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The purpose of this paper is to appraise the possible response outcomes (no response, fear control or danger control) of a fear-based message on falling behind current medical knowledge among health-care professionals (HCPs).

This study was conducted using a quantitative research design. A cross-sectional survey was carried out in 2,873 health-care facilities across 36 districts of Punjab. The Extended Parallel Process Model (EPPM) provided a theoretical framework for this study. The important components to EPPM such as threat, efficacy and outcomes were used to collect the data. The collected data was analyzed using Statistical Package for Social Sciences (SPSS) version 22.

HCPs perceived high susceptibility and threat of falling behind current medical knowledge. A majority of the HCPs were at the danger control process and engaged in a behavior that is recommended for adaptive behavioral changes. Clinical experience and enrollment in post-graduation programs (e.g. FCPS, MCPS) were significant factors as to HCPs’ perceived response efficacy.

The responses were obtained using a structured questionnaire, which is always subject to respondents’ personal biases and ability to understand the question’s statement.

This study has important implications in terms of introducing promotional, educational and logistical interventions that could help in HCPs overcoming the fear of falling behind current medical knowledge and develop productive and adoptive information behavior thus improving patient care and outcome.

This is the first large-scale empirical study in Pakistan that measured the level of threat and efficacy among HCPs using the EPPM. It proposes a framework for developing long-lasting adaptive information behavioral changes that may result in informed patient care and better decision-making.

This study is a part of the doctoral dissertation that proposes concrete measures to improve health-care information outreach program for rural health-care professionals in primary and secondary health care in Punjab, Pakistan. This study aims to report on the barriers to accessing and using online health-care information from rural settings of the Punjab province of Pakistan.

A cross-sectional survey was conducted in primary and secondary health-care settings in the Punjab province of Pakistan. The study’s population consisted of the rural primary care physicians (PCPs), who were geographically dispersed across 2,873 different remote health-care settings across Punjab. These practice settings included 2,455 basic health units, 293 rural health centers, 89 tehsil headquarter hospitals and 36 district headquarter hospitals.

Limited internet access, non-availability of required equipment and lack of training facilities were identified as the main barriers. PCPs’ gender, previous enrollment in post-graduation programs and type of health-care facility were significant factors in the perceived barriers related to both “non-availability of required equipment” and “inadequate training facilities on the use of information resources”.

The findings of the study hold some important practical implications for different stakeholders. This study identifies and addresses the barriers to accessing and using health-care information for PCPs in rural settings. The success of the health-care information outreach program in Punjab, Pakistan, should rely on the eradication of these barriers.

To the best of the authors’ knowledge, this is the first large-scale study in Pakistan that assesses the barriers and proposes ways to overcome these barriers to effectively access and use health-care information.

The purpose of this study Artificial intelligence (AI) is one of the important emerging trends in information technology and is slowly being implemented in libraries. The researchers have presented a brief strengths, weaknesses, opportunities and threats (SWOT) analysis of the application of AI in Pakistani university libraries.

This study uses an ethnographic approach for data retrieval. Five chief librarians were interviewed by phone, during which they were asked to identify one key strength, weakness, opportunity and threat in terms of introducing AI technologies. The researchers have used a standard SWOT matrix to report the respondents’ comments.

AI is already slowly being introduced into Pakistani university libraries. While commenting on ways in which AI could help their libraries deliver more innovative services and better meet user needs, respondents expressed concern about the investment required in funding, time and staff.

Further study is indicated to identify existing AI implementations in Pakistani university libraries and to assess relevant library users’ perspectives. This study is limited to brief, qualitative data; its main purpose is to validate the use of a SWOT analysis.

Given that AI-based tools are already being used in libraries to some degree regardless of location, now is an opportune time to develop strategies for implementing AI technologies more widely. A SWOT analysis can be used to identify and categorize challenges and risks specific to AI in a logical way to support strategic decision-making.

To date, no SWOT analysis has been conducted in the context of AI applications in libraries, let alone specifically university libraries in Pakistan.

The purpose of this study is to determine the level of awareness among library and information science (LIS) professionals regarding the perceived utility of big data (BD) and data analytics (DA) in academic libraries, as well as their influence on the provision of data services (DSs).

A cross-sectional survey was carried out to collect the data for this study. The population of this study comprised LIS professionals working in public sector university libraries. A four-factor measurement model estimating the influence of BD and DA on the provision of DSs in academic libraries was tested using the structural equation modelling.

The findings revealed that awareness (AW) (β = 0.141, CR = 2.534, p = 0.011) demonstrated a significant positive influence on the provision of DSs. The perceived utility of BD (β = 0.058, CR = 0.582, p = 0.561), and perceived utility of DA (β = 0.141, CR = 2.534, p = 0.905) exhibits a positive but statistically non-significant impact on the provision of DSs (β = 0.010, CR = 0.120, p = 0.905). The goodness of fit indices suggest a favourable fit for the model, as evidenced by the following values: χ² = 1.400, DF = 164; p = 0.001; IFI = 0.954; TLI = 0.946; CFI = 0.953; GFI = 0.906; and RMSEA = 0.043.

A new perspective on the use of BD and DA in academic libraries is presented in this study. It presents a four-factor measurement model on the influence of BD and DA on the provision of DSs in university libraries.

The study aims to identify the prospects and challenges associated with current practices regarding digital data sets management in university libraries in Pakistan.

A cross-sectional survey approach was used to collect the data from library and information science (LIS) professionals working in public sector university libraries in Pakistan. A four-part questionnaire was used to collect the data from the respondents. The collected data from 371 participants were analyzed using a statistical package for social sciences (SPSS-24 version) and analysis of moment structure (AMOS-24).

LIS professionals are better placed to support digital data management practices, such as finding, collecting, assessing and analyzing digital data sets and making digital data publicly discoverable and accessible via open access. In spite of this, a lack of leadership support, interest and cooperation among university departments and the absence of a data management plan, policies and procedures were reported as significant challenges.

To meet the needs of data users, LIS professionals must become knowledgeable about managing and reusing digital data sets. Due to the demands of the information society, university librarians need to learn about data-centric practices that can enhance research outputs and provide new insights.

This research paper is extracted from a PhD dissertation to present a contemporary picture of library data management services and the challenges LIS professionals face to provide possible solutions.

This study aims to determine the differences in information professionals’ perceived news literacy skills and sharing behaviors with their demographics (gender, age, qualification, professional experience and working designation).

Using a quantitative research design, a cross-sectional survey was conducted to collect the data from information professionals working in university libraries.

Findings reveal that the use of social media channels for sharing news was significantly higher among the professionals in the age group <30 years as compared to the older age groups. Female professionals determine the authenticity of a news story more frequently than males. The study concludes that the factors such as age, education level and work experience significantly influence information professionals’ use of social media for sharing news and their news literacy skills.

The study holds some important practical implications in terms of identifying demographic factors in the perceived news literacy skills and sharing behaviors. Having information about the significant variations in demographics may help in adopting the targeted approaches for organizing news literacy sessions, as well as to develop a framework for news literacy instructions.

This study adopted the Framework for Information Literacy in Higher Education given by the Association for College and Research Libraries (ACRL) to develop the theoretical framework and questionnaire. The validated questionnaire on news literacy skills has been specifically constructed for the study in absence of finding any in the literature. Moreover, studies were hardly found assessing the difference of demographics with information professionals’ perceived news literacy skills and their news sharing behaviors.

Digital libraries promote and accelerate scientific research in academic institutions. The subscribed database resources of digital libraries have become an increasingly valuable asset for researchers. Database resources help generate new ideas, determine research directions and promote productive academic interaction between teachers and students in the information age. The purpose of this study is to examine the use of electronic resources by students in various databases, the research productivity of the faculty in the science network and the number of students who graduate each year.

This study uses a quantitative method to collect secondary data from the central database of the Higher Education Commission (HEC) for the population of 26 universities for 2 years (2015–2016). In addition to the HEC digital library, data was also collected from the Web of Science to determine the quality academic performance of faculty and researchers. Moreover, in the study, the total strength of teaching staff and doctoral faculty was extracted from the HEC website for investigation. The authors applied the Spearman’s correlation test to the secondary data using Statistical Package for Social Sciences version 25.

The correlation results of the enrolled students and the downloaded papers from various databases were statistically insignificant (p > 0.05). However, the result showed a positive correlation (p < 0.05) between the use of selected/known databases from a number of databases accessed by the HEC. More importantly, it turns out that the faculty’s productivity in the scientific network and the number of students who graduated from public and private universities are found to be insignificant (p > 0.05). However, the authors found a positive correlation (p < 0.05) between doctoral and non-doctoral faculties, which show that a significant number of non-doctoral faculties are still actively involved in teaching and research.

Research based on academic activities by faculties and students, performed for the first time on the basis of secondary data, will help the HEC and university management to determine the right direction and develop plans to improve academic performance and research quality.

In the past, the field of public libraries proved to be a neglected area of government in terms of allocating handsome budgets for adequate services and developing infrastructure. The aim of this research is (1) to understand the level of library professionals and associated challenges in the preparation and implementation of the budget in public libraries and (2) to analyze the annual grand and regular library budget allocated to public libraries.

A comprehensive literature search was carried out from work published in the past – the quantitative study based on a structured research questionnaire followed by the five-point Likert scale. The primary data were collected by distributing printed questionnaires among the library professionals serving in the directorate of public libraries and its suboffices. The secondary data “Budget Grand” for seven years (2009–2015) and the regular budget for two years (2015–2016) were collected from seven public libraries, and data on the district population and literacy rate were obtained from the provincial bureau of statistics. The authors used the one-way ANOVA on primary data to determine the average difference between samples and descriptive statistics on secondary data.

Survey results show that budgeting is a useful tool for predicting the future, controlling resources and improving employee performance and departmental levels. The findings disclosed that the annual budget review includes guidelines for implementation without adequate discussion and guidance for overcoming challenges. In addition to increasing print and database resources, currency fluctuations, unfair resource allocation and budgeting processes proved to be a potential obstacle to the execution of the library budget. Moreover, library material usage and regular membership are decreasing compared to literacy rates in each district of the province. It also turned out that the limited resources in a library compared to the population and the insufficient budget for operation, maintenance and other library processes posed another challenge for the administration.

The results, which are based on the primary data of experts and the secondary data on the library budget, can help the directorate of public libraries to push ahead with budgetary reforms and overcome challenges.

This article outlines some basic steps for librarians, publishers and sellers to cope with changes caused by currency fluctuations and falling budget pressures. Given the regional population, literacy gaps and the current state of libraries, the results could also cause the government to expand the public library network across the province.

The study builds upon the qualitative method using a questionnaire and on the secondary data for an in-depth understanding of the whole budgetary process. This comprehensive coverage of the budgeting process provides professionals with useful information in preparing a balanced budget for public libraries.

The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant difference in length between the content and its title. In addition, relying solely on textual discrepancies between the title and content to distinguish between real and fake news has proven ineffective. The purpose of this paper is to develop a new approach called semantic enhancement network with content–title discrepancy (SEN–CTD), which enhances the accuracy of fake news detection.

The SEN–CTD framework is composed of two primary modules: the SEN and the content–title comparison network (CTCN). The SEN is designed to enrich the representation of news titles by integrating external information and position information to capture the context. Meanwhile, the CTCN focuses on assessing the consistency between the content of news articles and their corresponding titles examining both emotional tones and semantic attributes.

The SEN–CTD model performs well on the GossipCop, PolitiFact and RealNews data sets, achieving accuracies of 80.28%, 86.88% and 84.96%, respectively. These results highlight its effectiveness in accurately detecting fake news across different types of content.

The SEN is specifically designed to improve the representation of extremely short texts, enhancing the depth and accuracy of analyses for brief content. The CTCN is tailored to examine the consistency between news titles and their corresponding content, ensuring a thorough comparative evaluation of both emotional and semantic discrepancies.