Pharmacists’ knowledge, familiarity, and attitudes towards biosimilar drugs among practicing Jordanian pharmacists: A cross sectional study

2.1 Sample recruitment

The questionnaire of this study was performed online using Google Forms. An approval from the IRB of Al-Zaytoonah University of Jordan (ZUJ) was granted to conduct the study. By adopting snowball method for sampling recruitment, the questionnaire’s link was distributed via email and various social media applications, as was previously performed (Akour et al., 2021), between November 2021 and April 2022. The inclusion criteria for the study were licensed and practicing pharmacists in Jordan who are adept in English and use of online surveys. Questions regarding years of experience, place of work, and field of work were included in the questionnaire to ensure that participants met the inclusion criteria. The Krejcie and Morgan method for nonspecific population size was used to determine the required sample size (Krejcie & Morgan, 1970). The required number of participants for this study was calculated at a 95% confidence interval and 5% confidence level and was equal to 385 participants (Krejcie & Morgan, 1970). A total of 400 respondents submitted completed questionnaires. The questionnaire was sent to pharmacists in Jordan, as in the criteria specified for the study, who work in community pharmacies, hospital pharmacies, drug stores, pharmaceutical companies and factories and other pharmaceutical sectors, such as the JFDA and JPA. Data collection and analysis were anonymous.

2.2 Questionnaire

The beginning of the questionnaire was a short sentence describing the purpose of the study, the confidentiality of the collected data, the respondents being anonymous, and respondents’ informed consent. Some questions were adopted from several related articles (Beck et al., 2017; Cohen et al., 2017; Teeple et al., 2019a; Teeple et al., 2019b; Hadoussa et al., 2020; Barbier et al., 2021) and others were developed by the research team. There were 25 close-ended questions in the questionnaire. A panel of 6 academic licensed pharmacists at the Faculty of Pharmacy at ZUJ performed face and content validations. The panel included PhD holders in Pharmacology, Pharmacogenomics, and Pharmaceutics, who had also worked in community pharmacies before. Their suggestions were taken into consideration to further develop and amend the questions. The questions were translated from English to Arabic through forward–backward-forward technique (Beaton et al., 2000) as the official language in Jordan is Arabic. The questionnaire was later pilot tested on 12 academic licensed pharmacists in the Faculty of Pharmacy at ZUJ to assess their comprehension of the questionnaire and the time spent in completing it. The results of the pilot study were excluded from the analysis.

The questionnaire was divided into 4 sections. The first section was demographic characteristics of the participant (Table 1). The second section was the knowledge level of the participant about BSM and biological drugs in which 9 statements were included with the following possible answers: “True”, “False”, and “I do not know”. Knowledge scoring was calculated by granting one point for every correct answer, and zero for every incorrect response. The maximum possible knowledge score was nine (Table 2). The third section had 3 statements using 5-Point Likert response scale to assess the familiarity of the respondents with BSM drugs, the response options for these items were “Always”, “Most of the time”, “Usually”, “Rarely”, and “Never”. The scoring ranged from 1 point for “Never” to 5 points for “Always” except for the item “How frequent do you depend on the use of the brand name to distinguish biosimilar drugs?”, in which reverse scoring was applied. The highest maximum possible score for the familiarity scale was 15 (Table 3). The fourth section had 6 statements to evaluate the attitude of the participants towards BSM drugs. A 5-Point Likert response scale was used (“Strongly Agree”, “Agree”, “Neutral”, “Disagree”, and “Strongly Disagree”), and scoring ranged from 5 for “Strongly Agree” to 1 for “Strongly Disagree”. The maximum possible score for the Attitude scale was 30 (Table 3).

2.3 Statistical analysis

Categorical variables were presented as frequencies and percentages, and continuous variables were presented as medians and 25–75 quartiles. The internal consistency of the three latent variables (knowledge, familiarity, and attitude scores) were evaluated by computing Cronbach’s and values above 0.7 were considered acceptable. The participants were categorized according to their scores in the three computed scales (knowledge, familiarity, and attitude) to high- and low-level groups, as those who scored above the median were included in the high level and the rest were included in the low-level groups. Three binary regressions with knowledge, familiarity, and attitude levels as dependent variables and different sample characteristics as independent variables were constructed to identify variables associations with participants’ level of knowledge, attitude and practices towards BSM drugs. The data were analyzed using SPSS version 27.

3.1 Demographic characteristics

Demographic characteristics of the 400 participants who took part in the study are listed in Table 1. Most of the participants were females (72%). Half of the respondents (50.7%) were below 30 years old and 79% were bachelor’s degree holders. Almost half of the respondents (46.8%) have less than 5 years of experience. About two thirds of the participants (63.2%) worked in Amman (the capital city) and 63.5% worked in the private sector. Almost half of the participants worked in community pharmacies (43%) and a good share of respondents worked in hospital pharmacies (30.3%) while the rest were working in drug stores (7.2%), pharmaceutical companies/factories (4.3%), and other pharmaceutical sectors (15.3%), such as the JFDA and JPA.

3.2 Knowledge

Results revealing the knowledge level of our survey respondents about BSM drugs are shown in Table 2. Knowledge scores were computed based on the knowledge items for all the participants, the median for the knowledge score was 5 (quartiles = 4–6) out of a maximum possible score of 9. Accordingly, 50% of the respondents had a total knowledge score of 55.6% or below and 75% of the respondents had a knowledge score of 66.7% or below.

The questions with the highest number of correct answers in the knowledge domain were “A biosimilar drug must have the exact amino acid sequence as the biologic reference drug” (91.5%) and “A biosimilar drug has no clinically meaningful differences (similar safety and efficacy) compared to the biologic reference drug)” (90.5%), followed by “A biosimilar has similar immunogenicity compared with the biologic reference drug” (76.8%), “A biosimilar drug is interchangeable with the biologic reference drugs” (76.5%), “A biosimilar drug is a generic, has same chemical structure, as the biologic reference drug” (67.5%), and “A biosimilar drug is an FDA-approved version of a biologic reference drug that is manufactured after the expiry of the biologic reference drugs patent” (57.8%). The lowest correct answers were for “A biosimilar drugs manufacturing cost is higher than that of the biologic reference drug” (7.5%), “All FDA-approved biosimilar drugs undergo an extensive assessment to make sure that patients can trust their efficacy, safety, and quality” (16%) and “There is similar variability between the biologic reference drug formulation lots as there is a variability in biosimilar drug formulation lots” (30.8%). The computed Cronbach’s of this scale was 0.711 indicating acceptable internal consistency.

3.3 Familiarity

Familiarity scores were computed based on the answers of the respondents to the familiarity items, the median for the total familiarity score was 8 (quartiles = 7–10) out of a maximum possible score of 15 (Table 3). Accordingly, 50% of the respondents had a total familiarity score of 53.3% and 75% of the respondents had a knowledge score of 66.7% or below.

The highest medians for the familiarity items were reported in “How frequent have you ever dispensed a prescription that has biosimilar drugs?”, and “How frequent do you depend on the use of the brand name to distinguish biosimilar drugs?” median of 3 (quartiles = 2–4). Regarding the question about the frequency of dispensing BSM drugs only 6.8% have always dispensed BSM drugs and 53.1% of the respondents answered “most of the time/usually” and the rest have either rarely (23.3%) or never (17%) dispensed BSM drugs. On the other hand, 15% of the respondents always use the brand name to distinguish BSM drugs, about 58.5% of the respondents reported that most of the time/usually they use the brand name to distinguish BSM drugs, and the rest have either rarely (17.5%) or never (9%) use the brand name.

While the item “How frequent do you depend on the use of suffix in the non-proprietary name (active ingredient) and four-character suffix to distinguish Biosimilar drugs?” displayed a median of 2 (quartiles = 2–3). Regarding the question about the frequency of using suffix in the non-proprietary name (active ingredient) to distinguish BSM drugs, 18.8% answered that they always depend on the suffix while 56.5% of the respondents depended most of the time/usually on suffixes and the rest rarely (15.8%) or never (9%) use the suffix in the non-proprietary name to distinguish BSM drugs. The internal consistency of the familiarity scale was confirmed by computing Cronbach’s alpha, which was 0.76.

3.4 Attitude

The median of the Attitude scale score was 13.00 (quartiles = 12–15) out a maximum possible score of 30. Our study revealed that 73.8% of the respondents were in favor of dispensing BSM drugs (median = 2, quartiles = 2–3) and 82.3% believed that BSM drugs increase patients’ access to a variety of treatment options (median = 2, quartiles = 2–2). Despite the favorable attitude of the respondents towards BSM drug dispensing, only 54.3% of the respondents feel that they are trained enough to dispense and counsel patients about BSM drugs (median = 2, quartiles = 2–3). Regarding the role of pharmacists, 55.1% of the respondents believed that pharmacists should be allowed to substitute a biological reference drug with a BSM drug after patient agreement (median = 2, quartiles = 2–3) and 83.5% of the respondents are willing to substitute a biological reference drug with a BSM drug if the physician approved it (median = 2, quartiles = 1–2). However, 65.8% of the respondents believed that patients should participate in taking decision to use BSM drugs (median = 2, quartiles = 2–3). Cronbach’s alpha of the attitude scale was 0.82 confirming its internal consistency.

3.5 Variables associated with knowledge, familiarity, and attitude levels

Binary regression models were built to evaluate different sample characteristics associated with knowledge, familiarity, and attitude levels. The results indicated that there were no significant associations between any of the studied variables with knowledge level. Whereas the only variable that was significantly associated with familiarity level was field of work, as those who were working in pharmaceutical companies/factories and other pharmaceutical sectors, such as the JFDA and Jordanian Pharmacists association (JPA) had higher odds to be in the high level familiarity group ((OR = 2.975, p-value = 0.046, 95%CI = 1.021–8.669); (OR = 2.225, p-value = 0.026, 95%CI = 1.099–4.505), respectively), when compared with participants working in community pharmacies. The binary regression results indicated that respondent who work in pharmaceutical companies/factories or drug stores had higher odds to be in high attitude group ((OR = 3.474, p-value = 0.043, 95%CI = 1.040–11.606); (OR = 3.449, p-value = 0.011, 95%CI = 1.321–9.005), respectively), when compared to those who worked in community pharmacies. Moreover, participants who had low familiarity level had lower odds to be in the high attitude group (OR = 0.340, p-value = 0.000, 95%CI = 0.220–0.527).