The steps of the MEREC method are as follows:

Step 1 (Constructing the decision matrix). A decision matrix is created in this step, which shows the score of each alternative with respect to each criterion.

Step 2 (Normalizing the decision matrix). Linear normalization is applied in this method to make the elements of the decision matrix dimensionless.

Step 3 (Calculating the overall performance of each alternative). In this step, a logarithmic measurement with equal criterion weights is applied to obtain the overall performance of the alternatives. The following equation is used for this calculation:

Step 4 (One-by-one elimination of criteria). In this step, the performance of the alternatives is calculated by removing each criterion individually. At this stage, the logarithmic criterion similar to the previous step is used. The difference between this step and the previous one is that the performance of the alternatives is calculated separately based on the elimination of each criterion. Therefore, we obtain a set of performance values associated with the m criteria. The following relation is used to perform the calculations in this step:

Step 5 (Calculation of the sum of absolute deviations). In this step, the effect of removing criterion j is calculated based on the values obtained from Step 3 and Step 4. Let Ej denote the effect of removing criterion j. Using the following formula, we can calculate the values of Ej.

Ej = ∑|Si − Sij −|. (3)

Step 6 (Calculation of the final weights). In this step, the final weights of the criteria are determined. The following formula is used to calculate the weights:

Ej

Wj = . (4)

∑j Ej

The VIKOR method is based on compromise programming in MCDM. It is used to evaluate problems involving incommensurable and conflicting criteria. In situations where the decision-maker is not able to identify and clearly express the preferences or priorities of a problem at the initial stage of its formulation and design, this method can be employed as an effective decision-making tool.

Step 1 (Determination of the positive ideal and negative anti-ideal solutions). In this step, the positive and negative ideal solutions must be identified. For benefit (positive) criteria, the positive ideal is equal to the maximum value in the criterion column, and the negative ideal is the minimum value in that column. For cost (negative) criteria, the opposite applies. Benefit criteria are those whose increase leads to greater utility, while cost criteria are those whose decrease leads to greater utility.

Step 2 (Calculation of the utility measure (s) and regret measure for each criterion). The utility measure S represents the relative distance of alternative i from the ideal solution, while the regret measure R represents the maximum dissatisfaction of alternative i due to its distance from the ideal solution. These values are obtained using the following relations.

Step 3 (Calculation of the VIKOR index (Q) for each alternative). The VIKOR index for each alternative is calculated using the Eq. (7).

where,

Step 4 (Ranking the alternatives based on S, Q, and R). In the final step of the VIKOR technique, the alternatives are ranked in three groups according to the values of Q, R, and S, from the smallest to the largest. The best alternative is the one that achieves the top rank in all three measures. Otherwise, the preferred alternative is the one with the smallest Q value.

The criteria of this study, based on previous research, are as follows:

I. Permeability of materials into the glove (C1): to prevent the transmission of blood-borne infections to laboratory personnel, the use of appropriate gloves is essential.

II. Resistance to chemical substances (C2): laboratory personnel are exposed to chemicals and disinfectants; therefore, the selected glove should not degrade rapidly and should not cause damage to the skin of the staff.

III. Resistance to needle puncture (C3): given that blood sampling is performed using sharp needles, a suitable glove should have high resistance to puncture by needles.

IV. Tactile sensitivity and hand dexterity (C4): due to the delicate nature of the blood sampling process and the sensitivity required when handling laboratory instruments, thick gloves reduce sensory feedback and cause interference.

V. Comfort during long-term use (C5): laboratory personnel work for extended periods, and inappropriate gloves can cause fatigue, skin disorders, and consequently mental and cognitive discomfort.

VI. Ease of donning and doffing (C6): proper and rapid donning and doffing of gloves is essential in glove selection; otherwise, it may lead to glove tearing and, consequently, the transmission of infection to the hands.

VII. Cost (C7): considering financial constraints, selecting gloves with a reasonable price can be an important criterion in glove selection.

VIII. Durability (C8): glove durability is an effective factor in glove selection and can play a significant role in reducing costs as well as decreasing waste rates.

IX. Allergenic potential (C9): some materials used in gloves may cause skin sensitivity and allergic reactions, thereby endangering the physical health of personnel.

X. Compliance with international standards (C10): compliance with international standards improves glove quality and safety and is an influential factor in optimal glove selection.

XI. Positive criteria: criteria for which a higher value indicates a better option.

XII. Negative criteria: criteria for which a lower value indicates a better option.

Twenty commonly used types of blood-collection gloves were considered in this study, including latex, nitrile, vinyl, neoprene, chloroprene, PE, as well as specialized sterile and double-layer gloves (Table 1).

The following decision matrix was obtained from 30 students of the Occupational Health and Safety program at the University of Zanjan through a questionnaire with a Cronbach’s alpha of 0.81. In this questionnaire, the students evaluated and rated the alternatives based on the criteria using a 9-point Likert scale. The decision matrix of this study is presented below:

The weights of criteria in MCDM problems are fundamental elements that can significantly influence the results. To minimize biases arising from human judgment, the MEREC method was employed in this study for weighting. First, the decision matrix is normalized (dimensionless). The normalized matrix is presented in Table 3.

In this study, the overall performance table of the alternatives is presented in Table 4.

In this study, Step Four is presented as Table 5.

Ej score is presented as Table 6.

Finally, criteria weights is presented as Table 7.

Table 7 presents the results of weighting ten evaluation criteria for blood-collection gloves using the MEREC method, yielding the following findings:

The criterion “permeability to material penetration” with a very low weight of 0.005, has the least importance in decision-making. This indicates that all examined glove types perform similarly and satisfactorily as barriers against the penetration of biological fluids; therefore, this characteristic functions as a necessary requirement rather than a differentiating criterion.

In contrast, six key criteria chemical resistance (0.115), allergy potential (0.114), compliance with international standards (0.114), needle-stick resistance (0.112), tactile sensitivity (0.112), and ease of donning/doffing (0.113) with weights close to 0.11, exhibit nearly equal and high importance in the final selection. This reflects a critical balance among protective dimensions (chemical and mechanical protection), long-term safety (reduced allergenicity), clinical efficiency (tactile sensitivity and ease of use), and quality assurance (international standards).

The cost criterion, with a moderate weight of 0.088, indicates that in decisions related to clinically sensitive protective equipment, safety and performance considerations take precedence over economic factors, although cost still plays a significant role.

Overall, this distribution of weights supports the validity of the study, as it aligns with the risk-management literature in clinical environments: criteria associated with irreversible risks (such as permanent allergies or chemical leakage) receive higher weights, whereas criteria that are manageable or uniform across all alternatives (such as permeability) exert less influence on the final decision.

In the VIKOR method, the decision matrix is first normalized (made dimensionless). The normalized matrix in this study is as follows:

In the next step, the positive and negative ideals must be determined. For positive criteria, the positive ideal is equal to the largest value in the criterion column, and the negative ideal is the smallest value in that column. For negative criteria, the situation is reversed. Positive criteria are those whose increase leads to profit, while negative criteria are those whose decrease leads to profit.

The utility measure S represents the relative distance of the ith alternative from the ideal point, while the regret measure R represents the maximum dissatisfaction of the ith alternative due to its distance from the ideal point. The VIKOR index has been calculated and presented in Table 10.

Table 10 presents the results of the three key indices of the VIKOR method for ranking 20 types of blood-collection gloves, each reflecting a distinct dimension of option performance. The S index (group utility) measures the weighted distance of each option from the ideal solution across all criteria, and lower values (such as 0.001 for option 18 and 0.006 for Option 19) indicate balanced performance and overall proximity to the ideal across the full set of criteria. The R index (maximum regret) reflects the greatest weighted deviation of an option from the ideal in its worst-performing criterion, and lower values (such as 0.145 for Option 19 and 0.147 for Option 18) emphasize that these options lack a critical weakness in any of the vital criteria (such as allergenicity or chemical resistance). The Q index (final priority) is a weighted combination of S and R with the parameter v, accounting for the trade-off between collective optimization and the minimization of maximum risk. The simultaneous analysis of these three indices provides several clinical insights:

I. Nitrile gloves with lotion (Option 18), with the lowest values of S and R, demonstrate superiority in both overall performance and the absence of any critical weakness.

II. Powdered latex gloves and powdered vinyl gloves exhibit the poorest performance in both S and R, indicating structural weaknesses across several key criteria, particularly allergenicity and chemical resistance. III. The relative consistency between rankings based on S and Q confirms that, in the selection of clinical gloves, overall option performance (group utility) plays a more decisive role than the prevention of the worst-case scenario (maximum regret), a finding that is consistent with the risk-management literature in medical settings.

This analysis not only confirms the methodological validity of the proposed framework but also provides a clear roadmap for clinical decision-makers. Therefore, based on Table 10, the ranking of gloves is presented in Table 11.

In Table 11, the final ranking of alternatives using the VIKOR method based on the index has been carried out. This ranking provides several important insights for clinical decision-making and policy formulation. First, the top three alternatives show a significant gap compared with the other options and all belong to the nitrile family, which confirms the systematic superiority of this material in achieving an optimal combination of chemical resistance (weight = 0.115), low allergenic potential (weight = 0.114), and preservation of tactile sensitivity (weight = 0.112). Second, the performance gap between ranks 1–7 and the remaining alternatives indicates the existence of a “quality threshold,” above which options are recognized as acceptable solutions for high-risk laboratory environments, whereas options ranked 17 and 18 (powdered latex and powdered vinyl), due to poor performance in non-compensable criteria (such as allergenicity and permeability), are evaluated as completely unsuitable. Third, the consistency of the ranking with epidemiological literature, including [2] on glove durability in intensive care units and the evidence-based glove selection guidelines in [6], strengthens the validity of the proposed framework. Finally, this ranking not only provides a practical selection tool for laboratory managers but also, through the clear differentiation of “recommended,” “use with caution,” and “not recommended” options, lays the groundwork for the development of national standards for the selection of protective equipment.