Financial Inclusion and Determinants in South Asian Countries

Financial inclusion is considered an essential mediator to achieve economic growth in recent years. The main focus of this study is to construct the financial inclusion index and to explore the determinants of financial inclusion in Pakistan, Bangladesh, and India. Data is collected from InterMedia's financial inclusion insights datasets 2016 that are collected through random sampling. The financial inclusion index is used as a dependent variable that is calculated using levels of access and usage of financial services. Age, gender, education, financial situation, working type and use of mobile phones are used as independent variables. Results of multinomial logistic regression reveals that in South Asian countries educated, male, relatively older, rich and regular employees have a better chance to be financially included. Mobile phone users also prefer high financial inclusion. Developing countries like Pakistan, Bangladesh, and India can attain inclusive growth by increasing the contribution of weaker sections of the population with the mainstream. If weaker sections of the population have easy access to financial services, the economic growth of a country can be enlarged. So policymakers should focus on the financial sector's structural problems and pay attention to create modern financial institutes both in the banking sector and in financial markets

Primary repair of an esophageal rupture using pleural flap

Esophageal perforation remains an important thoracic emergency. Aggressive operative therapy remains the mainstay for treatment. A case of esophageal perforation, consequent upon impacted food bolus, is presented. An 80 years old female, with multiple comorbidities, presented with dysphagia and right sided chest pain, who had a distal esophageal tear, secondary to accidental meat ball ingestion. Rigid esophagoscopy showed complete occlusion of the distal esophagus with a meat ball. Right thoracotomy was performed, which showed perforated esophagus with large meat ball protruding from it. Endoscopic removal of the food particles was done, and the rupture was repaired using a pleural flap. The entire postoperative stay was uneventful and the patient was discharged on the ninth post-operative day

Prevalence and Levels of Information Seeking Anxiety among Business Students

This research assessed the prevalence and levels of information seeking anxiety among business students at Lahore School of Economics, Lahore, Pakistan so that remedial measures could be taken to reduce anxiety. The data were collected from 283 students using a survey questionnaire, containing an Information Seeking Anxiety Scale along with certain demographic and academic variables, and analyzed using descriptive and inferential statistics. The results indicated the prevalence of information seeking anxiety among these students across different dimensions and overall scale at mild to moderate levels. There was no significant relationship between nature of MBA program, gender, school background, geographical origin, ICT skills, English language competency, and information seeking anxiety. However, gender appeared to predict the dimension of search anxiety as female students were more anxious than males when searching for information. The results are very useful to inform policy and practice for development of information capabilities in the digital information landscape. These findings could be used as a guide for developing and designing information literacy programs aimed to reduce information seeking anxiety resulting in the improvement of students’ academic performance. This study has made a reasonable contribution to the existing literature on information seeking anxiety as a limited number of studies appeared focusing specifically on information seeking anxiety

Development and Validation of a Covid-19 Literacy Scale

This research intended to develop and validate a Covid-19 Literacy Scale (CLS). This study was conducted in two phases. In the first phase items were generated based on an extensive literature review, public advisory platforms, and public service messages related to Covid-19. After that these statements were submitted to a panel of experts for content and face validity. While in the second phase, a cross-sectional survey was conducted using students of three university from the province of Punjab, Pakistan for construct validity and reliability. An online questionnaire was administered among students with permission from the concerned authorities. A total of 369 responses received which were imported in SPSS for data analysis. The construct validity was assessed through exploratory factor analysis and the reliability of the instrument was determined using Cronbach alpha coefficient. The results indicated a 23-items scale structured into two dimensions, namely, ‘infection spread and symptoms’ (11 items) and ‘infection prevention and treatment’ (12 items), Each statement had loading strengths greater than .56 and the model explained 66.6% of the total variance. The values of reliability coefficient for overall scale (CA = .970) as well as for both sub-dimension such as ‘infection spread and symptoms’ (CA = .957) and ‘infection prevention and treatment (CA = .936) were great. The correlation coefficients of test retest ranged from 0.71 to .87 which also appeared at satisfactory level. Thus, the newly developed instrument appeared as a reliable and valid measure for Covid-19 literacy assessment. This research would make a worthwhile contribution to health literacy in general and Covid-19 literacy in particular as no such scale was available in the existing literature

Incidence and Surgical Outcome of the Intracranial Epidermoid Cyst at Punjab Institute of Neurosciences Lahore, Pakistan

Objectives:  The incidence and microsurgical outcomes of intracranial epidermoid cysts in the Department of Neurosurgery III, Punjab Institute of Neurosciences (PINS), Lahore, Pakistan, are described in this case series. Materials and Methods:  This study was a data analysis of a case series of 15 patients (mean age, 40 years) of both gender with intracranial epidermoid cysts who had microsurgical surgical excision over five years. Results:  This study comprised 11 (73.3%) male and 4 (26.7%) female patients, 11 (73.3%) cases were infratentorial and 4 (26.7%) cases were in supratentorial region. The epidermoid was located in the CP angle in 11 (73.3%) patients, 3 (20%) in the midline supra sellar region, and 1 (6.66%) in the frontotemporal region. The presenting complaints were mainly headache in 11 (73.33%), cranial nerve palsy and cerebellar signs in 8 (53.3%) patients, Trigeminal neuralgia in 3 (20%) patients, Fits and hydrocephalus in 2 (13.3%) patients. There were 14 (93.3%) patients with GTR (gross total resection), 1 (6.6%) patients STR (subtotal resection). According to Karnofsky's performance scoring (KPS), 3 (20%) patients improved, 11 (73.3%) patients had the same KPS, and 1 (6.6%) patient had a lower KPS. Conclusion:  The epidermoid cysts in the brain are usually found in the infratentorial region rather than the supratentorial region. Infratentorial lesions typically cause cranial nerve deficits, whereas the supratentorial area symptom is a headache

Machine Learning Based Diagnostic Paradigm in Viral and Non-Viral Hepatocellular Carcinoma

© 2024 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Viral and non-viral hepatocellular carcinoma (HCC) is becoming predominant in developing countries. A major issue linked to HCC-related mortality rate is the late diagnosis of cancer development. Although traditional approaches to diagnosing HCC have become gold-standard, there remain several limitations due to which the confirmation of cancer progression takes a longer period. The recent emergence of artificial intelligence tools with the capacity to analyze biomedical datasets is assisting traditional diagnostic approaches for early diagnosis with certainty. Here we present a review of traditional HCC diagnostic approaches versus the use of artificial intelligence (Machine Learning and Deep Learning) for HCC diagnosis. The overview of the cancer-related databases along with the use of AI in histopathology, radiology, biomarker, and electronic health records (EHRs) based HCC diagnosis is given.Peer reviewe