videos meeting the inclusion criteria were initially reviewed by the first author (MD). Videos were listed based on relevance, regardless of upload date, and the URLs of eligible videos were recorded. The technical features, CGM-related informativeness, reliability, and quality of the videos were evaluated independently by the first author (MD) and the second author (MG). The average of the 2 raters’ scores was used for CGM informativeness, reliability, and quality ratings. The interrater agreement was calculated using Cohen’s kappa coefficient. The overall kappa value was .88, with .85 for CGM informativeness, .80 for reliability, and .83 for quality. Any discrepancies were resolved through discussion and consensus. In cases where consensus could not be reached, the third author (DBB) was consulted to ensure reliability.
Reliability. In this study, the DISCERN tool was used to assess the informational quality of YouTube videos related to the installation and replacement of CGM systems. DISCERN is a validated and reliable measurement tool that allows for the evaluation of patient information materials regarding reliability, impartiality, and content quality. DISCERN consists of 16 items: 15 assessment questions and 1 overall quality score. Each item is rated on a scale of 1 to 5. Accordingly, the total score for a material can range from 16 to 80. The assessment systematically analyzes the informative aspects of each video.23 Total DISCERN scores range from 16 to 80 and are interpreted as follows: Scores between 63 and 80 indicate excellent quality, 51 to 62 indicate good quality, 39 to 50 indicate fair or moderate quality, 27 to 38 indicate poor quality, and 16 to 26 indicate very poor quality.24 The videos were evaluated by 2 independent researchers based on the DISCERN items, and the analysis was conducted using the average scores. This method allowed for an objective measurement of content reliability and a rating of the information quality provided by the videos.
Quality. To assess the overall quality of the videos, the Global Quality Scale (GQS) was used. GQS is a widely used 5-point Likert scale that subjectively evaluates the content quality, presentation style, and overall benefit to the viewer for health-related videos. The GQS scores range from 1 to 5. A score of 1 indicates poor quality with inadequate or misleading content, 2 reflects generally poor quality with some information but significant gaps, 3 indicates moderate quality with sufficient but limited detail, 4 reflects good quality with clear and mostly accurate content, and 5 indicates excellent quality that is comprehensive, reliable, and highly informative.25
A CGM Informational Survey (CIS) was developed by the researcher to evaluate the informational content presented in YouTube videos on the installation and replacement processes of CGM systems. The development process of the survey was based on current guidelines, manufacturer materials, and patient education content from the literature (Table 1). The survey consists of 7 subscales and 24 items. Each item is scored as 1 point for “yes” and 0 points for “no.” The subscales are as follows: (1) General Information, (2) CGM Insertion Preparation, (3) CGM Insertion, (4) Device Activation and Calibration, (5) CGM Use and Daily Monitoring, (6) CGM Removal and Replacement, and (7) Errors and Solutions.
The total CIS score ranges from 0 to 24, with higher scores indicating greater informational adequacy. A score of 0 indicates that no information was provided. Scores between 1 and 8 reflect low-level information, 9 to 16 indicate moderate-level information, and 17 to 24 reflect high-level information. The content validity of the survey was assessed by 5 experts, and necessary adjustments were made based on the preapplication. Videos were evaluated by 2 independent assessors, and the average scores were used for the analysis. The CIS is a comprehensive tool developed to objectively assess the educational value of videos related to CGM application processes.5,26-32
The data obtained from the study were analyzed using IBM SPSS Statistics (Version 22). Descriptive statistics were calculated for continuous variables related to the videos (eg, publication year, view count, video duration, number of likes, follower count, etc), including minimum, maximum, mean, and standard deviation. Nonparametric statistical methods were used when the parametric assumptions were not met based on the distribution characteristics and measurement levels of the data. Spearman’s rank correlation analysis was applied to assess the relationship between video characteristics and scale scores. This analysis was suitable for evaluating nonlinear relationships between data from ordinal scales and was found appropriate for the structure of the study’s data due to the lack of distribution assumptions. Videos were grouped based on the informational level (CIS scores) and content reliability (DISCERN scores), and the Kruskal-Wallis test was used to compare video characteristics across groups. This test is an appropriate nonparametric method for assessing median differences between 3 or more independent groups. The significance level for all statistical tests was set at P < .05.
The publication dates of the videos range from 2017 to 2025, with an average publication year of 2022.51. The view counts range from 154 to 3 200 000, with an average of 194 688.80 views. The video durations vary from .45 minutes to 46.52 minutes, with an average duration of 7.75 minutes. The like counts range from 0 to 551, with an average of 133.11 likes. The quality evaluations of the videos, measured by the GQS, range from 1 to 4, with an average score of 2.80. The DISCERN scores range from 17 to 62, with an average of 34.57. The informational adequacy of the videos, evaluated using the CIS criteria, has an average score of 11.86. The highest content scores were seen in the categories of CGM insertion preparation and device activation, and the lowest scores were in the areas of CGM removal and error solutions. The majority of the videos (80%) were published by individuals with diabetes, and a smaller proportion were produced by health care professionals (2.9%) or manufacturers (17.1%). The most reviewed CGM systems were Dexcom (34.3%) and FreeStyle Libre (25.7%; Table 2).
In this study, the statistical correlations between video characteristics (publication date, view count, video duration, like count, follower count) and information quality and reliability measures (GQS, DISCERN, and CIS) are presented. A significant positive correlation was found between view count and like count (r = .75, P < .001), and video duration showed significant correlations with various aspects of information quality, such as GQS (r =.71, P < .001), DISCERN (r = .64, P < .001), and CIS (r = .80, P < .001). Additionally, like count was positively correlated with CIS scores, particularly in the CGM removal and replacement category (r = .38, P = .02). These correlations suggest that videos with higher engagement (view and like counts) tend to have higher information quality and reliability scores. However, follower count showed limited significant correlations with information quality measures (Figure 2).
In this study, a statistical comparison of the video characteristics and information levels (low, moderate, and high) of CGM videos revealed significant differences in video duration, GQS, and DISCERN scores. Videos with highlevel information had significantly longer durations (19.71 ± 11.33 minutes) compared to those with low (2.11 ± 1.44 minutes) and moderate levels of information (4.55 ± 2.69 minutes; P < .001). High-level information videos also had significantly higher GQS (4.00 ± 0.00) and DISCERN scores (50.11 ± 9.50) compared to low-level (GQS: 1.60 ± 0.51; DISCERN: 22.80 ± 3.93) and moderate-level information videos (GQS: 2.88 ± 0.50; DISCERN: 33.19 ± 4.84), with both differences being statistically significant (P < .001). However, there were no significant differences observed for publication date, view count, like count, or follower count across the different information levels (Table 3).
A statistical comparison of video characteristics across DISCERN reliability groups (very poor, poor, fair/moderate, good) showed significant differences in video duration, GQS, CIS, and specific CIS subscales. Videos rated as good quality had the longest duration (23.99 ± 13.54 minutes) compared to those with very poor (2.53 ± 1.64 minutes), poor (4.86 ± 3.53 minutes), and fair/moderate (10.64 ± 7.61 minutes) ratings (P = .03). Videos with higher DISCERN reliability scores (good) also had significantly higher GQS (4.00 ± 0.00) and CIS scores (18.20 ± 2.16) compared to lower rated videos, with both differences being statistically significant (GQS: P < .001; CIS: P < .001). Specific subscales, such as CGM Insertion Preparation (P = .001), Device Activation and Calibration (P = .004), CGM Use and Daily Monitoring (P = .004), CGM Removal and Replacement (P = .01), and Errors and Solutions (P = .01), showed significant differences across the DISCERN groups. No significant differences were found for publication date, view count, like count, or follower count across the groups (Table 4).
Digital platforms, especially widely used video-sharing sites such as YouTube, have become an important educational resource in diabetes management.33,34 However, there are serious uncertainties regarding the informational nature, quality, and reliability of the content presented on these platforms. Findings from the analysis of YouTube videos in this study indicate that a significant portion of videos related to CGM systems are usergenerated and generally have a moderate level of informational adequacy. Most of these videos feature the experiences of individuals with type 1 diabetes and include personal solutions they have developed to address issues related to device usage. This suggests a potential gap in professionally developed educational content related to diabetes technology.
A study33 of English-language CGM videos reported an average comprehensiveness score of 4.56, indicating a moderate level of informational detail. Furthermore, 40% of the videos were shared by health care professionals, which was still considered insufficient in English-language videos as well.33 The fact that the videos analyzed were published between 2017 and 2025 suggests that the content is current and includes the most up-to-date information and versions of the latest generation CGM systems. The wide range of video views (range 154-3 200 000) and likes (range 0-551) demonstrates the variability in public interest regarding CGM-related content. The average video length of 7.75 minutes suggests that users tend to prefer brief access to information. In this study, videos with a higher level of informational content were significantly longer in duration, indicating that delivering educational content may require a minimum length and that engagement metrics alone may not reflect content quality. Studies evaluating the informational value, quality, and reliability of videos on various diseases on YouTube have also reported similar short durations and variability in technical features, such as likes and views.35 For example, osteoporosis-related videos averaged 5.80 minutes, insulin resistance videos 10 minutes, and insulin administration videos 8.55 minutes.36-38 The average CIS of the videos in this study was 11.86, which points to a moderate level of informational adequacy.
However, the average DISCERN score of 34.57 and GQS of 2.80 indicate that the videos were limited in terms of content quality and reliability. The highest scores were observed in the categories of CGM device activation and calibration, whereas the lowest scores were found in the CGM errors and solutions subdimension, particularly indicating a lack of accessible information in these areas. It was found that 33% of English CGM videos were of moderate quality and that 60% were moderately reliable. Additionally, the videos produced by health care professionals were found to be of higher quality and reliability.33 The most frequently evaluated CGM systems were Dexcom (34.3%) and FreeStyle Libre (25.7%), suggesting these systems are more commonly used globally and have higher recognition among users and content creators. This finding implies that these brands are more visible on social media and video platforms due to factors such as technological advancements, ease of use, or marketing strategies. Dexcom was also identified as the most commonly used CGM brand in a recent study.39
According to the research findings, video length was positively associated with higher levels of informational adequacy, quality, and reliability scores. Videos with a high level of informational content had an average length of 19.71 minutes, whereas those with low content quality averaged only 2.11 minutes (P < .001). Similarly, videos with high informational content received significantly higher DISCERN (50.11) and GQS (4.00) scores. These results suggest a direct relationship between video length and content quality, indicating that more detailed explanations provide greater benefit to users. Videos rated as having moderate usefulness for insulin administration had the shortest average duration (5.83 ± 4.23 minutes).38
On the other hand, no significant relationship was found between social media engagement metrics, such as view count, number of likes, or number of subscribers, and the information quality or content scores. This indicates that users are often exposed to low-quality content and that YouTube’s algorithm ranks videos based more on popularity than on content quality, which poses a serious risk in the context of health education. However, the finding of a significant positive correlation between engagement metrics (eg, number of likes) and CIS scores specifically in the CGM errors and solutions subdimension suggests that users value content that offers practical solutions. Videos containing more accurate information were reported to receive more views, likes, and comments.37
Significant differences observed among DISCERN reliability groups particularly regarding video length, overall information quality (GQS), and content adequacy (CIS) show that videos with higher reliability scores offer more qualified content. Longer video durations in the high-reliability group indicate that the information was conveyed more thoroughly, offering more comprehensive education to users. This supports the frequently emphasized point in the literature that the qualitative depth of video content, rather than its quantity, is the determining factor in user education. In another study,36 approximately two-thirds of the videos were presented by health care professionals, and these were reported to be of higher quality and reliability. Similarly, a positive correlation was found between DISCERN and GQS scores in a recent study.40
A study analyzing English CGM videos also reported that videos with high levels of informational content had higher quality and reliability.33 Additionally, significant differences found in the CIS subscales showed that videos that addressed CGM application processes in detail were perceived as more reliable. In contrast, no significant differences were found between DISCERN reliability groups and engagement indicators, such as views, likes, or subscribers, indicating that user engagement may not always reflect content reliability. These findings underscore the importance of prioritizing evidence-based content development over popularity-driven dissemination strategies. One study33 also noted that metrics such as views and likes are often used as indicators of popularity but do not necessarily reflect the accuracy or reliability of the information provided.
The findings of this study emphasize the need for standardizing the quality of digital health materials related to CGM use. It is essential for health care professionals and manufacturing companies to produce accurate, up-todate, and comprehensive content on high-access platforms like YouTube to reduce user errors and potential complications. Especially, companies should develop comprehensive videos in the language of each country where the device is marketed. Furthermore, mechanisms such as content accreditation or verified health information labels could help users access accurate information more easily.
This study has certain limitations. Because only Turkish-language videos were analyzed, the results cannot be generalized to other languages or cultures. Additionally, comments and user feedback on the videos were not analyzed. Nonetheless, the use of a unique assessment tool and the multidimensional, systematic evaluation of the videos are among the study’s strengths.
This study examined how accurate and useful Turkish-language YouTube videos are regarding the installation and replacement of CGM systems. The findings revealed that most of the videos were created by users and were primarily based on personal experiences. However, the majority of these videos lacked sufficient medical accuracy and detailed information. Notably, there were very few videos produced by health care professionals. From a public health perspective, it is essential that individuals with diabetes have access to reliable information, and therefore, health care professionals should take an active role in producing educational content on such topics. Additionally, ensuring that health-related content published on platforms like YouTube meets specific quality standards is crucial to prevent the spread of misinformation. As a result, it is recommended to provide training to enhance digital health literacy and to develop health policies that facilitate access to accurate and trustworthy information. In conclusion, YouTube content on CGM systems is insufficient in terms of informativeness. Because digital health content directly influences individuals’ health decisions, creating accurate and reliable content is critical. This study aims to contribute to efforts to improve the quality of digital health education.
The authors gratefully acknowledge the contributions of the content creators whose videos were evaluated in this study.
Study conception and design: Dilek Büyükkaya Besen, Merve Dervişoğlu. Data collection: Merve Dervişoğlu, Merve Günbaş. Data analysis and interpretation: Merve Dervişoğlu, Dilek Büyükkaya Besen, Merve Günbaş. Drafting of the article: Dilek Büyükkaya Besen, Merve Dervişoğlu. Critical revision of the article: Dilek Büyükkaya Besen.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Merve Dervişoğlu https://orcid.org/0000-0001-8257-9842
Merve Günbaş https://orcid.org/0000-0001-7868-3292
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From Internal Medicine Nursing Doctorate Program, Dokuz Eylul University Institute of Health Sciences, Izmir, Turkey (Ms Dervişoğlu, Dr Günbaş); and Internal Medicine Nursing, Dokuz Eylül University Faculty of Nursing, Izmir, Turkey (Assoc, Prof, Dr Dilek Besen).
Corresponding Author: Merve Dervişoğlu, Internal Medicine Nursing Doctorate Program, Dokuz Eylul University Institute of Health Sciences, Izmir 35210, Turkey. Emails: merve.dervisoglu@deu.edu.tr, merve.dervisoglu95@gmail.com
