COVID-19 Pandemic: Assessment of Behavior and Attitudes in Medical Waste Management Among Healthcare Workers in Kuwait

The COVID-19 pandemic has been affecting world economies, business revenues, and the livelihood of many individuals, and has also resulted in accumulated medical waste. Countries, governments, and health workers are striving to contain this virus by applying different strategies and protocols. This research investigates and identifies the significant determinants that influence the acceptance and Adoption of non-hazardous medical waste recycling behaviour in Kuwait. This article questions whether healthcare workers in Kuwait are actually behaving differently regarding non-hazardous medical waste recycling during the pandemic as opposed to previously. The study uses a deductive research approach involving a quantitative methodology by applying the theory of planned behaviour as a framework. From an overall perspective, individuals have positive intentions and behaviours toward recycling. However, COVID-19 and the fear of spreading the virus had a positive impact on the healthcare workers’ recycling behaviour in public hospitals in Kuwait.


INTRODUCTION
Countries produce a significant amount of medical waste each year despite significant progress in raising awareness in the field of medical waste management. The COVID-19 pandemic, in general, has generated massive amounts of medical waste among hospitals (Kalantary et al., 2021). This is exacerbated by our daily consumption of healthcare-related items like face masks and single-use gloves (Richter et al., 2021;Zhao et al., 2021). This, in turn, has resulted in an increase in medical cases were required to wear additional PPE like isolation gowns, gloves, masks, face shields or goggles, shoe covers, and caps. These PPE were discarded and replaced after every interaction with a confirmed case (Directorate of Infection Control & Sterilization, 2020). Countries were guided by the World Health Organization (WHO), the European Centre for Disease Prevention and Control, the U.S. Centers for Disease Control and Prevention (CDC), and other national guidelines, resulting in the accumulation of medical waste (Anthru, 2020;Gasana & Shehab, 2020). Thus, resulting in the accumulating medical waste.
It is important to understand the underlying behaviors of medical staff before determining whether a recycling framework could be developed to recycle nonhazardous medical waste in public hospitals of Kuwait. Furthermore, the medical sector throughout the pandemic was dynamic and complex, causing many medical institutions to adopt differing protocols.

Theoretical Framework
Many factors influence recycling behavior among healthcare workers. Due to the significance of recycling as a waste management approach, the current research employs the theory of planned behavior (TPB) to identify, explore, and understand factors that influence recycling behavior in healthcare workers. Actual behavior is determined by an individual's intention to engage in a behavior and adopt the view that the behavior is in their control. TPB is based on four variables; however, the theory allows for additional variables if they prove to have a significant influence in the explanation of a behavior (Ajzen, 2011;Davis & Morgan, 2008).
According to TPB, the direct facilitator of any behavior is the intention to perform such behavior in the presence of appropriate conditions. This suggests that an individual's recycling behavior is determined by their intention to recycle (Davies et al., 2002). Furthermore, intentions have a direct positive effect on recycling behavior. Moreover, the significance of behavioral intentions are key motivators for actual behavior, which subsequently asserts the importance of studying intention to recycle (Albarracin et al., 2001).
On the other hand, an individual's attitude is the extent to which they have a favorable or unfavorable assessment of said behavior (Prapavessis et al., 2015). An individual's attitude can predict and influence the intention to behave with specific attitudes toward environmental conservation behaviors, which are more likely to have an influential predictive power toward such behavior. Subjective norms are beliefs that concern the approval or disapproval of the behavior among many people. This is an individual's beliefs regarding whether peers or essential people think they should perform a specific behavior (Balderjahn, 1988). Perceived behavioral control is an individual's perception about the difficulty or ease of engaging in an interesting behavior. Significantly, it varies between circumstances and contexts, resulting in people who possess different perceptions about behavioral control based on a situation.
Studies found that two additional variables -an individual's level of knowledge and experience in said behavior -can influence recycling behavior (Davies et al., 2002). Numerous studies indicate the importance of experience and its direct effect on behavior (Tonglet et al., 2004). Many meta-analysis studies explored additional variables in the TPB model, finding they are significant in the study of recycling behavior. The current study looks at the behavior of healthcare workers because the hospital setting can affect employee behavior (Oke, 2015). According to the literature, the organizational factor is a main influencer on workers' behavior. This covers the organization's infrastructure, management support, training, and rules and regulations (Blankenberg & Alhusen, 2018;Tudor et al., 2007).
The general hypothesis of this research is that nonhazardous medical recycling behavior as an organizational activity originated in developed countries. As such, the implementation models are taken as a benchmark. Implementation barriers and the influential determinants for adopting nonhazardous medical recycling behavior in different regions and societies may or may not be the same as those in developed countries (with varying degrees of intensity or importance). Hence, the available implementation models may not be followed in all stages and steps when applied to different countries and societies. Accordingly, the implementation barriers and influential determinants may differ between cases.

RESEARCH METHODOLOGy
A quantitative method using a questionnaire-based survey was conducted to examine and validate the conceptual model. Hence, the ideal approach to data analysis is the application of statistical analysis to determine the relationship between research variables. Ethical considerations were reviewed when handling the integrity of the data and to respect the anonymity of the participants. The targeted population included healthcare workers in government hospitals of Kuwait. The study's sampling of respondents was undertaken using a random sampling strategy.

Dependent Variables
The dependent variable is what the researcher can observe or measure. The variable depends on the stability of other factors, especially the independent variable, which can cause a change in the dependent variable when it varies (Allen, 2017). A dependent variable, as the phrase suggests, is liable to change when other factors change.
Behavior is the dependent variable in this research. Therefore, healthcare workers' behavior toward recycling could be partly or fully dependent on attitude, subjective norms, perceived behavioral control, organizational factors, or emerging healthcare issues like COVID-19.

Independent Variables
An independent variable is tested by the researcher and affects dependent variables. Attitude is one independent variable that can influence the intention of a behavior (Teo & Lee, 2010). In TPB, the term "attitude" refers to the extent to which a person has a favorable or unfavorable evaluation of the behavior of interest. A person's attitude can influence how they relate to performing the recycling behavior as an environmental conservation practice (Smelser & Baltes, 2001). Hence, a person with a positive attitude toward environmental protection has a higher likelihood to show intentions to perform recycling behaviors than a person with a negative attitude toward environmental protection. Therefore, behavior to recycle could be largely or partly linked with a person's attitude toward environmental protection.
Subjective norm is the second independent variable that can influence change in intention to recycle. In TPB, subjective norms are beliefs concerning the approval or disapproval of the behavior among many people. It explains how behaviors are considered (i.e., socially or morally appropriate) in society (Manning, 2009). For instance, healthcare workers would perform recycling behavior because the profession considers it to be morally and professionally appropriate.
Perceived behavioral control is the third independent variable that can influence recycling behavior. In TPB, perceived behavioral control refers to difficulties in enacting a behavior (Kraft et al., 2005). The degree of difficulty to recycle in healthcare organizations could influence the intention of healthcare officials to recycle waste. Hence, whether a healthcare worker will show a positive intention to recycle largely or partly depends on perceived levels of difficulty in the process of the recycling of waste.
Experience and level of knowledge are the fourth and fifth independent variables in this framework (Fredricks & Dossett, 1983). Experience can determine how a health worker interacts or perceives the act of recycling in a hospital setting. According to TPB, experience implies the level of interaction with recycling practices (Xu et al., 2017). Experience with recycling could influence a health worker's recycling behavior; individuals with more waste recycling experience could be more competent and confident in recycling. In TPB, level of knowledge refers to the degree of skills necessary in performing a behavior. Level of knowledge could also help determine how a health worker would relate to the practice. A health worker with greater knowledge of recycling is more likely to engage in the practice than an inexperienced worker (Alkhaffaf & Makahleh, 2018).
The sixth independent variable, the organization, encompasses the cultural or structural factors that govern, influence, or challenge recycling behaviors or acts of an individual or organization (Taylor et al., 2006). The organizational factor includes infrastructure, management support, and training to regulate behaviors within an organization (Sola & Mota, 2020). Infrastructural availability may impact healthcare professionals' intent to recycle (Timlett & Williams, 2011). For instance, an inadequate infrastructure may discourage the proper disposal and recycling of waste by limiting the institutions' or officials' ability to recycle. Management support and training like workshops, informal education on environmental protection and safety norms, and leadership training on pollution can also influence healthcare workers' intent to recycle. Organizations could establish rules and regulations to influence waste recycling management in hospitals. For instance, strict rules on the disposal, sterilization, and treatment of recyclable waste could incentivize healthcare workers or institutions to engage in nonhazardous waste recycling (Nie et al., 2014).

Moderating Variables
Moderating variables differ from dependent and independent variables. According to Allen (2017, p. 3), the "moderating variable refers to a variable that can strengthen, diminish, negate, or otherwise alter the association between independent and dependent variables." Sometimes known as moderators, these variables act as a link to provide more information about the relationship between dependent and independent variables.
In this study, COVID-19 is the variable expected to moderate the relationship between independent and dependent variables. Pandemics are critical in promoting practices to better healthcare systems. Some hospitals could have been recycling because moderating factors like COVID-19 did not exist. Conversely, some organizations could have stopped recycling because COVID-19, as a moderating factor, impacted how people perceived recycling (Zambrano-Monserrate et al., 2020). Hence, the pandemic could have moderated the independent variables (i.e., attitudes, perceived behavioral control, subjective norm, and organizational factors) and dependent variables regarding engaging in the recycling of waste (Richter et al., 2021;Zhao et al., 2021).

Intervening Variables
Intervening variables differ from dependent, independent, and moderating variables. An intervening variable is a hypothetical variable used by researchers to explain the causal link among other variables (Allen, 2017). The value of these variables is not experimentally quantifiable; their value to research cannot be empirically validated or experimentally confirmed (Allen, 2017). Hence, an intervening variable has no experimental validation. Its value in research is determined by a manipulation or by combining a set of independent variables.
The term "intention" in the hypothesis forms the mediating or intervening variable of the current study. Intention in TPB refers to inspirational factors that could influence the performance of a particular behavior. Intention is an intervening variable because it does not have empirical validation in this study. For instance, when a respondent states that they intend to recycle more often, the intention remains abstract unless other independent variables influence that respondent's behavior toward recycling. Hence, intention is the intervening variable whose value remains dependent on manipulation or a combination of other independent variables.

Hypothesis
The main assumptions involve suppositions or hypothetical facts about the possible relationship between identified variables (Clark &Ivankova, 2015). These assumptions become valid or invalid depending on participant response and a data analysis on the relationship between variables (Clark & Ivankova, 2015). TPB was useful in establishing the hypothesis relative to the concept of recycling in Kuwait's public hospitals. Therefore, assumptions about the relationship between variables draw references from the theory and the current research pertinent to the theory.

H1:
There is a relationship between "attitude" and the "intention of healthcare workers to perform the recycling behavior" in public hospitals in Kuwait. H2: There is a relationship between "subjective norms" and the "intention of healthcare workers to perform the recycling behavior" in public hospitals in Kuwait. H3: There is a relationship between "perceived behavioral control" and the "intention of healthcare workers to perform the recycling behavior" in public hospitals in Kuwait. H4: There is a relationship between "level of knowledge" and the "intention of healthcare workers to perform the recycling behavior" in public hospitals in Kuwait. H5: There is a relationship between "organizational factors" and the "intention of healthcare workers to perform the recycling behavior" in public hospitals in Kuwait. H6: There is a relationship between "intention" and "healthcare workers' recycling behavior" in public hospitals in Kuwait. H7: There is a relationship between the "COVID-19 pandemic" and "healthcare workers' recycling behavior" in public hospitals in Kuwait.

Target Population and Sampling Methods
Target population refers to the overall number of participants pursued in the research environment. The public sector of Kuwait, the area of the current study, is the chosen research destination because the country lacks nonhazardous medical waste recycling initiatives. Therefore, few studies have explored this phenomenon. Dramatic changes emerged as COVID-19 threatened the country's healthcare system. Kuwait became an area of interest when investigating the nonhazardous medical waste recycling behavior of healthcare workers in public hospitals. At least six hospitals were selected for this study based on their rankings. Data from the WHO (2019) provided insight into the country's healthcare system, revealing that Kuwait's healthcare was split into six regions: (1) Hawali; (2) Ahmadi; (3) Kuwait City; (4) Al-Sabah; (5) Al-Farwania; and (6) Al-Jahra.
There were three reasons for researching these hospitals. First, the top hospitals in each of the healthcare regions work on a decentralized administration system. Second, the decentralized nature of these hospitals makes them independently liable in matters concerning financial planning and administrative affairs (WHO, 2019). Third, these hospitals are autonomous, making important decisions on the management of health delivery and training of healthcare officials (WHO, 2019).
The study aimed to collect data and establish whether nonhazardous medical recycling depends on personal behavior or a healthcare system's management approach. The study explored whether the problem could be moderated by the size of the hospital's infrastructure and financial strength. The study's empirical approach collected data by identifying and sampling appropriate respondents. After identifying the hospitals for the research, the study selected its sample of participants.
A random sampling strategy was used to sample respondents. The study assumed that healthcare professionals have the moral and professional knowledge to uphold the recycling of nonhazardous medical materials. Random sampling was used to select respondents because it provides an unbiased representation of a targeted population (Ponto, 2015). Besides, each sample of the targeted population would have an equal probability of being chosen to partake in the study. The approach increases generalizability; every member of the research is chosen by chance rather than a selective bias. This signifies that a random sampling technique would be an appropriate participant selection approach because it provides an unbiased representation of the targeted population and minimizes the selection and response biases.

Data Collection Instrument and Source
The study collected data from 200 randomly selected participants. It tested how individual attitudes, subjective norms, perceived behavioral control, and organizational factors influence individuals to perform recycling behaviors. The study adopted a survey approach to collect data from healthcare professionals in five hospitals. Survey research was identified to collect data from sampled respondents who answer questions that are structured in a specific way (Ponto, 2015). In quantitative research, the most common and ideal data collection instruments are questionnaires in a closed-ended format (Bolderston, 2012). Surveys can involve the use of quantitative data collection strategies when closedended questions seek to collect responses from the sampled population.
The survey approach use closed-ended questions. According to Ponto (2015), a quantitative survey approach collects data from respondents using questionnaires with numerical rating scales. According to Creswell and Hirose (2019, p. 2): Survey researchers collect quantitative, numbered data using questionnaires (e.g., mailed questionnaires) or interviews (e.g., one-on-one interviews) and statistically analyse the data to describe trends about responses to questions and to test research questions or hypotheses.
Three reasons justify the study's choice to use a survey as its data collection approach. First, surveys help researchers collect uncomplicated data because the responses are uniform and linked to the subject (Creswell J. W., 2014). Second, a survey's predesigned responses help the researcher collect data that is valid and consistent with the research problem. Third, responses in designed questionnaires are theoretical, helping the researcher validate opinions or suggestions based on the proof gathered from the respondents.
A framework would help respondents give valid, reliable, and consistent answers as intended by the questions. Qualitative research experts Creswell and Hirose (2019, p. 3) advise that "conducting cognitive interviews of the items to ascertain that the survey participant interprets the meaning of questions as intended is important." Hence, the survey used a five-point Likert scale to help the researcher determine how respondents perceive issues pertinent to the link between the four variables and the intent of healthcare workers to demonstrate recycling behaviors (Creswell & Creswell, 2017). The scale's five responses (strongly agree, agree, undecided, disagree, and strongly disagree) were essential in enhancing the reliability of the data collection. The "strongly agree" option implies that the respondent is giving a strong approval of the statement. "Strongly disagree" implies disapproval and "undecided" implies that the respondent is unsure about the statement.

RESULTS
A statistical analysis was performed using SPSS version 23 and SmartPLS 3 during the first step. Data were uploaded on SPSS version 23 to perform a preliminary data analysis (data cleaning and descriptive statistics). Additionally, the proposed hypotheses were tested using the PLS-SEM technique. This included the SmartPLS 3 software package, using partial least square structural equation modelling (PLS-SEM). The convergent and discriminant validity of each indicator under the construct were also tested. To examine the convergent validity, the study tested for the unidimensionality, loadings, communalities, and cross loadings of each indicator. Furthermore, Fornell-Larcker Criterion and heterotrait-monotrait (HTMT) ratio analysis were used to examine discriminant validity (Hair et al., 2017). Finally, PLS-SEM was utilized to validate the hypotheses. Table 1 demonstrates the summary statistics of the participants under the demographic variables. The data were summarized in the form of frequency and percentages. Most of the participants in the study were from age group 29 to 34 (n = 129, 33%) and 35 to 40 (n = 93, 24%). There were more female (n = 305, 78%) than male (n = 84, 22%) participants. Most participants had a bachelor's degree (n = 192, 49%) and 6 to 10 years (n = 118, 30%) of work experience. Around 19% (n = 75) of the participants worked at Al-Amiri Hospital; around 41% (n = 159) of the participants worked at other governmental hospitals.
The job distribution of the participants is illustrated in Figure 1. Most participants were physicians (21%). Around 15% of the participants worked in radiology, 13% worked as a pharmacist, and 9% worked in a medical laboratory. A small number of participants worked in nonmedical departments like customer service, accounting, human resources, finance, and occupational therapy.

Convergent Validity
The measurement model's assessment was done by inspecting the unidimensionality, loadings, communalities, and cross loadings of the indicator variables. Unidimensionality is defined as the property of the latent construct to be positively correlated with each indicator. In other words, if the latent variable increases in value, then each indicator should also increase (Sanchez, 2013). Cronbach's alpha (α) and Dillon-Goldstein's rho (ρ) were used to assess unidimensionality. For the unidimensionality of indicators, the threshold value of Cronbach's alpha (α) and Dillon-Goldstein's rho (ρ) indicators is 0.7.
In the present study, the latent variables SNO, PBC, and CWP did not exhibit unidimensionality. In addition, to reveal the indicators with weak loadings for the latent variables, the factor loadings and communalities were examined for reflective indicators. The variability in each indicator should explain at least 50% of its latent variable construct (|loading| 3 .707; communality 3 .50). Otherwise, it is identified as a weak loading (Henseler et al., 2009). PBC3 and CWP3 reflective indicators had weak loadings. Therefore, before proceeding, these indicators were evaluated to determine whether they belonged in the model's construct.
To verify that each latent variable had a strong association with its reflective indicators, the average variance extracted (AVE) for each construct was calculated (Table 2). To have a strong relationship, each latent variable should have an AVE 3 .50, which suggests that 50% or more of the variance for the indicators is explained by its latent variable (Chin, 2010;Henseler, 2015;Sanchez, 2013). From Table 2, it can be observed that no latent variables had AVE £ 50, which indicated that each latent variable accounted for a significant portion of the indicator's variance.
The crossloadings were examined for the reflective indicators to check the validity of the model. The situation of a crossloading occurs when an indicator has a higher absolute loading on a different latent variable than the one to which it is assigned . The analysis shows there were no crossloadings for reflective indicators in the model (see Table 3). This suggests that the specified latent variable structure is appropriate for the data.

Discriminant Validity
As shown in Table 4, the square roots of the AVE were higher than the correlations values in the row and the column. This indicated adequate discriminant validity. In summary, the measurement model demonstrated adequate convergent validity and discriminant validity.
In addition, Table 5 shows the results of the HTMT index for composites type that allows the measurement of the discriminant validity between indicators of the same composite and between indicators of different composites. To fulfil discriminant validity, the HTMT ratio values must be less than 0.85 (Henseler, 2015). Table 6 shows the results of the PLS hypothesis testing. The results indicated that ATT (B = 0.56, t = 13.57, p = 0.000) and LOK (B = 0.16, t = 3.51, p = 0.001) significantly predicted INT. Further, the effect of CWP (B = 0.13, t = 3.04, p = 0.003) and INT (B = 0.55, t = 11.91, p = 0.000) on BEH was significant. Additionally, the moderating effect of CWP on BEH (B = 0.19, t = 2.94, p = 0.004) was significant. However, the effect of MST, OIF, PBC, PEX, RRG, and SNO on NT was not as statistically significant as p > 0.05, which indicated that any changes in MST, OIF, PBC, PEX, RRG, and SNO did not influence INT. The node diagram for the PLS-PM model with loadings is shown in Figure 2. Table 7 demonstrates the results of the mediation analysis, in which a variable may influence the output variable by using a mediating variable. The analysis shows that the mediation effect of INT is significant for LOK and BEH (B = 0.09, t = 3.59, p = 0.001). Besides this, the effect of mediator INT was significant for ATT and BEH (B = 0.31, t = 7.99, p = 0.000). However, INT did not work as a mediator between PEX and BEH, MST and BEH, PBC and BEH, SNO and BEH, OIF and BEH, RRG and BEH, as p > 0.05. Table 8 shows the results of the total effect and moderation effect from CWP. The finding demonstrates that the direct effect of ATT (B = 0.31, t = 7.99, p = 0.000), CWP (B = 0.13, t = 3.04, p = 0.003), INT (B = 0.55, t = 11.91, p = 0.000), and LOK (B = 0.09, t = 3.59, p = 0.001) on BEH was significant. Additionally, the direct effect of ATT (B = 0.56, t = 13.57, p = 0.000) and LOK (B = 0.16, t = 3.51, p = 0.001) on INT was significant. The finding also demonstrates that the moderating effect of CWP on BEH (B = 0.19, t = 2.94, p = 0.004) was significant. On the other hand, the direct effect of MST, OIF, PBC, PEX, RRG, and SNO on BEH and INT was not significant (p > 0.05).
The slope plot (see Figure 3) indicates the relationship between INT and BEH that is moderated by CWP. The three lines represent the relationship between INT (x-axis) and BEH (y-axis). The mid-line corresponds to the mean level of the moderator variable CWP, whereas the line above the mid-line corresponds to the higher level and the line below the mid-line corresponds to the lower level of the moderator variable CWP. All three lines show a positive trend, which indicates that the lower the value of INT, the lower the value of BEH. The figure shows that CWP positively influences the relationship between INT and BEH.

DISCUSSION
To better understand the issue and its content in the public healthcare system of Kuwait, a primary interview was conducted with the engineer who managed the medical waste department in the environment public authority of Kuwait. The engineer stated that the waste produced by all hospitals is discarded by incineration. Practical segregation for discarded items is not taking place at the primary location; therefore, all waste is deemed hazardous (Almasoud, 2020). Some believe that hospitals in Kuwait separate and dispose of hazardous waste through incineration processes at remote sites. However, most individuals associated with hospital waste management are unable to identify the hazardous nature of different waste products. As a result, some domestic waste (e.g., cardboard, paper, plastic, metals, and glass) is disposed of as hazardous waste by incineration (without evaluating for the recycling process). Figure 4 demonstrates the increasing amount of waste     generated and processed each year through the medical incinerator in Kuwait (Environment Public Authority Kuwait, 2020). Alhumoud and Alhumoud (2007) showed that 71.4% of the waste from public hospitals in Kuwait were domestic, 27.8% were hazardous, and 0.76% were sharps. Similarly, the second edition of the Safe Management of Wastes Guidelines for Health-Care Activities (WHO, 2014) confirmed that 75% and 90% of the waste produced by healthcare facilities are nonhazardous wastes that are recyclable.
Incineration is the most recommended process for the disposal of hazardous waste. However, it could cause environmental pollution if domestic and recyclable wastes are disposed of in the same manner. As shown in Figure 5, Kuwait has the highest total healthcare waste generation compared to the other countries (WHO, 2014). Regarding total healthcare waste, infectious waste mirrors the value of other countries.
In the context of this research, having a positive attitude toward recycling can result in positive intentions and behavior toward recycling. The findings demonstrate consensus with the literature, noting a direct relationship of attitude on intention and an indirect relationship to behavior through intention. Subjective norm is also a part of TPB as the influence of others can lead to intention and behavior (Zhang et al., 2015). Individuals tend to solicit others' approval for their actions. The findings of this research agree with the literature on the role of the subjective norm in intention. However, there was no support for subjective norm's impact on behavior with intention as a mediator.
Another factor in TPB is the perceived behavioral control, in which individuals measure the difficulty or ease of carrying out an activity (Montaño & Kasprzyk, 2008). In this context, if individuals find it easy to carry out recycling practices in the workplace, they will be motivated and have a stronger intent to practice recycling. The findings of this research did not indicate perceived behavioral control to be significant; therefore, it did not demonstrate consensus with the literature regarding its importance in recycling behavior.
Moreover, experience of recycling can lead to an individual's recycling intention (Tonglet et al., 2004). The findings of this research agree with the literature regarding the direct impact of experience on intention. However, an indirect impact via intention on behavior was not established. The literature also pointed out that the level of knowledge of an individual will have a stronger impact on intention and behavior (Davies et al., 2002). The findings of this research support the literature findings regarding the effect of level of knowledge on intention. However, the level of knowledge did not affect behavior with intention as a mediator.
The present study also examined the effect of organizational factors like infrastructure, management support and training, and rules and regulations (Young et al., 2015). The findings of this research did not indicate the significance of any of the three organizational factors. Therefore, the findings of this research do not agree with the literature.
According to the literature, the use of disposables in healthcare organizations has increased due to COVID-19 (Zhao et al., 2021). This is due to the increased use of PPE, masks, gloves, gowns, and face shields. The disposal of these items must be carefully carried out to reduce the spread of the virus. Organizations like the WHO and CDC have set standards for disposing of and reusing these items (Gasana & Shehab, 2020). Healthcare organizations are taking extra care in the disposal and recycling of waste. In this research, the COVID-19 pandemic is studied as a mediator between intention and behavior. The findings support the literature regarding the need to improve recycling practices during the COVID-19 pandemic.

CONCLUSION
This research was designed to study the determinants that significantly influence recycling behaviors among healthcare workers in government hospitals of Kuwait. It aims to better understand the recycling behavior of medical staff in public hospitals by exploring their motivations, discouragements, and effects on behavior.
The study found that most medical workers have a positive predisposition toward recycling. There was a positive relationship between most of the individual variables (attitude and level of knowledge) and the intention of healthcare workers to perform the recycling behavior. The variables did not have a positive relationship on the intention of healthcare workers to perform the recycling behavior. Regarding organizational factors, the study found no positive relationship between the variables and the intention of healthcare workers to perform the recycling behavior. It found that intention positively mediates the relationship between attitude and healthcare workers' recycling behavior. However, it does not positively mediate the relationship between the other individual variables and organizational factors. Lastly, the study found that the COVID-19 variable positively moderates the relationship between healthcare workers' recycling intention and behavior in public hospitals in Kuwait.
Medical waste recycling is, without a doubt, a frequent and crucial challenge faced by all countries during the COVID-19 outbreak. The pandemic prompted international concern and a rise in medical waste production. Disposal continues to be essential in limiting the spread of the virus. This research examined the influence of the pandemic on the intention and willingness of hospital staff to recycle medical waste.
Emergency medical waste management processes should be developed at the national and regional levels to strengthen the emergency medical waste recycling system. A medical waste management culture should also be fostered and communicated, as the findings revealed a favorable association between knowledge level and intention to recycle medical waste.