The implementation of a FIP guidance for COVID-19: insights from a nationwide survey
Introduction
Presently, the coronavirus disease 2019 (COVID-19) pandemic is continuing to present a prominent challenge all over the world, and seriously endangering society (1). During a pandemic, the pharmacy becomes a vital access point for medicines and healthcare advice (2). As healthcare professionals, pharmacists join the medical collaborative team and provide pharmaceutical care. In order to support pharmacists in performing their key roles, the International Pharmaceutical Federation (FIP) established an interim guidance of COVID-19 for pharmacists worldwide (3). The FIP guidance covered disease transmission, incubation period, clinical treatment, preventive measures, cleaning and disinfection management, responsibilities and role of pharmacy etc. in primary care, hospital settings, and medical analysis laboratories.
The dissemination and implementation of medical guidance is a global challenge, resulting in the underutilization of guidelines (4-6). The study by Sousa Pinto et al. (7) described the strategy and measures adopted by FIP in collaboration with international experts to support the effective pharmaceutical service and their important value on health systems throughout the pandemic around the world. And previous studies (8-10) have analyzed the knowledge, attitudes, and practices (KAP) of pharmacists and found their actions are largely affected by their KAP towards COVID-19. However, there is a lack of status analysis of the FIP guidance, and pharmacists’ adherence to the guidance has remained ambiguous.
Thus, we investigated pharmacists’ KAP towards COVID-19 by conducting a nationwide survey, aiming to identify current practices and barriers of FIP guidance, and to provide relevant strategies for further actions.
We presented the following article in accordance with the SURGE reporting checklist (available at https://dx.doi.org/10.21037/atm-21-4157).
Methods
Setting and participants
This nationwide cross-sectional survey on Chinese pharmacists has been registered on the Chinese Clinical Trial Registry (ChiCTR2000035213).
A recruitment notice was posted to groups of WeChat through authors’ accounts (Yi and Song) from 9 December through 11 December 2020, which involved pharmacists come from various provinces and autonomous regions in mainland China, with different job titles and job positions. The notice contained a brief introduction including study background and funding resource, objective, procedures, voluntary nature of participation, declarations of anonymity and confidentiality, and notes for completing the questionnaire, as well as a link to the online questionnaire. To collect data of KAP from a cross section, the 18 December 2020 was set as the deadline for completion (maximum of 10 days). The recruitment notice was send out once and no incentive was provided.
All Chinese mainland pharmacists engaged in pharmacy were considered eligible, including pharmacists in hospital, community clinics, or retail pharmacy, regardless of their position, gender, or region. Two similar questions in the questionnaire were set as logic check items, which were used to assess the quality of collected questionnaires. The exclusion criteria were as follows: duplicate answer sheets from the same person; answer sheets where there were contradictory answers; partial completed questionnaires.
Study instrument and measures
The questionnaire was designed based on the FIP guidance (3) and KAP framework (11). The draft questionnaire was initiated by 3 authors (Rong-Sheng Zhao, Zhan-Miao Yi, and Zai-Wei Song) who have been actively participating in the development of FIP guidance (3) and its Chinese version (12). Senior pharmacy experts and epidemiology experts were consulted, and the questionnaire was pre-filled by students and pharmacists who did not then participate in this study. The final survey questionnaire was assessed and modified based on expert suggestions and the results of the pre-surveys.
The questionnaire consisted of 4 parts: demographics (including COVID-19 related information), knowledge, attitudes, and practices. Demographic variables included province/region, gender, job title, education, job responsibilities, working years, job position, participation in COVID-19 work or not, COVID-19 working content, and COVID-19 information source.
The KAP questions in the questionnaire were developed based on the FIP guidance. The knowledge questionnaire had 11 questions with multiple choice and true/false options: 6 (K1-K6) regarding transmission routes, and 5 (K7-K11) regarding clinical treatment of COVID-19 (medicine, convalescent plasma treatment, and vaccines). Attitudes towards COVID-19 were measured by 13 questions: 4 (A1-A4) regarding self-confidence in the role of pharmacists, and 9 (A5-A13) regarding the agreement of measures related to “supporting pharmacists and pharmacy teams”. Each question was scored from 1 to 10. The assessment of respondents’ practices was composed of 5 behaviors (P1-P5), including prevention and control measures, infection risk, and pharmacists’ advice.
Statistical analysis
The statistical analyses were performed with SPSS software version 26.0 (IBM Corp., Armonk, NY, USA). Multiple imputation approach was used for missing data. For quantitative data following a normal distribution, we calculated mean with standard deviations (mean ± SD) and used Pearson’s rank correlation test to identify the possible correlation between variables. For non-normally distributed data, we calculated median with interquartile range [median (IQR)] and used Spearman’s rank correlation test to test the correlation among variables. For qualitative data, we calculated frequency and constituent ratio and used the chi-squared test to compare the difference between the groups. The level of knowledge, attitudes, and practices were summarized and classified. A correct rate of answers above 60% was considered “qualified”, while below 60% was considered “unqualified”. A score of attitudes above 9 was considered “positive”, while below 9 was considered “not positive”.
We used a logistic regression model to identify independent factors of KAP. Empirically, each co-variable needs at least 10 participants in logistic regression models, thus at least 90 responses was required for 9 co-variables in the survey. Univariate analysis was performed for all baseline and COVID-19-related characteristics. Variables with statistical significance as well as gender, professional title, the highest education degree, job duties, length of working years, and operating post (determined by reading relevant literature and combining clinical experience) were included in the multivariate logistic regression using the Enter method. The level of statistical significance was set at P<0.05 (2-tailed analysis).
Ethical approval
All procedures performed in this study involving human participants were in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional ethics board of Peking University Third Hospital (No. IRB00006761-M2020299). The online voluntary and anonymous questionnaire secured the confidentiality of the participants, and did not collect any identity-exposing information of the participants.
Results
Basic information
During the study period, 237 responses from 237 pharmacists were received, and all met the inclusion criteria. Among all respondents, 69.20% were females. Pharmacists were from various regions of mainland China, including Northwest (39.66%), North (18.57%), Central (16.46%), Southwest (8.86%), South (7.17%), Northeast (5.91%), and East China (3.38%). Among the included pharmacists, 93.67% held a bachelor’s degree or above, and 78.06% has been working as a pharmacist for more than 5 years.
During the pandemic, 194 pharmacists (81.86%) participated in COVID-19 related work, such as drug supply and guarantee, pharmacy information support, drug dispensation, and guidelines/consensus development. The main information source for COVID-19 was in-hospital training, followed by National Health Commission and other official guidance documents, and other guidelines or consensus. Among the included pharmacists, 48.95% had studied the FIP guidance. Demographics of pharmacists and COVID-19-related information are shown in Table 1.
Table 1
Characteristics | Subgroup | n | % |
---|---|---|---|
Gender | Female | 164 | 69.20 |
Male | 73 | 30.80 | |
Job title | Primary and below | 62 | 26.16 |
Junior | 104 | 43.88 | |
Senior | 71 | 29.96 | |
Education background | College and below | 15 | 6.33 |
Bachelor | 128 | 54.01 | |
Master | 71 | 29.96 | |
Doctor | 23 | 9.70 | |
Job responsibility | Clinical pharmacist | 114 | 48.10 |
Drug dispensing | 59 | 24.89 | |
Pharmacy administrator | 47 | 19.83 | |
Othersa | 17 | 7.17 | |
Working years | 1–5 | 52 | 21.94 |
6–10 | 69 | 29.11 | |
11–15 | 48 | 20.25 | |
16–20 | 20 | 8.44 | |
≥21 | 48 | 20.25 | |
Job position (multiple choice) | General clinic | 83 | 35.02 |
General ward | 77 | 32.49 | |
General emergency | 32 | 13.50 | |
Fever clinic | 19 | 8.02 | |
Isolation ward or Fangcang Shelter | 8 | 3.38 | |
Othersb | 104 | 43.88 | |
COVID-19 work | Participation | 194 | 81.86 |
No participation | 43 | 18.14 | |
Working content of COVID-19 (multiple choice) | Drug supply and guarantee | 94 | 39.66 |
Pharmacy information support | 87 | 36.71 | |
Drug dispensation | 86 | 36.29 | |
Drug evaluation | 31 | 13.08 | |
Disinfectant preparation | 23 | 9.70 | |
Guidelines/consensus development | 14 | 5.91 | |
Othersc | 69 | 29.11 | |
Information source of COVID-19 (multiple |
In-hospital training | 208 | 87.76 |
National Health Commission and other official guidance documents | 194 | 81.86 | |
Other guidelines/consensus | 165 | 69.62 | |
News media | 145 | 61.18 | |
FIP guidance | 116 | 48.95 | |
Journal articles | 107 | 45.15 | |
Academic conferences | 90 | 37.97 | |
Othersd | 17 | 7.17 |
a, laboratory pharmacist (TDM and genetic testing), prescription reviews, drug information pharmacist, etc.; b, other departments of drug supply and guarantee, pharmacy laboratory (TDM and genetic testing), clinical trial institution, quality control, etc.; c, pharmacy consultation, popular science writing, conducting related research, laboratory nucleic acid testing, infection control work, etc.; d, municipal continuation education projects, clinical management of COVID-19 patients, etc.; COVID-19, coronavirus disease 2019; TDM, therapeutic drug monitoring; FIP, International Pharmaceutical Federation.
Knowledge: transmission routes and clinical treatment
The knowledge questionnaire consisted of 2 parts with 11 questions (K1-K11): transmission routes and clinical treatment of COVID-19 (answers are shown in Figure 1). Overall, the number of correct answers was 7 [2] {median [IQR]}, and 67.51% of respondents were classified as qualified. In terms of transmission routes (K1-K6), most pharmacists answered correctly; however, the correct answer rate of K3 on pregnant or lactating patients with COVID-19 was only 11.81%. The correct rate of the application of convalescent plasma therapy (K9) was 23.63%. The working content of COVID-19 “drug dispensation” (negative correlation) and the information source of COVID-19 “other guidelines or consensus” (positive correlation) were statistically significant independent factors in both univariate and multivariate logistic regression analysis (Table 2).
Table 2
Characteristics | Subgroup | Univariate analysis | Multivariate analysis | |||
---|---|---|---|---|---|---|
OR (95% CI) | P value | OR (95% CI) | P value | |||
Gender | Male ( |
1.067 (0.591–1.928) | 0.829 | 1.028 (0.536–1.970) | 0.935 | |
Job title | Primary and below | 0.948 (0.487–1.847) | 0.876 | 1.461 (0.580–3.677) | 0.421 | |
Junior | Reference | Reference | ||||
Senior | 1.082 (0.565–2.070) | 0.812 | 0.606 (0.230–1.596) | 0.311 | ||
Education background | College and below | 0.443 (0.151–1.302) | 0.139 | 0.478 (0.117–1.951) | 0.304 | |
Bachelor | Reference | Reference | ||||
Master | 1.056 (0.569–1.958) | 0.863 | 1.090 (0.509–2.335) | 0.825 | ||
Doctor | 3.373 (0.949–11.982) | 0.060 | 3.834 (0.873–16.843) | 0.075 | ||
Job responsibility | Clinical pharmacist | Reference | Reference | |||
Drug dispensing | 0.495 (0.257–0.955) | 0.036 | 0.569 (0.221–1.464) | 0.242 | ||
Pharmacy administrator | 0.920 (0.436–1.941) | 0.826 | 1.309 (0.508–3.372) | 0.577 | ||
Others | 0.937 (0.305–2.872) | 0.909 | 1.190 (0.348–4.064) | 0.781 | ||
Working years | 1–5 | 0.565 (0.260–1.226) | 0.148 | 0.430 (0.175–1.060) | 0.067 | |
6–10 | Reference | Reference | ||||
11–15 | 0.857 (0.377–1.951) | 0.713 | 0.797 (0.315–2.016) | 0.632 | ||
16–20 | 0.655 (0.226–1.900) | 0.437 | 1.201 (0.318–4.542) | 0.787 | ||
≥21 | 0.588 (0.266–1.301) | 0.190 | 0.925 (0.267–3.210) | 0.903 | ||
Job position (multiple choice) | General clinic ( |
0.658 (0.375–1.154) | 0.144 | 1.001 (0.411–2.441) | 0.998 | |
General ward ( |
1.196 (0.664–2.153) | 0.551 | 1.111 (0.486–2.543) | 0.803 | ||
General emergency ( |
1.268 (0.557–2.891) | 0.571 | 1.841 (0.605–5.599) | 0.282 | ||
Fever clinic ( |
1.381 (0.479–3.983) | 0.551 | 1.523 (0.409–5.676) | 0.531 | ||
Isolation ward or Fangcang Shelter ( |
3.477 (0.420–28.774) | 0.248 | 2.848 (0.273–29.711) | 0.382 | ||
Others ( |
1.151 (0.664–1.994) | 0.617 | 0.762 (0.294–1.974) | 0.575 | ||
COVID-19 work | Participation ( |
1.004 (0.496–2.032) | 0.992 | |||
Working content of COVID-19 (multiple choice) | Drug supply and guarantee ( |
0.890 (0.511–1.548) | 0.679 | |||
Pharmacy information support ( |
1.209 (0.684–2.137) | 0.515 | ||||
Drug dispensation ( |
0.477 (0.273–0.835) | 0.010 | 0.400 (0.203–0.790) | 0.008 | ||
Drug evaluation ( |
1.765 (0.725–4.297) | 0.211 | ||||
Disinfectant preparation ( |
0.725 (0.299–1.756) | 0.476 | ||||
Guidelines/consensus development ( |
3.041 (0.663–13.937) | 3.041 | ||||
Others ( |
0.864 (0.478–1.563) | 0.629 | ||||
Information source of COVID-19 (multiple choice) | In-hospital training ( |
0.926 (0.401–2.143) | 0.858 | |||
National Health Commission and other official guidance documents ( |
1.647 (0.836–3.248) | 0.149 | ||||
Other guidelines/consensus ( |
1.956 (1.098–3.484) | 0.023 | 1.905 (0.999–3.631) | 0.050 | ||
News media ( |
0.857 (0.489–1.503) | 0.591 | ||||
FIP guidance ( |
1.330 (0.770–2.296) | 0.307 | ||||
Journal articles ( |
1.061 (0.614–1.834) | 0.831 | ||||
Academic conferences ( |
0.800 (0.459–1.395) | 0.431 | ||||
Others ( |
0.874 (0.311–2.457) | 0.798 |
COVID-19, coronavirus disease 2019; OR, odds ratio; CI, confidence interval.
Attitudes: pharmacists’ roles and actions
Overall, 145 pharmacists (61.18%) were classified as having positive attitudes. The score of pharmacists’ roles and actions was 9.2 [1.4] {median [IQR]}. The scores of the attitudes section are shown in Figure 2. When asked to grade their self-confidence in the role of pharmacists (A1-A4), 129 participants (54.43%) displayed positive attitudes. Compared with pharmacists’ role in clinical management of COVID-19 {median [IQR]: 9 [2]}, pharmacists were more confident about their role in relevant research {median [IQR]: 10 [2]}. As for the agreement of measures related to “supporting pharmacists and pharmacy teams” (A5-A13), the median (IQR) was 9.4 (1.4). Among items A5-A13, the item “Recognize pharmacists as pivotal anti-epidemic staff” (A5) returned the lowest score of 8.0 (3.0). The COVID-19 information source “the National Health Commission and other official guidance documents” was identified as a significant positive impact factor in both univariate and multivariate logistic regression analysis (Table 3).
Table 3
Characteristics | Subgroup | Univariate analysis | Multivariate analysis | |||
---|---|---|---|---|---|---|
OR (95% CI) | P value | OR (95% CI) | P value | |||
Gender | Male ( |
1.353 (0.772–2.371) | 0.291 | 1.240 (0.680–2.259) | 0.483 | |
Job title | Primary and below | 1.345 (0.706–2.562) | 0.368 | 1.463 (0.628–3.407) | 0.378 | |
Junior | Reference | Reference | ||||
Senior | 1.655 (0.882–3.108) | 0.117 | 1.486 (0.610–3.620) | 0.383 | ||
Education background | College and below | 0.686 (0.234–2.010) | 0.492 | 0.951 (0.239–3.779) | 0.943 | |
Bachelor | Reference | Reference | ||||
Master | 0.869 (0.480–1.573) | 0.643 | 1.012 (0.497–2.063) | 0.973 | ||
Doctor | 1.125 (0.444–2.850) | 0.804 | 1.269 (0.415–3.883) | 0.676 | ||
Job responsibility | Clinical pharmacist | Reference | Reference | |||
Drug dispensing | 1.531 (0.791–2.964) | 0.206 | 1.823 (0.733–4.530) | 0.196 | ||
Pharmacy administrator | 1.409 (0.694–2.862) | 0.343 | 1.222 (0.523–2.855) | 0.643 | ||
Others | 0.646 (0.233–1.797) | 0.403 | 0.748 (0.248–2.250) | 0.605 | ||
Working years | 1–5 | 1.008 (0.484–2.099) | 0.983 | 1.012 (0.442–2.318) | 0.978 | |
6–10 | Reference | Reference | ||||
11–15 | 1.042 (0.491–2.211) | 0.914 | 1.025 (0.448–2.347) | 0.953 | ||
16–20 | 1.024 (0.371–2.828) | 0.963 | 0.956 (0.280–3.267) | 0.943 | ||
≥21 | 1.366 (0.633–2.946) | 0.427 | 1.084 (0.346–3.4030 | 0.890 | ||
Job position (multiple choice) | General clinic ( |
1.289 (0.741–2.243) | 0.369 | 1.397 (0.603–3.237) | 0.435 | |
General ward ( |
1.267 (0.721–2.228) | 0.411 | 1.819 (0.798–4.146) | 0.154 | ||
General emergency ( |
1.467 (0.660–3.258) | 0.347 | 0.788 (0.265–2.345) | 0.669 | ||
Fever clinic ( |
1.412 (0.517–3.855) | 0.501 | 1.736 (0.486–6.204) | 0.396 | ||
Isolation ward or Fangcang Shelter ( |
1.060 (0.247–4.543) | 0.938 | 1.166 (0.235–5.771) | 0.851 | ||
Others ( |
0.956 (0.565–1.617) | 0.866 | 1.756 (0.685–4.502) | 0.241 | ||
COVID-19 work | Participation ( |
1.037 (0.528–2.040) | 0.915 | |||
Working content of COVID-19 (multiple choice) | Drug supply and guarantee ( |
1.298 (0.758–2.225) | 0.342 | |||
Pharmacy information support ( |
1.146 (0.665–1.975) | 0.624 | ||||
Drug dispensation ( |
1.030 (0.598–1.774) | 0.915 | ||||
Drug evaluation ( |
0.861 (0.400–1.854) | 0.703 | ||||
Disinfectant preparation ( |
1.212 (0.299–1.756) | 0.676 | ||||
Guidelines/consensus development ( |
1.151 (0.374–3.550) | 0.806 | ||||
Others ( |
1.275 (0.711–2.285) | 0.414 | ||||
Information source of COVID-19 (multiple choice) | In-hospital training ( |
0.809 (0.358–1.826) | 0.610 | |||
National Health Commission and other official guidance documents ( |
2.341 (1.197–4.575) | 0.013 | 2.385 (1.114–5.107) | 0.025 | ||
Other guidelines/consensus ( |
1.400 (0.797–2.458) | 0.241 | ||||
News media ( |
0.815 (0.475–1.399) | 0.458 | ||||
FIP guidance ( |
1.539 (0.909–2.606) | 0.109 | ||||
Journal articles ( |
1.290 (0.651–2.187) | 0.344 | ||||
Academic conferences ( |
1.073 (0.626–1.841) | 0.431 | ||||
Others ( |
1.177 (0.420–3.299) | 0.757 |
COVID-19, coronavirus disease 2019; OR, odds ratio; CI, confidence interval.
Practices: prevention, control measures, and pharmacist’s advice
The assessment of practices was composed of 5 behaviors (P1-P5). Answers to the knowledge section are shown in Figure 3. The number of correct answers was 3 [1] {median [IQR]}, and 50.63% of pharmacists were classified as qualified. The incorrect answers were mainly focused on disinfectant. Among them, 78.90% (P2) and 60.76% pharmacists (P4) believed that chlorhexidine could effectively inactivate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Additionally, 23.21% pharmacists held that 75% ethanol could be used to disinfect large areas such as the air. The job position “others” (positive correlation), participation in COVID-19 work (positive correlation), and the COVID-19 information source “others” (negative correlation) were statistically significant independent factors in both univariate and multivariate logistic regression analysis (Table 4).
Table 4
Characteristics | Subgroup | Univariate analysis | Multivariate analysis | |||
---|---|---|---|---|---|---|
OR (95% CI) | P value | OR (95% CI) | P value | |||
Gender | Male ( |
1.168 (0.673–2.029) | 0.581 | 1.057 (0.566–1.974) | 0.861 | |
Job title | Primary and below | 0.846 (0.450–1.587) | 0.602 | 0.974 (0.407–2.329) | 0.952 | |
Junior | Reference | Reference | ||||
Senior | 1.108 (0.605–2.028) | 0.739 | 1.036 (0.396–2.707) | 0.943 | ||
Education background | College and below | 0.266 (0.072–0.988) | 0.048 | 0.718 (0.143–3.599) | 0.687 | |
Bachelor | Reference | Reference | ||||
Master | 1.374 (0.767–2.461) | 0.286 | 1.205 (0.585–2.483) | 0.613 | ||
Doctor | 1.996 (0.791–5.036) | 0.143 | 1.660 (0.520–5.293) | 0.392 | ||
Job responsibility | Clinical pharmacist | Reference | Reference | |||
Drug dispensing | 0.536 (0.283–1.014) | 0.055 | 1.173 (0.462–2.978) | 0.737 | ||
Pharmacy administrator | 0.815 (0.413–1.611) | 0.557 | 0.788 (0.327–1.899) | 0.595 | ||
Others | 0.694 (0.250–1.929) | 0.484 | 0.925 (0.279–3.072) | 0.899 | ||
Working years | 1–5 | 1.133 (0.551–2.331) | 0.734 | 1.332 (0.570–3.111) | 0.508 | |
6–10 | Reference | Reference | ||||
11–15 | 1.249 (0.596–2.618) | 0.556 | 1.254 (0.535–2.938) | 0.603 | ||
16–20 | 0.971 (0.359–2.629) | 0.954 | 1.156 (0.322–4.149) | 0.824 | ||
≥21 | 0.694 (0.330–1.459) | 0.335 | 0.693 (0.209–2.304) | 0.550 | ||
Job position (multiple choice) | General clinic ( |
0.688 (0.402–1.176) | 0.172 | 1.371 (0.596–3.154) | 0.458 | |
General ward ( |
0.735 (0.426–1.269) | 0.269 | 1.421 (0.638–3.167) | 0.390 | ||
General emergency ( |
0.840 (0.398–1.773) | 0.648 | 0.724 (0.245–2.141) | 0.560 | ||
Fever clinic ( |
1.091 (0.427–2.790) | 0.856 | 2.205 (0.639–7.610) | 0.211 | ||
Isolation ward or Fangcang Shelter ( |
1.652 (0.386–7.076) | 0.499 | 1.841 (0.362–9.363) | 0.462 | ||
Others ( |
2.364 (1.397–4.000) | 0.001 | 4.172 (1.637–10.635) | 0.003 | ||
COVID-19 work | Participation ( |
2.202 (1.107–4.381) | 0.024 | 2.194 (1.008–4.776) | 0.048 | |
Working content of COVID-19 (multiple choice) | Drug supply and guarantee ( |
1.185 (0.704–1.996) | 0.523 | |||
Pharmacy information support ( |
0.996 (0.587–1.690) | 0.989 | ||||
Drug dispensation ( |
1.288 (0.757–2.190) | 0.351 | ||||
Drug evaluation ( |
1.412 (0.658–3.030) | 0.376 | ||||
Disinfectant preparation ( |
1.300 (0.546–3.093) | 0.553 | ||||
Guidelines/consensus development ( |
0.369 (0.112–1.212) | 0.100 | ||||
Others ( |
1.286 (0.732–2.257) | 0.381 | ||||
Information source of COVID-19 (multiple choice) | In-hospital training ( |
1.530 (0.696–3.363) | 0.290 | |||
National Health Commission and other official guidance documents ( |
0.776 (0.399–1.507) | 0.453 | ||||
Other guidelines/consensus ( |
2.153 (1.220–3.798) | 0.008 | 1.633 (0.861–3.098) | 0.133 | ||
News media ( |
0.971 (0.576–1.637) | 0.911 | ||||
FIP guidance ( |
1.247 (0.749–2.077) | 0.396 | ||||
Journal articles ( |
1.390 (0.832–2.324) | 0.209 | ||||
Academic conferences ( |
1.841 (1.081–3.135) | 0.025 | 1.700 (0.943–3.065) | 0.078 | ||
Others ( |
0.276 (0.087–0.873) | 0.028 | 0.251 (0.065–0.970) | 0.045 |
COVID-19, coronavirus disease 2019; OR, odds ratio; CI, confidence interval.
Correlation between knowledge, attitudes, and practices
The chi-squared (χ2) test was performed to evaluate the correlation between knowledge and attitudes (K&A), knowledge and practices (K&P), and attitudes and practices (A&P). No significant correlation was observed in any of these pairings (K&A: χ2=1.368, P=0.242; K&P: χ2=0.312, P=0.577; A&P: χ2=1.492, P=0.222).
Discussion
Currently, the important role of pharmacist and innovative strategies of pharmacy interventions have been widely established and published. However, the information on the dissemination and implementation of guidance for pharmacists is limited and remains to be fully understood. In this study, we assessed the implementation of FIP guidance through a survey of the knowledge, attitudes, and practices of representative pharmacists. Most pharmacists were shown to have sufficient knowledge of transmission routes and clinical treatment for COVID-19, as well as positive attitudes towards their roles and actions. About half of the cohort were qualified in the practices of prevention and control measures, risk factor control, and pharmacist’s advice. Several factors were revealed as having impact on pharmacists’ KAP, such as whether they were participating in COVID-19 work, working content, and information source.
Most respondents (67.51%) showed appropriate knowledge regarding transmission routes and clinical treatment, which is consistent with studies in other countries, such as Lebanon, Turkey, Vietnam, and Pakistan (9,13-15). Over 60% had positive attitudes towards pharmacists’ roles and actions. However, pharmacists referred to other guidelines or consensus more than FIP guidance, including information and guidance from the Chinese National Health Commission (16) and those developed by Chinese associations and institutions (17,18). Authorized guidance of COVID-19 was a positive impact factor to the attitudes of pharmacist towards COVID-19.
The accessibility, validity, adaptability, applicability, and usability were considered important factors to guidance implementation (6,19,20). Mandatory requirements and supervision by authorities also played an essential role. During the COVID-19 pandemic, it was required that all medical staff should learn the authorized guidance of COVID-19. Thus, pharmacists obtaining COVID-19 information from official guidance documents may have better knowledge and attitudes.
Effective prevention measures and infection risk monitoring for pharmacists are necessities during the COVID-19 pandemic, which can reduce the risk of infection for both themselves and others (21). They must maintain and promote good hygiene conditions, take prevention measures such as wearing disposable gloves, protective clothing, eye protection, and masks, and maintain appropriate social distance with patients and other healthcare staff (15,21,22). In our study, 69.62% of pharmacists took adequate prevention measures against workplace infections. The result is similar to the study in Henan, where 89.7% of healthcare staff took effective measures (23). However, it has been reported that as many as 72.4% of pharmacists in Jordan believed that keeping a distance of half a meter from COVID-19 patients can effectively prevent viral transmission (24). Thus, it is still necessary to seek an understanding of pharmacists’ behavior around the world to determine barriers for the implementation of medical guidance.
As for practice to promote treatment of COVID-19, although some antiviral agents such as interferon-α, ribavirin, arbidol and chloroquine phosphate were observed to have therapeutic effect on COVID-19 based on available clinical studies, there is still no specific therapeutic drug approved for COVID-19 worldwide (25). Thus, pharmacists are encouraged to cooperate with clinicians to closely monitor and evaluate the medication safety and efficacy.
To the best of our knowledge, our study was the first survey to explore the implementation of FIP guidance on COVID-19. The status of pharmacists’ adherence and barriers of FIP guidance were analyzed and identified. However, our study had a few limitations that need to be addressed in further studies. Firstly, the study sample was relatively small and covered only mainland China, and the KAP of pharmacists from other regions should be considered. Secondly, this was a self-reported online survey through WeChat, face-to-face interviews might yield more information towards a better understanding of the implementation of the guidance. Due to unknown number of duplicate people in different WeChat groups, we did not know the number of nonresponse and the response rate was not calculated. Thirdly, bias cannot be excluded due to the nature of convenience sampling; thus, stratified sampling may strengthen sample representativeness.
In addition to strengthening the usability and applicability of such guidelines, it is encouraged to fully involve the knowledge, attitudes, and relevance of target users in the future directives. It is also important to integrate local policy to gain support and promotion from the relevant authorities during guidance implementation (26).
Conclusions
Our study revealed an appropriate level of knowledge, attitudes, and practices towards COVID-19 among pharmacists in mainland China, which indicated that the FIP guidance has a certain degree of dissemination and implementation in China. However, the implementation of guidelines can be improved through effective actions directed towards impact factors.
Acknowledgments
We would like to express our gratitude to all pharmacists who responded to our questionnaire. We also feel grateful for Prof. Shao Lin from School of Public Health, University at Albany, State University of New York for help with editing and Dr. Lin Zhuo from the Research Center of Clinical Epidemiology, Peking University Third Hospital for consultation.
Funding: The study is funded by the National Key R&D Program of China (2020YFC2008305), and the National Natural Science Foundation of China (NSFC) (72104003, 72042013).
Footnote
Reporting Checklist: The authors have completed the SURGE reporting checklist. Available at https://dx.doi.org/10.21037/atm-21-4157
Data Sharing Statement: Available at https://dx.doi.org/10.21037/atm-21-4157
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/atm-21-4157). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All procedures performed in this study involving human participants were in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional ethics board of the Peking University Third Hospital (No.: IRB00006761-M2020299). The online voluntary and anonymous questionnaire secured the confidentiality of the participants, and did not collect any identity-exposing information of the participants.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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(English Language Editor: J. Jones)