BACKGROUND

In the current global context of a coronavirus pandemic, the level of knowledge of professionals working in health institutions is a key factor in being able to control the transmission of the infection, as well as to contribute to the improvement of the health education of the population. Low levels of knowledge by healthcare professionals are known to increase the risk of infection and increase their anxiety levels (Alsahafi & Cheng, 2016; Rabaan et al., 2017). Their perception of being well-prepared has a protective effect, not only on safety in dealing with new pandemic waves, but also on the prevention of mental health problems (De Brier et al., 2020).

A rapid response of the healthcare systems to the risk of coronavirus infection is crucial to preventing accelerated expansion. Primary healthcare must provide effective community coordination in case detection and management, as it is the first link in the response of healthcare systems to the pandemic (Sarti et al., 2020). Most cases of SARS-CoV-2 infection are monitored and controlled in primary care in person, at home, and remotely, either by telephone or video-consultation. However, during the early months of 2020, there were significant knowledge gaps regarding the management and behavior of SARS-CoV-2 (Llor & Moragas, 2020). This knowledge deficit raised doubts among professionals about how to act at primary care facilities to curb the rising number of cases and the rapid spread of the disease. Basic training in knowledge, skills, and attitudes regarding the control and management of the novel coronavirus is therefore crucial for all primary care professionals. In addition, the role of nurses at primary care facilities has been critical in the pandemic, leading early detection through diagnostic testing, case monitoring, symptom control, close contact tracing, and, more recently, the mass vaccination process targeting the entire Spanish population (Nunciaroni et al., 2020).

The Nursing Outcomes Classification (NOC) (Moorhead et al., 2018) is a tool designed conceptually to measure the effectiveness of nursing interventions in an international framework of care language standardization. It consists of seven domains. Among them, domain IV is called “Health Knowledge & Behavior” and it includes “outcomes that describe attitudes, comprehension, and actions with respect to health and illness.” This domain is, in turn, made up of seven classes, among these are “Knowledge: health condition” and “Knowledge: health promotion.” Both classes comprise 40% of the outcome labels of the entire domain, with a total of 74. The first of these classes includes the “outcomes that describe an individual's understanding in applying information to manage a health condition” and the second includes “outcomes that describe an individual's understanding in applying information to optimise health.”

The NOC has numerous applications in the field of care research (Swanson, 2020). A number of outcome criteria, belonging to the classes mentioned above, have provided the basis for the construction of tools for measuring knowledge in health care (Romero et al., 2021; Paloma-Castro et al., 2017).

METHODS Design

Quasi-experimental study with a before–after analysis of the conduct of a 5-week online training program for healthcare professionals on prevention and control of SARS-CoV-2 infection.

Setting

This study was conducted within the institutional framework of the Primary Care Management of Tenerife (Canary Islands, Spain). The Canary Islands archipelago is made up of eight islands which are divided into seven health areas. Tenerife is one of them: the largest in size and in number of inhabitants. The Primary Care Management of Tenerife employs a total of 1782 healthcare professionals and 639 nonhealthcare professionals in the area of administration, management, and services, distributed among 40 basic healthcare districts. The total population covered is 778,251 people.

Sample

The population under study was made up of all primary healthcare professionals in Tenerife, both medical and otherwise, enrolled in one of the four editions of the online course called Coronavirus y COVID-19 en Atención Primaria (Coronavirus and COVID-19 in Primary Healthcare, in English). Each edition had an enrolment limit of 250 students and five mentors. The total number of preenrolled employees for the four editions of the course was 880. As an inclusion criterion in the research, the participants had to successfully complete and pass the course. This was achieved by completing and passing all the evaluation tests with a score of 8 or more out of 10. Additionally, prior to completing the pre- and posttraining data collection logs, they must agree to participate in the study. In addition, as an inclusion criterion for the course, participants had to be currently working in Primary Care Management in Tenerife in any of the following categories: healthcare professionals (nurses, doctors, nursing assistants, hospital porters, dentists, oral hygiene technicians, pharmacists, and physiotherapists) and nonhealthcare professionals (administrative assistants and social workers).

A sample size close to the aforementioned figure, 880 cases, would allow us to estimate nonparametric correlation coefficients of at least 0.28 and to verify the expected differences in the before–after comparisons, with a minimum output of 90% in two-tailed hypothesis testing and at an alpha significance level of 0.05 and 95% confidence intervals.

Characteristics of the training program

The five-week training program (undergone by each participant) was free of charge for the institution's employees and was aimed at all professional categories. Each professional could register and participate in one edition only. The training editions overlapped in time, with a maximum of two being held at the same time. This was in response to the high demand for enrolment and how important it was for the institution to train the greatest number of professionals in the shortest amount of time possible, given the healthcare demands of the pandemic.

The design, construction, and implementation of the course, as well as the conduct of this research, were carried out by the nurses who are part of the Training, Research, Innovation, and Implementation of Good Practices in Health Care (FIIBPCS, in Spanish) department. These nurses, five in total, have a teaching and research role in the institution. They created and implemented the course online, following the recommendations of the Management due to the restrictions for conducting group in-person training sessions. The course was accessible through the Primary Care Management's Moodle online training platform, after applying to enroll through the continuing professional development department. To create and develop the content, existing primary healthcare guidelines and protocols for the action of healthcare professionals against COVID-19, which had been published by the Ministry of Health of the Government of Spain and by the Canary Islands’ Health Service in 2020, were used.

The purpose of the course was to consolidate knowledge about the basic prevention and management measures for community infection with the new coronavirus. It was 20 h long (distributed over 5 weeks per participant) and was accredited by the Regional Commission for Continuing Professional Development. It was divided into five modules: (1) general information; (2) primary healthcare management of COVID-19; (3) home management; (4) pediatric management; and (5) prevention measures and infection control. Each of the modules consisted of several sections: content, with downloadable PDF files and/or links related to the subject; summary sheets, with the key points of the content, and evaluation tests, one or two according to the module and between 10 and 30 test questions for each one. The objective knowledge assessment was carried out using a total of 110 test questions, with four response options, distributed between the five modules according to their subject matter. The distribution of questions and answers of the objective assessment was different for each participant when completing the online questionnaires, being automatically randomized by the Moodle online training platform. In addition, each assessment questionnaire was allocated a response time limit. By randomizing the distribution of questions and answers and setting time limits on the completion of the questionnaires, we sought to ensure that each participant would complete the test on their own, minimizing the chances of cheating. The participants had to pass each test with at least 80% correct answers.

In addition to the five modules discussed, the course had a video library, a module with links to relevant websites, forums for discussing doubts and to promote debate among students, and three activities with gamified content to strengthen their learning in a fun, competitive context which did not involve assessment.

Variables and instruments The variables of interest for the research were as follows: Sex: male/female. Age, in years, and by group: 18–35 years; 36–54 years; 55–65 years. Professional profile: From this polytomous categorical variable, a new dichotomous variable was obtained to group healthcare professionals on the one hand and on the other, the nonhealth professionals. Professional experience: in years. From the original quantitative variable, another categorical variable was obtained in three categories: 5 years of professional experience or less, between 6 and 15 years and, finally, more than 15 years of professional experience. Perceived knowledge: self-assessment by the participating professionals. For this, the NOC outcome criteria “Knowledge: Infection management” [1842] (Moorhead et al., 2018) was used.

The research team reviewed the indicators available in the classification, agreeing to use 12 of them out of a total of 25. The aim was to have the means to measure the different factors of interest related to the content of the training program which were susceptible to change in response to the training received. The selected indicators agreed upon were: “Mode of transmission” [184201]; “Factors contributing to infection transmission” [184202]; “Practices that reduce transmission” [184203]; “Signs and symptoms of infection” [184204]; “Monitoring procedures for infection” [184206]; “Importance of hand sanitation” [184207]; “Follow-up for diagnosed infection” [184210]; “Signs and symptoms of exacerbation of infection” [184211]; “Strategies to manage stress” [184222]; “Factors that affect immune response” [184223]; “Available community resources” [184225]; and “When to obtain assistance from a health professional” [184226].

An operational definition of each indicator (Table 1) was constructed to explain each aspect of self-assessed knowledge. These definitions were evaluated and agreed upon in three Delphi rounds by a group of five external professionals with experience in each particular aspect to be assessed. Subsequently, each participant gave a response, before and after the training program, about their perceived level of knowledge in relation to each indicator, scoring on a Likert-type scale between 1, no knowledge, and 5, extensive knowledge. The response to each of these self-assessments were taken as ordinal quantitative variables. The total score, adding up the 12 indicators selected, ranged from 12 points (minimum knowledge) to 60 points (maximum knowledge). This score was considered a quantitative variable. The result of the difference between pre- and posttraining scores formed another quantitative variable, which reflected the perceived increase in knowledge. Additionally, another dichotomous categorical variable was generated from the responses to each NOC indicator in the pre- and posttraining comparison. Scores between 1 and 3 on the Likert scale (no knowledge to moderate knowledge) were considered inadequate, and scores between 4 and 5 (substantial and extensive knowledge) were considered adequate knowledge.

Table 1. Frequency distribution for responses to the NOC outcome criterion “Knowledge: Infection management” NOC [1842] Pre % (n) Post % (n) Knowledge: Infection management Inadequate knowledge Adequate knowledge Inadequate knowledge Adequate knowledge Indicators and operational definition / Likert 1 2 3 4 5 1 2 3 4 5 [184201] Mode of transmission: Set of mechanisms through which SARS-CoV-2 comes into contact with the human host. 0.1 (1) 5.0 (35) 43.1 (304) 42.7 (301) 9.1 (64) 0.0 (0) 0.1 (1) 8.8 (62) 47.4 (334) 43.7 (308) [184202] Factors contributing to infection transmission: Intrinsic and extrinsic aspects that facilitate infection or that are related to the mode of transmission of the virus. 0.3 (2) 7.4 (52) 48.1 (339) 37.2 (262) 7.1 (50) 0.0 (0) 0.1 (1) 9.9 (70) 46.0 (324) 44.0 (310) [184203] Practices that reduce transmission: A set of measures and behaviours adopted to maintain health and prevent COVID-19 by minimising the possibility of human-to-human transmission of the virus. 0.1 (1) 4.8 (34) 32.9 (232) 50.9 (359) 11.2 (79) 0.0 (0) 0.1 (1) 7.4 (52) 38.4 (271) 54.0 (381) [184204] Signs and symptoms of infection: Clinical manifestations that are present in individuals infected with SARS-CoV-2 or ill with COVID-19. 0.0 (0) 6.1 (43) 40.6 (286) 42.3 (298) 11.1 (78) 0.0 (0) 0.3 (2) 8.8 (62) 42.3 (298) 48.7 (343) [184206] Monitoring procedures for infection: Healthcare practice methods and/or community measures aiming to reduce and/or eliminate the spread of SARS-CoV-2. 0.9 (6) 11.6 (82) 48.5 (342) 32.1 (226) 7.0 (49) 0.0 (0) 0.6 (4) 11.3 (80) 44.4 (313) 43.7 (308) [184207] Importance of hand sanitation: Level of relevance attributed to the hand washing procedure as a universal protective measure against coronavirus infection. 0.0 (0) 1.1 (8) 14.3 (101) 35.9 (253) 48.7 (343) 0.0 (0) 0.1 (1) 3.4 (24) 21.6 (152) 74.9 (528) [184210] Follow-up for diagnosed infection: Procedure for ongoing assessment of SARS-CoV-2 infection. 2.7 (19) 15.2 (107) 43.1 (304) 30.1 (212) 8.9 (63) 0.0 (0) 1.0 (7) 12.6 (89) 43.8 (309) 42.6 (300) [184211] Signs and symptoms of exacerbation of infection: Clinical manifestations suggestive of worsening COVID-19. 3.0 (21) 16.9 (119) 45.2 (319) 28.9 (204) 6.0 (42) 0.0 (0) 2.0 (14) 13.5 (95) 42.8 (302) 41.7 (294) [184222] Strategies to manage stress: Set of measures adopted by individuals in a community, with or without COVID-19, to minimise the negative psychological impact of the pandemic. 4.0 (28) 27.1 (191) 47.7 (336) 17.9 (126) 3.4 (24) 0.1 (1) 1.4 (10) 20.1 (142) 48.7 (343) 29.6 (209) [184223] Factors that affect immune response: Aspects that alter the ability of the human body and its natural defence systems to react to and protect itself against SARS-CoV-2. 6.1 (43) 30.1 (212) 44.5 (314) 17.4 (123) 1.8 (13) 0.1 (1) 2.6 (18) 19.6 (138) 47.8 (337) 29.9 (211) [184225] Available community resources: Accessible support systems in the local community to improve or maintain people's health care in the face of a coronavirus pandemic. 3.5 (25) 30.4 (214) 45.2 (319) 18.2 (128) 2.7 (19) 0.0 (0) 1.6 (11) 17.9 (126) 46.8 (330) 33.8 (238) [184226] When to obtain assistance from a health professional: Time at which consultation with local healthcare professionals is deemed necessary to address questions regarding the prevention and/or management of COVID-19. 0.6 (4) 6.2 (44) 34.8 (245) 40.9 (288) 17.6 (124) 0.0 (0) 0.1 (1) 5.8 (41) 34.3 (242) 59.7 (421) Mean value as % 1.8 13.5 40.7 32.9 11.2 0.0 0.8 11.6 42.0 45.5 Data collection

Data collection was conducted at the time interval during which all of the editions of the course were carried out, between 12 May and 31 July 2020. For this purpose, the participants completed a data collection log containing the variables needed for the study, before and after and as part of the course content. These logs were edited in Google Forms and were available via a website link on the Moodle platform of the course, at the start and at the end of the course.

Data analysis

The description of the categorical variables was done using the frequency of their categories. For the quantitative variables, the mean and standard deviation or the median and its percentiles (5–95) were used, according to the normality of the distribution. To compare the results relating to the perceived level of knowledge before and after the training and making these comparisons between ordinal quantitative variables, Student's t-test or the nonparametric Wilcoxon test was used, according to the normality of the distribution. Cochran's Q test was used when comparing the expected change, postintervention, from inadequate knowledge to adequate knowledge, from the dichotomous categorical variable generated as a secondary variable.

For bivariate analysis, the quantitative variables were correlated with each other using Pearson or Spearman–Brown coefficients. For the comparisons between quantitative and categorical variables in two categories, Student's t-test or the Mann–Whitney U-test were used, according to the distribution, or for the categorical variables in more than two categories, one-way analysis of variance (ANOVA) was used.

All tests were two-tailed and performed at an alpha significance level <0.05 and with the help of the IBM® Statistical Package for the Social Sciences (SPSS) v.25.0.

Ethical considerations

The study complied with national and international ethical standards for research with human beings, in accordance with the Helsinki Declaration, and was approved by the institutional review board of the Primary Care Management of Tenerife, The Canary Islands Health Service, Spain. The professionals participated anonymously and voluntarily by enrolling in an online training program. These participants authorized their inclusion in the study online and by filling in the first data collection log. They received information on the objectives and characteristics of the research, as well as about how their anonymity would be maintained in the data handling by the research team. For this purpose, the pre- and posttraining data collection logs were identified using an alphanumeric code that only the participant knew. To avoid repeated codes, the research team added a recruitment code to each one according to their order of receiving the information in the data collection logs. All participants voluntarily collaborated and were able to leave the study whenever they wished, without giving explanations or reasons.

FINDINGS Description of the participants

Of the 880 healthcare professionals preenrolled on the course, 766 (87.1%) started the training. From these, 705 (92.0%) successfully passed assessments and completed the pre- and posttraining surveys, forming the final sample of this research. This sample represents 29.12% of the total number of healthcare professionals in Tenerife. A total of 79.7% (n = 562) of the sample were women and the median age was 45 (28–60) years. By age group, 60.3% (n = 425) were between 36 and 54 years, 22.4% (n = 158) were between 18 and 35 years, and the rest were 17.3% (n = 122), between 55 and 65 years. Up to 10 different profiles participated in the professional training program, the most prevalent being nurses with 40.6% (n = 286) of the total, followed by doctors with 30.5% (n = 215), administrative assistants with 18.6% (n = 131), and nursing assistants with 5% (n = 35). These four profiles brought together 94.7% of the healthcare professionals who completed the training. The rest of the participants were hospital porters (2.1%, n = 15), dentists (1.1%, n = 8), oral hygiene technicians (1.1%, n = 8), social workers (0.6%, n = 4), pharmacists (0.3%, n = 2), and physiotherapists (0.1%, n = 1). By dividing the professional profile into two categories (healthcare and nonhealthcare), we found that the healthcare profiles made up 80.9% (n = 570) of the sample. The median professional experience time was 16 (2–33) years. The distribution of the professional experience was 52.1% (n = 367) for the group with more than 15 years of experience, 30.9% (n = 218) between 6 and 15 years, and the rest, 17% (n = 120), had 5 years of professional experience or less.

Distribution of the scores. Pre- and posttraining evaluation and correlations

In Table 1 the frequency distribution of responses on the Likert scale is shown for each of the indicators. Likewise, the grouping between inadequate and adequate knowledge is described, both in the pre- and posttraining periods.

The pre-training median total score of perceived knowledge score was 40 (29–53) points, which the posttraining total score was 53 (39–60) points, confirming significance in this difference (p < 0.001, Wilcoxon's Z: –22.407). Table 2 shows the differences between the means of the pre- and post-training scores and their p-value statistical significance for each of the indicators.

Table 2. Comparison of mean Likert scale scores (1–5) for the perceived knowledge for each of the indicators of the NOC outcome criterion “Knowledge: Infection management” (n = 705) NOC [1842] Pre Post Related differences test p-value Knowledge: Infection management Mean SD Mean SD Mean 95% Confidence Interval Indicators / Likert Lower limit Upper limit [184201] Mode of transmission 3.56 0.733 4.35 0.641 –0.790 –0.846 –0.734 <0.001 [184202] Factors contributing to infection transmission 3.43 0.744 4.34 0.657 –0.904 –0.961 –0.846 <0.001 [184203] Practices that reduce transmission 3.68 0.739 4.46 0.637 –0.782 –0.837 –0.726 <0.001 [184204] Signs and symptoms of infection 3.58 0.766 4.39 0.657 –0.810 –0.868 –0.752 <0.001 [184206] Monitoring procedures for infection 3.33 0.802 4.31 0.690 –0.986 –1.047 –0.925 <0.001 [184207] Importance of hand sanitation 4.32 0.757 4.71 0.531 –0.391 –0.449 –0.334 <0.001 [184210] Follow-up for diagnosed infection 3.27 0.919 4.28 0.717 –1.006 –1.071 –0.941 <0.001 [184211] Signs and symptoms of exacerbation of infection 3.18 0.886 4.24 0.757 –1.062 –1.125 –1.000 <0.001 [184222] Strategies to manage stress 2.90 0.857 4.06 0.751 –1.166 –1.233 –1.099 <0.001 [184223] Factors that affect immune response 2.79 0.866 4.05 0.780 –1.260 –1.327 –1.192 <0.001 [184225] Available community resources 2.86 0.846 4.13 0.750 –1.267 –1.337 –1.196 <0.001 [184226] When to obtain assistance from a health professional 3.69 0.853 4.54 0.612 –0.850 –0.910 –0.790 <0.001 Mean value as % 40 (29–53) 53 (39–60) <0.001 SD: standard deviation. Statistical analysis performed using the Wilcoxon Test.

Table 3 describes the frequency of appropriate knowledge in the pre- and posttraining periods, the differential value, and statistical significance. With regard to indicators, the lowest percentage of knowledge perceived as adequate was, during the pre- and posttraining periods, for the “Factors that affect immune response” [184223] indicator. By contrast, the highest percentage of adequate knowledge was, before and after, for the “Importance of hand sanitation” [184207] indicator. The broadest difference in learning between the two period was for the “Available community resources” [184225] indicator.

Table 3. Pre- and post-training differences in the perception of adequate knowledge for the control of coronavirus infection (n = 705) NOC [1842] Adequate Knowledge Knowledge: Infection management Pre Post Indicators / Likert % (n) % (n) Learning differential Cochran's Q p-value [184201] Mode of transmission 51.8 (365) 91.1 (642) 39.3 (277) 260.098 <0.001 [184202] Factors contributing to infection transmission 44.3 (312) 89.9 (634) 45.6 (322) 304.953 <0.001 [184203] Practices that reduce transmission 62.1 (438) 92.5 (652) 30.4 (214) 197.397 <0.001 [184204] Signs and symptoms of infection 53.3 (376) 90.9 (641) 37.6 (265) 249.911 <0.001 [184206] Monitoring procedures for infection 39.9 (275) 88.1 (621) 48.2 (346) 325.315 <0.001 [184207] Importance of hand sanitation 84.5 (596) 96.5 (680) 12.0 (84) 66.566 <0.001 [184210] Follow-up for diagnosed infection 39.0 (275) 86.4 (609) 47.4 (334) 320.563 <0.001 [184211] Signs and symptoms of exacerbation of infection 34.9 (246) 84.5 (596) 49.6 (350) 338.398 <0.001 [184222] Strategies to manage stress 21.3 (150) 78.3 (552) 57.0 (402) 384.771 <0.001 [184223] Factors that affect immune response 19.3 (136) 77.7 (548) 58.4 (412) 392.926 <0.001 [184225] Available community resources 20.9 (147) 80.6 (568) 59.7 (421) 409.333