Search results for: self-driven and self-evaluated learning experience

Authors: Jennifer K. Bowerman, Rhonda L. Reich

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The purpose of this paper is to explore the concepts ACDC (Amore, Consciousness, Discipline, and Commitment) which the authors first discovered as a philosophy and framework for recruitment and organizational development in a successful start-up tech company in Brazil. This paper represents an exploration of these concepts as a potential pedagogical foundation for undergraduate business education in the classroom. It explores whether their application has potential to build emotional and practical resilience in the face of constant organizational and societal change. Derived from Holonomy this paper explains the concepts and develops a narrative around how change influences the operation of organizations. Using examples from leading edge organizational theorists, it explains why a different educational approach grounded in ACDC concepts may not only have relevance for the working world, but also for undergraduates about to enter that world. The authors propose that in the global context of constant change, it makes sense to develop an approach to education, particularly business education, beyond cognitive knowledge, models and tools, in such a way that emotional and practical resilience and creative thinking may be developed. Using the classroom as an opportunity to explore these concepts, and aligning personal passion with the necessary discipline and commitment, may provide students with a greater sense of their own worth and potential as they venture into their ever-changing futures.

Keywords: ACDC, holonomic thinking, organizational learning, organizational change, business pedagogy

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Authors: Ailin Agaahi, Nafise Daneshvar Hoseini, Shahnaz Tamizi, Mehrdad Sabet

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Music education has been recognized as a valuable therapeutic and educational intervention for children with Autism Spectrum Disorder (ASD). This study explores the experiences and perceptions of parents whose children with ASD have participated in music lessons at the Tehran Conservatory. The aim is to understand the impacts and barriers of this educational approach, providing insights into the real-world experiences of families integrating music into the lives of their children. Qualitative research was conducted through in-depth interviews with parents of children with ASD enrolled in the Tehran Conservatory's music program. The interviews examined parental motivations, observations of their child's progress, and evaluations of the program's effectiveness. Preliminary findings suggest that the music program positively impacts social interaction, emotional regulation, and communication. Parents highlighted the program's adaptability to meet the unique needs of children with ASD and the supportive environment fostered by specialized instructors. However, several barriers were identified, including the need for greater awareness and acceptance of music education for children with ASD and the limited availability of similar programs in the region. This research contributes valuable insights from parents and caregivers, emphasizing the importance of inclusive and effective music programs to support the needs of children with ASD and their families.

Keywords: autism spectrum disorder, music education, therapeutic intervention, parental perspectives

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Authors: O. Yu Shchelkova, E. B. Usmanova

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Introduction: Last decades scientific research of quality of life (QoL) is developing fast worldwide. QoL concept pays attention to emotional experience of disease in patients, particularly to personal sense of possibility to satisfy actual needs and possibility of full social functioning in spite of disease limitations. QoL in oncological patients is studied intensively. Nevertheless, the issue of QoL in patients with bone tumors focused on psychological factors of QoL and relation to disease impact on QoL is not discussed. The aim of the study was to reveal the basic aspects and personality factors of QoL in patients with bone tumor. Results: Study participants were 139 patients with bone tumors. The diagnoses were osteosarcoma (n=42), giant cell tumor (n=32), chondrosarcoma (n=32), Ewing sarcoma (n=10) and bone metastases (n=23). The study revealed that patients with bone metastases assess their health significantly worse than other patients. Besides patients with osteosarcoma evaluate their general health higher than patients with giant cell tumors. Social functioning in patients with chondrosarcoma is higher than in patients with bone metastases and patients with giant cell tumor. Patients with chondrosarcoma have higher physical functioning and less restricted in daily activities than patients with bone metastases. Patients with bone metastases characterize their pain as more widespread than patients with primary bone tumors and have more functional restrictions due to bone incision. Moreover, the study revealed personality significant influence on QoL related to bone tumors. Such characteristics in structure of personality as high degree of self-consciousness, personal resources, cooperation and disposition to positive reappraisal in difficult situation correspond to higher QoL. Otherwise low personal resources and slight problem solving behaviour, low degree of self-consciousness and high social dependence correspond to decrease of QoL in patients with bone tumors. Conclusion: Patients with bone metastasis have lower QoL compared to patients with primary bone tumors. Patients with giant cell tumor have the worth quality of life among patients with primary bone tumors. Furthermore, the results revealed differences in QoL parameters associated with personality characteristics in patients with bone tumors. Such psychological factors as future goals, interest in life and emotional saturation, besides high degree of personal resources and cooperation influence on increasing QoL in patients with bone tumors.

Keywords: quality of life, psychological factors, bone tumor, personality

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Authors: Dasom Kim, Chen Liu, Myungsu Lim, Su-Hyeon Jeon, ByeoungKug Jeon, Kee-Young Kwahk, Namgyu Kim

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Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we previously proposed a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. In this paper, we design a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: big data analysis, document classification, multi-category, text mining, topic analysis

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Authors: Marisa P. De Brito

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The internet is affecting the way the industry operates and communicates. It is also becoming a customary means for leisure, tourism, and hospitality consumers to seek and exchange information and views on hotels, destinations events and attractions, or to develop social ties with other users. On the one hand, the internet is a rich field to conduct leisure, tourism, and hospitality research; on the other hand, however, there are few researchers formally embracing online methods of research, such as netnography. Within social sciences, netnography falls under the interpretative/ethnographic research methods umbrella. It is an adaptation of anthropological techniques such as participant and non-participant observation, used to study online interactions happening on social media platforms, such as Facebook. It is, therefore, a research method applied to the study of online communities, being the term itself a contraction of the words network (as on internet), and ethnography. It was developed in the context of marketing research in the nineties, and in the last twenty years, it has spread to other contexts such as education, psychology, or urban studies. Since netnography is not universally known, it may discourage researchers and educators from using it. This work offers guidelines for researchers wanting to apply this method in the field of leisure, tourism, and hospitality or for educators wanting to teach about it. This is done by means of a double approach: a content analysis of the literature side-by-side with educational data, on the use of netnography. The content analysis is of the incidental research using netnography in leisure, tourism, and hospitality in the last twenty years. The educational data is the author and her colleagues’ experience in coaching students throughout the process of writing a paper using primary netnographic data - from identifying the phenomenon to be studied, selecting an online community, collecting and analyzing data to writing their findings. In the end, this work puts forward, on the one hand, a research agenda, and on the other hand, an educational roadmap for those wanting to apply netnography in the field or the classroom. The educator’s roadmap will summarise what can be expected from mini-netnographies conducted by students and how to set it up. The research agenda will highlight for which issues and research questions the method is most suitable; what are the most common bottlenecks and drawbacks of the method and of its application, but also where most knowledge opportunities lay.

Keywords: netnography, online research, research agenda, educator's roadmap

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Authors: Andrea Gatti, Federica Coppotelli, Ma Primavera, Laura Palmieri, Umberto Tarantino

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Aim of study: Scientific literature is scarce of studies and reviews valuing the pros and cons of the paratricipital approach for the treatment of humeral shaft fractures; the lateral paratricipital approach is a valid alternative to the classical posterior approach to the humeral shaft as it preserves both the triceps muscle and the elbow extensor mechanisms; based on our experience, this retrospective analysis aims at analyzing outcome, risks and benefits of the lateral paratricipital approach for humeral shaft fractures. Methods: Our study includes 14 patients treated between 2018 and 2019 for unilateral humeral shaft fractures: 13 with a B1 or B2 and a patient with a C fracture type (according to the AO/ATO Classification); 6 of our patients identified as male while 8 as female; age average was 57.8 years old (range 21-73 years old). A lateral paratricipital approach was performed on all 14 patients, sparing the triceps muscle by avoiding the olecranon osteotomy and by assessing the integrity and the preservation of the radial nerve; the humeral shaft fracture osteosynthesis was performed by means of plates and screws. After surgery all patients have started elbow functional rehabilitation with acceptable pain management. Post-operative follow-up has been carried out by assessing radiographs, MEPS (Mayo Elbow Performance Score) and DASH (Disability of Arm Shoulder and Hand) functional assessment and ROM of the affected joint. Results: All 14 patients had an optimal post-operative follow-up with an adequate osteosynthesis and functional rehabilitations by entirely preserving the operated elbow joint; the mean elbow ROM was 0-118.6 degree (range of 0-130) while the average MEPS score was 86 (range75-100) and 79.9 for the DASH (range 21.7-86.1). Just 2 patients suffered of temporary radial nerve apraxia, healed in the subsequent follow-ups. CONCLUSION: The lateral paratricipital approach preserve both the integrity of the triceps muscle and the elbow biomechanism but we do strongly recommend additional studies to be carried out to highlight differences between it and the classical posterior approach in treating humeral shaft fractures.

Keywords: paratricepital approach, humerus shaft fracture, posterior approach humeral shaft, paratricipital postero-lateral approach

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: Michael W. Markowitz, Jeffrey Gingerich

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The landscape of higher education in the United States has undergone significant changes in the last 25 years. What was once a domain of competition among prospective students for a limited number of college and university seats has become a marketplace in which institutions vie for the enrollment of educational consumers. A central figure in this paradigm shift has been the Chief Academic Officer (CAO), whose institutional role has also evolved beyond academics to include such disparate responsibilities as strategic planning, fiscal oversight, student recruitment, fundraising and personnel management. This paper explores the scope and impact of this transition by, first, explaining its context: the intersection of key social, economic and political factors in neo-conservative, late 20th Century America that redefined the value and accountability of institutions of higher learning. This context, in turn, is shown to have redefined the role and function of the CAO from a traditional academic leader to one centered on the successful application of corporate principles of organizational and fiscal management. Information gathered from a number of sitting Provosts, Vice-Presidents of Academic Affairs and Deans of Faculty is presented to illustrate the parameters of this change, as well as the extent to which today’s academic officers feel prepared and equipped to fulfill this broader institutional role. The paper concludes with a discussion of the impact of this transition on the American academy and whether it serves as a portend of change to come in higher education systems around the globe.

Keywords: academic administration, higher education, leadership, organizational management

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Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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Authors: Martial Amou

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This study was carried out to assess the situation of households’ livelihood under a changing climate pattern in the Zio district of Togo, West Africa. The study examined three important aspects: (i) assessment of households’ livelihood situation under a changing climate pattern, (ii) farmers’ perception and understanding of local climate change, (iii) determinants of adaptation strategies undertaken in cropping pattern to climate change. To this end, secondary sources of data, and survey data collected from 235 farmers in four villages in the study area were used. Adapted conceptual framework from Sustainable Livelihood Framework of DFID, two steps Binary Logistic Regression Model and descriptive statistics were used in this study as methodological approaches. Based on Sustainable Livelihood Approach (SLA), various factors revolving around the livelihoods of the rural community were grouped into social, natural, physical, human, and financial capital. Thus, the study came up that households’ livelihood situation represented by the overall livelihood index in the study area (34%) is below the standard average households’ livelihood security index (50%). The natural capital was found as the poorest asset (13%) and this will severely affect the sustainability of livelihood in the long run. The result from descriptive statistics and the first step regression (selection model) indicated that most of the farmers in the study area have clear understanding of climate change even though they do not have any idea about greenhouse gases as the main cause behind the issue. From the second step regression (output model) result, education, farming experience, access to credit, access to extension services, cropland size, membership of a social group, distance to the nearest input market, were found to be the significant determinants of adaptation measures undertaken in cropping pattern by farmers in the study area. Based on the result of this study, recommendations are made to farmers, policy makers, institutions, and development service providers in order to better target interventions which build, promote or facilitate the adoption of adaptation measures with potential to build resilience to climate change and then improve rural livelihood.

Keywords: climate change, rural livelihood, cropping pattern, adaptation, Zio District

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: Stephen Osei Akyiaw, Divine Kwabena Atta Kyere-Owusu

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Malaria has been a worldwide menace of a health condition to human beings for several decades with majority of people on the African continent with most causalities where Ghana is no exception. Therefore, this study employed the use of animation to enhance awareness creation on the spread and prevention of Malaria in Effutu Communities in the Central Region of Ghana. Working with the interpretivist paradigm, this study adopted Art-Based Research, where the AIDA Model and Cognitive Theory of Multimedia Learning (CTML) served as the theories underpinning the study. Purposive and convenience sampling techniques were employed in selecting sample for the study. The data collection instruments included document review and interviews. Besides, the study developed an animation using the local language of the people as the voice over to foster proper understanding by the rural community folks. Also, indigenous characters were used for the animation for the purpose of familiarization with the local folks. The animation was publicized at Health Town Halls within the communities. The outcomes of the study demonstrated that the use of animation was effective in enhancing the awareness creation for preventing and controlling malaria disease in rural communities in Effutu Communities in the Central Region of Ghana. Health officers and community folks expressed interest and desire to practice the preventive measures outlined in the animation to help reduce the spread of Malaria in their communities. The study, therefore, recommended that animation could be used to curtail the spread and enhanced the prevention of Malaria.

Keywords: malaria, animation, prevention, communities

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Authors: Chidozie C. Nwobi-Okoye, Basil Q. Ochieze, Stanley Okiy

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This research reports on the modeling of age hardening process using adaptive neuro-fuzzy inference system (ANFIS). The age hardening output (Hardness) was predicted using ANFIS. The input parameters were ageing time, temperature and percentage composition of cow horn particles (CHp%). The results show the correlation coefficient (R) of the predicted hardness values versus the measured values was of 0.9985. Subsequently, values outside the experimental data points were predicted. When the temperature was kept constant, and other input parameters were varied, the average relative error of the predicted values was 0.0931%. When the temperature was varied, and other input parameters kept constant, the average relative error of the hardness values predictions was 80%. The results show that ANFIS with coarse experimental data points for learning is not very effective in predicting process outputs in the age hardening operation of A356 alloy/CHp particulate composite. The fine experimental data requirements by ANFIS make it more expensive in modeling and optimization of age hardening operations of A356 alloy/CHp particulate composite.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), age hardening, aluminum alloy, metal matrix composite

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Authors: Rajendra Chetty

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Decolonial aesthetics departs and delinks from colonial ideas about ‘the arts’ and the modernist/colonial work of aesthetics. Education is trapped in the western epistemic and hermeneutical vocabulary, hence it is necessary to introduce new concepts and work the entanglement between co-existing concepts. This paper will discuss the contribution of Ronnie Govender, a South African writer, to build decolonial sensibilities and delink from the grand narrative of the colonial and apartheid literary landscape in Govender’s text, At the Edge and other Cato Manor Stories. Govender uses the world of art to make a decolonial statement. Decolonial artists have to work in the entanglement of power and engage with a border epistemology. Govender’s writings depart from an embodied consciousness of the colonial wound and moves toward healing. Border thinking and doing (artistic creativity) is precisely the decolonial methodology posited by Linda T. Smith, where theory comes in the form of storytelling. Govender’s stories engage with the wounds infringed by racism and patriarchy, two pillars of eurocentric knowing, sensing, and believing that sustain a structure of knowledge. This structure is embedded in characters, institutions, languages that regulate and mange the world of the excluded. Healing is the process of delinking, or regaining pride, dignity, and humanity, not through the psychoanalytic cure, but the popular healer. The legacies of the community of Cato Manor that was pushed out of their land are built in his stories. Decoloniality then is a concept that carries the experience of liberation struggles and recognizes the strenuous conditions of marginalized people together with their strength, wisdom, and endurance. Govender’s unique performative prose reconstructs and resurrects the lives of the people of Cato Manor, their vitality and humor, pain and humiliation: a vibrant and racially integrated community destroyed by the regime’s notorious racial laws. The paper notes that Govender’s objective with his plays and stories was to open windows to both the pain and joy of life; a mission that is not didactic but to shine a torch on both mankind’s waywardness as well as its inspiring and often moving achievements against huge odds.

Keywords: Govender, decoloniality, delinking, exclusion, racism, Cato Manor

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Authors: Emma Groenewald

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In 1994, numerous policies of a democratic dispensation envisage social justice and the transformation of the South Africa society. The drive for transformation and social justice resulted in an increasing number of university students from diverse backgrounds, which in turn, lead to the establishment of Sol Plaatje University (SPU) in 2014. A re-curriculated B. Ed. programme at SPU aims to equip students with knowledge and skills to realise the aim of social justice and to enhance the transformation of the South African society. The aim of this study is to explore the experiences and perceptions of students at a diverse university campus on a curriculum that aims to promote social justice. Four education modules, with the assumption that it reflects social justice content, were selected. Four students, representative of different ethnic and language groupings found at the SPU, were chosen as participants. Data were generated by the participants through four reflective exercises on each of the modules, spread over a period of four years. The module aims, linked with the narratives of the participants' perceptions and experiences of each module, provided an overview of the enacted curriculum. A qualitative research design with an interpretivist approach informed by Vygotsky's theory of learning was used. The participants' experiences of the four modules were analysed, and their views were interpreted. The students' narratives shed light on the strengths and weaknesses of how the B.Ed. Curriculum works towards social justice and revealed student's perceptions of otherness. From the narratives it became apparent that module did promote a social justice orientation in prospective teachers trained at a university.

Keywords: student diversity, social justice, transformation, teacher education

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Authors: Ellen Dahl Gundersen, Berit Johannessen

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Introduction: Dementia and depression are common mental disorders of nursing home residents. The care of these residents consists of providing both physical, social and mental care. Too often, the physical needs are given priority, and municipal health services are urged to focus more on the patients mental and social needs. The presence of dogs may have positive impact on the mental health of nursing home residents by improving mood, social interaction and enjoyment of the visits. The voluntary organization Red Cross, has given priority to this subject by training and certifying dogs and owners (equipages), committed for regular visits at local nursing homes. Focus of this study: How do the dog owners and employees experience the presence of a dog equipage concerning the mental health of nursing home residents? Method: Individual interviews with 8-10 certified dog owners who are volunteers from Red Cross, contributing with regular visits at local nursing homes. Focus group interviews with 10 employees working in two different nursing homes. Preliminary results: Five to seven residents and one or two employees attended weekly dog equipage visits during a period of six months. The presence of an equipage seems to have made the residents calm and more social orientated with a lighter mood and better verbal expression. Some of the residents with dementia remembered the name of the dog from one week to another. The informants also reported positive outcome for the residents by their opportunity to give and get close through physical contact with a dog. Further, the presence of an equipage affected the atmosphere at the nursing home positively by promoting joy and initiating conversations about dogs. A conscious approach by the dog owners towards the residents seems to be of significance to this matter. The positive attitude and support from employees also seem to be of crucial importance for the maintenance of these visits. Conclusion: The presence of trained dog equipages in nursing homes seems to have had an overall positive impact on the mental health of residents. A conscious approach from the dog owners as well as positive support from employees seems to have a crucial impact on the success and maintenance of the visits. These findings correspond well to former research and can thereby give implications for more extended use of dogs as a mental health promoting initiative towards geriatric consumers of municipal health care services. Further research through larger studies is needed.

Keywords: animal assisted intervention, geriatric mental health, nursing home, resident

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Authors: Ricardo Hugo Gonzalez, Amanda Figueiredo Vasconcelos, Francisco Loureiro Neto Monteiro, Yara Luiza Freitas Silva, Ana Cristina Lindsay, Márcia Maria Tavares Machado

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The use of sport as an integration mean is a very important tool regarding the social involvement of children and teenagers in a vulnerability situation. This study aims to report the experiences of a multidisciplinary program that intends to improve the quality of life of children and teenagers in Fortaleza, in the Northeast of Brazil. More than 400 children and teenagers aging 11 and 16 years participated in this study. Poor communities experience many particular difficulties in the urban centers such as violence, poor housing conditions, unemployment, lack in health care and deficient physical education in school. Physical education, physiotherapy, odontology, medicine and pharmacy students are responsible for the activities in the project supervised by a general coordinator and a counselor teacher of each academic unit. There are classes about team sports like basketball and soccer. Lectures about sexual behavior and sexually transmitted diseases are ministered beside the ones about oral health education, basic life support education, first aids, use and care with pharmaceuticals and orientations about healthy nutrition. In order to get the children’s family closer, monthly informative lectures are ministered. There is also the concern about reflecting the actions and producing academic paperwork such as graduation final projects and books. The number of participants has oscillated lately, and one of the causes is the lack of practicing physical activities and sports regularly. However, 250 teenagers have participated regularly for at least two years. These teenagers have shown a healthier lifestyle and a better physical fitness profile. The resources for maintaining the project come from the Pro-Reitoria of Extension, Federal University of Ceara, as well as from the PROEXT/MEC, Federal Government. Actions of this nature need to be done thinking for long periods so the effects results can become effective. Public and private investments are needed due to low socioeconomic families who are most vulnerable and have fewer opportunities to enhance to health prevention services.

Keywords: children and teenagers, health, multidisciplinary program, quality of life

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Noor Ayuni Che Zakaria, Takashi Komeda, Cheng Yee Low, Kaoru Inoue, Fazah Akhtar Hanapiah

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Previous studies have shown that there are arguments regarding the reliability and validity of the Ashworth and Modified Ashworth Scale towards evaluating patients diagnosed with upper limb disorders. These evaluations depended on the raters’ experiences. This initiated us to develop an upper limb disorder part-task trainer that is able to simulate consistent upper limb disorders, such as spasticity and rigidity signs, based on the Modified Ashworth Scale to improve the variability occurring between raters and intra-raters themselves. By providing consistent signs, novice therapists would be able to increase training frequency and exposure towards various levels of signs. A total of 22 physiotherapists and occupational therapists participated in the study. The majority of the therapists agreed that with current therapy education, they still face problems with inter-raters and intra-raters variability (strongly agree 54%; n = 12/22, agree 27%; n = 6/22) in evaluating patients’ conditions. The therapists strongly agreed (72%; n = 16/22) that therapy trainees needed to increase their frequency of training; therefore believe that our initiative to develop an upper limb disorder training tool will help in improving the clinical education field (strongly agree and agree 63%; n = 14/22).

Keywords: upper limb disorder, clinical education tool, inter/intra-raters variability, spasticity, modified Ashworth scale

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Authors: Nihal Atif Salim

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To improve the quality of life in cities, a variety of interventions are used. Noise is a substantial and important sort of pollution that has a negative impact on the urban environment and human health. According to the complaint survey, it ranks second among environmental contamination complaints (conducted by EEAA in 2019). The most significant source of noise in the city is traffic noise. In order to improve the sound urban environment, many physical techniques are applied. In the local area, noise barriers are considered as one of the most appropriate physical techniques along existing traffic routes. Alexandria is Egypt's second-largest city after Cairo. It is located along the Mediterranean Sea, and El- Gish Road is one of the city's main arteries. It impacts the waterfront promenade that extends along with the city by a high level of traffic noise. The purpose of this paper is to clarify the design considerations for the most appropriate noise barrier type along with the promenade, with the goal of improving the Quality of Life (QOL) and the sonic urban environment specifically. The proposed methodology focuses on how noise affects human perception and the environment. Then it delves into the various physical noise control approaches. After that, the paper discusses sustainable design decisions making. Finally, look into the importance of incorporating sustainability into design decisions making. Three stages will be followed in the case study. The first stage involves doing a site inspection and using specific sound measurement equipment (a noise level meter) to measure the noise level along the promenade at many sites, and the findings will be shown on a noise map. The second step is to inquire about the site's user experience. The third step is to investigate the various types of noise barriers and their effects on QOL along existing routes in order to select the most appropriate type. The goal of this research is to evaluate the suitable design of noise barriers that fulfill environmental and social perceptions while maintaining a balanced approach to the noise issue in order to improve QOL along existing roadways in the local area.

Keywords: noise pollution, sonic urban environment, traffic noise, noise barrier, acoustic sustainability, noise reduction techniques

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Knol Hester, Müller Swantje, Danchenko Natalya

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Objective: Falls in older people cause an autonomy loss and result in an economic burden. LCare is an AI-based application to manage fall risks. The study's aim was to assess the effect of LCare use on patient outcomes in nursing homes in Germany. Methods: LCare identifies and monitors fall risks through a 3D-gait analysis and a digital questionnaire, resulting in tailored recommendations on fall prevention. A study was conducted with AOK Baden-Württemberg (01.09.2019- 31.05.2021) in 16 care facilities. Assessments at baseline and follow-up included: a fall risk score; falls (baseline: fall history in the past 12 months; follow-up: a fall record since the last analysis); fall-related injuries and hospitalizations; gait speed; fear of falling; psychological stress; nurses experience on app use. Results: 94 seniors were aged 65-99 years at the initial analysis (average 84±7 years); 566 mobility analyses were carried out in total. On average, the fall risk was reduced by 17.8 % as compared to the baseline (p<0.05). The risk of falling decreased across all subgroups, including a trend in dementia patients (p=0.06), constituting 43% of analyzed patients, and patients with walking aids (p<0.05), constituting 76% of analyzed patients. There was a trend (p<0.1) towards fewer falls and fall-related injuries and hospitalizations (baseline: 23 seniors who fell, 13 injury consequences, 9 hospitalizations; follow-up: 14 seniors who fell, 2 injury consequences, 0 hospitalizations). There was a 16% improvement in gait speed (p<0.05). Residents reported less fear of falling and psychological stress by 38% in both outcomes (p<0.05). 81% of nurses found LCare effective. Conclusions: In the presented study, the use of LCare app was associated with a reduction of fall risk among nursing home residents, improvement of health-related outcomes, and a trend toward reduction in injuries and hospitalizations. LCare may help to improve senior resident care and save healthcare costs.

Keywords: falls, digital healthcare, falls prevention, nursing homes, seniors, AI, digital assessment

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Authors: Colin David La Grange, Lisa Frost Ramsay

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Hydrogen sulphide (H2S) is a minor component of landfill gas, but significant in its distinct odorous quality and its association with landfill-related community complaints. The World Health Organisation (WHO) provides two guidelines for H2S: a health guideline at 150 µg/m3 on a 24-hour average, and a nuisance guideline at 7 µg/m3 on a 30-minute average. Albeit a practical distinction for impact assessment, this paper highlights the danger of the apparent dualism between nuisance and health impact, particularly when it is used to dismiss community concerns of perceived health impacts at low concentrations of H2S, as in the case of a community battle against the impacts of a landfill in Shongweni, KwaZulu-Natal, South Africa. Here community members reported, using a community developed mobile phone application, a range of health symptoms that coincided with, or occurred subsequent to, odour events and localised H2S peaks. Local doctors also documented increased visits for symptoms of respiratory distress, eye and skin irritation, and stress after such odour events. Objectively measured H2S and other pollutant concentrations during these events, however, remained below WHO health guidelines. This case study highlights the importance of the physiological link between the experience of environmental nuisance and overall health and wellbeing, showing these to be less distinct than the WHO guidelines would suggest. The potential mechanisms of impact of an odorous plume, with key constituents at concentrations below traditional health thresholds, on psychologically and/or physiologically sensitised individuals are described. In the case of psychological sensitisation, previously documented mechanisms such as aversive conditioning and odour-triggered panic are relevant. Physiological sensitisation to environmental pollutants, evident as a seemingly disproportionate physical (allergy-type) response to either low concentrations or a short duration exposure of a toxin or toxins, remains extensively examined but still not well understood. The links between a heightened sensitivity to toxic compounds, accumulation of some compounds in the body, and a pre-existing or associated immunological stress disorder are presented as a possible explanation.

Keywords: immunological stress disorder, landfill odour, odour nuisance, odour sensitisation, toxin accumulation

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Authors: Roberto Machado

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We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, analyzing 2,996 studies and synthesizing 41 of them to explore the evolution of data science and its integration into geography. By employing optimization algorithms, we accelerated the review process, significantly enhancing the efficiency and precision of literature selection. Our findings indicate that data science has developed over five decades, facing challenges such as the diversified integration of data and the need for advanced statistical and computational skills. In geography, the integration of data science underscores the importance of interdisciplinary collaboration and methodological innovation. Techniques like large-scale spatial data analysis and predictive algorithms show promise in natural disaster management and transportation route optimization, enabling faster and more effective responses. These advancements highlight the transformative potential of data science in geography, providing tools and methodologies to address complex spatial problems. The relevance of this study lies in the use of optimization algorithms in systematic reviews and the demonstrated need for deeper integration of data science into geography. Key contributions include identifying specific challenges in combining diverse spatial data and the necessity for advanced computational skills. Examples of connections between these two fields encompass significant improvements in natural disaster management and transportation efficiency, promoting more effective and sustainable environmental solutions with a positive societal impact.

Keywords: data science, geography, systematic review, optimization algorithms, supervised learning

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Authors: Vertika Goswami, Gargi Sharma

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The rapid evolution of fintech has led to the rise of robo-advisor platforms that utilize artificial intelligence (AI) and machine learning to offer personalized investment solutions efficiently and cost-effectively. This research paper conducts a comprehensive sentiment analysis of investor experiences with these platforms, employing natural language processing (NLP) and sentiment classification techniques. The study investigates investor perceptions, engagement, and satisfaction, identifying key drivers of positive sentiment such as clear communication, low fees, consistent returns, and robust security. Conversely, negative sentiment is linked to issues like inconsistent performance, hidden fees, poor customer support, and a lack of transparency. The analysis reveals that addressing these pain points—through improved transparency, enhanced customer service, and ongoing technological advancements—can significantly boost investor trust and satisfaction. This paper contributes valuable insights into the fields of behavioral finance and fintech innovation, offering actionable recommendations for stakeholders, practitioners, and policymakers. Future research should explore the long-term impact of these factors on investor loyalty, the role of emerging technologies, and the effects of ethical investment choices and regulatory compliance on investor sentiment.

Keywords: artificial intelligence in finance, automated investment, financial technology, investor satisfaction, investor sentiment, robo-advisors, sentimental analysis

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Ayman Al Yaari, Montaha Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Background & Aims: Audio-visual aids and computer-aided language instruction (CALI) have been documented to improve receptive skills, namely listening skills, in normal students. The increased listening has been attributed to the understanding of other interlocutors' speech, but recent experiments have suggested that audio-visual aids and CALI should be tested against the listening of students of special needs to see the effects of the former in the latter. This investigation described the effect of audio-visual aids and CALI on the performance of these students. Methods: Pre-and-posttests were administered to 40 students of special needs of both sexes at al-Malādh school for students of special needs aged between 8 and 18 years old. A comparison was held between this group of students and another similar group (control group). Whereas the former group underwent a listening course using audio-visual aids and CALI, the latter studied the same course with the same speech language therapist (SLT) with the classical method. The outcomes of the two tests for the two groups were qualitatively and quantitatively analyzed. Results: Significant improvement in the performance was found in the first group (treatment group) (posttest= 72.45% vs. pre-test= 25.55%) in comparison to the second (control) (posttest= 25.55% vs. pre-test= 23.72%). In comparison to the males’ scores, the scores of females are higher (1487 scores vs. 1411 scores). Suggested results support the necessity of the use of audio-visual aids and CALI in teaching listening at the schools of students of special needs.

Keywords: listening, receptive skills, audio-visual aids, CALI, special needs

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Authors: Abigail Kusi Amponsah, Evans Frimpong Kyei, John Bright Agyemang, Hanson Boakye, Joana Kyei-Dompim, Collins Kwadwo Ahoto, Evans Oduro

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Staff shortages, deficient knowledge, inappropriate attitudes, demanding workloads, analgesic shortages, and low prioritization of pain management have been identified in earlier studies as the nursing-related barriers to optimal children’s pain management. These studies have mainly been undertaken in developed countries, which have different healthcare dynamics than those in developing countries. The current study, therefore, sought to identify and understand the nursing-related barriers to children’s pain management in the Ghanaian context. A descriptive qualitative study was conducted among 28 purposively sampled nurses working in the pediatric units of five hospitals in the Ashanti region of Ghana. Over the course of three months, participants were interviewed on the barriers which prevented them from optimally managing children’s pain in practice. Recorded interviews were transcribed verbatim and deductively analysed based on a conceptual interest in pain assessment and management-related barriers. NVivo 12 plus software guided data management and analyses. The mean age of participating nurses was 30 years, with majority being females (n =24). Participants had worked in the nursing profession for an average of five years and in the pediatric care settings for an average of two years. The nursing-related barriers identified in the present study included communication difficulties in assessing and evaluating pain management interventions with children who have nonfunctional speech, insufficient training, misconceptions on the experience of pain in children, lack of assessment tools, and insufficient number of nurses to manage the workload and nurses’ inability to prescribe analgesics. The present study revealed some barriers which prevented Ghanaian nurses from optimally managing children’s pain. Nurses should be educated, empowered, and supported with the requisite material resources to effectively manage children’s pain and improve outcomes for families, healthcare systems, and the nation. Future studies should explore the facilitators and barriers from other stakeholders involved in pediatric pain management

Keywords: Nursing-Related Barriers, Children, Pain Management, Ghana

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Authors: Xue Wang, Li-Wei Fan

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The technology innovation has become the driving force of social and economic development and transformation. The guidance and support of public policies is an important condition to promote the realization of technology innovation goals. Policy effectiveness evaluation is instructive in policy learning and adjustment. This paper reviews existing studies and systematically evaluates the effectiveness of policy-driven technological innovation. We used 167 articles from WOS and CNKI databases as samples to clarify the measurement of technological innovation indicators and analyze the classification and application of policy evaluation methods. In general, technology innovation input and technological output are the two main aspects of technological innovation index design, among which technological patents are the focus of research, the number of patents reflects the scale of technological innovation, and the quality of patents reflects the value of innovation from multiple aspects. As for policy evaluation methods, statistical analysis methods are applied to the formulation, selection and evaluation of the after-effect of policies to analyze the effect of policy implementation qualitatively and quantitatively. The bibliometric methods are mainly based on the public policy texts, discriminating the inter-government relationship and the multi-dimensional value of the policy. Decision analysis focuses on the establishment and measurement of the comprehensive evaluation index system of public policy. The economic analysis methods focus on the performance and output of technological innovation to test the policy effect. Finally, this paper puts forward the prospect of the future research direction.

Keywords: technology innovation, index, policy effectiveness, evaluation of policy, bibliometric analysis

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Authors: Nadya Patel, Jawn Lim

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Foresight 3.0 is a synergistic methodology that encompasses systems analysis, future studies, capacity building, and forward planning. These components are interconnected, fostering a collective anticipatory intelligence that promotes societal resilience (Ravetz, 2020). However, traditional applications of these strands can often fall short, leading to missed opportunities and narrow perspectives. Therefore, Foresight 3.0 champions a holistic approach to tackling complex issues, focusing on systemic transformations and power dynamics. Businesses are pivotal in preparing the workforce for an increasingly uncertain and complex world. This necessitates the adoption of innovative tools and methodologies, such as Foresight 3.0, that can better equip young employees to anticipate and navigate future challenges. Firstly, the incorporation of its methodology into workplace training can foster a holistic perspective among employees. This approach encourages employees to think beyond the present and consider wider social, economic, and environmental contexts, thereby enhancing their problem-solving skills and resilience. This paper discusses our research on integrating Foresight 3.0's transformative principles with a newly developed Critical Design Futures (CDF) framework to equip organisations with the ability to innovate for the world's most complex social problems. This approach is grounded in 'collective forward intelligence,' enabling mutual learning, co-innovation, and co-production among a diverse stakeholder community, where business transformation and innovation are achieved.

Keywords: business transformation, innovation, foresight, critical design

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Authors: Ming Yi Hsu, Hui Jung Chao

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The anxiety and depression adolescents in Taiwan experience can cause suicide attempts and result in unfortunate deaths. An effective method for relieving anxiety and depression is brisk walking; a moderate and low intensity aerobic exercise, which uses large muscle groups rhythmically. The research purpose was to investigate the effects of a 12-week, school-based, brisk-walking program in decreasing anxiety and depression, and in improving self-concept among high school students living in central Taiwan. A quasi-experiment using the time series design (T1 T2 X T3 T4) was conducted. The Beck Youth Inventories 2 (BYI-II) Chinese version was given four times: the first time T1 was in the 4th week prior to intervention, T2 was in the intervention week, T3 was in the 6th week after the start of the intervention period and T4 was in the 12th week post intervention. The baseline phase of the time series constituted T1 and T2. The intervention phase constituted T2, T3, and T4. The amounts of brisk walking were recorded by self-report The Generalized Estimating Equation (GEE) was used to examine the effects of brisk walking on anxiety, depression, and self-concept. The independent t-test was used to compare mean scores on three dependent variables between brisk walking over and less than 90-minutes per week. Findings revealed that levels of anxiety and self-concept had nonsignificant change during the baseline phase, while the level of depression increased significantly. In contrast, the study demonstrated significant decreases in anxiety and depression as well as increases in positive self-concept (p=.001, p<.001, p=.017) during the intervention phase. Furthermore, a subgroup analysis was completed on participants who demonstrated elevated anxiety (23.4%), and depression (29.7%), and below average self-concept (18.6%) at baseline (T2). The subgroup of anxious, depressed, or low self-concept participants who received the brisk-walking intervention demonstrated significant decreases in anxiety and depression, and significant increases in self-concept scores. Participants who engaged in brisk walking over 90 minutes per week reported decreased mean scores on anxiety (t=-2.395, p=.035) and depression (t=-2.142, p=.036) in contrast with those who engaged in brisk-walking time less than 90 minutes per week. Regarding the effects on participants whose anxiety, scores were within the normal range at baseline, there was demonstrated significant decrease in the level of anxiety when they increased their time on brisk walking before each term examination. Overall, the brisk-walking program was effective and feasible to promote adolescents’ mental health by decreasing anxiety and depression as well as elevating self-concept. It also helped adolescents from anxiety before term examinations.

Keywords: adolescents, anxiety, depression, self-concept

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