Perceptions of medical waste exposure prevention among medical waste handlers in Hadiya zone, Ethiopia: a mixed-methods study using the health belief model
- Open Access
- 01.12.2025
- Research
Abstract
Introduction
According to world health organization (WHO), wastes produced by the health-care providers are broadly categorized as general (non-hazardous) and hazardous waste [1, 2]. General waste constitutes about 85% of the total waste produced in the health care facilities (HCFs) and it is comparable to domestic waste. Medical waste is the waste produced during medical procedures such as diagnosis and treatment and includes things like syringes, needles, dressings, and plastics. It is infectious, hazardous, and poses serious health risks to patients and the public if not managed properly [3‐6]. According to the World Health Organization, every year, 16 billion injections are given globally, but not all needles and syringes are disposed of safely, which can lead to injury, infection, or even reuse [2]. More recently, 16 million unsafe injections or exposure to contaminated needles and syringes resulted in 4.5 million new HBV infections, 160,000 new HCV infections, and 160,000 new HIV infections annually [7]. Thus, improper management of medical waste poses a serious health hazard and can spread diseases like hepatitis B, and HIV [7‐9].
Medical waste handlers and healthcare workers are particularly susceptible to these diseases through the occupational exposure risk of needle injuries and blood-borne pathogens [8, 10, 11]. Preventing the spread of infection in healthcare settings means preventing exposure to medical waste. This can be done by consistently using personal protective equipment, practicing good hand hygiene, getting vaccinated for hepatitis B, and properly segregating waste in designated bins [12, 13]. Workers in charge of handling medical waste face exposure to hazardous materials and accidents due to manual handling and unfavorable conditions [14, 15]. This is due to poor handling practices, inadequate use of personal protective equipment (PPE), and improper waste segregation methods, which increase the risk of infection [16]. The risk of infection is increased in developing countries, including Ethiopia, where there is a lack of adequate resources, policies, and training [14]. A lack of awareness and access to personal protective equipment in low- and middle-income countries, which can contribute to the spread of diseases acquired through medical waste [17]. Studying preventive health behavior based on theory and models, such as the Health Belief Model (HBM), can help improve infection prevention efforts [4, 18]. In Ethiopia, there is a lack of attention to medical waste management (MWM), and healthcare staffs don’t have adequate knowledge about the hazards associated with handling medical waste [19]. Preventive actions, such as wearing personal protective equipment (PPE) and taking recommended measures, are important in reducing the risk of infection and injury. Understanding MWM and perceptions towards medical waste exposure (MWE) are crucial in achieving infection prevention [13].
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The risk of healthcare-associated infections (HCAIs) due to exposure to medical waste remains high in Ethiopia despite the availability of several infection prevention trainings and guidelines [12, 20, 21]. However, the reason for the continuous exposure to infectious waste in health facilities may be due to individual risk perception and a lack of preventive behavior. To address this, assessing individual perceptions to facilitate effective infection prevention in hospitals is important. This is an important area of study in health psychology, as interventions based on theory and models are more effective [17].
In order to understand preventive health behavior, HBM scientists carried out numerous research that considered a variety of viewpoints, including health motivation and the individual’s perception, which can be impacted by past experiences as predictors of what an individual will and will not do. Accordingly, the HBM addresses how a person perceives the threat of a health issue (susceptibility, severity), the benefits of avoiding the threat, and the elements that affect the decision to take action (barriers, cues to act, and self-efficacy). The reasoning and prediction in HBM are now used to explain and predict preventative health and illness behaviors and are applied to many studies of all types of health behaviors, based on the understanding that a person will take a health-related action (medical waste exposure prevention) if this waste handlers that a negative health condition [injury] can be avoided. If the waste handler believes that medical waste exposure prevention reduces the risk of developing diseases or injury, he/she will use waste exposure prevention method and thus prevents injury or diseases. HBM is employed in this study because it is a health education model that looks into the factors that influence people’s health behaviors, particularly preventive behaviors. Individuals will engage in preventative behaviors if they perceive risk and believe the behavior is beneficial. The model predicts that individuals will engage in recommended preventative activities when perceived benefits surpass perceived barriers to the behavior [4, 22]. The concept of self-efficacy is also part of the HBM. Medical waste handlers (MWHs) have weaker risk perception, higher vulnerability to medical waste, and low practice of medical waste management [4, 17, 22]. However, medical wastes handling has received less attention in practice, and existing research is inconclusive as well [11, 14, 17] and health research emanating from Africa is scarce, despite the continent’s share of 18% of the world population and 25% of the disease burden [23]. Therefore, the study aims to assess the likelihood of engaging in medical waste exposure prevention among medical waste handlers working at public hospitals in Hadiya Zone, Ethiopia, using the Health Belief Model (HBM) framework [4, 22]. This will provide evidence for developing interventions and identifying barriers, which will help hospitals, create infection-prevention strategies and strengthen their programs (Fig. 1).
Fig. 1
Conceptual framework of a health belief model to predict likelihood of engaging iri medical waste exposure prevention among medical waste handlers working in public hospitals, Hadiya Zone, Ethiopia, 2022
Materials and methods
Study area and period
We conducted this study in the central part of Ethiopia, in Hadiya Zone hospitals. The Hadiya zone is one of the zones in central Ethiopia. Its capital city is Hossana, and it is located 230 km Southwest of Addis Ababa, the capital city of Ethiopia. They have thirteen rural districts and eight administrative towns. There are three primary hospitals and one comprehensive specialized teaching hospital. The study was conducted from May 5 to June 5, 2022.
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Study design and populations, participants’ selection procedure
A facility-based cross-sectional survey was conducted by using quantitative and qualitative methods among 325 medical waste handlers. Since the medical waste handlers in the study area were 325, this survey included all the medical waste handlers for the quantitative study. And for the qualitative study, a total of 8 participants were participated in in-depth interviews, including 4 waste handlers’ coordinators who were not part of the quantitative study and 4 infection prevention officers chosen purposefully based on their experience, current role, and responsibility. Study participants were consecutively interviewed until the end.
Study variables
The intended outcome for this study was likelihood of preventing medical waste exposure (perceived benefits minus perceived barriers). The exposure variables were Socio-demographic and facility related factors, knowledge of medical waste prevention and its preventive measures, perceived susceptibility, perceived severity, self-efficacy, cues to actions, and past behaviors related to medical waste preventive behaviors. Socio-demographic and facility related factors such as age, educational status, marital status, income level, year of work experience, religion, ethnicity, training, availability of personal protective equipment. There are 14 knowledge questions with a response format of ‘yes’ or ‘no’. Knowledgeable are those respondents who have answered 50% and above of all the knowledge questions about medical waste prevention. Not knowledgeable were those respondents who could answer below 50% of all the knowledge questions about medical waste prevention. Perceived susceptibility is the respondent’s self-perception of vulnerability to medical waste related injury or diseases, measured by a summed score of related 7 belief items on a 5-point Likert scale. Perceived severity is the respondent’s held belief concerning the effects of medical waste related injury or diseases seriousness, measured by a summed score of related 6 belief items on a 5-point Likert scale. Perceived benefits of using preventive measures is a respondent’s belief about the effectiveness of the method as a strategy for medical waste related injury or diseases prevention, measured by a summed score of related 8 belief items on a 5-point Likert scale. Perceived barriers are respondents’ beliefs about the difficulty of using the given preventive action by a summed score of related 8 belief items on a 5-point Likert scale. Self-efficacy is the respondent’s confidence in using recommended preventive measures by himself/herself in any condition and elsewhere to prevent medical waste exposure, measured by a summed score of related 6 belief items on a 5-point Likert scale. Cues to actions are conditions that may facilitate them to perform preventive measures in the respondents’ surroundings, measured by a summed score of related 5 belief items on a 5-point Likert scale.
Operational and term definition
Medical waste exposure prevention behavior: undertook preventive actions that are considered good for improving infection prevention, such as using all PPEs, hand washing and sanitizing, taking vaccinations, and appropriate waste segregation with separated bins to prevent oneself from disease-causing microorganisms during working hours [17, 24]. Likelihood of performing medical waste exposure preventive behavior: The composite score of the weighted mean of the perceived benefit of applying preventive actions minus the weighted mean of the perceived barrier for taking preventive actions. High likelihood of performing medical waste exposure preventive behavior: medical waste handlers who scored above the mean for the composite score of weighted mean of perceived benefit of applying preventive actions minus weighted mean of perceived barrier for taking preventive actions. Low likelihood of performing medical waste exposure preventive behavior: medical waste handlers who scored below the mean for the composite score of weighted mean of perceived benefit of applying preventive actions minus weighted mean of perceived barrier for taking preventive actions. Medical waste handlers: a person engaged in medical waste collection, transportation, and disposal [1, 2, 17].
Perceived susceptibility: a medical waste handler who believes he/she is vulnerable to MW exposure/hazards and its consequences (HCAI, injury, etc.) [4, 22]. The individual response on a list of seven questions using Likert five-scale of point was computed and individuals were categorized in to high and low perceived susceptibility categories.
High Perceived susceptibility: medical waste handlers who scored above the mean for questions provided reflect stronger agreement that at the risk behaviors towards medical waste exposure and categorized into high perceived susceptibility and below mean were categorized as low. Perceived severity: How medical waste handler views the consequence MW exposures like injury, infecting with (HIV, HBV, tetanus) and air born infection(Covid-19, TB) [4, 22]. The individual response on a list of six questions using Likert five-scale of point was computed and individuals were categorized in to high and low perceived severity categories. High Perceived severity: medical waste handlers who scored above the mean for questions provided reflect stronger agreement that more awareness regarding the potential seriousness of infectious disease due to exposure of medical waste and categorized into high perceived severity and below mean were categorized as low. Perceived benefit: medical waste handler who believes the use PPE, hand washing and sanitizer an important to prevent waste exposure /its consequence (HAI, injury, etc.) [4, 22]. The individual response on a list of 8 questions using Likert five-scale was computed.
Perceived barriers: a medical waste handler who believes the availability, affordability and feasibility of PPE, hand washing and Sanitizes are to impede the prevention of medical waste exposure and is consequences [25]. The individual response on a list of 8 questions using Likert five-scale of point was computed. Self-efficacy: a medical waste handler who has able to use PPE, sanitizer, hand washing, vaccine and safe waste handling techniques without hindering of affordability, accessibility and knowledge gap [4, 25]. The individual response on a list of 6 questions using Likert five-scale of point was computed and individuals were categorized in to having high and low self-efficacy categories. High Self-efficacy: medical waste handlers who scored above the mean for questions provided reflect stronger agreement that individuals have confidences to prevent exposure without hindering of any barriers and categorized into high self-efficacy and below mean were categorized as low. Cues to action: a medical waste handler from where to gain additional information and knowledge the use of PPE, hand washing, sanitizer and safe waste handling techniques are an importance to prevent MW exposure and it consequence (HAI, injury) [4]. The individual response on a list of five questions using Likert five-scale of point was computed and individuals were categorized in to having high and low. High cues to action: medical waste handlers who scored above the mean for questions provided reflect stronger agreement that individuals have cues to action to protect him from infectious disease. Adequate knowledge: medical waste handlers who scored above the mean of the correct answers for questions prepared to assess knowledge of respondent on medical waste and its prevention. The mean score is determined after computing knowledge assessing questions [26].
Data collection procedure, quality management, and measurement
Data were collected using a pre-tested, interviewer-administered structured questionnaire through face-to-face interviews at the study area. The questionnaires were adapted after reviewing various literatures to assess the likelihood of engaging in preventive behavior (perceived benefit minus perceived barrier) [21‐28]. The questionnaire was first prepared in English and then translated into Amharic by independent translators and was thoroughly examined by experienced health education experts. Trained data collectors (environmental health and MPH professionals) conducted the process and supervised to monitor data quality. Closer supervision was undertaken during data collection. Before the real data collection, a pretest was done with 5% of medical waste handlers at Butajira Hospital outside the study area. Chronbach’s alpha coefficient was used to estimate the reliability of the questionnaire, which was greater than 0.7. Accordingly, the alpha of knowledge of MW α = 0.94, perceived susceptibility α = 0.81, perceived severity α = 0.87, perceived benefit α = 0.78, perceived barrier α = 0.83, perceived self-efficacy α = 0.73, and cue to action α = 0.71. The data were collected by a face-to-face interview conducted in private, which included socio-demographic characteristics, knowledge of medical waste management, which was measured through a set of yes-or-no questions, and risk perception (perceived susceptibility, severity, benefit, barriers, self-efficacy, and cues to action). Each belief statement has a five-point Likert scale optioning “strongly disagree,” “disagree,” “neutral,” “agree” or “strongly agree,” with 1 and 5 indicating the lowest and highest level of agreement, respectively. Before analysis, negatively worded questions were reversed. Those who scored above the mean on certain questions were categorized as having high.
In-depth interviews were conducted to gather information on factors that affect medical waste handlers’ exposure prevention practices, their choice to use personal protective equipment (PPE), and other factors that affect effective waste management techniques. A field guide was used with semi-structured, open-ended questions to initiate discussion, which was continued by probing. Each interview lasted 1 to 1.5 h and took place in a private setting. Information depth was determined through reaching ‘point of saturation. To maintain the trust worthiness and validity of the findings, the researchers developed rapport with participants. Credibility/conformability was maintained through participant checking during in-depth interview, and through feedback of findings at the end of the study from whom the information was obtained. Keeping a record of information about impressions was enhanced conformability. Dependability was maintained through capturing the range and depth of responses through reaching ‘saturation point’. Finally, participants were given the chance to review and provide feedback on their interviews.
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Data management and analysis
For quantitative data, the data was edited, coded, and cleaned to check for completeness and missing values through double entry. The data was entered into Epi Data version 4.6.0.2 and exported into SPSS version 25.0. Descriptive, bi-variable analyses were conducted, followed by multivariable logistic analysis to see the independent effects of predictor variables on the outcome, accounting for potential confounding variables with a 95% CI. Hosmer-Lemeshow goodness of fit was tested, and the model was fit (P-value = 0.53). Thus, no multicollinearity existed. For the qualitative study, after the interview, data was transcribed word for word from audio tape-recorded data and field notes. The authors read and re-read all the transcripts to obtain a full understanding. The transcribed verbatim messages were translated from Amharic to English language. Prior to categorizing into different themes, we conceptualized perception of the medical waste exposure in various ways owing to the preventive behavior. First, medical waste prevention is defined as an action taken by the medical waste handlers using personal protective equipment. Second, perception related to medical waste handling is defined as the perception towards medical waste related injuries and diseases prevention. Later, these concepts were analyzed in various themes following the constructs of HBM. Then, themes emerged out and data analysis was done accordingly by Atlas ti.7 software. Then, the qualitative data triangulated with the quantitative findings.
Results
Socio-demographic and facility-related factors
The study had 325 participants with a 98% response rate. Of these, 119 medical waste handlers were aged 18–29, and most (98.1%) were female. The majorities were protestant (87.1%) and had over 10 years of experience (Table 1).
Table 1
Socio-demographic and health facility related characteristics of medical waste handlers at public hospital, Hadiya zone, Ethiopia, 2022, N = 325
Variables | Category | Frequency (n) | Percentage (%) |
|---|---|---|---|
Age | 18–29 | 119 | 36.6 |
30–40 | 96 | 29.5 | |
40–50 | 72 | 22.1 | |
Greater than 50 years | 38 | 11.6 | |
Sex | Male | 6 | 1.8 |
Female | 319 | 98.1 | |
Marital status | Single | 105 | 32.3 |
Married | 186 | 57.2 | |
Divorced | 23 | 7.0 | |
Widowed | 11 | 3.3 | |
Religion | Orthodox | 27 | 8.3 |
Protestant | 283 | 87.0 | |
Catholic | 3 | 0.9 | |
Others | 12 | 3.6 | |
Ethnicity | Hadiya | 295 | 90.7 |
Kembata | 10 | 3.0 | |
Amhara | 13 | 4.0 | |
Garage | 5 | 1.5 | |
Others | 2 | 0.6 | |
Level of education | Grade 1–4 | 51 | 15.6 |
Grade 5–8 | 73 | 22.4 | |
Grade 9–10 | 90 | 27.6 | |
Grade 11–12 | 50 | 1.5 | |
Certificate and Diploma | 61 | 18.7 | |
Time spent at Work daily | Less than 8 h | 199 | 61.2 |
More than 8 h | 126 | 38.7 | |
Experience | Less than a year | 57 | 17.5 |
1–5 | 65 | 20.0 | |
6–10 | 66 | 20.3 | |
Above 10 years | 137 | 42.1 | |
Monthly salary | ≤ 1500 | 125 | 38.4 |
≥ 1500 | 200 | 61.5 | |
Training | Not trained | 140 | 43.1 |
Trained | 185 | 56.9 | |
Availability of PPE | No | 156 | 48.0 |
Yes | 169 | 52.0 |
Knowledge about medical waste management
The study shows the overall knowledge score of the respondents, 132(40.6%) of them had adequate knowledge and other 193 (59.4%) had inadequate knowledge (Fig. 2).
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Fig. 2
Knowledge categories of the study participants about medical waste exposure preventive behavior among waste handlers in public hospital of Hadiya Zone. Ethiopia, 2022
Likelihood of performing medical waste exposure preventive behavior
The likelihood of medical waste handlers engaging in preventive measures to avoid exposure to medical waste was determined by subtracting the perceived barriers from the perceived benefits. Accordingly, the likelihood of engaging in preventive behavior is 56.3% [AOR: 3.19, 95% CI: 2.73, 6.34]. However, 43.7% of the waste handlers were low likelihood of engaging in preventive behavior (Fig. 3).
Fig. 3
Likelihood of engaging in medical waste exposure preventive behavior among waste handlers in public hospital of Hadiya Zone, Ethiopia. 2022
Perception towards medical waste handling among medical waste handlers
Medical waste handlers were asked about their beliefs regarding perceived susceptibility, perceived severity, perceived benefit, perceived barrier, self-efficacy, and cue to action. Among this, 48.0% of them perceive themselves as highly susceptible to these risks, while. 57.9% of respondents perceived the severity of medical waste as high, 58.4% of the respondents perceived a high benefit of prevention methods, nearly half of the respondents (42.5% perceived high barriers to preventing medical waste exposure, and 56.3% were confident in their ability to prevent exposure to medical waste without any obstacles. On the other hand, the study found that 64.6% of respondents were reminded to avoid exposure to medical waste by seeing health professionals who advised them. 61.2% were reminded to use personal protective equipment (PPE) by their partners. 49.5% were encouraged by their fear of death, and 40.3% were reminded by posted information on health facilities (Table 2).
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Table 2
Summary scores for perception towards medical waste exposure among waste handlers in public hospital of Hadiya zone, Ethiopia, 2022
Constructs | Range | Mean | Standard deviation | |
|---|---|---|---|---|
Possible | Observed | |||
Perceived susceptibility | 7–35 | 7–35 | 22.87 | 6.57 |
Perceived severity | 6–30 | 6–30 | 22.12 | 5.82 |
Perceived benefit | 8–40 | 13–40 | 31.98 | 3.79 |
Perceived barrier | 8–40 | 11–36 | 22.51 | 6.70 |
Self-efficacy | 6–30 | 6–30 | 16.80 | 4.21 |
Cue to action | 5–25 | 5–25 | 17.75 | 2.90 |
Multivariable logistic regression analysis
The variables with a p-value less than 0.25 in bivariate analysis were added to the multivariable regression model to get independent predictors. Based on this, the likelihood of engaging in medical waste exposure prevention measures was 4.30 times higher for MWHs with experience above 10 years [AOR (95% CI) = 4.30 (1.33–13.86)]. And when compared with respondents who were not trained, those trained respondents were 5.18 times more likely to engage in preventive measures [AOR (95% CI) = 5.18 (2.46–10.91)]. Thus, the respondents who have adequate knowledge about MW have a 3.41 times greater probability of performing preventive behavior than those who have inadequate knowledge [AOR (95% CI) = 3.41 (1.58 7.32)]. Regarding perception, MWHs who perceived susceptibility were 3.51 times more likely to perform preventive behavior compared with those who perceived low susceptibility [AOR (95% CI) = 3.51 (1.63 7.56)]. Also, those who perceived severity were 6.75 times more likely to engage in prevention than those who had low perceived severity [AOR (95% CI) = 6.75(3.33–13.65)] (Table 3).
Table 3
Logistic regression analysis result for the associated factors on LMWEPB among MWHs of public hospitals in Hadiya zone, SNNPR, Ethiopia, 2022, N = 325
Variables | Likelihood of preventive behavior | COR (95% CI) | AOR(95% CI) | |||
|---|---|---|---|---|---|---|
Low n (%) | High n(%) | Total n(%) | ||||
Age | ||||||
18–29 | 69(21.2) | 50(15.3) | 69(21.2) | 1 | 1 | |
30–40 | 47(14.4) | 49(15.0) | 47(14.4) | 1.43[0.83–2.47] | 1.39[0.52–3.72] | |
41–50 | 38(11.7) | 34(10.4) | 38(11.7) | 1.23[0.68–2.22] | 0.51[0.16–1.57] | |
Above 50 | 29(8.9) | 9(2.7) | 29(8.9) | 0.42[0.18–0.98]*** | 0.71[0.23–2.18] | |
Sex | ||||||
Male | 5(1.5) | 1(0.3) | 6(1.8) | 1 | 1 | |
Female | 178(54.7) | 141(43.3) | 319(98.1) | 3.96[0.45–34.28]*** | 2.41[0.22–25.64] | |
Marital status | ||||||
Single | 65(20.0) | 40(12.3) | 105(32.3) | 1 | 1 | |
Married | 99(30.4) | 87(26.7) | 186(57.2) | 1.42[0.87–2.32] *** | 1.52[0.60–3.84] | |
Widowed | 15(4.6) | 8(2.4) | 23(7.0) | 0.86[0.33, 2.22] | 0.50[0.11–2.21] | |
Divorced | 4(1.2) | 7(2.1) | 11(3.3) | 2.84[0.78,10.33] *** | 0.98[0.14–6.87] | |
Level of education | ||||||
Grade 1–4 | 27(8.3) | 24(7.3) | 51(15.6) | 1 | 1 | |
Grade 5–8 | 37(11.3) | 36(11.0) | 73(22.4) | 0.91[0.44–1.86] | 1.51[0.35–6.51] | |
Grade 9–10 | 33(10.1) | 57(17.5) | 90 (27.6) | 0.51[0.25–1.03] ** | 1.43[0.39–5.15] | |
Grade 11–12 | 17(5.2) | 33(10.1) | 50(1.5) | 0.45[0.20–1.02] ** | 0.72[0.22–2.34] | |
Certificate and above | 28(8.6) | 33(10.1) | 61(18.7) | 0.75[0.35–1.58] | 1.83[0.52–6.44] | |
Time spent at Work daily | ||||||
≤ 8 h | 49(15.0) | 77(23.9) | 126(38.7) | 1 | 1 | |
≥ 8 h | 93(28.6) | 106(32.6) | 199(61.2) | 1.37[0.87, 2.17] *** | 1.10[0.56–2.15] | |
Experience | ||||||
< 1 year | 19(5.8) | 38(11.6) | 57(17.5) | 1 | 1 | |
1–5 years | 15(4.6) | 50(15.3) | 65(20.0) | 0 0.67[0.30–1.49] | 0.28[0.06–1.16] | |
5–10 years | 18(5.5) | 48(14.7) | 66(20.3) | 0.74 [0.34–1.64] | 0.86 [0.24–3.07] | |
>10 years | 90(2.7) | 47(14.4) | 37(42.1) | 4.08 [2.1–7.92] | 4.30[1.33–13.86]** | |
Training | ||||||
Not trained | 23(7.0) | 117(36.0) | 140(43.0) | 1 | 1 | |
Trained | 119(36.6) | 66(20.3) | 185(56.9) | 9.17[5.35–15.72] | 5.18[2.46–10.91]** | |
Perceived susceptibility | ||||||
Low | 44(13.5) | 126(38.7) | 170(52.0) | 1 | 1 | |
High | 98(30.1) | 57(17.5) | 155(48.0) | 4.92[3.06–7.90] | 3.51[1.63–7.56]** | |
Perceived severity | ||||||
Low | 34(10.4) | 103(31.6) | 137(42.1) | 1 | ||
High | 108(33.2) | 80(24.6) | 188(57.9) | 4.08[2.52–6.63] | 6.75[3.33–13.65]** | |
Knowledge | ||||||
Inadequate | 27(8.3) | 98(30.1) | 125(38.4) | 1 | 1 | |
Adequate | 115(35.3) | 85(26.1) | 200(61.6) | 4.91[2.94–8.17] | 3.41[1.58–7.32]** | |
Discussion
This study assessed medical waste exposure prevention among medical waste handlers in terms of the perception of individuals to threat acquiring, seriousness, and averting efficaciousness using the health belief model in Hadiya Zone, Ethiopia. According to the health belief model, individuals’ perceived susceptibility to and severity of a disease condition is a baseline to take the next step to avert this condition, which by far helps to develop self-confidence to stand for tackling this problem, which in turn helps individuals to go through the effective method, which adds value for his/her health (response efficacy), provided that people are already aware of a particular health threat since the model best works in situations where respondents have a higher level of awareness than motivational variables [4, 22].
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In this study, the overall likelihood of performing medical waste exposure prevention behavior was 56.3%., and work experience, taking training, having adequate knowledge, perceived susceptibility, and perceived severity of medical waste were independent predictors of the likelihood of taking part in medical waste exposure prevention behavior.
This study showed that the benefits of performing preventive actions that are considered good for improving IP, such as using all PPE, hand washing and sanitizing, taking vaccinations, and appropriate waste segregation to prevent oneself from disease-causing microorganisms during working hours, outweigh the possible barriers that hinder engagement in preventive measures. In line with the study conducted in Ethiopia [16]. Many previous studies confirm that perception of individual preventive behavior is one of the determining factors for engagement in good behavioral practices, which helps to take recommended health action [5, 29, 30]. This might be having a perception of self-susceptibility and severity as well as a good attitude of using the recommended responses, which has universal importance in averting medical waste exposure.
A supportive result from a qualitative study reported that “most of the time there is a shortage of PPE supply in our facility. But in these conditions, I take care of myself.” [MWH, age 28]. Also, another report revealed that “if there was not enough equipment, I did not even touch any waste.” [MWH, age 34] also says an Amharic proverb, “Feri le-inatu,” which means I want to live. Additionally, “I always put sanitizer in my pocket for the time of the protective equipment shortage.” [MWH, age 34] ” In agreement with this finding, the Elvis E. Tarekegn study reported that a person would take preventive action if they had a positive expectation of following the recommended action [31]. The possible reason for the higher significant acceptance of recommended responses among waste handlers might be related to the fear of the threat of immediate injury from the wastes seen immediately.
In the present study, the likelihood of engaging in medical waste exposure preventive behaviors increased by decreasing possible barriers, and high barriers can be obstacles and prevent the adoption of desirable health behaviors. Similarly, this is supported by a study conducted in Egypt [32] and at Alexandria University [33].
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Accordingly, this study showed that perceived susceptibility to medical waste increases the medical waste handler’s likelihood of taking part in medical waste exposure preventive behavior. In agreement with this, the study conducted in Debre-Berhan found that perceived susceptibility increases the utilization of personal protective equipment [34]. Tarekegn’s study showed that individuals were more likely to take preventive action if they believed that they had a chance of getting a disease [31]. It is also supported by a study conducted in Egypt [32]. In general, workers who perceive themselves as highly susceptible to MWE-related illness and injury are more likely to engage in preventive measures and apply good MWEPB. A depth interview with a 38-year-old female medical waste handlers indicated that “waste handling activities are more vulnerable to diseases induced by medical waste, and there is continuous exposure because of our job.” An environmental health expert and IPPS leader at a certain hospital also strengthens the idea, saying, “Since waste handling is directly related to waste, they are more susceptible to disease.” Also supported by a qualitative study conducted in India, they said that our chances of acquiring the disease were high [35]. This discrepancy might be due to study area differences and socio-cultural and socio-economic variation in the study area.
In this study, the perceived severity of medical waste showed a positive effect on the likelihood of performing preventive measures. Similarly, findings showed that perceived severity was a significant determinant of preventive health behaviors [5, 36]. Similarly, perceived severity increased personal protective equipment utilization [34]. Waste handlers’ beliefs about the seriousness of the infectious MW and the possible outcome of the disease were a good influencing factor in enhancing preventive measures. This is also supported by a qualitative study of female MWH who have worked in hospitals for more than five years. She said that nosocomial infections are more severe than any other because once you get the disease, there is no medication for it.
In this study, the year of experience had a positive effect on the likelihood of performing medical waste exposure prevention behavior. Thus, more experienced medical waste handlers were more likely to engage in medical waste exposure prevention behavior. A study conducted on the sharp injuries of medical waste handlers in eastern Ethiopia concluded that total service year had a significant effect on health care workers management and the probability of exposure decreased with an increase in work year [37].
It is obvious that health care waste handling is a dangerous activity that requires training in order to prevent exposure. In this study, the training status of the medical waste handlers was confirmed as one of the significant factors contributing to their likelihood of engaging in MWEPB. Thus, trained medical waste handlers have a greater likelihood of engaging in MWEPB. This is higher than a similar study done in Nepal, where the perceived risk of healthcare waste was higher among those who attended training than among those who didn’t attend the training [29]. The implementation of different initiatives by the ministry of health, like CASH and IPPS, in HFs may increase it. In line with this, the findings concluded that training HWs in implementing the MWM program is critical [38]. The training should aim at developing awareness of health and safety issues relating to MW and how these can affect them. This is supported by an in-depth interview: “I think formal training should be given to all employees to create a better understanding of prevention behavior [IPPS focal]. Also, another interview with a 34-year-old MWH reveals that “I perform preventive behavior occasionally, and I do not follow the instructions given to me carelessly.” Also, having adequate knowledge of MW made them more likely to perform preventive measures. This is similar to this finding in Addis Ababa [39], which concluded that safety practice with good knowledge was higher. But much higher than the other finding of a study conducted in Ethiopia, which shows that having good knowledge regarding IP makes people more likely to have good infection prevention practices [16]. This was supported by a qualitative study that stated, “I do not have enough awareness of medical waste and its exposure prevention.” [MWH, aged 34]. This shows adequate knowledge is a key factor in effective MW exposure prevention.
As strength, this study has advantages in that it used both quantitative and qualitative methods to support findings, and it utilized a health belief model that has been effective in predicting preventive behavior. However, a limitation of the study is that it was cross-sectional and therefore unable to determine whether the behavior or the predicting variables happened first. Another limitation, the health belief model, is entitled to understanding only an individual’s perception, and it is limited to addressing the social, environmental, and economic factors that are broadly affecting the system.
In conclusion, the likelihood of realizing the desired results in practice of preventive measures against medical waste exposure in low-income countries is unlikely to occur unless there is a strong focus on creating awareness and building health-seeking behavior. Most importantly, work experience, training, and knowledge, perceived susceptibility, and severity also have positive effects on adopting preventive behaviors and were found to predict the likelihood of taking preventive measures. However, there are still areas for improvement regarding access to tools and addressing knowledge and perception gaps. The findings urged to recommend for zonal health department, hospitals, and infection prevention and patient safety officer separately. The zonal health department should develop strategies on current identified predictors and give training to provide adequate personal protective equipment in the hospitals. Hospitals should train waste handlers on medical waste handling and ensure the regular provision and use of personal protective devices. Finally, infection prevention and patient safety officers should do regular follow-up, supervise, and give on-the-job direction on proper waste handling methods, and they should also provide special emphasis to susceptibility and severity of infectious disease due to exposure to medical waste and needle stick injuries. They should also focus on increasing perceived benefits of preventive measures and reducing barriers to preventive measures.
Acknowledgements
The authors want to give their sincere gratitude for their willingness to participate in this study to data collectors, supervisors, hospital managers, and participants.
Declarations
Ethics approval and consent to participate
This study was approved and conducted per the principles of the Helsinki Declaration. Ethical clearance was obtained from the Research Ethics Review and Approval Committee (REAC) of Wachemo University with reference number Ref.No.WCU/SGS/657/2014 and 29/4/2022 with unique student registration number WCU1300064. To acquire permission, a formal letter from the college of medicine and health sciences was obtained and delivered to hospital. After thoroughly outlining the study’s objectives and benefits, each participant provided informed written consent. The study participants were informed that they might withdraw from the study at any moment. Participants were also told that their responses would be kept private and that their names would not be disclosed. The rights of all participants to self-determination and autonomy were protected. The participants’ information was gathered in private settings by trained, neutral interviewers. The participants were assured that there was no loss of advantages from the study and that ceasing to answer the question did not harm them and resulted in no penalties at all.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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