Related Knowledge Research Articles

Health literacy-related knowledge, attitude, perceived barriers, and practice among primary care doctors in Malaysia.

This study aimed to assess the health literacy (HL) related knowledge, attitude, perceived barriers, and practice among primary care doctors (PCDs) in Malaysia, and to determine the factors associated with HL-related practice. A cross-sectional study was conducted using an online questionnaire. Sociodemographic and work-related details were collected. HL-related knowledge, attitude, perceived barriers, and practice were assessed. Descriptive and inferential analyses using linear regression were performed. 373 PCDs were included in the study with a mean (SD) age of 37.9 (8.1) years old. The mean (SD) HL-related knowledge, attitude, and practice scores were 6.89 (1.27), 36.33 (7.04), and 30.14 (4.7), respectively. 90.9% of the participants had good HL-related knowledge scores, and 89.5% had positive HL-related attitude. More than 80% of participants found that "time constraint to implement health literacy screening" and "lack of human resources to administer HL screening tools in their settings" were among the barriers for them to implement HL practices. PCDs of Chinese and other ethnicities had lower HL-related practice scores compared to those of Malay ethnicity (adjusted b = - 1.74; 95% CI - 2.93, - 0.54, and - 2.94; 95% CI - 5.27, - 0.60, respectively). PCDs who had heard of the term "health literacy" were associated with higher HL-related practice scores (adjusted b = 2.32; 95% CI 1.17, 3.47). Age (adjusted b = 0.10; 95% CI 0.04, 0.16) had significant linear positive relationship with HL-related practice. In conclusion, the HL-related knowledge, attitude, and practice among PCDs in Malaysia were at an acceptable level. Along with educating PCDs on HL, the perceived barriers identified need to be addressed to improve the HL-related practice and ultimately patient care.

Psychological Experience of the First Pulmonary Function Test in Elderly Patients with Poor Cooperation: A Qualitative Study

Objectives: In this study, we aimed to understand the real psychological experience of the first pulmonary function test (PFT) of elderly patients with poor cooperation, provide a reference for reporting their psychological characteristics and needs, and offer suggestions for developing appropriate guidance strategies to improve cooperation and compliance of patients. Methods: We used a phenomenological approach. We selected 21 elderly patients with poor cooperation who underwent PFT in a Tertiary Grade A comprehensive hospital in Nanning from December 2021 to June 2022 for a semi-structured interview using an objective sampling method. We used the Colaizzi analysis method to collate and analyze the data. Results: We extracted 6 distinct psychological experiences of elderly patients with poor cooperation in the first PFT, including distrust, tension and worry, the desire to understand PFT-related information, high psychological sensitivity, frustration and positive self-adjustment, and negative self-perception of aging. According to participants′ own explanation, most of the psychological experience was mainly related to the lack of understanding of PFT related knowledge, which was greatly affected by the way of information acquisition and the allocation of PFT resources. In addition, elderly patients also revealed that unfamiliarity with their own disease history and physical status affected their psychological enthusiasm during the examination. Conclusions: Elderly patients who failed to cooperate during the first PFT have complex psychological states and a wide range of psychological needs. In clinical practice, medical staff should focus on patients, thoroughly investigate the psychological experiences of elderly patients undergoing PFT and implement corresponding measures to encourage elderly patients′ cooperation and improve examination compliance.

THE MISUSE OF SOCIAL MEDIA AS A CAUSE OF DIVORCE AT THE MAJENE RELIGIOUS COURT (STUDY OF FIQH AND SOCIAL MEDIA)

ABSTRACT
 Misuse of social media is one of the leading causes of divorce in the digital era. This research is aiming at determining the misuse of social media that causes divorce in the study of jurisprudence and social media. This research applies a qualitative descriptive type of research is sourced from interviews with judges at the Majene Religious Court, relevant books and articles. The results of the research show that social media is one of the platforms that causes a husband or wife to become nusyuz (disobedience) which can be shown by a change in the partner's attitude (infidelity) which then continues to become shiqaq which is a dispute between the couple, while in the study of social media, there is a relationship between cognitif dissonnance theory and virtual space that can cause divorce if the elements of attitude, perception and behaviour are not interconnected. This research provides to knowledge in relation to the impact of misuse of social media which results in divorce from a review of Islamic law and social media
 

Effect evaluation of rubella knowledge attitudes and practices (KAP) intervention on parents of 0 to 2 year old children in Chongqing, China.

To evaluate the effect of rubella elimination publicity and communication project intervention activities on rubella related knowledge attitudes and practices (KAP) on parents of 0 to 2 year old children in Chongqing, and to provide basis for the formulation of rubella elimination strategies and measures. We choose 7 townships (streets) of parents of 0 to 2 year old children who live for more than 6 months in Chongqing to investigate the status of rubella knowledge, attitude and practice. Parents' cognition and behavior related to rubella, congenital rubella syndrome (CRS) and rubella component vaccine (RCV) were analyzed and evaluated before and after intervention. 420 people were surveyed before and after the intervention. The awareness rate of rubella prevention knowledge of parents after intervention was significantly higher than that before intervention, with statistical significance (P < .05). After intervention, parents' support rate of "rubella antibody test before pregnancy" and "RCV vaccination for children" were 89.52% and 72.14%, respectively, which were higher than those of parents before intervention (84.05% and 27.38%, P < .05). The RCV timely vaccination rate of children after intervention was 92.78%, which was higher than that of children before intervention (83.90%, P < .05). Targeted publicity and communication methods should be adopted for urban and rural areas to create a good publicity atmosphere, popularize rubella and CRS related popular science knowledge, and improve the RCV timely vaccination rate of school-age children and high-risk population.

An Institutional Curriculum for Opioid Prescribing Education: Outcomes From 2017 to 2022

IntroductionPrescription opioids, including those prescribed after surgery, have greatly contributed to the US opioid epidemic. Educating opioid prescribers is a crucial component of ensuring the safe use of opioids among surgical patients. MethodsAn annual opioid prescribing education curriculum was implemented among new surgical prescribers at our institution between 2017 and 2022. The curriculum includes a single 75-min session which is comprised of several components: pain medications (dosing, indications, and contraindications); patients at high risk for uncontrolled pain and/or opioid misuse or abuse; patient monitoring and care plans; and state and federal regulations. Participants were asked to complete an opioid knowledge assessment before and after the didactic session. ResultsPresession and postsession assessments were completed by 197 (89.6%) prescribers. Across the five studied years, the median presession score was 54.5%. This increased to 63.6% after completion of the curriculum, representing a median relative knowledge increase of 18.2%. The median relative improvement was greatest for preinterns and interns (18.2% for both groups); smaller improvements were observed for postgraduate year 2-5 residents (9.1%) and advanced practice providers (9.1%). On a scale of 1 to 10 (with 5 being comfortable), median (interquartile range) self-reported comfort in prescribing opioids increased from 3 (2-5) before education to 5 (4-6) after education (P < 0.001). ConclusionsEach year, the curriculum substantially improved provider knowledge of and comfort in opioid prescribing. Despite increased national awareness of the opioid epidemic and increasing institutional initiatives to improve opioid prescribing practices, there was a sustained knowledge and comfort gap among new surgical prescribers. The observed effects of our opioid education curriculum highlight the value of a simple and efficient educational initiative.

Research on a Classification Method for Strip Steel Surface Defects Based on Knowledge Distillation and a Self-Adaptive Residual Shrinkage Network

Different types of surface defects will occur during the production of strip steel. To ensure production quality, it is essential to classify these defects. Our research indicates that two main problems exist in the existing strip steel surface defect classification methods: (1) they cannot solve the problem of unbalanced data using few-shot in reality, (2) they cannot meet the requirement of online real-time classification. To solve the aforementioned problems, a relational knowledge distillation self-adaptive residual shrinkage network (RKD-SARSN) is presented in this work. First, the data enhancement strategy of Cycle GAN defective sample migration is designed. Second, the self-adaptive residual shrinkage network (SARSN) is intended as the backbone network for feature extraction. An adaptive loss function based on accuracy and geometric mean (Gmean) is proposed to solve the problem of unbalanced samples. Finally, a relational knowledge distillation model (RKD) is proposed, and the functions of GUI operation interface encapsulation are designed by combining image processing technology. SARSN is used as a teacher model, its generalization performance is transferred to the lightweight network ResNet34, and it is conveniently deployed as a student model. The results show that the proposed method can improve the deployment efficiency of the model and ensure the real-time performance of the classification algorithms. It is superior to other mainstream algorithms for fine-grained images with unbalanced data classification.

Multimodal Dialog Systems with Dual Knowledge-enhanced Generative Pretrained Language Model

Text response generation for multimodal task-oriented dialog systems, which aims to generate the proper text response given the multimodal context, is an essential yet challenging task. Although existing efforts have achieved compelling success, they still suffer from two pivotal limitations: (1) overlook the benefit of generative pretraining and (2) ignore the textual context-related knowledge . To address these limitations, we propose a novel dual knowledge-enhanced generative pretrained language mode for multimodal task-oriented dialog systems (DKMD), consisting of three key components: dual knowledge selection , dual knowledge-enhanced context learning , and knowledge-enhanced response generation . To be specific, the dual knowledge selection component aims to select the related knowledge according to both textual and visual modalities of the given context. Thereafter, the dual knowledge-enhanced context learning component targets seamlessly, integrating the selected knowledge into the multimodal context learning from both global and local perspectives, where the cross-modal semantic relation is also explored. Moreover, the knowledge-enhanced response generation component comprises a revised BART decoder, where an additional dot-product knowledge-decoder attention sub-layer is introduced for explicitly utilizing the knowledge to advance the text response generation. Extensive experiments on a public dataset verify the superiority of the proposed DKMD over state-of-the-art competitors.

A comprehensive review of mechanical fault diagnosis methods based on convolutional neural network

Mechanical fault diagnosis can prevent the deterioration of mechanical equipment failures and is important for the stable operation of mechanical equipment. Firstly, this paper reviews three basic methods of fault diagnosis and common methods of data-driven fault diagnosis, focusing on the characteristics and advantages of deep learning and convolutional neural networks. Then, the basic structure and working principle of CNN (Convolutional Neural Networks) and some basic methods to achieve better training results are introduced. In the next place, from data processing, data fusion, sample set construction, and so on, it is reviewed that the method of fault diagnosis based on CNN and their application scenarios and advantages and disadvantages; for another, the related knowledge and concepts of transfer learning are introduced, and some current application scenarios and advantages and disadvantages of mechanical fault diagnosis techniques combining migration learning and convolutional neural networks are reviewed. Finally, the current difficulties and challenges of convolutional neural networks are discussed, and the research directions have been prospected for CNN applied to the field of fault diagnosis. Although there is quite some similar literature reviewed, this review aims to introduce the basic methods of fault diagnosis, which draw forth the basic applications of the fault diagnosis of data-driven, CNN in the domain of fault diagnosis, and the application scenarios and advantages and disadvantages of combining TL (Transfer Learning) and CNN in fault diagnosis, as well as some problems and prospects. It helps researchers to have a basic understanding of this.

A Contextual Dependency-Aware Graph Convolutional Network for extracting entity relations

Dependency trees reflect rich structural information, which can effectively guide models to understand text semantics and are widely used for relation extraction. However, existing dependency-based models suffer from noise in dependency trees, which distorts the modeling of contextual information, particularly when introducing dependency types, further exacerbating the propagation and accumulation of errors. In addition, rule-based pruning strategies used to eliminate noise in dependency trees may lose crucial information for capturing relational patterns, whereas unconstrained learning-based pruning strategies may introduce more noisy edges. These two aspects of dependency trees may cause models to produce semantic confusion, which is detrimental to relation extraction. In this study, we propose a Contextual Dependency-Aware Graph Convolutional Network (C-DAGCN) that works on complete dependency trees and perceives the importance of word dependencies from multiple angles without considering the noise in dependency trees. This study includes three parts. First, the sequence model captures semantic information for the input sentence and its words. We considered the appropriate outputs as word and sentence-level representations based on model characteristics. Second, the structure model enhances the description of the sentence structure and its guidance. We consider that position knowledge implies associations between words; therefore, we propose the Current Word Global Relative Position Knowledge (CW-GRPK) to globally enhance text structure modeling and reduce the models’ overreliance on single noisy structure guidance. A dependency-aware module weighs heuristic syntactic knowledge and non-heuristic CW-GRPK to capture fine-grained word-level interactions that effectively distinguish words related to relational semantics. Subsequently, a dependency-guided module, based on the results of the dependency-aware layer, encodes a knowledge-enhanced word graph without losing global linguistic patterns. Third, we constructed high-level linguistic representations based on the results of the sequence and structure model in C-DAGCN as a relational representation and mapped it to the relational decision space for relational prediction. The experimental results demonstrate that our method outperforms nine strong baseline models on two benchmark datasets. Compared with the best baseline Attentive Graph Convolutional Networks (A-GCN) model (Tian et al., 2021), our proposed C-DAGCN model with 90.15 macro-average F1 and 79.52 micro-average F1 achieves 0.28 macro-average F1 and 0.47 micro-average F1 improvement on the SemEval2010-Task8 and ACE2005 datasets, respectively. 11Our code is available at https://github.com/dymyyc/RE_C-DAGCN. The released code when run produces results which are the same as those reported in this paper.

Heartbeat recordings in music therapy bereavement care following suicide: Action research single case study of amplified cardiopulmonary recordings for continuity of care

Bereavement services incorporating family-centered practices are emerging within hospital-based care but are often time-limited and lack personalization. This action research single case study explored one father’s experience of music therapy using amplified cardiopulmonary recordings (ACPR) during bereavement following his son’s death by suicide, to critique current norms and inspire transformative change in systems of care. As co-researchers, a bereaved father, his music therapist, and a music therapy researcher used iterative cycles to qualitatively analyze a series of dialogic reflections upon an 8-year experience of ACPR to construct two overarching themes: 1) continuity experienced as compassion, and 2) process of music therapy with ACPR as tool for resilience and positive growth. Aspects of continuity in the ACPR process, in relation with the music therapist, in journeying through grief, and in the heart and heartbeat were perceived as overwhelming compassion that fostered positive growth in the face of profound loss. We see our study as a first step in promoting culture change by exposing underlying practices, assumptions and policies within the context of hospital-based bereavement care and identifying an exceptional example of possibilities. Our findings add to the literature on action research for transformation by demonstrating that the process of relational knowledge co-creation can be perceived as part of the therapeutic journey.

Parameters of learning during clinical nursing study abroad: Focused analysis of phenomenological data using a change-transformative learning theory lens

AimsTo explore the nature and extent of learning attained as a result of unaccompanied-by-faculty clinical nursing study abroad experiences and to answer the research question ‘what is the nature and extent of learning during study abroad?’. BackgroundFollowing the Covid-19 restrictions, international placement opportunities for student nurses are now resuming. In light of this, it is an opportune time for nurse educators to reflect and consider the effectiveness of clinical study abroad placements as contexts of learning, especially in relation to attainment of desired learning outcomes such as personal and professional growth and the development of culturally competent global graduates. This is an important area to research as specific understanding in relation to the extent of learning and variations in learning between students is limited. Design:The study was situated within the interpretivist paradigm to elicit experiences of study abroad. Aligned to this, a hermeneutic phenomenological methodology was applied to ensure these experiences emerged from the subjective horizon of student nurses. Methods:Following ethical approval, two semi-structured interviews per student (post-return and follow-up) were conducted with student nurses who had undertaken a study abroad experience. Phenomenological hermeneutical data analysis for multiple context research was undertaken and a change-transformative learning theory lens was additionally employed to the analysis to differentiate between the extent of and variations in, learning attained. Twenty UK and European student nurses, who were registered onto a study abroad programme prior to the Covid-19 restrictions participated. Results:Variations between participants were identified in relation to the nature and extent of learning. Participants experienced personal and professional growth and they experienced transformation in relation to self as a person, learner and nurse. However, variations existed when considering the attributes of global graduateness and cultural competence development. Whilst participants changed by expanding their knowledge in relation to global and cultural issues, some participants also appear to have concurrently experienced a reinforcement of ethnocentric frames of reference. ConclusionsAnalysis revealed that study abroad offered opportunities for students to experience change and transformation. Whilst students demonstrated learning in both the domains of change and transformation, transformative learning in all identified outcome areas was not guaranteed. Whilst transformative learning was apparent when considering personal and professional growth, less extensive learning was demonstrated when considering development of the attributes of global graduateness and cultural competence. The paper therefore recognises the complex nature of study abroad experiences and recommends continued investigation in this field.

Lessons from the pandemic: Teacher educators’ use of digital technologies and pedagogies in Vietnam before, during and after the Covid-19 lockdown

This article reports on responses from an online survey designed to explore the before, during and after lockdown experiences of higher education teacher educators in Vietnam (n = 145) who were required to use digital technologies and pedagogies exclusively in their teaching during the 2020/21 lockdown. The data is interpreted using the TPACK framework (Koehler & Mishra, 2009) which enables analysis of the participants’ technological, pedagogical and content knowledge in relation to teaching online using digital tools. The findings indicate mixed responses and experiences of teacher educators during this period with many having struggled with new technologies and unfamiliar pedagogical strategies whilst others enjoyed the opportunity to develop new approaches to their teaching. The paper concludes with key recommendations for best practice in this sector going forward post pandemic including the development of national and institutional e-learning policies, improvements in IT infrastructure and increased provision of professional training.

Analysis of Verilog-based improvements to the memory transfer

Memory copy technology is widely used for data transfer between CPU and memory, and is an important step in all types of operating systems and drivers, and is one of the bottlenecks in the current speed-up of computing. This paper has done more research on the historical development, theoretical basis and experimental details of different memory copy accelerators and related knowledge, and summarised and compared them, with emphasis on reviewing two related papers that provide an overview of their acceleration theory and experiments. The paper concludes that memory copy accelerators using a variety of innovative technologies have largely improved copy speeds and reduced energy consumption, laying a solid foundation for the future development of memory copy acceleration technology, which has been successful in improving and enhancing the user experience with the performance gains of this technology. At the same time, the development of memory copy accelerators has advanced more advanced technologies, such as machine learning, to power the development of human technology.

Improvement of the legislation of Kazakhstan on the prevention of offences by persons sentenced to restriction of liberty

Modern world trends tend to introduce standards under which there is a gradual departure from imprisonment as the main type of criminal punishment of convicts. Following the norms of the current legislation of Kazakhstan, the functions of mon- itoring such persons are carried out by the probation service. It implements a wide range of powers to supervise the registered contingent and interacts in this area with many government agencies and institutions. The article examines the issues of or- ganizing effective preventive work in Kazakhstan with persons sentenced to re- striction of liberty and other measures of criminal punishment not related to deprivation of liberty. The methods used in the work are: analysis of legislative and ap- plied aspects of the activities of state bodies and institutions executing criminal pen- alties, system-structural (scientific knowledge of intra-industry relations), compara- tive analysis (identification of continuity and specificity of various approaches to the formation of an optimal model of interaction between the subjects of preventive ac- tivities), logical method and method of transition from general concepts to private ones. It was found out that the role of the probation service in preventing new of- fences on the part of convicts is great since in recent years their number has been constantly growing, which indicates insufficient preventive work carried out by in- terested state bodies. One of the reasons for this situation is the imperfection of the legal framework governing their activities. The analysis of the current legislation showed the absence of norms in it that create a unified system for organizing pre- ventive work with the registered contingent for all bodies. With this in mind, pro- posals are being made to improve the norms of the Law of Kazakhstan "On Proba- tion".

Perineal care incontinence training for caregivers: randomised controlled trial

ObjectivesThe aim of this study was to implement training to increase the perineal care knowledge of relatives caring for incontinent palliative care patients and to examine the effectiveness of this...

LRseg: An efficient railway region extraction method based on lightweight encoder and self-correcting decoder

This paper proposes a lightweight and efficient railway region extraction model LRseg, which provides technical support for detecting foreign objects on the railway. LRseg consists of a lightweight encoder, self-correcting decoder, and segmentation head. The lightweight encoder is based on lightweight principles and consists of the LR-unit and Focus module. The self-correcting decoder is based on SC-FFM (Self-Correcting Feature Fusion Module) and cascade structure, efficiently utilizing the context and spatial information. The segmentation head introduces PPM (Pyramid Pooling Module) to extract multi-scale context information. At the same time, the segmentation performance of LRseg is enhanced by CIRKD (Cross-Image Relational Knowledge Distillation). The method has 0.78 M parameters and 1.47 G FLOPs (Floating Point of Operations), and the model size and memory demand are only 2.98 MB and 37.5 MB, respectively. On the self-built Railway-seg and public Railsem19 datasets, the method achieved mIoU (mean Intersection over Union) of 92.2% and 92.4%, respectively. When the input image size is 512×512, on Jetson TX2 and personal computer with Intel Core i9-12900, the method achieves 18 FPS and 94 FPS (Frames Per Second), respectively. Combining real-time and accuracy, the method is advantageous over the mainstream models, suitable for on-board devices with continuous work. The code will be released at https://github.com/CV-Altrai2023/LRseg.

Promoting communication between pediatric nurse practitioner students and patients with language barriers utilizing an innovative simulation scenario

BackgroundCommunication and health literacy are essential care components to understand basic health information. Clients with language barriers experience additional difficulties with health literacy and healthcare providers need to be trained in caring for patients with language barriers. AimIn an effort to improve communication abilities of pediatric nurse practitioner students for clients with language barriers, the Promoting Communication in Patients with Language Barriers Simulation was developed. MethodsThe simulation was developed using INACSL standards. Mixed methods were used to evaluate the simulation. ResultsQuantitative and qualitative data showed increased knowledge and confidence in relation to communication in those with language barriers. ConclusionsThe simulation was found to be successful regarding improving knowledge and confidence in communication using translators in clients with language barriers.

Values and representations in land registers and their legal, technical, social effects on land rights as an administrative artefact

Improvements in land administration tend to focus on initiating or completing titling efforts. Yet, finding and monitoring inequality and intransparency of land ownership and of land tenure is equally problematic. The central question is how land registration epitomizes and monitors the distribution of land rights, and if the administrative choices reinforce or hinder the insights into these aspects. The article reasons from a theoretical basis that land rights are socio-technical products of administrative procedures with inscribed concepts and visions of (desirable) farm structures. The analysis relies on an analysis of five specific cases of techno-administrative structures: land registration in combination with cadastres and trade registers; the administrative system of compensation after German unification; the management system controlling land transfers; the system of collecting agrarian statistics; the system of land market statistics. All represent sociotechnical constructs related to current authentic and public information repositories related to land, land rights and statistical data about land. All systems exhibit a very narrow thematic focus and extreme rigidity of system design and design choices. The construction and use of the systems depend on two historically persistent assumptions and narratives: land prices will always increase, and land is held by individual small farm holders. Both these visions and the systematic land information infrastructures conceal certain objects and dynamics, such as existing complex land ownership constellations and land use practices. Secondly, the data collection choices do not align with what land related policies require. Agricultural statistics are example following individual land ownership structures and ignoring private agglomerate ownership structures and dependencies. Consequently, the design of techno-administrative structures related to land lead to insufficient insights of land distribution and equality of land rights. The conclusion is therefore that the land related knowledge and information infrastructures need to be much more aligned with policy interventions and problem-oriented policy making. Currently they act as information silos and rely on outdated visions and assumptions. This requires however new models of land information organisation and governance.

FORMATION OF PROFESSIONAL COMPETENCE OF A LECTURER IN AN INSTITUTION OF HIGHER EDUCATION UNDER INCLUSIVE CONDITIONS

The article describes the process of formation of professional competence of teachers in institutions of higher education in the process of professional activity in the conditions of inclusive education. Now, competence is interpreted as the ability or readiness to implement the acquired knowledge, skills, and abilities in real activity. Competence components are subject and operational knowledge, skills and abilities - ability and readiness to use them in activities and confidence in activities and responsibility for their results. In modern society, which is constantly undergoing changes, the high professionalism and professional competence of teaching specialists, teachers, has acquired an important importance, because the competitiveness of specialists is an urgent issue that is being prepared by a higher education institution. This directly applies to workers in the field of education with an inclusive population, because teachers must be competent in the scientific field of activity, because professional education has always been and continues to be aimed at the comprehensive development of the individual in order to prepare him for active and effective participation in public production with the greatest benefit for themselves and for society as a whole. In world educational practice, the concept of competence acts as a central, a kind of "nodal" concept, because the competence of an individual: combines the intellectual and practical components of education; the concept of competence contains the ideology of interpreting the content of education, which is formed from the result; the competence of the individual has an integrative nature, as it incorporates a number of homogeneous or closely related knowledge and experience belonging to broad spheres of culture and activity (informational, legal, etc.). Personal competence has a certain structure, the components of which are related to a person's ability to solve various problems in everyday, professional or social life. The structure of competence of a person includes: competence in the field of independent cognitive activity; in the sphere of civil and social activities; in the field of social and labor activity; competence in the household sphere; in the field of cultural and recreational activities. Among the knowledge and practical experience formed in the process of a person achieving a certain level of competence are the skills of self-education, critical thinking, independent work, self-organization and self-control, teamwork, the ability to predict the results and possible consequences of various solutions, establish cause-and-effect relationships connections, find, formulate and solve problems.

Determinants of infectious disease-related knowledge among adolescents in Armenia

Abstract Background Adolescence is an important period of life, characterized by increasing level of responsibility and independent decision-making, hence it is crucial to explore the infectious disease (ID) related knowledge, which may affect lifelong healthy behavior and control over own health in adulthood. We assessed the level of knowledge for common IDs and explored associated factors among 15-17 years old adolescents in Armenia. Methods We conducted a survey among adolescents from three public and one private high schools from capital Yerevan and an adjacent province in 2023. The instrument included items on measles, HIV, TB, influenza, HPV, and socio-demographics. Summative scores were calculated for each ID knowledge, and the scores were combined for measles, HIV, and TB. Univariate and multivariable regression explored socio-demographics associated with each of the scores. Results Overall, 368 students completed the survey, most of them being females (64.4%). Nearly 85% have heard about measles and half of them knew that vaccination is the most effective preventive measure (44.5%). About 89%, 78%, and 29% of the adolescents heard about HIV, TB and HPV, respectively, and even few of them identified the correct paths for their transmission and prevention. Almost all (96.5%) heard about influenza, yet 44.1 % reported antibiotics being effective against it. The percent knowledge scores for measles-HIV-TB, influenza, and HPV were 39.7%, 56.3%, and 10.3%, respectively. In the adjusted analysis across all socio-demographics, only the private school type was associated with higher mean score for measles-HIV-TB (p &amp;lt; 0.001), while no differences were found in relation other ID scores. Conclusions There is substantial lack of awareness about the most common infectious diseases among adolescents in Armenia. Targeted interventions should address the knowledge gaps among adolescents and promote safe infectious disease-related behaviors. Key messages • There is substantial lack of awareness about the most common infectious diseases (measles, HIV, TB, HPV, influenza) among adolescents in Armenia. • Targeted interventions should address the infectious disease knowledge gaps among adolescents and promote safe infectious disease-related behaviors.