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Article

Use of Educational Animated Videos by Kidney Transplant Seekers and Social Network Members in a Randomized Trial (KidneyTIME)

1
Department of Surgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA
2
Transplant and Kidney Care Regional Center of Excellence, Erie County Medical Center, Buffalo, NY 14215, USA
3
Department of Epidemiology and Environmental Health, University at Buffalo School of Public Health and Health Professions, Buffalo, NY 14203, USA
*
Author to whom correspondence should be addressed.
Kidney Dial. 2025, 5(1), 4; https://doi.org/10.3390/kidneydial5010004
Submission received: 30 November 2024 / Revised: 7 January 2025 / Accepted: 8 January 2025 / Published: 22 January 2025

Abstract

:
Animated video could improve the reach of health education to kidney transplant (KT) seekers and their social network. Usage outcomes are rarely considered. This exploratory study aims to investigate use patterns of an animated video-based intervention (KidneyTIME) and examined associations with patient characteristics. Descriptive, quantitative analyses were conducted on user data (April 2022–March 2024) of KT-seekers allocated to the intervention arm of an ongoing randomized controlled trial of KidneyTIME. Of 195 KT-seekers allocated to KidneyTIME, optional use (defined as ≥1 video view or share) was 74% at 6 months follow-up and significantly higher among patients in the pre-evaluation phase (Odds Ratio [OR] 2.63, p = 0.0051) and with an active Facebook account (OR 2.93, p = 0036). Higher total video viewings were associated with single adult household (p = 0.0496). Not employed participants viewed more different videos (p = 0.0168). More days of viewing was significantly (p < 0.05) associated with older age, worse health, not employed, and single adult household. Video sharing was significantly associated with social media use (OR 2.86, p = 0.0264), active Facebook account (OR 2.55, p = 0.0411), and lower health literacy score (OR 2.80, p = 0.0274) and inversely associated with lower social support score (OR 0.35, p = 0098) and male sex (OR 0.48, p = 0.0394). Web-based animated video education promoted through email or text links is a viable modality to reach diverse KT-seekers.

1. Introduction

Many transplant programs provide an initial bolus of transplant education to kidney transplant (KT) seekers and their supportive others in the early process of evaluation, but then may have minimal contact during initial transplant testing and while on the waiting list. Patients need education throughout the kidney transplant process to optimally get on the waitlist, consider organ offers, and search for living donors [1,2,3]. Supportive others need education to know how to help patients in the transplant process and to consider living kidney donation. Limited time and resources prevent optimal education provision from transplant centers. Digital interventions may be an effective way to engage individuals in self-learning; however, prior research demonstrates that digital interventions are not equally accessed by people who could benefit from them [4], and there is little evidence that digital interventions for transplant access can effectively engage individuals. This study examined transplant information-seeking behaviors of KT-seekers and social network members when web-based animated videos are promoted through links delivered by email or text message, such as within the KidneyTIME study, and the inclusivity of usage.
KidneyTIME is a self-directed digital intervention designed to influence the behavior of patients and social network members towards kidney transplantation and living donation [1,2,5]. The intervention leverages shareable animated videos to, on the one hand, facilitate individual outreach actions based on video sharing, and on the other hand, patient and social network knowledge, motivation, and self-efficacy, based on educational content. Each video within the intervention has been feasibility tested and shown to increase knowledge between 10% to 70% in before-and-after studies [5]. The intervention is currently being trialed among KT-seekers at a single center for effectiveness to increase living-donor kidney transplant cognition and behaviors.

Objectives

With very few digital interventions available for transplant access [6,7,8], it is unclear whether KT-seekers and/or their social network members are likely to access transplant education when provided in links to a webpage containing animated educational videos and whether usage differs across patient factors. This 6-month evaluation is the first review of KidneyTIME trial data conducted to provide insight into intervention usage and its ability to promote inclusive transplant education uptake. We chose to focus on the first 6 months after program enrollment because we hypothesized that participants may be more likely to interact with the intervention shortly after joining the program reflecting their initial motivation to participate. Future analyses will report on the effects of the intervention on LDKT cognitions, behaviors, and live kidney donor inquiry, the main outcomes for this randomized trial. This study investigated use patterns of an animated video-based intervention (KidneyTIME) and examined associations with patient characteristics.

2. Materials and Methods

2.1. Study Design

This is an analysis of cross-sectional data obtained during a single-center randomized controlled trial (RCT)—KidneyTIME. The outcomes of this study were to explore optional use of the digital intervention during the first 6 months of intervention access and usage variation in relation to participant factors. Details regarding the study design and methods are reported below. The RCT from which these data were drawn was pre-registered (#NCT05154773). However, the analyses reported here were exploratory and not preregistered. User data was extracted from the KidneyTIME server to create an isolated dataset and an attributable user key is created within to enable analysis for each patient participant. Electronic data were supplemented by survey results for the outcome of video sharing, since not all sharing behaviors are detectable electronically. The study protocol was approved by the University at Buffalo, The State University of New York, Internal Review Board.

The Intervention

Through electronic messages, email or text, the KidneyTIME trial delivered to patients a 13-min core educational animated video followed by time-based electronic messages with links to a study webpage containing more intervention videos. The study webpage hosted 25 videos, of which 12 were structured around kidney transplant access, 12 around the donation process, and 1 was an introduction to donor search advocacy. Electronic messages were delivered every 21 days for 12 months; 12 unique messages reminded users to access certain videos and 1 general message (delivered 5 times) promoted viewing of the video collection as a whole. Intervention use was possible with all smart devices on any browser by clicking on unique links sent via email or text and did not require activation or log in. All intervention content was designed by transplant providers, experts, and patients, donors, and family/friends to support self-learning about kidney transplantation and donation.

2.2. Participant Recruitment and Inclusion Criteria

The KidneyTIME webpage was provided to intervention arm participants in a randomized controlled trial. To be eligible for the trial, patients must be referred to Erie County Medical Center (ECMC) for a kidney transplant, English-speaking, age ≥ 18 years, have access to email or text messaging, and provide electronic informed consent. Previous exposure to a LDKT educational intervention or lack of internet access were considered exclusion criteria.
Research staff attempted to approach all pre-transplant patients referred to the center who had not been previously exposed to the intervention, and enrollment was entirely remote through the participant’s device; 85% were found eligible and 57% (n = 422) enrolled. Allocation to intervention or active control arms was 1:1 and race- stratified. The control group received the transplant centers usual care video online-a 13-min nurse-narrated power-point-based video outlining recipient process and outcomes while briefly covering the option of LDKT. The day after completing an electronic baseline survey, intervention-group participants received a unique link to the webpage via email or text and could use it at any time after receiving access. Participants also received use-reminder messages with links to the webpage every 3 weeks for one year. The link opened to a simple homepage that required 3 clicks to view content. Participants were encouraged to view and share videos through electronic messages and prominent share buttons positioned on the homepage and under each video. As shown in Figure 1, video sharing was possible by forwarding electronic messages, copy-pasting a link to the video or webpage, and by using share buttons on the webpage that directly shared through email, Facebook, and Twitter-X. Research staff did not encourage intervention use. No participant training was provided. Of the original 212 intervention participants, 14 were removed since they did not complete baseline and 3 were removed due to a technical glitch resulting in no webpage access. The total analytic sample was n = 195.

2.3. Data Integrity

Data were monitored over the course of the study to ensure participants were appropriately randomized, baseline data were collected, and automated user statistics on program use were being appropriately captured.

2.4. Measures

Baseline measures are shown in Table 1. Sociodemographic and other measures, including health, technology access or use, health literacy [9], and basic social support [10] were taken during the self-report baseline survey. Measures of health insurance type, estimated post-transplant survival (EPTS), and evaluation phase at study enrollment were derived from the medical record.
Electronic usage measures were recorded by the intervention server including mode of receiving the intervention (text, email) and usage data (log-stamp data) and supplemented by self-report survey. Measures reflecting essential interactions in the digital intervention to facilitate behavior change were selected [11]. Intervention use was defined as any video view or share. A video view was defined as opened or did not open a video (detected electronically), regardless of duration of the view since most viewed the whole video. A video share was defined as sharing at least one intervention video or webpage. Video sharing was assessed on self-report survey at 1- and 6- months post-baseline, including relationship of sharee and sharing channel (in-person, email, text, Facebook, other). Extent of video usage was explored through 3 dosage operationalizations detected electronically, number of days on which videos were viewed, number of different videos viewed, and total number of times the videos were viewed. Each dosage operationalization provides a unique perspective. Dosage in days of use examines persistence of engagement over time. Number of different videos viewed examines the amount of the content engaged with. Number of total videos viewed examines the extent that people they shared the content with (sharees) engaged with the content or that participants rewatched.

2.5. Data Collection and Analysis

Descriptive quantitative analysis was conducted to explore program usage. Activity in the program at the feature level was described for all users, patients and sharees, across the 6 months among patients that remained active in the study. Categorical variables were summarized as frequencies and percentages. Continuous variables were summarized as median and interquartile range or mean and standard error. Logistic regression modeling was used to identify associations between participant factors and intervention used/not used and video shared/not shared. Odds ratios (ORs) with 95% confidence intervals (CI) and p values are provided. ANCOVA models investigated the relationship between baseline characteristics on days of video viewing, number of different video views, and total videos viewed. In the trial, study status was inactivated when patients received transplants or were determined ineligible for transplantation. Therefore, all models adjusted for participant time in study. Sensitivity analyses were conducted assessing alternative video view durations of >50% and >90% in ANCOVA models and the significance or direction of the results did not change. Data on video titles viewed and video categories were summarized descriptively. Statistical analyses were performed using SAS version 9.4 (SAS Institute, Inc., Cary, NC, USA). A two-sided p-value < 0.05 was considered statistically significant.

3. Results

3.1. Sample Characteristics

A total of 212 KT-seekers participated and were randomized to use KidneyTIME between April 2022 to July 2023. After allocation and baseline completion, 195 participants completed the main survey (including questions and core educational video) resulting in access to the optional intervention featuring time-based emails or texts with links to the study webpage (Figure 2). Table 1 shows the characteristics of the 195 participants who received access to the optional intervention (electronic reminders to use webpage). Within 1 month 48% (95/195) of participants or sharees used the optional intervention by viewing or sharing at least one video. This increased to 74% (144/195) at 6 months follow-up.

3.2. Optional Intervention Users vs. Not Users

Compared to not users, optional intervention use was significantly higher among patients in the pre-evaluation phase of the transplant process (OR 2.63, p = 0.0051) and who self-reported as active Facebook users (OR 2.93, p = 0.0036) (Table 2). No statistically significant differences were observed in optional intervention use across age, race, gender, education status, employment, income, insurance, health status, computer ownership, social media use, literacy level, social support score, or modality of study enrollment.

3.3. Extent of Video Viewing by Users

Education videos were viewed by or on behalf of 122 participants (63%) a total of 4853 times (median 21.0, IQR 7–49, range 1–267) over 6 months. The observed distribution of education video viewing showed that 59% of participants viewed ≥ 1 video (themselves or their sharee) in the first month of having KidneyTIME webpage access. Viewing incrementally decreased over time from 38% in the second month to 20% in month 6 (Figure 3).
On average, video viewers accessed the content on 2.7 different days (median 2, IQR 8, range 1–9), viewed an average of 11.6 different videos (median 11, IQR 15, range 1–25), and clocked an average of 40 video viewings (median 21, IQR 42, range 1–267). Table 3 shows education video activity for users by patient characteristics. More days of video use was significantly associated with older age (age < 50 mean 1.99, age 50–60 mean 2.55, age > 60 mean 3.47), poorer health (EPTS > 70% mean 3.69; EPTS < 70% mean 2.50), not employed (not employed mean 2.92, employed mean 1.95), and single adult household (single adult mean 3.40, another adult mean 2.48). More different videos viewed was significantly associated with not working status (not working mean 12.54, working mean 8.06). More total video views were significantly associated with single adult household (single mean 55.00, another adult mean 34.37). No statistically significant differences were observed between video viewing dosage operationalizations and patient characteristics including sex, race, educational attainment, dialysis duration, insurance, income, computer ownership, literacy level, social support score, evaluation phase of study entry, or modality of study enrollment while adjusted for active study days (Table 3).

3.4. Video Sharing

At 1-month follow-up, 43% of 138 participants had shared a video from the intervention and by the 6-month follow-up this increased to 52% (72/138) of participants having shared according to self-reported survey data. Of the 72 who shared, 93% (62/72) shared to core family members (partners 64%, children 39%, siblings 36%, parents 19%); 51% (37/72) shared with peripheral members (friends 36%, other relatives 29%, other people in my life 24%); and 11% (8/72) shared with strangers. Sharing occurred predominantly in person (83%), including in person only (56%) and both in person and electronically (27%); 17% shared electronically only through email, text, or social media. Significantly greater odds of sharing was associated with patient’s use of social media (OR 2.86, p = 0.0264), active Facebook account (OR 2.55, p = 0.0411), and lower health literacy score (OR 2.80, p = 0.0274) and was inversely associated with lower social support score (OR 0.35, p = 0.0098) and male sex (OR 0.48, p = 0.0394). Video sharing did not vary as a function of patient age, race, educational attainment, health, computer ownership, insurance type, evaluation stage of study entry, or modality of study enrollment while adjusted for active study days. (Table 4)

3.5. Video Content

Figure 4 shows the number of mean video views per participant for each unique video on the webpage and the extent of viewing duration in terms of: any view duration, 50% view duration, and 90% view duration. Regardless of viewing duration definition, the top 3 most viewed topics were: an introduction to living kidney donation, living kidney donation surgical complications, and post-transplant clinic visits.

4. Discussion

In order to maximize accessibility of future digital programs for promoting LDKT access, we need a better understanding of who engages in these programs and the amount of engagement. Program engagement is critical for any intervention to be effective; however, promoting program engagement is a particularly important issue in digital interventions because treatment exposure is often dependent on the motivation and self-direction of the individual user. This evaluation explored trial-based digital intervention usage data to provide insight into viewing and sharing of educational animated videos among KT-seekers at a single transplant center, using KidneyTIME as a potential method to promote education uptake by patients and their social network members and compared the relative usage of the intervention by participant characteristics. KidneyTIME trial usage data shows that 74% of participants used the optional intervention (either patients or sharees) by sharing and/or viewing a video over 6 months. Below, we discuss usage activity within the context of the intervention and patient characteristics.

4.1. Intervention Context

Use of the intervention after initial exposure to core educational content was high, with 49% (patients and/or sharees) choosing to view or share study videos in the first month, demonstrating interest in the topic and content in the form of animated video. This increased to 74% by month 6. The rate is similar to our previous work in which both patients and caregivers in the clinic received links to the study webpage; 77% of either patients or caregivers self-reported viewing it and 63% shared it by 6 weeks [12]. It is difficult to compare the ongoing usage to other technology-based studies. Gordon et al. found that 33% returned to a multimedia website at 3-weeks’ time after returning home from viewing it at the transplant center. Arriola et al. found that educational DVDs were watched at home by 46% by 6 months follow-up [13].
Active viewing of KidneyTIME videos was electronically detected amongst 59% of participants during month 1 and was maintained around 20% during months 5 and 6. Ongoing usage was likely due to technological features that encouraged revisiting. For example, gaining access did not require logging in, tunneling through web pages, entering time-consuming data fields, or downloading an app. The architecture of the webpage was simple and functionally intuitive. Use of automated messages to prompt intervention usage (8 total messages by 6 months) may have had additional benefit. Aligning with these findings, qualitative interviews of intervention participants indicated that participants valued the program content for being ‘good information’ and ‘interesting’ and that the site was ‘convenient’ and ‘simple to use,’ including on their phones and that the electronic reminders both prevented forgetting and motivated viewing of proposed topics [14].
Videos were shared by 52% of survey respondents. This self-reported data up to 6 months revealed that the videos were predominantly presented face-to-face (by 83% of patients) to core family members and were electronically shared (email, text, Facebook, Twitter-X) by 44% of patients. Prior interview data of patients indicated that the most used ways of electronic sharing were by forwarding links in electronic messages or copy-pasting links, rather than using the webpage share buttons [14]. In terms of sharing LDKT access interventions with others, many interventions seek to include individuals from patients’ social network to attend educational sessions, yet social network attendance to physical sessions has been problematic, with 33% [15] to 100% [16] not attending with the patient. This is especially important since positive effect of such interventions correlates with social network size and attendance at the session [3]. To offset low attendance by social network members, interventions, such as ours, that facilitate dissemination of LDKT knowledge are needed.

4.2. Patient Characteristics

The literature reports a number of concepts concerning variable usage patterns in technology-based interventions for those with long-term conditions, such as age, social status, education, and health literacy that influence behaviors [17]. We found KidneyTIME video viewing on more different days was significantly higher with populations that may be hard to reach with physical site interventions including older persons, those with worse health, non-employed (retired, disabled, unemployed), and lacking another adult living in the household. Age is often considered a barrier to technology use, yet these results show that age did not appear to represent significant barriers to use of KidneyTIME. In fact, a trend was observed, indicating an increase in viewing activity from younger to older users. Subpar engagement is often attributed to low levels of digital health literacy, however, usability and design of digital health technologies play a large role [18]. Our prior qualitative data indicated that links to the webpage were easy to find in emails, and texts and access to the content was simple to use by clicking buttons on the site [14]. In contrast, fewer days of video viewing was seen among individuals who were younger, healthier, employed, and living with another adult in the household. This may be due to time constraints or feeling sufficiently informed. Some patients may have benefited from a single day of access to the educational content and therefore did not necessarily require continuous long-term engagement. This would be in keeping with interview findings that some patients viewed all the videos in a row and did not return to re-watch whereas others returned to the site when they had time or questions [14].
The reasons for intervention non-usage are unknown, however, it is possible that the access link to the videos was not received, potential users were not technology enabled, did not have consistent access to the internet or would have been the cohort not to engage, regardless of the additional digital option to support transplant education. Regarding the most appropriate cohort to engage, our data show that pre-evaluation patients who had not yet attended the evaluation at the transplant center (which includes transplant education) were more likely to use the intervention compared to post-evaluation patients, who may have felt they had received sufficient information. Participants self-reporting male sex and lower basic social support were less likely to share the intervention; however, these characteristics did not influence the amount of video viewing. The reasons for this discrepancy are unclear.
The heterogeneity in animated educational video usage among KT-seekers and sharees shows that there is room for improvement. To improve usage, additional components of the intervention may need to be structured/mandatory or further enabled by providing digital support and human interaction, such as by mobilizing caregivers, involving navigators, leveraging provider encouragement and/or using social networking sites. Trials have shown that patients who are supported (human contact) to use a web-based self-education platform had greater uptake in registration to wider demographics of patients than those who are less supported [19].

4.3. Limitations

It is unclear how much intervention activity was by the patient compared to social network members or the public since video use activity could also be generated by sharees, who could open the participants unique link to view the content and further share it themselves. It is not clear if the results will generalize to other web-based LDKT access programs since engagement is associated with the specific content and format of an intervention. Similarly, we do not know if the results will generalize to other KT-seekers outside of our area. All KT-seekers in the current study were referred to a center in western New York, and the majority were White and Black race and low-income. Most demographic data in this study are user reported and some putative sociodemographic characteristics may not have been measured. Sharing data was self-reported and potentially subject to social desirability and recall bias. There was no social network data collected, meaning social network measurements cannot be determined because of intervention implementation. Use of study webpage educational resources are unlikely to be true reflections of patterns of use in the real world. As a result, further research is needed to assess other user demographics and potential selection bias of those who used versus who did not use the video content. Exploration of the impact of user engagement on transplant access was not possible due to the nature of the study. However, this is an important consideration for future studies. There’s also a need to further understand user engagement with digital health attrition rates and behaviors that influence self-education for individuals seeking kidney transplantation and their social network members. Studies focusing on social network engagement and defining optimal content delivery strategies would provide knowledge of clinical and economic impact, benefits, and challenges.

5. Conclusions

Using technologies to improve patient and social network learning about kidney transplantation and donation may improve transplant access. Effectiveness will depend on uptake of the educational technology. This work explores the use of the KidneyTIME intervention during its deployment in a randomized clinical trial. This analysis highlights the wide range of demographics that engaged with the offer of KidneyTIME, where results show no large differences across age, gender, and socioeconomic status. Although pre-transplant phase and active Facebook account were associated with any use of the intervention, these characteristics did not influence the amount of video viewing. Video sharing was higher amongst females, social media/Facebook users, lower-literacy learners, and those with greater perceived social support. Results suggest that through email or text transmissions of links directing patients to a simple interface hosting shareable animated videos, digital platforms such as KidneyTIME can provide reinforcement to promote transplant self-education with broad reach, offer the ability to simplify education for patients and their social network, overcome attendance barriers, and increase access to education delivery for those, unable or unwilling to attend in person, as well as facilitate education dissemination toward finding a live kidney donor and generating social support. There is potential for decreasing healthcare system burden and increasing transplant education rates by offering patients additional digital options in combination with traditional service delivery which should be substantiated through further research.

Author Contributions

Conceptualization, L.K.K.; methodology, L.K.K.; formal analysis, L.K.K. and J.N.; data curation, A.S., M.H. and M.K.; writing—original draft preparation, L.K.K.; writing—review and editing, L.K.K., A.S., M.K. and M.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health, grant number R01DK129845.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of the University at Buffalo, the State University of New York (protocol number 00005449; approved 1 July 2021).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

We wish to express thanks to Katia Noyes, Laurene Tumiel-Berhalter, Renee Cadzow, Jon Von Visger, and Thomas Hugh Feeley for their review of the manuscript. We are thankful for the data collection and entry assistance, consultation, and collaborative efforts we received from several individuals, including Sydney Pelino, Colleen Hagler, and Beth Dolph.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Possible ways participants could share the intervention webpage and videos.
Figure 1. Possible ways participants could share the intervention webpage and videos.
Kidneydial 05 00004 g001
Figure 2. Study Flow Diagram at 6-months Follow-up. unk, unknown; (–) not done; (+) done.
Figure 2. Study Flow Diagram at 6-months Follow-up. unk, unknown; (–) not done; (+) done.
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Figure 3. Proportion of participants or sharees who viewed any video across 6 months of access (number of participants who viewed/number active in the study). m, months post-baseline.
Figure 3. Proportion of participants or sharees who viewed any video across 6 months of access (number of participants who viewed/number active in the study). m, months post-baseline.
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Figure 4. Amount of viewing per video.
Figure 4. Amount of viewing per video.
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Table 1. Baseline Patient Characteristics.
Table 1. Baseline Patient Characteristics.
Characteristic
% or Median (Interquartile Range)
Total
(N = 195)
Email delivery of intervention
Text delivery of intervention
67%
33%
Pre-evaluation phase at study enrollment
Post-evaluation phase at study enrollment
51%
49%
Age < 50 years
Age 50–60 years
Age > 60 years
32%
35%
33%
Sex, Male56%
Black or African American
non-Hispanic White
Hispanic or Latino
Other
35%
49%
7%
9%
Education, no college degree62%
No prior kidney transplant86%
Not requiring dialysis at study enrollment23%
EPTS a, continuous 44 (46)
Works full or part-time19%
Medicaid, state, or Veterans insurance
Other insurance
53%
47%
Total annual household income ≤ US $30,000
Total annual household income $30,000 to $50,000
Total annual household income > $50,000
Prefer not to answer
50%
18%
22%
10%
Number of close friends or relatives: 4+48%
Single adult household28%
Has working computer63%
Watches videos online89%
Uses social media78%
Has active Facebook account77%
Health Literacy b < 25th percentile23%
Basic Social Support c < 25th percentile26%
a EPTS, Estimated Post Transplant Survival Score. Based on a range of 0–100%, higher scores predict worse patient survival. Computed using https://optn.transplant.hrsa.gov/data/allocation-calculators/epts-calculator/ (accessed on 14 June 2023). b Health literacy was measured with two items [9] scored on 4 point Likert-type scales: “How often do you have someone help you read hospital materials?” “How confident are you filling out forms by yourself?” (Cronbach’s alpha = 0.62 in the trial). c Basic Social Support was measured by a 6-item survey [10] with items scored on 4 point Likert-type scales (4 options): Frequency someone is available to: prepare meals if unable to do so [instrumental], take to doctor if needed [instrumental], help with daily shores if sick [instrumental], give good advice about crisis [emotional], confide or talk to about problems [emotional], who can understand your problems [emotional]. (Cronbach’s alpha = 0.90 in the trial).
Table 2. Logistic regression analysis of intervention used by baseline characteristics (n = 195) a.
Table 2. Logistic regression analysis of intervention used by baseline characteristics (n = 195) a.
LogisticIntervention Used
Characteristic
(Reference)
Odds Ratio
(95% CI)
p-Value
Text (email)1.48 (0.71–3.06)0.2952
Pre-evaluation phase (Post-evaluation)2.63 (1.34–5.19)0.0051
Age 50–60 years (18–49) b
Age > 60 years (18–49)
1.56 (0.70–3.48)
1.29 (0.59–2.82)
0.2732
0.5273
Sex, Male (female)0.53 (0.27–1.05)0.0678
Race, Black or African American (other)0.53 (0.27–1.04)0.0636
Education, no college degree (college degree)0.59 (0.30–1.19)0.1390
No prior kidney transplant (prior kidney transplant)1.25 (0.51–3.11)0.6259
Not requiring dialysis (some dialysis)1.68 (0.72–3.94)0.2322
EPTS at evaluation ≥ 70% (<70%) b1.09 (0.49–2.42)0.8388
Not working (works full or part-time)0.52 (0.20–1.35)0.1810
Medicaid, state or Veteran’s insurance (other)1.21 (0.63–2.32)0.5640
Total annual household income ≤ US $30,000 (other)1.01 (0.53–1.93)0.9842
Has working computer (none)1.51 (0.78–2.93)0.2180
Watches videos online (no)1.74 (0.68–4.49)0.2503
Uses social media (never)1.62 (0.77–3.43)0.2063
Active Facebook account (no)2.93 (1.42–6.04)0.0036
Number of close friends or relatives: 4+ (<4)1.72 (0.89–3.36)0.1081
Single adult household (another adult lives in household)0.83 (0.42–1.68)0.6001
Health Literacy a < 25th percentile (≥25th percentile)0.66 (0.31–1.38)0.2668
Basic Social Support < 25th percentile (≥25th percentile) 0.65 (0.32–1.32)0.2315
EPTS, estimated post-transplant survival. a Adjusted for active study days. b Not significant when examined as a continuous variable. Emboldened values indicate p < 0.05.
Table 3. ANCOVA analysis of video view dosage operationalizations by baseline characteristics (n = 122) a.
Table 3. ANCOVA analysis of video view dosage operationalizations by baseline characteristics (n = 122) a.
Unique Video ViewsVideo Viewing DaysTotal Video Views
CharacteristicMean (SE)p-ValueMean (SE)p-ValueMean (SE)p-Value
Text
Email
11.70 (1.22)
11.57 (0.98)
0.93182.75 (0.27)
2.70 (0.22)
0.899136.23 (7.47)
42.08 (6.00)
0.5450
Pre-evaluation
Post-evaluation
10.83 (0.97)
12.84 (1.20)
0.19462.65 (0.22)
2.83 (0.27)
0.618436.58 (5.95)
44.70 (7.39)
0.3943
Age 18–49 years
Age 50–60 years
Age > 60 years
10.31 (1.45)
11.84 (1.27)
12.42 (1.28)
0.54271.99 (0.31)
2.55 (0.28)
3.47 (0.31)
0.002124.26 (8.72)
40.65 (7.64)
50.89 (7.74)
0.0803
Male
Female
10.91 (1.04)
12.44 (1.11)
0.31752.60 (0.23)
2.86 (0.25)
0.462335.08 (6.35)
45.14 (6.78)
0.2814
Black or African American
All others
13.53 (1.38)
10.83 (0.89)
0.10382.89 (0.31)
2.65 (0.20)
0.512942.42 (8.56)
38.67 (5.54)
0.7142
No college degree
College degree
12.49 (1.00)
10.49 (1.15)
0.19102.84 (0.23)
2.57 (0.26)
0.440443.73 (6.17)
34.64 (7.05)
0.3350
No prior kidney transplant
Prior kidney transplant
11.74 (0.81)
10.78 (2.17)
0.67902.73 (0.18)
2.65 (0.49)
0.874939.78 (4.97)
39.77 (13.27)
0.9994
Not requiring dialysis
Some dialysis
11.29 (1.46)
11.75 (0.89)
0.79132.79 (0.33)
2.70 (0.20)
0.818843.92 (8.93)
38.24 (5.44)
0.5880
EPTS at evaluation ≥ 70%
EPTS at evaluation < 70%
13.06 (1.67)
11.30 (0.89)
0.35753.69 (0.37)
2.50 (0.20)
0.005455.30 (10.31)
35.87 (5.51)
0.1013
Not employed
Full or part-time job
12.54 (0.83)
8.06 (1.65)
0.01682.92 (0.19)
1.95 (0.37)
0.020743.14 (5.18)
26.75 (10.23)
0.1564
Medicaid, state, or VA insurance
Insurance (other)
11.94 (1.03)
11.25 (1.12)
0.65692.51 (0.23)
2.97 (0.25)
0.176635.90 (6.32)
44.35 (6.86)
0.3682
Household income ≤ US $30,000
Other
12.19 (1.09)
11.09 (1.06)
0.47192.47 (0.24)
2.96 (0.24)
0.152338.99 (6.70)
40.52 (6.49)
0.8706
Has working computer
None
11.00 (0.93)
12.80 (1.29)
0.25812.61 (0.21)
2.94 (0.29)
0.357937.06 (5.73)
44.96 (7.91)
0.4199
Watches videos online
No
11.48 (0.80)
12.93 (2.43)
0.57252.69 (0.18)
2.97 (0.55)
0.632239.46 (4.90)
42.69 (14.87)
0.8371
Uses social media
Never uses social media
11.26 (0.85)
12.96 (1.64)
0.36062.70 (0.19)
2.81 (0.37)
0.794538.85 (5.24)
43.21 (10.07)
0.7012
Active Facebook account = yes
Active Facebook account = no
11.22 (0.84)
13.34 (1.74)
0.27602.62 (0.19)
3.15 (0.39)
0.230537.89 (5.15)
47.90 (10.70)
0.4016
Number of close friends or relatives: 4+
Number of close friends or relatives: <4
11.53 (1.07)
11.72 (1.09)
0.90012.63 (0.24)
2.81 (0.24)
0.602140.54 (6.55)
38.99 (6.66)
0.8690
Single adult household
Another adult lives in the household
12.46 (1.48)
11.33 (0.88)
0.51383.40 (0.33)
2.48 (0.19)
0.017155.00 (8.94)
34.37 (5.33)
0.0496
Basic Social Support < 25th percentile
Basic Social Support ≥ 25th percentile
12.11 (1.56)
11.47 (0.87)
0.72302.95 (0.35)
2.65 (0.20)
0.464645.85 (9.53)
37.88 (5.32)
0.4668
Health Literacy a < 25th percentile
Health Literacy a ≥ 25th percentile
12.67 (1.79)
11.39 (0.84)
0.52063.14 (0.40)
2.63 (0.19)
0.255651.62 (10.93)
37.17 (5.11)
0.2338
EPTS, estimated post-transplant survival; VA, veteran’s administration. a adjusted for active study days. Emboldened values indicate p < 0.05.
Table 4. Logistic regression analysis of any video shared by baseline characteristics (n = 138) a.
Table 4. Logistic regression analysis of any video shared by baseline characteristics (n = 138) a.
Any Video Shared
Characteristic
(Reference)
Odds Ratio
(95% CI)
p-Value
Text (email)0.92 (0.45–1.91)0.8317
Pre-evaluation phase (Post-evaluation)1.13 (0.57–2.22)0.7317
Age 50–60 years (18–49) b
Age > 60 years (18–49)
0.85 (0.37–1.96)
0.68 (0.29–1.63)
0.7017
0.3904
Sex, Male (female)0.48 (0.24–0.97)0.0394
Race, Black or African American (other)1.62 (0.77–3.40)0.2009
Education, no college degree (college degree)1.75 (0.88–3.49)0.1140
No prior kidney transplant (prior kidney transplant)2.18 (0.80–5.98)0.1292
Not requiring dialysis (some dialysis)0.67 (0.31–1.45)0.3049
EPTS at evaluation > 70% (<70%) b1.06 (0.45–2.49)0.8879
Not working (works full or part-time)0.65 (0.28–1.51)0.3134
Medicaid, State, VA insurance (other)1.06 (0.54–2.10)0.8567
Total annual household income ≤ US $30,000 (other)0.84 (0.43–1.66)0.6207
Has working computer (none)1.43 (0.70–2.92)0.3253
Watches videos online (no)1.24 (0.42–3.69)0.6978
Uses social media (never)2.86 (1.13–7.21)0.0264
Active Facebook account (no)2.55 (1.04–6.25)0.0411
Number of close friends or relatives: 4 + (<4)1.44 (0.73–2.84)0.2923
Single adult household (no)0.73 (0.33–1.59)0.4212
Health Literacy < 25th percentile 2.80 (1.12–6.97)0.0274
Basic Social Support < 25th percentile0.35 (0.16–0.77)0.0098
EPTS, estimated post-transplant survival. a adjusted for active study days. b Not significant when examined as a continuous variable. Emboldened values indicate p < 0.05.
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MDPI and ACS Style

Kayler, L.K.; Nie, J.; Solbu, A.; Keller, M.; Handmacher, M. Use of Educational Animated Videos by Kidney Transplant Seekers and Social Network Members in a Randomized Trial (KidneyTIME). Kidney Dial. 2025, 5, 4. https://doi.org/10.3390/kidneydial5010004

AMA Style

Kayler LK, Nie J, Solbu A, Keller M, Handmacher M. Use of Educational Animated Videos by Kidney Transplant Seekers and Social Network Members in a Randomized Trial (KidneyTIME). Kidney and Dialysis. 2025; 5(1):4. https://doi.org/10.3390/kidneydial5010004

Chicago/Turabian Style

Kayler, Liise K., Jing Nie, Anne Solbu, Maria Keller, and Matthew Handmacher. 2025. "Use of Educational Animated Videos by Kidney Transplant Seekers and Social Network Members in a Randomized Trial (KidneyTIME)" Kidney and Dialysis 5, no. 1: 4. https://doi.org/10.3390/kidneydial5010004

APA Style

Kayler, L. K., Nie, J., Solbu, A., Keller, M., & Handmacher, M. (2025). Use of Educational Animated Videos by Kidney Transplant Seekers and Social Network Members in a Randomized Trial (KidneyTIME). Kidney and Dialysis, 5(1), 4. https://doi.org/10.3390/kidneydial5010004

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