Advanced Journal of Management, Humanity and Social Science

Abstract This study examines the impact of microfinance services on the financial sustainability and performance of medium-sized enterprises (SMEs) in Mazar-e-Sharif, Afghanistan, using data from 100 firms selected through systematic random sampling. The primary objective is to assess how microcredit access, savings services, and entrepreneurial development training affect return on assets (ROA) and financial sustainability (FS), while controlling for firm age and size. Data were collected via structured questionnaires administered to SME owners/managers, with reliability confirmed by Cronbach's alpha of 0.780 (N=100 items) and content validity established through review by 10 Afghan microfinance experts. Analysis employed descriptive statistics, Pearson correlation matrices, and multiple linear regression models following established SME research methodologies. The first regression model revealed that internal finance (β=0.012, t=10.78, p<0.001) and trade credit (β=0.008, t=7.23, p<0.001) significantly enhance ROA (R²=0.61, F=24.37, p<0.001), while non-institutional finance shows a negative effect (β=-0.130, p=0.017). The second model demonstrated strong positive impacts of microcredit (β=0.287, t=5.02, p<0.001), savings services (β=0.214, t=3.67, p=0.01), and entrepreneurial training (β=0.176, t=3.11, p=0.002) on financial sustainability (R²=0.65, Adj. R²=0.62, F=28.45, p<0.001), with larger/younger firms benefiting most. Nine of ten hypotheses were supported, underscoring microfinance's comprehensive role (financial + non-financial services) in fragile economies. Policy recommendations include government investment in energy infrastructure, transportation networks, and SME training programs to enhance competitiveness. These findings offer actionable insights for post-conflict development strategies.

Abstract Perfectionism has become a salient construct in understanding students’ psychological functioning within academic settings. Defined as the pursuit of excessively high standards accompanied by critical self-evaluation, perfectionism manifests in both adaptive and maladaptive forms. This paper explores the psychological correlates of perfectionism among students, highlighting its influence on mental health, motivation, coping strategies, and social relationships. Research indicates that while adaptive perfectionism may foster organization, persistence, and academic success, maladaptive perfectionism is closely linked to heightened anxiety, depression, low self-esteem, and academic burnout. Perfectionistic students often struggle with cognitive distortions, such as all-or-nothing thinking, and rely on maladaptive coping strategies like avoidance and rumination, which exacerbate stress. Additionally, perfectionism affects interpersonal dynamics, where fear of failure and excessive competitiveness can hinder collaborative learning and peer support. Cultural and parental expectations also reinforce perfectionistic tendencies, intensifying psychological vulnerability in highly competitive educational environments. Mechanisms such as achievement motivation, self-worth contingencies, and distorted cognitive appraisals help explain the varying outcomes of perfectionism. Interventions including cognitive-behavioral therapy, mindfulness, self-compassion training, and growth-mindset educational practices are proposed as effective strategies to mitigate the negative impacts of maladaptive perfectionism while preserving the motivational benefits of adaptive forms. Understanding the psychological correlates of perfectionism is critical for educators, counselors, and policymakers aiming to promote academic excellence without compromising students’ well-being. Ultimately, fostering balanced forms of perfectionism may enable students to strive for high achievement while maintaining resilience, self-acceptance, and positive mental health in their educational journey.

Abstract Social anxiety is a type of anxiety that occurs when facing social situations and communicating with others. People who suffer from social anxiety experience intense fear and worry in social situations and feel unable to manage and control these situations. Cognitive behavioral therapy is an evidence-based treatment for anxiety disorders. Due to various barriers, many people face difficulties in accessing treatment. Therefore, researchers have investigated the possibility of using the Internet to deliver CBT. It is important to ensure that the decision to promote such a treatment is based on high-quality evidence. Exposure therapy is a technique designed to help people cope with their fears. Using this method, the person is gradually exposed to stimuli that provoke a fear response in them. These triggers can range from external stimuli such as objects or social situations to internal factors such as thoughts, mental images, or physical sensations related to the trauma. When people are anxious because of a fear, phobia, or a traumatic memory, they often avoid anything that reminds them of it. This avoidance provides temporary relief, but ultimately maintains and reinforces the fear and avoidance pattern. In fact, avoidance can make things worse. Exposure therapy enables people to face and experience feared stimuli by creating a safe environment. This leads to a reduction in fear and anxiety, minimizing avoidance of feared situations, and improving quality of life. The ultimate goal is to desensitize people to the point where they can face their fears without experiencing intense anxiety.

Abstract Artificial Intelligence (AI), as one of the most advanced technologies of the 21st century, has increasingly entered the world's judicial systems and has transformed judicial decision-making processes. With its ability to analyze large volumes of data, identify complex patterns, and predict outcomes, this technology enables the acceleration and increase of accuracy in the process of handling cases. In this regard, AI can help judges and lawyers make more accurate and objective decisions based on evidence and information, thereby promoting judicial justice. In addition, the use of intelligent systems in predicting the risk of committing a crime or returning to the criminal justice system greatly contributes to decisions related to conditional release or setting bail. Also, text analysis and behavioral pattern recognition tools in criminal and legal cases can reduce the possibility of human errors and unintentional biases. However, the use of AI in decriminalization also comes with significant challenges and concerns. The most important of these challenges is the issue of transparency and understandability of algorithms; because AI decisions may be ambiguous and uninterpretable for human users and even judges due to technical complexities. Also, the risk of algorithmic discrimination resulting from inappropriate training data or biases in the data can jeopardize judicial justice. Concerns related to privacy, data security, and liability in the event of errors are also important concerns. Ultimately, the impact of AI on judicial decision-making processes depends largely on how it is designed, monitored, and the legal and ethical frameworks governing its use.

Abstract The present study examines the concept of resilience and its related problems. Resilience is the ability to return to balance and grow after challenges. Unlike endurance, which refers only to resistance, resilience includes learning and adaptation after crises. This is an acquired skill and plays an important role in mental health and improving the quality of life. Being resilient means having the flexibility to return to normal. Someone who has this characteristic and strengthens it is someone who faces disappointment, failure, and hardship, but can control everything in such a way that a return to the normal course of life is possible. Disasters, accidents, losses, and unpleasant events are not far from people's lives. Someone who knows resilience well and strengthens it in themselves, goes through all this and endures and perseveres in the struggle of difficult days in life. Suppose, a serious accident has occurred and you have suffered serious physical injuries. Enduring the situation and trying to recover, along with not getting discouraged and tired of the treatment process, shows that you are a resilient person.

Abstract The rapid evolution of artificial intelligence (AI) has transformed strategic decision-making processes in organizations, enabling faster insights, predictive analytics, and automation. However, the integration of AI systems also raises critical challenges concerning data governance, ethics, and regulatory compliance. Effective data governance ensures that data used in AI-driven decisions is accurate, secure, transparent, and aligned with corporate objectives. Ethical frameworks are essential to mitigate biases, prevent discrimination, and maintain trust among stakeholders. Moreover, the establishment of AI guidelines, including accountability, explainability, and fairness, plays a pivotal role in guiding organizations toward responsible innovation. This paper explores how robust data governance structures and ethical AI guidelines can enhance strategic decision-making and corporate integrity. It analyzes current models of governance frameworks, including ISO/IEC 38505 and OECD AI Principles, and their implications for business strategy. The discussion emphasizes that organizations adopting transparent and ethical data practices not only comply with regulations but also gain a competitive advantage through enhanced reputation and stakeholder confidence. Ultimately, the study concludes that integrating governance and ethics into AI decision systems is no longer optional—it is a strategic necessity for sustainable, fair, and accountable business practices in the era of intelligent automation.

Abstract Sports injuries remain a major concern in both professional and recreational athletics, leading to significant physical, psychological, and economic consequences. Recent advances in biomechanics have provided a powerful framework for analyzing movement patterns, loading mechanisms, and tissue responses associated with sports-related injuries. This paper explores how biomechanical data analysis contributes to the understanding and prevention of sports injuries. Using motion capture systems, force plates, electromyography, and wearable sensors, researchers can quantify kinematic and kinetic variables that reveal underlying risk factors such as improper joint alignment, asymmetrical loading, or excessive repetitive forces. By integrating these biomechanical indicators with machine learning algorithms, predictive models can be developed to identify athletes at higher risk before injury occurs. The paper further reviews intervention strategies, including neuromuscular training, equipment design modifications, and individualized biomechanical feedback systems. Case studies from sports such as soccer, running, and basketball demonstrate how biomechanical insights have successfully reduced injury rates through targeted prevention programs. Ultimately, the synthesis of biomechanical data with modern computational tools represents a paradigm shift from reactive to proactive injury management. This approach not only enhances athletic performance but also promotes long-term musculoskeletal health. The findings underscore the need for interdisciplinary collaboration between biomechanists, sports scientists, medical professionals, and data analysts to create comprehensive injury-prevention ecosystems supported by empirical evidence.

Abstract Social abnormalities are one of the manifestations of civilization and social living. It is obvious that where a group lives together, there will also be a discussion about social abnormalities, and social abnormalities are the result of the social environment. If the social environment establishes a relationship by forming correct social relations and creating a harmonious and balanced structure between desires and possibilities and between means and goals, and uses the culture of the society to form such a context, the behavior of the people of the society will be directed towards fulfilling the desires of the social system and the individuals. Social abnormalities are those social deviations that the custom of the society considers as deviations from norms, but written laws have not considered them as examples of crimes and punishable. Social misconduct refers to a person who does not fall within the framework of moral principles and general rules of collective action existing in the society where the activist is active. Therefore, he faces legal prohibition and moral and social ugliness. In fact, people who conform to the norms and values of society are called normal, and people who do not conform are called abnormal, and among abnormal people, someone whose abnormal behavior is not fleeting and lasts for a long time is called deviant or deviant. Social deviance refers to any behavior that a person performs contrary to social norms and forms, disrupts his or her functioning, and consequently affects the functioning of the family and society.