Effect of Mobile Application- and AI Supported Video-Based Patient Education on Patient Outcomes in Teaching Clean Intermittent Catheterization
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Mobile application, Artifial intellgience.
- Who it may be relevant to
- Registry conditions: Clean Intermittent Catheterization. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Turkey (Türkiye)
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Effect of Mobile Application- and Artificial Intelligence-Supported Video-Based Patient Education on Patient Outcomes in Teaching Clean Intermittent Catheterization
Overview
The study aimed to determine the effects of a mobile application and an artificial intelligence-supported educational video, developed for patients who will perform clean intermittent catheterization (CIC), on patients' adherence, levels of difficulty, self-confidence, infection parameters (urinalysis, urine culture, infection incidence), and recurrent hospital admissions.The number of CIC patients who applied to the Urology Outpatient Clinic of Mersin University within the last year was 110. Since no similar study was found, the sample size was calculated using an a priori power analysis with G\*Power 3.1.9.7 software. . As a result of the power analysis, the total sample size was calculated as 90, with 30 participants in each group. Considering a possible data loss (dropout) rate of approximately 10%, it was planned to include 33 participants in each group (a total of 99 participants) at the beginning of the study.Data will be collected using the "Descriptive Information Form," "Intermittent Catheterization Adherence Scale," "Self-Confidence Scale in Clean Intermittent Self-Catheterization," "Intermittent Catheterization Difficulty Questionnaire," and the "Patient Follow-up Form."Patients who will perform clean intermittent catheterization will receive training through a mobile application (intervention group 1) and an artificial intelligence-supported educational video (intervention group 2). Patients in the control group will be trained using the routine brochure provided in the outpatient clinic.
Detailed description
The study was designed as a prospective, three-arm (1:1:1), randomized controlled clinical trial. The study will be conducted at the Urology Outpatient Clinic of Mersin University Faculty of Medicine Hospital. The Urology Outpatient Clinic includes adult and pediatric outpatient units, an intervention room, an ultrasound room, an andrology laboratory, a lithotripsy unit, and a urodynamics unit. The Department of Urology consists of seven faculty members and 11 research assistants. In the urology outpatient clinic, there is one nurse, two technicians, two secretaries, and one cleaning staff member. Outpatient services are provided between 08:00 and 17:00, and clean intermittent catheterization (CIC) training is also delivered to patients during these hours. The nurse provides training to patients who will perform CIC using a brochure. After the training, patients routinely return to the outpatient clinic for follow-up visits on the 15th day and at the 3rd month. study aimed to determine the effects of a mobile application and an artificial intelligence-supported educational video, developed for patients who will perform clean intermittent catheterization (CIC), on patients' adherence, levels of difficulty, self-confidence, infection parameters (urinalysis, urine culture, infection incidence), and recurrent hospital admissions.The number of CIC patients who applied to the Urology Outpatient Clinic of Mersin University within the last year was 110. Since no similar study was found, the sample size was calculated using an a priori power analysis with G\*Power 3.1.9.7 software. For the one-way analysis of variance (ANOVA), the parameters used were α error probability = 0.05, power (1-β error probability) = 0.80, number of groups = 3, and effect size f = 0.40 (large effect size). As a result of the power analysis, the total sample size was calculated as 90, with 30 participants in each group. Considering a possible data loss (dropout) rate of approximately 10% , it was planned to include 33 participants in each group (a total of 99 participants) at the beginning of the study.Data will be collected using the "Descriptive Information Form," "Intermittent Catheterization Adherence Scale," "Self-Confidence Scale in Clean Intermittent Self-Catheterization," "Intermittent Catheterization Difficulty Questionnaire," and the "Patient Follow-up Form."Patients who will perform clean intermittent catheterization will receive training through a mobile application (intervention group 1) and an artificial intelligence-supported educational video (intervention group 2). Patients in the control group will be trained using the routine brochure provided in the outpatient clinic.
Interventions
- Other Mobile application
Patients who will perform clean intermittent catheterization will receive training through a mobile application (intervention group 1) - Other Artifial intellgience
Patients who will perform clean intermittent catheterization will receive training through an artificial intelligence-supported educational video (intervention group 2)
Primary outcome measures
- Adherence [Time frame: 6 months]
- Self-Confidence [Time frame: 6 months]
Eligibility criteria
Inclusion criteria
- Patients who require intermittent catheterization (TAK),
- Aged 18 years or older,
- Willing to participate in the study,
- Able to understand Turkish,
- Literate,
- Without visual or hearing impairments,
- Owning a smartphone, tablet, or computer,
- Without difficulties using technology.
Exclusion criteria
- Patients who do not require intermittent catheterization (TAK),
- Under 18 years of age,
- Not willing to participate in the study,
- Do not understand Turkish,
- Illiterate,
- With visual or hearing impairments,
- Do not own a smartphone, tablet, or computer,
- Having difficulties using technology.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Triple blind
- Primary purpose
- Other
Study locations
Turkey (Türkiye) · 1 center
- Mersin Unıversıty — Mersin
Publications
- Bobian M, Kandinov A, El-Kashlan N, Svider PF, Folbe AJ, Mayerhoff R, Eloy JA, Raza SN. Mobile applications and patient education: Are currently available GERD mobile apps sufficient? Laryngoscope. 2017 Aug;127(8):1775-1779. doi: 10.1002/lary.26341. Epub 2016 Oct 18. PMID 27753101
- Cerantola Y, Valerio M, Persson B, Jichlinski P, Ljungqvist O, Hubner M, Kassouf W, Muller S, Baldini G, Carli F, Naesheimh T, Ytrebo L, Revhaug A, Lassen K, Knutsen T, Aarsether E, Wiklund P, Patel HR. Guidelines for perioperative care after radical cystectomy for bladder cancer: Enhanced Recovery After Surgery (ERAS((R))) society recommendations. Clin Nutr. 2013 Dec;32(6):879-87. doi: 10.1016/j. PMID 24189391
- Bhuyan SS, Sateesh V, Mukul N, Galvankar A, Mahmood A, Nauman M, Rai A, Bordoloi K, Basu U, Samuel J. Generative Artificial Intelligence Use in Healthcare: Opportunities for Clinical Excellence and Administrative Efficiency. J Med Syst. 2025 Jan 16;49(1):10. doi: 10.1007/s10916-024-02136-1. PMID 39820845
- Hernandez-Rodriguez JC, Garcia-Munoz C, Ortiz-Alvarez J, Saigi-Rubio F, Conejo-Mir J, Pereyra-Rodriguez JJ. Dropout Rate in Digital Health Interventions for the Prevention of Skin Cancer: Systematic Review, Meta-analysis, and Metaregression. J Med Internet Res. 2022 Dec 9;24(12):e42397. doi: 10.2196/42397. PMID 36485027
- Alasker A, Alsalamah S, Alshathri N, Almansour N, Alsalamah F, Alghafees M, AlKhamees M, Alsaikhan B. Performance of large language models (LLMs) in providing prostate cancer information. BMC Urol. 2024 Aug 23;24(1):177. doi: 10.1186/s12894-024-01570-0. PMID 39180045
Identifiers
NCT: NCT07489261 · MU-002