Telecommunication Technology-based Online Survey

January 23, 2026 updated by: Nina D. Anfinogenova, Tomsk National Research Medical Center of the Russian Academy of Sciences

New Challenges for the Population on the Path to Achieving Active Longevity: an Online Survey of Respondents Using Telecommunication Technologies

The aim of this study is to identify and assess new health-associated risk factors, including clinical-pharmacological risk factors. The cohort is built using telecommunication approaches. The associations between clinical-pharmacological, social, demographic, behavioral, and environmental characteristics will be assessed. The continuous depersonalized online survey is performed using the original informational resources in the form of specially designed web-site aimed at identification and assessment of population-based pharmacotherapy patterns including characteristics of self-medication, biologically active food supplement intake, polypharmacy, and adverse drug-drug interactions in the people residing in the ecological conditions of various regions of the country. The invitations to participate in the online survey are sent via the SMS messages using the SMS-Target tool provided by OOO T2 Mobile Company. The survey is performed online at www.zdorov.tpu.ru and www.zdorov.expert both specifically designed for questionnaire publication and data accumulation.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Polypharmacy-associated serious drug-drug interactions and adverse drug reactions may increase the risk of morbidity and mortality in the population, especially in cardiovascular patients. Insufficient patient compliance to treatment and potential self-medication overlap with behavioral, psychosocial, demographic, and environmental conditions and pose new challenges for the population striving to achieve active longevity. These issues have been especially relevant during and after the COVID-19 pandemic. The aim of this study is to identify and assess new health-associated risk factors, including clinical-pharmacological risk factors. Telecommunication approaches are used for the formation of study cohort. The associations between clinical-pharmacological, social, demographic, behavioral, and environmental characteristics of study cohort will be assessed. The continuous depersonalized online survey is performed using the original informational resource in the form of specially designed web-site aimed at identification and assessment of population-based pharmacotherapy patterns including characteristics of self-medication, biologically active food supplement intake, polypharmacy, and adverse drug-drug interactions in the people residing in the ecological conditions of various regions of the country. The acquired data may lay a foundation for the development decision support system for control of previously unrecognized or poorly recognized risk factors. The study will enroll as least 2000 respondents aged 18 years and older. The invitations to participate in the online survey are sent via the SMS messages using the SMS-Target tool provided by OOO T2 Mobile Company. The survey is performed online at www.zdorov.tpu.ru and www.zdorov.expert both specifically designed for questionnaire publication and data accumulation. Both websites have built-in functionality for downloading survey results in tabular format (.xls, .csv). All the respondents are required to sign the informed consent form electronically according to local legislation and international standards of ethical research. Considering that no physical medical examinations or interventions are involved in the study, and all data undergo complete depersonalization, participation in this study does not pose any risks for respondents. Financial support for the study is provided by the Russian Science Foundation (project No. 22-15-00313). Respondents will not be covered by insurance due to the non-interventional nature of the study.

Study Type

Observational

Enrollment (Estimated)

2000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Nina D Anfinogenova, PhD
  • Phone Number: +73822554111
  • Email: anfiyj@gmail.com

Study Locations

  • Russia
      • Tomsk, Russia, 634012
        • Recruiting
        • Tomsk National Research Medical Center, Russian Academy of Sciences
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Probability Sample

Study Population

Nonstructured population aged 18 years and older willing to complete the entire questionnaire and signing the informed concent form.

Description

Inclusion Criteria:

  • age of 18 years and older
  • signing the informed concent form online
  • completion of the entire questionnaire

Exclusion Criteria:

  • age under 18 years
  • refuse to sign the informed concent form

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Non-structured population
The respondent will represent the non-structured population of the Russian Federation invited to participate in the study using the SMS-Target tool provided by OOO T2 Mobile Company.
Other: Online Survey
The participants of the study undergo the online survey at www.zdorov.tpu.ru and www.zdorov.expert.
Other Names:
  • Telecommunication-Based Survey
Diagnostic test: Genetic Testing
Genetic testing will be performed in subgroup of survey respondents willing to participate in the study of polymorphisms of genes involved in drug metabolism or affecting biological effects of medications including CYP2D6, ACE, UGT1A1, CYP2C9, and CYP2C19.
Other Names:
  • Genetic Polymorphisms of Drug-Metabolizing Enzymes

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Incidence of serious drug-drug interactions (percent)
Time Frame: Five years
Incidence of serious drug-drug interactions (DDIs) is assessed as a percentage (%) of completed survey questionnaires associated with serious DDIs relative to the size of respondent population.
Five years
Median number of serious drug-drug interactions (n)
Time Frame: Five years
Median number of serious drug-drug interactions is assessed per one completed survey questionnaire containing information on pharmacotherapy.
Five years

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Incidence of polypharmacy (percent)
Time Frame: Five years
Polypharmacy refers to using five or more medications. Incidence of polypharmacy is assessed as a percentage (%) of completed survey questionnaires reporting polypharmacy relative to the size of respondent population.
Five years
Incidence of MRI administration (percent)
Time Frame: Two years
Incidence of magnetic resonance tomography (MRI) administration is assessed as a percentage (%) of completed survey questionnaires where respondents report the fact of undergoing MRI procedure for the past two years relative to the size of respondent population.
Two years
Incidence of CT administration (percent)
Time Frame: Two years
Incidence of computed tomography (CT) administration is assessed as a percentage (%) of completed survey questionnaires where respondents report the fact of undergoing CT procedure for the past two years relative to the size of respondent population.
Two years
Incidence of diagnostic ultrasound administration (percent)
Time Frame: Two years
Incidence of diagnostic ultrasound administration is assessed as a percentage (%) of completed survey questionnaires where respondents report the fact of undergoing ultrasonography procedure for the past two years relative to the size of respondent population.
Two years
Incidence of diagnostic X-ray administration (percent)
Time Frame: Two years
Incidence of diagnostic X-ray administration is assessed as a percentage (%) of completed survey questionnaires where respondents report the fact of undergoing X-ray for the past two years relative to the size of respondent population.
Two years
Incidence of scintigraphy administration (percent)
Time Frame: Two years
Incidence of scintigraphy administration is assessed as a percentage (%) of completed survey questionnaires where respondents report the fact of undergoing scintigraphy for the past two years relative to the size of respondent population.
Two years
Incidence of chest fluoroscopy administration (percent)
Time Frame: Two years
Incidence of chest fluoroscopy administration is assessed as a percentage (%) of completed survey questionnaires where respondents report the fact of undergoing chest fluoroscopy for the past two years relative to the size of respondent population.
Two years
Clinically significant CYP2D6 gene polymorphisms
Time Frame: Two months
Clinically significant CYP2D6 gene polymorphisms will be identified by diagnostic sequencing using EDTA whole blood.
Two months
Clinically significant ACE gene polymorphisms
Time Frame: Two months
Clinically significant ACE gene polymorphisms will be identified by real-time PCR with melting curve detection using EDTA whole blood.
Two months
Clinically significant UGT1A1 gene polymorphisms
Time Frame: Two months
Clinically significant UGT1A1 gene polymorphisms will be identified by real-time PCR with melting curve detection using EDTA whole blood.
Two months
Clinically significant CYP2C9 gene polymorphisms
Time Frame: Two months
Clinically significant CYP2C9 gene polymorphisms will be identified by real-time PCR with melting curve detection using EDTA whole blood.
Two months
Clinically significant CYP2C19 gene polymorphisms
Time Frame: Two months
Clinically significant CYP2C19 gene polymorphisms will be identified by real-time PCR with melting curve detection using EDTA whole blood.
Two months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Tomsk National Research Medical Center of the Russian Academy of Sciences

Investigators

  • Principal Investigator: Nina D Anfinogenova, PhD, Tomsk NRMC

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 2, 2022

Primary Completion (Estimated)

September 1, 2028

Study Completion (Estimated)

December 31, 2028

Study Registration Dates

First Submitted

November 28, 2023

First Submitted That Met QC Criteria

November 28, 2023

First Posted (Actual)

December 7, 2023

Study Record Updates

Last Update Posted (Actual)

January 27, 2026

Last Update Submitted That Met QC Criteria

January 23, 2026

Last Verified

January 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • CRI-248

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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