Comparison Of Rankings Research Articles

RANCOM: A novel approach to identifying criteria relevance based on inaccuracy expert judgments

The identification of the criteria relevance from the expert in the multi-criteria problem could be a challenging task. It is important to provide simple and intuitive techniques that reflect the expert knowledge effectively. When the problem includes many criteria, it is possible to occur some probability of error in determining the criteria relevance. However, most subjective weighting methods perform correctly when the experts do not hesitate, are repeatable, and are very precise. Consequently, there is interest in improving the currently used approaches to handle expert hesitation more effectively. To fill this gap, we propose the RANking COMparison (RANCOM) method, which can be used to determine criteria weights based on expert knowledge. Its performance is based on defining the criteria ranking order to obtain the weights vector. The illustrative example and a comparative analysis of the selected subjective weighting methods show that the proposed approach provides reliable results, highly correlated with the existing approaches. However, it offers a simple manner of use, adjusted for less and more experienced users. The comparison of the RANCOM and AHP methods shows that when a slight probability of error in expert judgments occurs, the RANCOM method proves to be a more suitable solution to handle the expert inaccuracies for the problems with 5 or more criteria. Performed experiments showed that the RANCOM method is a repeatable and more consistent method regarding possible judgment errors. The obtained results showed that the RANCOM method guarantees more repeatable results than the AHP method, especially for a greater number of criteria.

Birth weight and gestational age distributions in a rural Kenyan population

BackgroundWith the increased availability of access to prenatal ultrasound in low/middle-income countries, there is opportunity to better characterize the association between fetal growth and birth weight across global settings. This is important, as fetal growth curves and birthweight charts are often used as proxy health indicators. As part of a randomized control trial, in which ultrasonography was utilized to establish accurate gestational age of pregnancies, we explored the association between gestational age and birthweight among a cohort in Western Kenya, then compared our results to data reported by the INTERGROWTH-21st study.MethodsThis study was conducted in 8 geographical clusters across 3 counties in Western Kenya. Eligible subjects were nulliparous women carrying singleton pregnancies. An early ultrasound was performed between 6 + 0/7 and 13 + 6/7 weeks gestational age. At birth, infants were weighed on platform scales provided either by the study team (community births), or the Government of Kenya (public health facilities). The 10th, 25th, median, 75th, and 90th BW percentiles for 36 to 42 weeks gestation were determined; resulting percentile points were plotted, and curves determined using a cubic spline technique. A signed rank test was used to quantify the comparison of the percentiles generated in the rural Kenyan sample with those of the INTERGROWTH-21st study.ResultsA total of 1291 infants (of 1408 pregnant women randomized) were included. Ninety-three infants did not have a measured birth weight. The majority of these were due to miscarriage (n = 49) or stillbirth (n = 27). No significant differences were found between subjects who were lost to follow-up. Signed rank comparisons of the observed median of the Western Kenya data at 10th, 50th, and 90th birthweight percentiles, as compared to medians reported in the INTERGROWTH-21st distributions, revealed close alignment between the two datasets, with significant differences at 36 and 37 weeks. Limitations of the current study include small sample size, and detection of potential digit preference bias.ConclusionsA comparison of birthweight percentiles by gestational age estimation, among a sample of infants from rural Kenya, revealed slight differences as compared to those from the global population (INTERGROWTH-21st).Trial registrationThis is a single site sub-study of data collected in conjunction with the Aspirin Supplementation for Pregnancy Indicated Risk Reduction In Nulliparas (ASPIRIN) Trial, which is listed at ClinicalTrials.gov, NCT02409680 (07/04/2015).

Comparison of different objective weighting methods in a multi‐criteria model for watershed prioritization for flood risk assessment using morphometric analysis

AbstractMorphometric analysis of watersheds coupled with multi‐criteria decision making (MCDM) techniques is a widely used approach in identifying and prioritizing subwatersheds for flood risk assessment. Finding the appropriate weight for each morphometric parameter is one of the most important steps in MCDM methods. The present research focuses on analyzing the effect of using objective weighting methods in watershed prioritization in Daroungar Watershed in Northeast of Iran. To this aim, the weights of morphometric parameters were determined using six objective weighting methods and were used for ranking subwatersheds based on flood generation by a multi‐criteria model. Study results show that the highest weight in various methods belonged to different parameters. Comparison of flood susceptibility ranking maps indicated, except standard deviation method, there is a significant correlation among WM, preference selection index, criteria importance through intercriteria correlation, entropy, and method based on the removal effects of criteria methods; however, the distribution of flood susceptibility classes is not the same in the six weighting methods. The flood hazard ranking map using aggregation methods depicts that subwatersheds 6, 74, 27, and 67 which have high priority for flood hazard, have the same rank in all aggregation methods. Overall, in the present study, the importance of choosing the appropriate weighting method in prioritizing watersheds was emphasized.

A decision-making framework for COVID-19 infodemic management strategies evaluation in spherical fuzzy environment.

100years after the Spanish flu, the COVID-19 crisis showed that large-scale epidemics and pandemics do not belong to the past. On the report of the World Health Organization, COVID-19 is the most significant public health problem of the twenty-first century. Like previous epidemics, the current crisis is accompanied by uncertainty, mistrust, doubt and fear, and this has led to an infodemic connection to the epidemic. So not only are we fighting an epidemic, but also, we are brawling an infodemic. To reduce the social and economic consequences and harmful effects of infodemic health, and to overcome it, we need to implement strategies against infodemic. Evaluating strategies based on multiple characteristics can be considered multi-criteria decision-making (MCDM) problem. According to the literature, there is no study that aims on proposing an integrated approach to evaluate infodemic management strategies under uncertain environment. Therefore, in this paper, an integrated framework based on the extended version of best-worst method (BWM) and Combined Compromise Solution (CoCoSo) methods under a spherical fuzzy set (SFS) is developed for the first time to address the COVID-19 infodemic management strategies selection. Initially, the criteria are weighted using the developed SFS BWM which reduces uncertainty in pairwise comparisons. In the next step, the 15 selected strategies are analyzed and ranked using SFS CoCoSo. The outputs of this paper illustrate that online tools for fact checking COVID-19 information and engage and empower communities are placed in the first and second priorities, respectively. The comparison of ranking results SFS-CoCoSo with other MCDM methods demonstrates the performance of the proposed approach and its ranking stability.

Evaluating the Performance of Subjective Weighting Methods for Multi-Criteria Decision-Making using a novel Weights Similarity Coefficient

In every decision-making problem which involves two or more criteria, there is to identify the relative importance of those criteria in order to make a proper decision. Very often, a decision-makers employee, for this purpose, subjective weighting methods, such as Analytic Hierarchy Process (AHP) or Ranking Comparison (RANCOM). However, there is no simple way to compare the quality of the weights identification using different methods. To address this issue, this paper proposes a simple but Efficient Weights Similarity Coefficient, which allows us to evaluate the relative performance of different subjective weighting methods. Furthermore, we propose a framework that utilizes the proposed coefficient in order to provide more complete comparison results. To demonstrate the applicability and effectiveness of the proposed framework, a case study is performed to compare two popular weighting methods: AHP and RANCOM. The results of the comparison prove that proposed coefficient with the combination of the proposed framework is an Efficient instrument for weighing methods comparison.

Comparison of multi-criteria decision methods for customer-centered decision making: A practical study case

In this paper, we show the practical application of two recently proposed Multi-Criteria Decision Analysis (MCDA) methods, namely the Stable Preference Ordering Towards the Ideal Solution (SPOTIS) and the Reference Ideal Method (RIM) methods. Both of these methods can utilize the Expected Solution Point (ESP) concept, which allows it to easily reflect the decision-maker's or the customer's preferences and expectations. We show the comparison of those methods in the practical study case of laptop choice for the customer with specific needs and expectations for the hardware expressed using ESP. The comparison also includes rankings built toward an optimal solution to underline the necessity of such an approach as the Expected Solution Point. We also use the recently developed Ranking Comparison (RANCOM) method to identify criteria weights to include customer preferences in the weights. The paper also contains a broad discussion of the obtained results and limitations of the presented methods.

A New ELECTRE Method Based on Left and Right Score for Multicriteria Decision-Making.

The procedure for ranking the performance of systems using the method Elimination and Choice Translating Reality (ELECTRE) is one of the most important and practical methods in multicriteria decision-making (MCDM). The classical ELECTRE technique uses the concept of dominance implicitly. In this method, all options are evaluated using a comparison of unexpected rankings, thus eliminating ineffective options. All stages of the electrification technique are based on a coordinated set and an uncoordinated set, which is why it is known as "coordination analysis." The ELECTRE method has two important weaknesses, first, the use of thresholds, which are used to calculate the coordination and noncoordination matrix, and second, this method does not give us a complete and final ranking and is limited to the top options. In order to reduce these weaknesses in this research, interval fuzzy numbers have been used. In the proposed process, the numbers to the left and right of the intervals are considered, and a better method is presented with fuzzy techniques based on the ELECTRE technique. In the research results, using the examples taken from previous researches, the ability of the proposed method is shown.

Analyzing efficiency of decision-making units in data envelopment analysis

A variety of irrigation management systems are evaluated using Data Envelopment Analysis (DEA) to see which one is the most cost-effective, environmentally friendly, and socially responsible. Accordingly, an irrigation management project report serves as the basis for the comparison of different ranks in MCDM and DEA. There are DEA approaches termed CCR, BCC, and RCCR that use criterion weights integrated with the inclusion of assurance areas to increase the analysis' discriminating power and reach the ranking of strategies. The findings show that DEA is a good alternative or supplement to MCDM, and including management preferences into the DEA methodology yields comparable outcomes to MCDM procedures.

The influence of random-coil chemical shifts on the assessment of structural propensities in folded proteins and IDPs.

In studying secondary structural propensities of proteins by nuclear magnetic resonance (NMR) spectroscopy, secondary chemical shifts (SCSs) serve as the primary atomic scale observables. For SCS calculation, the selection of an appropriate random coil chemical shift (RCCS) dataset is a crucial step, especially when investigating intrinsically disordered proteins (IDPs). The scientific literature is abundant in such datasets, however, the effect of choosing one over all the others in a concrete application has not yet been studied thoroughly and systematically. Hereby, we review the available RCCS prediction methods and to compare them, we conduct statistical inference by means of the nonparametric sum of ranking differences and comparison of ranks to random numbers (SRD-CRRN) method. We try to find the RCCS predictors best representing the general consensus regarding secondary structural propensities. The existence and the magnitude of resulting differences on secondary structure determination under varying sample conditions (temperature, pH) are demonstrated and discussed for globular proteins and especially IDPs.

A ranking comparison of the traditional, online and mixed laboratory mode learning objectives in engineering: Uncovering different priorities

<abstract> <p>The laboratory, an integral component of engineering education, can be conducted via traditional, online or mixed modes. Within these modes is a diverse range of implementation formats, each with different strengths and weaknesses. Empirical evidence investigating laboratory learning is rather scattered, with objectives measurement focused on the innovation in question (e.g., new simulation or experiment). Recently, a clearer picture of the most important laboratory learning objectives has formed. Missing is an understanding of whether academics implementing laboratories across different modes think about learning objectives differently. Using a survey based on the Laboratory Learning Objectives Measurement instrument, academics from a diverse range of engineering disciplines from across the world undertook a ranking exercise. The findings show that those implementing traditional and mixed laboratories align closely in their ranking choices, while those implementing online-only laboratories think about the objectives slightly differently. These findings provide an opportunity for reflection, enabling engineering educators to refine the alignment of their teaching modes, implementations and assessments with their intended learning objectives.</p> </abstract>

Çok Kriterli Karar Verme Problemlerinde Duyarlılık Analizi

The aim of this study is to propose a model of stability and sensitivity for the studies used in the implementation of multi-criteria decision making (MCDM). In this context, it is proposed to use the steps "sensitivity analysis based on the variation of criterion weight, sensitivity analysis based on sequence reversal feature and comparison analysis with results from different sorting methods" for stability and sensitivity analysis. In the implementation part of the method, the Fragile Five countries were used as criteria for the unemployment rate, state budget, GDP growth, inflation, current account balance, risk premium for these countries. The criteria were weighted with MEREC and the ordering of alternatives was carried out with WISP. In the application phase of the method, it was found that the model was sensitive to changes in weight coefficients with different weights assigned to criteria over 22 scenarios. It has been observed that the model provides valid results in a dynamic environment through 4 different scenarios created in the sequence inversion step of the model. For the reliability of the MEREC-WISP-based model, a ranking comparison was made with some commonly used methods such as PIV, CoCoSo, COPRAS, WEDBA, TOPSIS and SAW and the results were found to have a high correlation.

The scientific publication score - a new tool for summarizing evidence and data quality criteria of biomedical publications.

The number of biomedical research articles increases by over 2.5million publications each year, making it difficult to stay up to date. In this study, we introduce a standardized search and evaluation tool to combat this issue. Employing crowdsourcing, a large database of publications is gathered. Using a standardized data entry format, coined the "scientific publication score" (SPS), specific publication results can be easily aggregated, thereby allowing fast and accurate comparisons for clinical questions. The SPS combines two quality dimensions. The first captures the quality of evidence of the study using the evidence criteria defined by the Centre for Evidence-Based Medicine, Oxford, UK. The second is more fine-grained and considers the magnitude of statistical analyses on individual and specific results. From 2014 to 2019, experts of the European Bone and Joint Infection Society (EBJIS) were asked to enter data of relevant publications about prosthetic joint infection. Data and evidence levels of specific results were averaged, summarized and ranked. A total of 366 publications were divided into two groups: (I)risk factors (e.g.,host-related factors, pre- and postoperative issues) with 243 publications and (II)diagnostic methods (e.g.,laboratory tests, imaging methods) with 123 publications. After ranking, the highest score for risk factors of prosthetic joint infection were calculated by the SPS for anemia (mean SD0.91), malignancy (mean SD0.29) and previous alloarthroplasty (mean SD0.35). A comparison of the full SPS ranking with the ranking determined at the 2018 International Consensus Meeting (ICM) on Musculoskeletal Infection resulted in a Spearman rank correlation coefficient of 0.48 and a value of 0.0382. The diagnostic methods ranked highest by the SPS were aspirate leucocyte count (mean SD1.21), interleukin6 (mean SD1.07) and aspirate (neutrophils over 80 %) (mean SD0.63). The comparison to the ICM ranking yielded a Spearman rank correlation coefficient of 0.91 and a value of 0.0015. Our pilot study evaluated a new tool for the quality assessment of specific results based on the quality of the source publication. The SPS is suitable for a ranking of specific results by evidence and data quality criteria important for systematic reviews.

A Story of Strengths and Weaknesses in Tertiary Education: Evaluating ‘Mobility’ and ‘Opportunities’ in OECD Countries with Composite Indicators

Assuming a high education level associated with a high probability of job occupancy and greater income, comparative exercises analyzing academic performances and socioeconomic dynamics at regional, country, or supra-national scales have intensified in recent years. As far as tertiary education is concerned, a great disparity in academic performance was characteristic of OECD countries. While adults 25–34 years old were attaining tertiary degrees more frequently than adults 55–64 years old, adults 30–34 years old with at least one tertiary-educated parent were more likely to attain a tertiary degree than individuals from families whose parents have attended secondary—or at least primary—education. ‘Mobility’ and ‘opportunities’ are two dimensions of sustainable education systems that deserve further investigation when assessing disparities in academic performances as a possible source of unsustainable development and social polarizations. ‘Mobility’ refers to the probability of achieving tertiary education for children coming from families with a different—i.e., lower (e.g., secondary or primary)—level of education. ‘Opportunities’ refers to the probability for a child to attain tertiary education, regardless of the education level achieved by the parents. The present study proposes a quantitative assessment of both dimensions through an original approach and novel statistical measures ranking OECD countries. A comparison of individual rankings of ‘mobility’ and ‘opportunities’ reveals counterintuitive results in some cases. To overcome this issue, our study introduces aggregate methods combining the two measures with the aim of developing a bivariate ranking that accounts for both dimensions simultaneously and delineates a more complete evolution of academic performance divides in advanced economies.

The Grey Relation Comparison of Brand Value and Business Ranking for L’Oréal and Dior

As the only luxury company in the Fortune Global 500 list, Dior is far behind the FMCG company L’Oréal in the world’s most famous brand value appraisal agency Interbrand. However, Dior is far superior to L’Oréal in the Fortune Global 500 ranking. The difference between which is due to the calculation basis. This paper analyzes the calculation basis of Interbrand and Fortune Global 500 ranking by Gray Relation Analysis, and finds that the impact of profits, assets, shareholders’ equity and number of employees on the ranking of Fortune Global 500 and Interbrand models is significantly different. The analysis shows that both Dior and L’Oréal have the strongest correlation between shareholders’ equity and its ranking results in both Fortune Global 500 results. This is true for L’Oréal in the Interbrand valuation model. For Dior, however, profits has the strongest impact on its ranking in the Interbrand valuation model. The two companies need to start from the two factors of shareholders’ equity and profits respectively if they want to improve their corporate rankings and brand value.

Risk assessment of enteric viruses along the food chain and in the population.

Food-borne microbial illness contributes up to one third of global disease burden. The largest category of food-borne illness is gastroenteritis, the majority of which is caused by enteric viruses. Viruses like these are transmitted to food either by waste-contaminated waters, or by handling and transfer during processing. An important tool for reducing or controlling food-borne microbial risk is risk analysis. This framework has been adopted globally to manage risks associated with microbial contamination in food. Several hundred microbial risk assessments (MRAs) have been published by different national and international organisations, for different food-hazard combinations. The use of MRAs in controlling and understanding virus risk has, to date, been limited, compared with the efforts made on bacterial pathogens. Given the large disease burden that viruses are responsible for, this disparity should be addressed. The main reasons for the relative lack of risk assessments are the difficulty in detecting and monitoring viruses compared with bacteria. This means less data on prevalence, concentration and inactivation, and allows viruses to remain silent contributors to global disease. There are also key conceptual differences between virus risk assessment and bacterial risk assessment. This project aimed to assess the current state of the art for food-borne virus risk assessment, then to progress the field further by using the data available to produce risk rankings and risk assessments. This was done by a combination of literature reviewing and various risk assessment tools. The result was an assessment of the overall evidence base in the literature, a semi-quantitative ranking comparison between the viruses and foods of most concern, and a survey of inactivation methods, leading to a quantitative ranking of the effectiveness of each in reducing and managing food-borne virus risk.

Bayesian Performance Analysis for Algorithm Ranking Comparison

In the field of optimization and machine learning, the statistical assessment of results has played a key role in conducting algorithmic performance comparisons. Classically, null hypothesis statistical tests have been used. However, recently, alternatives based on Bayesian statistics have shown great potential in complex scenarios, especially when quantifying the uncertainty in the comparison. In this work, we delve deep into the Bayesian statistical assessment of experimental results by proposing a framework for the analysis of several algorithms on several problems/instances. To this end, experimental results are transformed to their corresponding rankings of algorithms, assuming that these rankings have been generated by a probability distribution (defined on permutation spaces). From the set of rankings, we estimate the posterior distribution of the parameters of the studied probability models, and several inferences concerning the analysis of the results are examined. Particularly, we study questions related to the probability of having one algorithm in the first position of the ranking or the probability that two algorithms are in the same relative position in the ranking. Not limited to that, the assumptions, strengths, and weaknesses of the models in each case are studied. To help other researchers to make use of this kind of analysis, we provide a Python package and source code implementation at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://zenodo.org/record/6320599</uri> .

A real-life decision-making problem with Hendecagonal fuzzy numbers

Making the correct decision in a real-time situation is extremely difficult. In today’s technological age, computational methods are available, and they may assist the company’s top leaders in making sound decisions and strengthening the organization. There are several techniques for dealing with decision-making problems, one of which is the use of Hendecagonal fuzzy numbers. These fuzzy numbers are used to represent the ambiguity or ambiguity of eleven linguistic variables. To address these shortcomings, we use the ranking method, relativity function, and comparison matrix to aid in decision-making because we have eleven constraints (linguistic variables) that can be expressed in a hendecagonal fuzzy number matrix (HdcgFNM). The raking technique, relativity function, and comparison matrix were evaluated using a case study.

Reference genes selection of Paeonia ostii 'Fengdan' under osmotic stresses and hormone treatments by RT-qPCR.

Tree peony possess significant ornamental, medicinal and oil values. Osmotic stresses including dehydratiuon and salinity limit the expansion of cultivation area of tree peony. Information on reference genes selection under osmotic stress and hormone stimulation of tree peony still limited. This study aimed to determine the stable reference genes suitable for tree peony under osmotic stresses and hormone treatments, and provide a theoretical basis for the molecular biology research. Twelve candidate reference genes were evaluated in Paeonia ostii 'Fengdan' under osmotic stress and hormone treatments by RT-qPCR. Delta Ct method, geNorm, and NormFinder were used for the comprehensive expression stability ranking comparison. The results revealed that tubulin-α was the preferred internal reference genes for drought and ABA treatment, tubulin-β was identified as the most suitable reference gene under drought and OPDA induction, 18s-rRNA was regarded as the most stable gene for salinity and JA treatment, eIF-5A was listed as the most stable gene for JA and MeJA treatments. The experiments also displayed that EF1-α were comparatively unstable under ABA and BR hormone treatments. These preferred reference genes could be useful in qPCR studies involving osmotic or hormonal stresses in Paeonia ostii 'Fengdan'. It is anticipated that the results will benefit tree peony functional genomics studies and molecular breeding research in the future.

Clinical Outcomes of Stereotactic Body Radiation Therapy across Treatment Platforms Employing Varied Approaches to Respiratory Management at a Single Institution

<h3>Purpose/Objective(s)</h3> Stereotactic Body Radiation Therapy (SBRT) has been the standard of care for early-stage non-small cell lung cancer patients who do not undergo surgery since soon after the publication of RTOG 0236. Since then, various linear accelerator platforms have been employed with a variety of approaches to respiratory management, treatment planning and treatment delivery. Comparisons of local control and survival end points using a variety of treatment platforms in addition to respiratory management techniques have not been reported. Here, we present the results of our analysis of clinical outcomes at a single institution across multiple treatment platforms representative of the available technology since the widespread adoption of SBRT for early-stage lung cancer. <h3>Materials/Methods</h3> Consecutive patients who underwent SBRT for early-stage lung cancer between 2011 and 2018 at a single institution were retrospectively analyzed. Treatments were planned and delivered with standardized simulation, dose and fractionation per institutional guidelines. Overall Survival (OS), Local Control (LC), Distant Metastasis Free Survival (DMFS), and Progression Free Survival (PFS) were calculated for the entire cohort. Log rank comparisons of all survival endpoints were then calculated by treatment platform: stereoscopic orthogonal kV x-ray localization with conventional Linac (Linac1), volumetric cone beam CT localization with conventional Linac (Linac2), and megavoltage CT with helical tomotherapy (Linac3). Comparisons were also performed by respiratory management technique: free breath (FB), breath hold (BH) or end expiration respiratory gating (RG). <h3>Results</h3> A total of 240 patients were included in the analysis. Treatment platform utilization was well balanced in the group: 28% on Linac1, 32% on Linac2, and 40% on Linac3. The majority of patients were treated with FB, 72%. Median OS for the entire cohort was 50 months. The crude rate of local recurrence was 7%. Kaplan-Meier estimate of LC for the entire cohort was 94% at 3 years. The median time to local recurrence was not reached. LC was not impacted by treatment platform, p = 0.897, or respiratory management technique, p = 0.623. Comparisons by treatment platform and respiratory management technique revealed no significant differences in OS, DMFS, and PFS. <h3>Conclusion</h3> Irrespective of treatment platform or approach to respiratory management, SBRT remains highly effective at providing durable LC in patients with early-stage lung cancer. Differences in treatment delivery platform and respiratory management do not significantly influence other disease control and survival outcomes.

Associations between perceived stress and health outcomes in adolescents

BackgroundAdolescents are reporting increasing symptoms of anxiety, depression and somatization and an increase in perceived stress is a plausible explanation. The first aim of this study was to examine the occurrence of perceived stress and health outcomes in adolescents, and to evaluate if there are any sex differences. The second aim was to investigate if there is an association between perceived stress and the health outcomes and, if so, possible gender differences in this association. The third aim was to compare samples of adolescent girls and boys from two different European countries to enhance the generalizability of potential findings.MethodsThe sample included 636 students from Sweden and Bulgaria, aged 15–16, 164 (58% males, 41% females, 1% not specified) from Sweden and 472 (71% males, 28% females, 1% not specified) from Bulgaria. Perceived stress and health outcomes were measured by the 14-item “Perceived Stress Scale” (PSS-14), and a shorter version of the questionnaire "Children and Young People in Skåne" (Folkhälsoenkäten, FHE), respectively. T-test and Chi2 and/or Fisher’s exact test was used to compare results between boys and girls from the PSS-14 and health outcomes. The association between PSS and the health outcomes was assessed using Spearman’s rank correlation and comparisons between boys and girls were calculated using linear regression.ResultsThere were significant associations between perceived stress and psychiatric symptoms in all groups. Adolescent girls in both Sweden and Bulgaria consistently reported higher levels of perceived stress and more psychiatric and somatic symptoms than the boys.ConclusionsEvaluating methods for lessening the perception of stress, and their clinical presentation, should be considered in order to reduce the occurrence of psychiatric symptoms in adolescents.