The COVID-19 pandemic has great consequences on mental health. We aimed to assess medical students’ psychological condition and influencing factors as a baseline evidence for interventions promoting their mental wellbeing. We conducted an online survey from April 8 to April 18, 2020 to examine the mental health of medical students by the nine-item Patient Health Questionnaire, seven-item Generalized Anxiety Disorder Scale, seven-item Insomnia Severity Index, and six-item Kessler psychological distress scale. Factors associated with mental health outcomes were identified by multivariable logistic regression analysis. Five hundred forty-nine students completed the survey; 341 (62.3%), 410 (74.6%), 344 (62.6%), and 379 (69%) reported anxiety, depression, insomnia, and distress, respectively. Female students, living in high COVID-19 prevalence locations, more than 25 days confinement, psychiatric consult history, and being in a preclinical level of studies had higher median scores and severe symptom levels. Multivariable logistic regression showed female gender as a risk factor for severe symptoms of anxiety (odds ratio [OR]: 1.653; 95% CI: 1.020–2.679; P = 0.042), depression (OR: 2.167; 95% CI: 1.435–3.271; P < 0.001), insomnia (OR: 1.830; 95% CI: 1.176–2.847; P = 0.007), and distress (OR: 1.994; 95% CI: 1.338–2.972; P = 0.001); preclinical level of enrollment as a risk factor for depression (OR: 0.679; 95% CI: 0.521–0.885; P = 0.004), insomnia (OR: 0.720; 95% CI: 0.545–0.949; P = 0.02), and distress (OR: 0.650; 95% CI: 0.499–0.847; P = 0.001), whereas living in high COVID-19 prevalence locations was a risk factor for severe anxiety (OR: 1.628; 95% CI: 1.090–2.432; P = 0.017) and depression (OR: 1.438; 95% CI: 1.002–2.097; P = 0.05). Currently, medical students experience high levels of mental health symptoms, especially female students, those at a preclinical level and living in regions with a high prevalence of COVID-19 cases. Screening for mental health issues, psychological support, and long-term follow-up could alleviate the burden and protect future physicians.

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Purpose China Pakistan Economic Corridor (CPEC) projects are widely spread throughout Pakistan with the potential to have a massive impact on Pakistan’s economic future. CPEC projects have, therefore, made it imperative that green practices are adapted to provide sustainability to the CPEC projects. The adoption of green supply chain management (GSCM) framework will significantly increase the value attained from CPEC projects through the increased benefits to the socio-cultural and economic conditions of Pakistan without causing harm to the environment. The purpose of this paper is to identify and rank the GSCM practices for implementation in the construction industry of Pakistan according to expert opinion. Design/methodology/approach This study targets the experts who are employed as supply chain managers in the different construction industries of Pakistan. The opinions of these experts have been extracted through an online questionnaire that was based on six alternatives along with four criteria. The tool of multi-criteria decision making (MCDM) that is a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been used to analyze the results. Findings Six alternatives that have been used for this study are green design, green procurement, green production, green warehousing, green transportation and green recycling. The top-ranked alternative as a practice for GSCM is green warehousing followed by green production. The lowest ranked alternative in this study is green recycling. The alternatives have been ranked on the basis of “cc” values derived through TOPSIS. Practical implications As the advancement in the construction industry will definitely going to impact the environmental sustainability of the country, the results derived through this research will assist the managers of the construction industry of Pakistan to adopt best practices among green supply chain in order to lower their impact. Originality/value Framework using TOPSIS in order to find the best GSCM practice in Pakistan has not been reported before this study.

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Purpose The rate of cesarean sections has been rapidly increased in the last few decades in all the developing as well as developed countries. The rate of cesarean sections determined by the World Health Organization has been crossed by many countries, like Brazil, India, China, USA, Australia, etc. Similarly, this rate has also increased in Pakistan. The purpose of this paper is to explore and identify the factors that are responsible for the rising rate of cesarean sections in Pakistan. Design/methodology/approach These factors are categorized under medical and non-medical factors. The medical factors include the obesity of mother, age of mother, weight of the baby, umbilical cord prolapse, fetal distress, abnormal presentation, dystocia and failure to progress. The non-medical factors include financial incentives of doctors, time convenience for doctors, high tolerance to surgery, patient’s preference toward cesarean section, private hospitals, public hospitals, income status of patients, rural areas, urban areas and the education of patients. To identify the critical factors, data have been collected and a multi-criteria decision-making technique, called Decision Making Trial and Evaluation Laboratory, is used. Findings The result shows that the medical factors that are responsible for the rise in the rate of cesarean sections are umbilical cord prolapse, age of mother and obesity of mother. On the other hand, the non-medical factors that are the reasons for the increase in cesarean sections are the large number of private hospitals and the unethical acts of the doctors in these hospitals, preference of patients, and either the unavailability of doctors or poor conditions of hospitals in rural areas. Originality/value Cesarean section is an important surgical intervention and is considered to be very essential in the cases of existing as well as potential medical problems to the mother or the baby. Cesarean section is also performed for non-medical reasons. In Pakistan, the number of private hospitals has increased and these hospitals provide good health care. However, these hospitals do not work under the rules and regulations set by the government. The doctors in private hospitals perform unnecessary cesarean sections in order to fulfill the demands of private hospital’s owners. In addition to this, it is also found that, nowadays, most women prefer to give birth through cesarean section in order to eliminate the pain of normal vaginal delivery.

This paper investigates the welfare effect of travelling through congested areas and adverse weather through changes in the speed of individuals' car trips based on the entire commuting trip. Weather measurements are local and time specific (hourly basis). As most commuters travel twice a day between home and work, we are able to employ panel data techniques, which deals with issues related to unobserved heterogeneity and data selection. We find that travelling through congested areas reduces speed by about 7%. For most commuters the welfare effects of adverse weather conditions are negative but small. However, the commuters' welfare costs due to rain are rather substantial during the evening peak in congested areas (and up to 12% of the overall commuting costs).

The number of refugees in the world is on increase once again just like the 1990s. There is plentiful scholarly literature available on the nexus of refugees and host country. This particular study brings new insight into existing literature by focusing on Pakistan (the home of the second largest refugees by numbers) and employing the multi-criteria decision-making (MCDM) techniques such as analytic hierarchy process (AHP) and order of preference by similarity to ideal solution (TOPSIS) to determine how refugees influence host country, and how these influences vary among various refugee populations in the very same country while considering opinions of local communities and organizations dealing with these refugees. At the same time, using last 15 years' data, the study forecasts the refugee number that may repatriate by 2018 using exponential smoothing technique. The study is useful for policy makers dealing with refugees, such as UNHCR or governments of refugee-hosting countries, and local populations of the host countries, and to the greater general readers having interest in this area.