This study employed a computer-assisted web interview (CAWI) methodology, whereby data was collected through a specialized online survey platform. Respondent recruitment was conducted using river sampling, a method that involves real-time recruitment of internet users specifically for the given survey. Participants were recruited via targeted advertising messages disseminated across social media platforms and popular internet resources.
The selection of these methods was driven by several factors:
- The number of medical and IT specialists in Russia is relatively small compared to the country’s overall adult population. This renders traditional telephone surveys impractical, as the probability of randomly contacting an individual from the target profession is low;
- Utilizing online respondent panels (services that allow people to regularly participate in surveys for monetary rewards) carries the risk of data distortion due to selection bias, i.e. the overrepresentation of individuals motivated by financial incentives to frequently take part in various surveys;
- Reliable data on the overall population size, demographic distribution (age, gender), and geographic spread of medical and IT professionals in Russia is unavailable. This lack of information precluded the establishment of accurate sampling quotas.
River sampling is a method widely employed by researchers when surveying relatively small or hard-to-reach target audiences that are difficult to access via traditional offline survey methods. This approach involves targeting advertisements proposing survey participation to a clearly defined audience – in this instance, medical or IT specialists. Firstly, this strategy minimizes unnecessary contact with non-target audiences, a common issue with telephone surveys when the target audience is relatively small. Secondly, it provides for a broad reach and representativeness within the target groups, something often lacking in online panel surveys.
In other words, river sampling allows researchers to access a broad audience of medical and IT professionals that closely mirrors their geographical, age, and other demographic characteristics within the overall population – due to the high penetration of Internet and social media in Russia, particularly among the working-age population. Notably, unlike online panels, river sampling does not involve monetary incentives for respondents, thus eliminating the bias towards “professional respondents.” Consequently, the research sample effectively represents the target professional groups and their socio-demographic characteristics.
It is crucial to note that the advertisements inviting to participate in the survey do not disclose the survey topic or any specific characteristics required to qualify as a respondent. Internet users who click on the link and agree to participate are presented with a series of screening questions, i.e. the questions that serve to filter out respondents who do not meet the study criteria. For both professions, this includes a question about their field of employment (with six response options, only one of which allows for further participation) and a question about their age (excluding respondents under 18 years old and those who decline to disclose their age).
As an additional quality control measure for respondent selection, the screening section of the questionnaire for medical specialists included verification questions assessing basic medical knowledge: the sequence of waveforms on a normal ECG, the number of cranial nerves in humans, and the meaning of the term “cito.” Each respondent was randomly assigned one of these questions (with four response options, only one of which was correct). If a respondent provided an incorrect answer, the interview was terminated. This ensured that respondents lacking basic medical knowledge were excluded from the sample.
The socio-demographic characteristics of the resulting sample generally support the absence of unexplained sampling bias towards any particular subgroups. The sample includes respondents of diverse ages, locations, income levels, educational backgrounds, and marital statuses. A significant imbalance is observed only in terms of gender within the sample of medical specialists (71% of them are female). However, this can be attributed to a similar skew in the overall population of Russian doctors and medical staff, as acknowledged by officials in relevant ministries (https://tass.ru/ obschestvo/5587049).
Overall, the validity of the collected data is ensured through adherence to the general principle of representativeness in this study. The results, with a 95% confidence level (the standard level of reliability), exhibit a maximum measurement error of 3.09% (for each of the two studied groups independently).
To further enhance the reliability of the research findings, an additional validation process was conducted, involving the cleansing of the dataset by removing inconsistent responses. This process involved systematically comparing the logical consistency of answers across different questions.
The main methods employed for data analysis include statistical techniques such as the calculation of weighted averages, descriptive statistics, correlation analysis, factor analysis etc. The primary tool for data processing is the SPSS Statistics software.