This study aimed to elucidate perceived gender barriers to KTE activities in vaccination related research in low, middle- and high-income countries.
Our specific objectives were to (1) compare perceived structural barriers and facilitators to KTE activities among men and women in vaccine-related research; and (2) investigate the association between gender and structural factors to KTE activities in low, middle- and high-income countries.
This study was based on a cross-sectional data from a self-administered questionnaire distributed to researchers between 28 March and 22 April 2018. The questionnaire was developed and validated by the World Health Organization (WHO) and McMaster University, Canada (26).
Recruitment of participants
Participants were recruited based on identification of vaccination-related articles obtained from PubMed using the search terms “(vaccinate* [MeSH Terms]) OR (immunize* [MeSHTerms])”. The articles were screened for publication between 1 January and 31 December 2017, availability of abstract and unique e-mail addresses, included human subjects, and were written in English language.
Based on these criteria, articles were included if the study population included children (< 18 years) or those in the proximity (e.g. parents, paediatrics, policy/programs targeting children); conducted quantitative or qualitative analysis; and systematic reviews. Additionally, articles were excluded if articles were based on opinions, comments or a case report; did not discuss VPD; did not include human subjects; was not written in English; and if e-mail of corresponding author was not provided.
Authors were invited to participate in the study via the e-mail addresses obtained from the articles identified as relevant to the topic. In order to increase the response rate, reminders were sent on several occasions during a one-month period (once per week during the first two weeks; twice a week during the third week; daily during the fourth week).
During the recruitment process, a total of 717 researchers were identified and invited to participate in the survey. Of these, we included authors who had valid e-mail addresses, provided consent, and conducted research in vaccination-related field. This resulted in a total number of 158 participants (Fig. 1).
Data collection and measures
Structural factors to KTE were assessed using 12 statements measured with 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). The statements included:
1.
The cost for translating research on the health topic into action was very low
2.
KTE activities could be paid for through research grants for which I was eligible to apply
3.
Structures and processes existed to link researchers and your target audiences
4.
Personal and organizational contacts among your target audiences were quite stable over time (e.g., low turnover among representatives and/or members of your target audiences)
5.
Perceived crises in the health system drew attention away from research on the health topic
6.
Target audiences lacked the expertise for translating research on the health topic into action
7.
Target audiences had access to technical support for translating research on the health topic into action
8.
Target audiences created opportunities to develop joint research initiatives with them
9.
Target audiences did not make decisions about the health topic on the basis of research
10.
Target audiences invested financial and/or human resources in joint research initiatives
11.
Target audiences created events for knowledge transfer and exchange related to the health topic (e.g., forums that bring researchers and target audiences together for discussion)
12.
Target audiences invested financial and/or human resources in knowledge transfer and exchange activities (e.g., hired staff to identify and make available relevant research).
The survey included gender (men; women), year of birth, country of primary affiliation, education (medical doctor; bachelor’s degree; master’s degree; doctoral degree), and area of specialization (biomedical research; population and public health; clinical research; other). Based on the participants’ country of primary affiliation, the countries were divided into two income levels based on the country’s Gross National Income (GNI) per capita, according to the definition of the World Bank in 2018. Countries were categorized as LMIC if their GNI per capita was below or equal to 12,235 USD, while countries were categorized as high income countries (HIC) if their GNI per capita was above 12,235 USD (27). In addition, age was calculated as the difference between ‘2018’ and ‘year of birth’.
Statistical analysis
We tested the 12 statements for internal reliability using Cronbach’s alpha. The results showed some inconsistencies between the statements (Cronbach’s alpha = 0.504). In order to have consistent measure of the items, the following items were reverse coded: ‘Target audience lacked the expertise for translating research on the health topic into action’; ‘Target audience did not make decisions about the health topic on the basis of research’, increasing the internal consistency of the 12 statements (Cronbach’s alpha = 0.71). Further, we created an index with the 12 items, ranging from 12 to 60 points for KTE barriers, in which a lower score indicated more frequent experiences related to structural barriers regarding KTE activities.
To describe the study population, we computed descriptive statistics using Fisher’s exact test for the variables ‘country of primary affiliation’, ‘research specialization' and ‘educational attainment’. For the variable ‘structural factors to KTE’, Mann-Whitney test was carried to compare differences among men and women.
Linear regression analysis was applied to test the association between perceived KTE barriers and gender. In our model, the outcome (dependent variable) was continuous variable on KTE score and our independent variable was gender. We also included age and country of primary affiliation as covariates. The variables gender and country of primary affiliation were treated as binary variables. Dummy variables were created and coded as follows male = 0, female = 1, HIC = 0 and LMIC = 1. Age was included as a continuous variable. Results are presented using beta coefficients and 95% confidence intervals (95% CI). We considered alpha p < 0.05 statistically significant. All statistical analyses were computed using SPSS statistical software version 25 (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.).