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Investigating the Effects of Consumer’s Lifestyles on Their Brand

Investigating the Effects of Consumer’s Lifestyles on Their Brand Preferences: A Case of Macau

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Investigating the Effects of Consumer’s Lifestyles on Their Brand Preferences: A Case of Macau

1.0 Introduction

1.1 Context Overview

Macau’s luxury goods market has been growing dramatically in recent years, evinced by the growing numbers of nationalist Chinese shoppers who prefer spending in this market. So, luxury goods consumption remains an essential part of modern lifestyles in this emerging Asian market. Bian and Forsythe (2012) affirm this assertion by suggesting that luxury brands, which represent considerable portions of consumer product sales globally, are no longer limited to developed Western countries but have permeated new rich markets in Eastern economies. Luxury goods’ consumption and luxury retailing have continued to enjoy dynamic and steady growth even during times of economic downturn such as the recent one caused by the effects of the COVID-19 pandemic (Deloitte, 2020; Zhang, 2017). This indicates that the market will continue to attract many brands and actors due to its lucrativeness. Even so, proper and adequate comprehension of luxury consumption requires going beyond market growth dynamics to understanding consumer purchasing behaviours in this market and their brand preferences derived from their lifestyles.

1.2 Research Background

Contemporary research indicates that consumer lifestyles are constantly changing due to ongoing global cultural shifts, the continual evolution of the demographic mix, and rapid technological advances that shape consumers’ values and habits (Bian & Forsythe, 2012; Sheth, 2020). These changes are giving rise to new consumption trends embedded in consumers’ lifestyles, eventually shaping their preferences and choices for luxury commodities. Essentially, the importance of consumer lifestyle and its effects on purchasing choices and brand preferences is well documented in the literature. For instance, Cătălin and Andreea (2014) advocate that lifestyle has a significant impact on both consumer behaviour and clients’ brand preferences. Salajeghe and Mousavi (2012) further suggest that lifestyle is a strong source of identity and its associated consumption preferences. This means that people’s lifestyles are critical identifiers of their identity, which influences their consumption choices. Based on these researchers’ stance, lifestyle defines people’s distinguishing identity and their consumption motivations, eventually shaping their luxury brand preferences. This observation corroborates Cătălin and Andreea (2014) that consumers’ personal lifestyles are a means of the self-expression of their social identity and self-identity, expressed through the choices consumers make, including their purchasing choices.

From another perspective, Kashani et al. (2017) established that consumers’ lifestyles and their attitude functions directly influence individuals’ emotional attachment to specific luxury brands. In another study, Mohiuddin (2018) furthered the importance of lifestyle in determining brand preferences by arguing that lifestyle drives consumers’ decision making, especially among female consumers. This scholar submits that lifestyle, established by consumers’ beliefs, attitudes, and mindsets, significantly impacts the decisions that go into their professional and personal lives. Further research work by Ebrahim et al. (2016) confirms that lifestyle experiential aspects of specific brands directly influence client brand experiences, which eventually drive their brand preferences. These authors advocated that positive brand experiences stored in consumers’ memories are critical determinants of their repurchase intentions, particularly for luxury products.

Haryanto et al. (2019) affirms that various dimensions of lifestyle influence clients’ selection of foreign brands differently from their selection of local brands. Among these dimensions, those found to have significant correlations with consumers’ brand preferences include fashion consciousness, health consciousness, attentiveness lifestyle, leadership lifestyles, and extroversion lifestyles. In a separate study, Husnain and Akhtar (2015) advanced the investigation of lifestyle dimensions that have been found to directly impact consumer brand preferences for luxury products. The three dimensions addressed include price consciousness, need for uniqueness, and status consciousness. According to these researchers, these three variables or dimensions influence buying behaviours regarding genuine brands versus counterfeits brands.

1.3 Statement of the Problem

While studies on the impact of lifestyle on brand preferences for luxury commodities is relatively plenty, the number of lifestyle studies focusing on Asian markets are overly scarce. Additionally, those that have attempted to explain the role of lifestyle in shaping brand preferences in luxury consumption have concentrated in developed Asian countries such as China, thereby making it difficult to find studies on a developing territories such as Macau. The current study bridges this gap by contributing knowledge about the impact of lifestyle on people’s brand preferences in luxury clothing consumption in Macau. The study adopts a similar approach as adopted by Husnain and Akhtar (2015) in exploring the lifestyle-related variables of price consciousness, status consciousness, and the need for uniqueness in determining brand preferences for luxury clothing brands versus regular clothing brands within the Macau luxury market.

1.4 Study Scope and Significance

The study is empirical in nature, involving the use of the survey questionnaire method to gather and synthesize data about these three lifestyle dimensions as they relate to luxury clothing brands in Macau. The study will be valuable because it will generate insights that luxury retailers can leverage to link up their luxury business investments to consumers’ lifestyle features to enhance market productivity and guarantee optimal profitability. Additionally, the study will provide unique perspectives in comprehending lifestyle-driven customer needs and consumer brand preferences.

1.5 Research Objectives

To discuss the dimensions of lifestyle and their impact on brand preferences for luxury products.

To examine the effect of status consciousness on consumers’ brand preferences for branded luxury clothing in Macau.

To explore the impact of price consciousness on brand preferences for luxury clothing among Macau consumers.

To study how the need for uniqueness positively influences brand preferences for luxury clothing among Macau consumers.

2.0 Literature Review

Understanding consumers’ brand preferences within the context of luxury commodities constitute an indispensable step towards comprehending their brand choice behavior (Ebrahim et al., 2016), actual purchasing behavior (Kwok et al., 2006; Zhang, 2017), and consumption dispositions (Cătălin & Andreea, 2014; Haryanto et al., 2019). Essentially, brand preferences for luxury brands have continued to receive great attention from marketing scholars. However, a significant portion of these researchers have limited their focus on luxury commodities’ utility maximization (Bronnenberg et al., 2012; Ebrahim et al., 2016; Heilman et al., 2000). A research model that explores brand preferences from the perspective of consumer lifestyle, its dimensions (Husnain & Akhtar, 2015), and their impact in shaping brand preferences is valuable in expanding the scope of scholarly inquiry in this area.

2.1 The Evolution of Brand Preferences within a Lifestyle Context

Scholars began exploring brand preferences across several products in the late 1960s and early 1970s. The conclusive outcomes of most of these early studies (Bass & Talarzyk, 1972; Bass & Wilkie, 1973; Churchill, 1972; Sheth, 1968; Sheth & Talarzyk, 1972) demonstrate close correlations between brand preferences and consumers’ salient attitudes and beliefs embedded in their lifestyles. When these attitudes and behaviors are activated at specific times, they drive their purchasing behaviors towards specific brands, thereby defining their preferences for (Husnain & Akhtar, 2015; Kwok et al., 2006; Mohiuddin, 2018; Zhang, 2017) and emotional attachment (Bian & Forsythe, 2012; Kashani et al., 2017; Miao et al., 2019) to those brands.

With time, researchers have dedicated efforts to explore the evolution of brand preferences entrenched in lifestyle, extending the understanding of this phenomenon within luxury brands’ contexts. In an earlier study, Heilman et al. (2000) examined the evolution of brand preferences and consumers’ responses to marketing activities for new clients. Their findings established that brand preferences among new consumers vary depending on learning (or brand information collection) and purchasing experience. With more learning and augmented purchasing experience, consumers garner more insights into the brand within the confines of their lifestyle. This increases their loyalty towards the brand and their probability of choosing the brand, even if it was inferior at the beginning of the purchasing experience.

The outcomes from Heilman et al. (2000) were corroborated sixteen years later by the findings from a study by Ebrahim et al. (2016), who affirmed that brand experience shapes consumer loyalty. Eventually, this influences their repurchasing intension, which has a direct impact on their brand preferences. Sharing the same sentiments, Husnain and Akhtar (2015) contend that brand preference evolution hinges on brand loyalty, giving insights into market segmentation for luxury brands. In another study, Bronnenberg et al. (2012) utilized data on consumers’ life histories and their purchases of packaged consumer goods to examine the long-term evolution of brand preferences. They discovered that brand preferences develop and evolve endogenously as a function of customers’ life histories and remain highly persistent components of their lifestyle once they are formed. In their study, Cătălin and Andreea (2014) suggested that brand preferences evolve as a function of consumers’ social identity and personal identity reflected in their lifestyle.

2.2 Impact of Lifestyle on Brand Preferences

Scholarly literature on the evolving area of brand preferences has expanded to include the role of consumers’ lifestyle in shaping their purchasing behaviors (Mohiuddin, 2018; Salajeghe & Mousavi, 2012). Essentially, research on the influence of lifestyle on luxury products’ brand preferences is plenty. While studying the association between consumers’ lifestyle and individual preferences in choosing foreign or domestic brands, Haryanto et al. (2019) described lifestyle as characterizing the orientation of persons who create life’s structure based on their activities, opinions, interests, and demographic characteristics. These authors define lifestyle as the value inherent in each individual expressed in different behaviors depicted in everyday life. From another perspective, Naim et al. (2019) consider lifestyle as a combination of indices such as demographic characteristics, social class, personality, excitements, emotions, macro-cultures, motivations, values, family position, previous experiences, and culture, which impact consumption behaviors, decisions, preferences, and tendencies.

Lifestyle and its various dimensions impact brand preferences for luxury products in various ways well-established in research. For instance, Salajeghe and Mousavi (2012) sustain that an individual’s lifestyle integrates that person’s characteristics, previous experience, and current position or attitudes towards a brand, all of which directly impact all aspects of their consumption behavior. According to Mohiuddin (2018), lifestyle affects brand preferences from the perspective that it defines their purchasing decisions and consumption choices. Specifically, this author submits that lifestyle depends on people’s standards of living, which is a factor determinant of their purchasing power, thus their consumption choices. Additionally, lifestyle reflects their beliefs, mindsets, attitudes, and thoughts towards brands, significantly impacting theirs purchasing decisions (Mohiuddin, 2018). Corroborating these sentiments, Cătălin and Andreea (2014) and Zhang (2017) hold that each person’s lifestyle reflects their aesthetic style, values, life goals, visions, and symbolic meaning, brand quality perceptions, all of which have a great impact on brand preferences.

In their study, Kashani et al. (2017) admit that lifestyle drives brand preference by defining the level of emotional attachment that consumers develop towards luxury brands. These scholars suggest that consumers’ attitudes mediate the relationship between their lifestyle and their emotional attachment to luxury goods. Accordingly, they affirmed that a lifestyle characterized by value-oriented attitudes towards luxury brands augment consumers’ emotional attachment to those brands, translating to high preferences for the brands. Husnain and Akhtar (2015), who argue that customers’ preferences largely depend on consumers’ lifestyle, sustain that the phenomenon impacts purchasers’ luxury brand preferences by forecasting their needs. Precisely, they believe that lifestyle is a valuable element in predicting luxury consumers’ needs and designing segmentation, positioning, and marketing strategies to meet these needs in a way aligning with the desired lifestyle. Zhang (2017) agrees with this observation, suggesting that the lifestyle projected by luxury brands and their respective marketing messages reflect the brand image attached to those brands, which ultimately dictate consumers’ attitudes and preferences towards them. Finally, Cătălin and Andreea (2014) believe that lifestyle is a rational instrument for creating a robust sense of self that resonates and aligns with consumers’ social and personal identities, which they express via their brand choices and preferences.

2.3 Dimensions of Lifestyle Influencing Luxury Brand Preferences

Researchers have identified more than ten dimensions of lifestyle that influence brand preferences, in general. According to Haryanto et al. (2019), the thirteen dimensions of lifestyle include fashion consciousness, cost consciousness, craftsmanship, health consciousness, adventure, community consciousness, family orientations, leadership, practicality, extroversion, attention, casualness, and interest in sports. In the context of genuine versus counterfeit brands. Husnain and Akhtar (2015) identified three additional dimensions: price consciousness, status consciousness, and need for uniqueness. According to these researchers, the attainment of strong brand preferences entails taking account of the brand-customer relationships and brand perceptions, establishing sound brand positioning, and linking up these considerations with the dimensions of lifestyle that shape luxury goods’ consumption. The three dimensions identified by Husnain and Akhtar (2015) form the conceptual framework applied for the current research study.

2.3.1 Status Consciousness and Luxury Clothing Brands

Researchers Husnain and Akhtar (2015) have defined status consciousness as the motivational process by which individuals strive to improve and enhance their social repute or position by deliberately engaging in conspicuous consumption of consumer goods that symbolize or signal eminence for them and their surroundings. Millan and Mittal (2017) use the term “status concern” to refer to status consciousness, suggesting that it describes the value individuals place on attaining higher societal and community status. Status-conscious or status-concerned consumers are highly predisposed to participating in status consumption of luxury clothing brands because such brands are regarded as emblems of social class, prestigious identity, and grander eminence (Cham et al., 2018). Reinforcing this observation, Chan (2015) and Millan and Mittal (2017) affirm that status-conscious consumers will always buy luxury goods (luxury clothing) to fulfill their need for status because they are highly mindful of the status they currently have and are motivated to display and guard it.

Status consciousness is a mentally conceived construct that captures individuals’ desires to achieve, improve, and maintain a respectable standing within their status hierarchies (Millan & Mittal, 2017). Within such a psychological makeup, consumers find themselves continually motivated to become a part of a certain socially prestigious or desirable class in society (Chan, 2015) where they achieve notability among their reference groups to be regarded with respect as influential and successful. According to Husnain and Akhtar (2015), this desire drives the decisions they make concerning the types of luxury products to purchase, with such decisions hinging principally on whether or not these products’ characteristics are commensurate with maintaining their prestigious status. Essentially, this translates to the inference that luxury brands (such as luxury clothing) constitute an essential and potent means of communicating and displaying individuals’ facets of identity and status (Millan & Mittal, 2017). So, high status consciousness is a prerequisite for engendering brand preferences for luxury clothing because these brands serve to express their prestige (Chan, 2015). Consistent with Husnain and Akhtar (2015), status-conscious consumers will demonstrate lesser acceptance for regular clothing than luxury clothing. Based on this literature, the first hypothesis for this study is:

H1: Status consciousness positively affects Macau consumers’ preferences for branded luxury clothing and has no effect on preferences for regular clothing.

2.3.2 Price consciousness and Luxury Clothing Brands

Husnain and Akhtar (2015) and Khurram et al. (2018) collectively define price consciousness as the degree to which consumers focus their attention exclusively on paying low prices for what they purchase. In other words, it entails their unwillingness to pay higher prices for a particular product. In their research, Cham et al. (2018) suggest that price consciousness constitute a factor that moderately influence consumers’ purchasing intentions and interests when buying clothing. The study by Gaston-Breton (2011) also acknowledge the importance of price consciousness in shaping brand preferences, suggesting that it plays a mediating role in driving the persuasiveness of 99-ending prices. Specifically, these scholars use linear regressions to confirm that price-conscious consumers demonstrate strong sensitivity and preferences for brands with 99-ending prices, particularly new products. Husnain and Akhtar (2015) affirm that for price-conscious customers, the essence of seeking the lowest or the best prices for brands is to get perceived optimal value for their money.

The mediating role of price consciousness means that before buying even the smallest item, price-conscious consumers will always check the prices of all related products and compare these prices before making their purchases. So, they are more predisposed to engage in price comparisons before purchasing than their less price-conscious counterparts (Khurram et al., 2018). Based on this knowledge, marketers try to infuse the perception that certain brands have greater value for reasonably lower prices than competitors’ to augment brand recognition and purchasing chances (Gaston-Breton, 2011; Khurram et al., 2018). Unfortunately, focusing overly on such aspects of price consciousness has the potential of causing consumers to buy regular products unknowingly, thinking that they are luxury goods (Husnain & Akhtar, 2015). Confirming this assertion, Kundi and Mughal (2021) recently affirmed that price sensitivity is an important mediating variable in the purchase of counterfeit brands. This indicates why price-conscious consumers tend to show positive attitudes toward counterfeit products because they will consider these brands as giving them the value for their money. This literature leads to the second hypothesis for this study:

H2: Price consciousness positively affects brand preferences for regular clothing and negatively affects brand preferences for luxury clothing among Macau consumers.

2.3.3 Need for Uniqueness and Luxury Clothing Brands

This dimension of lifestyle has been comprehensively addressed in literature, with Husnain and Akhtar (2015) defining it as the individualistic desire to look different from the rest of society by consuming brand types that augment one’s self- and social image. According to Zhang (2017), consumers’ need for uniqueness constitute a personality trait characterized by the need to exhibit individuality by acquiring, displaying, and utilizing distinctive consumer goods typical of rarity and extraordinariness. For this reason, the distinctive image and scarcity of value associated with luxury brands make them ideal to meet consumers’ need for uniqueness. Corroborating this point, Cham et al. (2018) and Chan (2015) assert that consumers who crave for the need for uniqueness will generally be motivated to internally maintain this sense of uniqueness, sustain interpersonal differences, and externally project the unique self onto others using the ‘wow’ and ‘cool’ effects derived from luxury commodities, specifically luxury clothing.

In the contemporary luxury domain, the need for uniqueness as a lifestyle dimension has transformed into a universal personality that drives status consumption for modern consumers. This implies that the need for uniqueness works hand-in-hand with status consciousness in shaping brand perceptions and preferences for luxury products and the associated purchasing intentions (Chan, 2015). In this domain, consumers are curious of trying new things provided they feel that these items help them display a unique self-image and interpersonal difference with the rest of society. They tend to depict high inquisitiveness for new brands while constantly anticipating the emergence of self-differentiating and upscale consumer items (Cham et al., 2018). Such curiosity comes along with risk-taking and novelty-seeking behaviours that augment their chances of falling into the trap of buying counterfeit luxury products (Husnain & Akhtar, 2015). As per this literature, the third hypothesis for this study is:

H3: The need for uniqueness positively affects brand preferences for luxury clothing and has no effect on preferences for regular clothing.

References

Bass, F. M., & Talarzyk, W. W. (1972). An attitude model for the study of brand preference. Journal of Marketing Research, 9(1), 93-96. Doi: 10.2307/3149618.

Bass, F. M., & Wilkie, W. L. (1973). A comparative analysis of attitudinal predictions of brand preference. Journal of Marketing Research, 10(3), 262–269. Doi: 10.2307/3149693.

Bian, Q., & Forsythe, S. (2012). Purchase intention for luxury brands: A cross cultural comparison. Journal of Business Research, 65(10), 1443-1451. Doi: 10.1016/j.jbusres.2011.10.010.

Bronnenberg, B. J., Dubé, J. P. H., & Gentzkow, M. (2012). The evolution of brand preferences: Evidence from consumer migration. American Economic Review, 102(6), 2472-2508. Doi: 10.1257/aer.102.6.2472.

Cătălin, M. C., & Andreea, P. (2014). Brands as a mean of consumer self-expression and desired personal lifestyle. Procedia-Social and Behavioral Sciences, 109, 103-107. Doi: 10.1016/j.sbspro.2013.12.427.

Cham, T. H., Ng, C. K. Y., Lim, Y. M., & Cheng, B. L. (2018). Factors influencing clothing interest and purchase intention: a study of Generation Y consumers in Malaysia. The International Review of Retail, Distribution and Consumer Research, 28(2), 174-189. Doi: 10.1080/09593969.2017.1397045.

Chan, W. Y. (2015). Consumers’ repurchase intention of luxury goods: Examining the relationship among status consumption, need for uniqueness, materialism and affective response. (Doctoral Thesis, Hong Kong Polytechnic University).

Churchill Jr, G. A. (1972). Linear attitude models: A study of predictive ability. Journal of Marketing Research, 9(4), 423-426. Doi: 10.2307/3149308.

Deloitte. (2020). Global powers of luxury goods 2020: The new age of fashion and luxury. Deloitte.

Ebrahim, R., Ghoneim, A., Irani, Z., & Fan, Y. (2016). A brand preference and repurchase intention model: the role of consumer experience. Journal of Marketing Management, 32(13-14), 1230-1259. Doi: 10.1080/0267257X.2016.1150322.

Gaston-Breton, C. (2011). Consumer preferences for 99-ending prices: The mediating role of price consciousness. Business Economic Series 03, Working Paper 5. Departamento de Economía de la Empresa, Universidad Carlos III de Madrid.

Haryanto, B., Febrianto, A., & Cahyono, E. (2019). Lifestyle and consumer preferences in choosing local or foreign brands: A study of consumer behavior in Surakarta–Indonesia. Jurnal Manajemen dan Kewirausahaan, 21(1), 74-88. Doi: 10.9744/jmk.21.1.74–88.

Heilman, C. M., Bowman, D., & Wright, G. P. (2000). The evolution of brand preferences and choice behaviors of consumers new to a market. Journal of Marketing Research, 37(2), 139-155. Doi: 10.1509/jmkr.37.2.139.18728.

Husnain, M., & Akhtar, M. W. (2015). Impact of lifestyle on brand preferences (genuine versus counterfeits smartphones). Journal of business administration research, 4(2), 30-39. Doi: 10.5430/jbar.v4n2p30.

Kashani, M., Aslani, A., Esfidani, M. R., & Javadin, S. R. S. (2017). The impact of lifestyle and attitude functions on luxury goods on emotional attachment towards luxury brands. International Journal of Applied Logistics (IJAL), 7(2), 21-40.

Khurram, M., Qadeer, F., & Sheeraz, M. (2018). The Role of Brand Recall, Brand Recognition and Price Consciousness in Understanding Actual Purchase. Journal of Research in Social Sciences, 6(2), 219-241.

Kundi, G. M., & Mughal, Y. H. (2021). Model for antecedents of attitude and price on the purchase intention of consumers and trade of counterfeit luxury products. International Journal of Customer Relationship Marketing and Management (IJCRMM), 12(4), 17-30. Doi: 10.4018/IJCRMM.2021100102.

Kwok, S., Uncles, M., & Huang, Y. (2006). Brand preferences and brand choices among urban Chinese consumers: An investigation of country‐of‐origin effects. Asia Pacific Journal of Marketing and Logistics, 18(3), 163-172. Doi: 10.1108/13555850610675634.

Miao, M., Jalees, T., Qabool, S., & Zaman, S. I. (2019). The effects of personality, culture and store stimuli on impulsive buying behavior: Evidence from emerging market of Pakistan. Asia Pacific Journal of Marketing and Logistics 32(1), 188-204. Doi: 10.1108/APJML-09-2018-0377.

Millan, E., & Mittal, B. (2017). Consumer preference for status symbolism of clothing: the case of the Czech Republic. Psychology & Marketing, 34(3), 309-322. Do: i10.1002/mar.20990.

Mohiuddin, Z. A. (2018). Effect of lifestyle on consumer decision making: A study of women consumer of Pakistan. Journal of Accounting, Business and Finance Research, 2(1), 12-15. Doi: 10.20448/2002.21.12.15.

Naim, A. M., Hamid, M. L. A., & Wahab, M. Z. H. (2019). The roles of lifestyle, future need and customer preferences in customer’s satisfaction on Islamic banks products and services. The Journal of Muamalat and Islamic Finance Research 16(2), 60-76.

Salajeghe, S., & Mousavi, E. (2012). Effect of lifestyle on consumers of luxury goods. Journal of Basic and Applied Scientific Research, 2(9), 8600-8599.

Sheth, J. (2020). Impact of Covid-19 on consumer behavior: Will the old habits return or die?. Journal of Business Research, 117, 280-283.

Sheth, J. N. (1968). How adults learn brand preference. Journal of Advertising Research, 8(3), 25-36. Doi:

Sheth, J. N., & Talarzyk, W. W. (1972). Perceived instrumentality and value importance as determinants of attitudes. Journal of Marketing Research, 9(1), 6-9. Doi: 10.2307/3149597.

Zhang, L. (2017). Factors affecting Chinese consumers’ purchase intentions for luxury clothing (Doctoral Dissertation, University of Georgia).

Investigating Bullying on Teens

Investigating Bullying on Teens

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Table of Contents

TOC o “1-3” h z u INTRODUCTION PAGEREF _Toc98958488 h 3LITERATURE REVIEW PAGEREF _Toc98958489 h 5METHODOLOGY PAGEREF _Toc98958490 h 7RESEARCH FINDINGS PAGEREF _Toc98958491 h 10CONLUSION AND RECOMMENDATION PAGEREF _Toc98958492 h 12REFERENCES PAGEREF _Toc98958493 h 13

INTRODUCTIONBackground of the Study

Bullying is a significant public health issue that affects many children and teenagers’ lives (Liu et al., 2014). The most widely accepted definition of bullying by policymakers and researchers was proposed by Dan Olweus, who defined bullying as indirect and direct aggression that is (i) purposeful, (ii) repetitive, and (iii) entails a power disparity between the aggressor(s) and the target (Olweus, 1978). According to Ang (2015), teenagers have a high risk of being bullied due to their vulnerability as they cannot fully comprehend the link between their behaviors and consequences.

Bullying can take many different forms, including hostile physical, verbal, and psychological behaviors. It can also include behaviors aimed at disrupting relationships (Hellström & Lundberg, 2020). Bullying is more common in situations where people do not have a say in which group they want to be a part of. This is the situation for teenagers at schools or at home who have siblings confined by people over whom they have no control (Bakar, 2021). Bullies try to exercise their control over all children as they try to form a social network. Those who exhibit an emotional response, such as crying or fleeing, and who have no one to defend them become targets of bullies. Other bullies join in to make fun of the victims, attack them, tease them, or circulate rumors about them (Bakar, 2021).

Bullying can occur both online and offline (Hellström & Lundberg, 2020). Patchin and Hinduja (2015) reveal that with the growing use of the internet as a platform for forming peer relationships, most of the communication and victimization that occurs among children and adolescents remains hidden from the adult world, making the problem more difficult to comprehend. This research paper is devoted to providing a more comprehensive understanding of bullying among teenagers by covering the causes and effects of bullying, as well as the prevention measures for bullying.

Statement of Problem

Bullying is widely acknowledged as a serious public health problem that affects both children and teenagers. Some of the effects of bullying on teenagers include poor mental health, reduced safety, greater unhappiness, and lower educational achievement (Zhu et al., 2021). On the same note, Bradshaw et al. (2017) reveal that cyberbullying among adolescents is regarded as a severe public health issue that is intimately tied to adolescents’ behavior, mental health, and development, despite the fact that it is still a relatively young topic of research. Cyberbullying, one of the most forms of bullying, has increased dramatically in the observed 5-year period (Zhu et al., 2021). The increased use of the internet worldwide, along with the popularity of social media platforms, have contributed significantly towards the increased prevalence of bullying among children and teenagers. As such, researchers must focus sufficient attention on adolescents’ and teenagers’ cyberbullying (Zhu et al., 2021). This study seeks to fill this research gap by exploring the issue of bullying among teenagers, including the causes and effects of bullying among teenagers and practical solutions to minimize bullying among teenagers.

With the increasing prevalence of bullying among children and adolescents, Hellström and Lundberg (2020) urge that the most important thing is what adults can do to help and support young people in minimizing the amount of stress and anxiety they suffer as a result of online and offline victimization. The authors add that adults may be unable to intervene effectively due to a lack of knowledge and awareness of how to minimize it. Therefore, this study uncovers practical means of minimizing bullying among teenagers.

Research Aims and Objectives

Research reveals that bullying is among the most significant factors associated with teen suicide, which is the leading cause of death for youngsters aged between 15 and 24 years (Cuesta et al., 2021). Therefore, much attention must be dedicated to minimizing teens bullying. The primary goal of this study is to explore bullying among teens and uncover the risk factors, causes, and protective factors of bullying on teenagers. The following specific research objectives guide the study.

To determine the risk factors of bullying on teenagers.

To determine the effects of bullying on teenagers.

To uncover practical solutions for minimizing bullying among teenagers.

Research Questions

The following research questions have been formulated from the research aims and objectives.

What are the risk factors of bullying on teenagers?

What are the effects of bullying on teenagers?

What are some of the practical solutions for minimizing bullying among teenagers?

LITERATURE REVIEWIntroduction

This section presents the review of literature that relates to the study topic. The section aims to provide the researcher with a comprehensive understanding of the research topic. The section is organized into several subsections, with the first section providing a detailed description of the concept of bullying. The second sub-section provides a discussion of the different types of cyberbullying and their different forms.

The Concept of Bullying

Bullying is defined as aggressive behavior characterized by repetition and a power imbalance (Bakar, 2021). On the same note, Capurso et al. (2017) define bullying as repetitive aggressive behavior. Hudson (2018) further defines bullying as hostile conduct that is intentional, willful, discriminatory, and designed to damage and instill fear through threats of more aggression.

According to Bakar (2021), bullying entails a pattern of power abuse in which a person abuses their power on a regular basis. The victim of bullying is unable to defend himself or herself for a variety of reasons, including a lack of physical strength and psychological resilience compared to the bully. Bullying has distinct characteristics, such as the victim’s fear of reporting it, and the majority of the results include anxiety, depression, and the development of low self-esteem in the victim. Victims of bullying are mostly defenseless; hence, other individuals are obligated to help, given that the victim has democratic rights (Bakar, 2021).

Types of Bullying

There are two main types of bullying: traditional and cyberbullying. Traditional bullying is a form of aggressive behavior that is characterized by intentional, deliberate, repetitive, and harmful power abuse against victims who are unable to defend themselves (Bennett, 2013) easily. According to Bennett (2013), traditional bullying occurs in various forms, including verbal, physical, and exclusion bullying. Verbal bullying may be in written or oral form, and it includes calling names, threatening damage, making improper sexual comments, and using abusive words. On the other hand, physical bullying entails kicking, slapping, spitting, pinching, destroying the victim’s goods, unpleasant gestures, and punching (Bennett, 2013). Online bullying, also known as social bullying, involves harming another person’s reputation through the use of social media platforms, phones, or computers. Exclusion bullying arises where one is left out in activities, influencing people against a victim, public disgrace, and propagating false rumors. The most prevalent kind of bullying is verbal, but internet bullying is also on the rise (Bakar, 2021).

On the other hand, cyberbullying refers to harassing or threatening others via the internet (Lindfors et al., 2012). Cyberbullying can also be defined as bullying in cyberspace (Baldry et al., 2015). Capurso et al.(2017) further add that cyberbullying entails the use of electronic devices, digital images or messages, or site posts to a cellular phone. Cyberbullying can take numerous forms: flaming, harassment, cyberstalking, cyberstalking, denigration, impersonation, outing, trickery, and exclusion. Flaming involves online fights utilizing electronic messages with furious and profane language. On the other hand, harassment entails continuously sending rude, insulting messages. Cyberstalking is persistent severe harassment that involves threats or produces significant fear, while denigration involves propagating stories online and/or sending or uploading gossip about a person to destroy his/her reputation or friendships (Capurso et al., 2017). Impersonation involves pretending to be someone else and sending or uploading something to place that person in difficulty or danger or ruin that person’s reputation or friendships. On the other hand, outing involves sharing another person’s secrets or any embarrassing images or information online, while trickery entails tricking another person into revealing embarrassing information or their secrets ad sharing such information online. Exclusion entails deliberately removing someone from an online group. Emails and chat rooms are the most commonly used tools of cyberbullying (Capurso et al., 2017). When compared to traditional bullying, cyberbullying has several distinct characteristics that may exacerbate its harmful effects, including the difficulty in escaping the bullying, the size of the potential audience, the bully’s anonymity, and the ability to attack at any time and from any location (Lindfors et al., 2012).

METHODOLOGYIntroduction

This section gives an outline of the research methodology used in this study. There are several concepts presented, including research design, search strategy, and data collection and analysis procedures.

Research Design

A literature-based design was used in this investigation. Notably, literature analysis is used to build arguments based on what a researcher already knows and doesn’t know about a topic (Newman & Gough, 2020). To determine the bullying risk factors, its effects, and prevention strategies, the researcher conducted a comprehensive meta-analysis. Systematic literature review refers to a research method utilized to pinpoint and critically appraise relevant research and collect and critically analyze data from existing studies (Snyder, 2019). Contrary, a meta-analysis involves combining results from different scholars to compare and highlight relationships, patterns, and disagreements that arise in the context of different studies in relation to the same topic (Snyder, 2019).

Search Strategy and Selection Criteria

To find the most relevant publications for review, the researcher searched through reputable databases such as ProQuest, EbscoHost, Sage, Google Scholar, and Science Direct. To identify relevant data sources, several search terms were used. They include: ”Effects of teenagers bullying,” Impact of teenagers bullying,” “Effects of bullying on adolescents,” “risk factors of teenage bullying,” and “protective measures of teenage bullying.” The search results were then narrowed down using Boolean operators like NOT, AND, and OR, as well as truncation and wildcards systems. Also, an ancestry search was utilized to find sources for inclusion. This involved keeping track of any relevant footnote and cited references and including them in the review. The researcher created a set of exclusion and inclusion criteria to find the most relevant and reputable sources of information for the review.

Based on the inclusion criterion, the researcher only reviewed articles on bullying among teenagers/adolescents. Studies that were reviewed were those published in the past ten years to ensure that only up-to-date information was included in the report. Additionally, the researcher only included articles published in English to ensure comprehension of the data sources used. Ony peer-reviewed and scholarly journal articles were included in the study. Furthermore, the researcher included only the publications with free access and those that were available in full text. This was aimed at ensuring that detailed information about the study being reviewed was available. Lastly, the researcher included articles whose topic or abstract had at least one of the search terms. All materials that did not meet the inclusion criteria were excluded.

All of the studies that were regarded as relevant and reputable for this investigation were retrieved for examination after preliminary screening. A data extraction sheet was created that included publication information study parameters such as sample size, location, design, and study outcomes. The risk of bias for the papers chosen for review was determined by concentrating on methodological problems such as the suitability of the research design and if the sample was representative of the population to guarantee the data produced was reliable.

Data Analysis Procedure

To answer the three study questions, the researcher used content and thematic analysis of secondary sources. The researcher began by doing a thematic analysis to compile evidence from multiple data sources. Thematic analysis typically focuses on patterns that lead to the discovery of important themes. The researcher further used content analysis to critically analyze the main themes discovered through thematic analysis. The results are presented and discussed in the next section.

RESEARCH FINDINGSIntroduction

The goal of this study was three-fold. First, the study sought to determine the risk factors of bullying on teenagers. Secondly, the study was aimed to determine the effects of bullying on teenagers. Lastly, the study sought to uncover practical ways of minimizing bullying among teenagers. The study applied secondary data to address the research objectives. This section presents the findings of the study, which was guided by the following research questions.

What are the risk factors of bullying on teenagers?

What are the effects of bullying on teenagers?

What are some of the practical solutions for minimizing bullying among teenagers?

RQ1: What are the risk factors of bullying on teenagers?

The first research question sought to determine the factors that place teenagers at an increased risk of being bullied. Study findings revealed that individual and socio-family-related factors are associated with cyberbullying. Among the personal factors, which are risk factors linked with bullying among teenagers, include gender, age, health conditions, and online behavior. In terms of gender, most studies showcased that females have a higher likelihood of being bullied compared to their male counterparts (Aizenkot & Kashy-Rosenbaum, 2021; Álvarez-García et al., 2018; Tesler et al., 2019; Zhu et al., 2021). However, boys have been found to have a higher likelihood of bullying others.

In terms of age, findings revealed that older teenagers, mostly those above the age of 15 years, are at a greater risk of becoming cyberbullying perpetrators (Álvarez-García et al., 2018). Findings further revealed that teenagers with mental health issues such as sleep deprivation, depression, eating disorders, Borderline Personality Disorder (BPD) have higher risks of being bullies (Zhu et al., 2021). Additionally, findings established that teenagers who spent much of their time on the internet had a higher risk of being bullied (Festl, 2016; Rao et al., 2019; Simsek et al., 2019).

In terms of socio-family-related factors, findings revealed that parental abuse, family dysfunction, parental neglect, communication issues, and inadequate monitoring contribute to an increased risk of being abused (Hong et al., 2018; Katz et al., 2019). Zhu et al. (2021) further added that teenagers who reside in cities have higher chances of being bullied compared to their counterparts who reside in rural areas. Furthermore, research reveals that teenagers whose parents practice authoritarian or over-controlling parenting styles, as well as inharmonious teacher-student relations, are at a higher risk of victimization (Charalampous et al., 2018; Zhu et al., 2021). Cuesta et al. (2021) disclose other predisposing risk factors of bullying, which include parental miscommunication, lack of support, lack of monitoring, mental problems, domestic violence, family dysfunction, and single-parent family.

RQ2: What are the effects of bullying on teenagers?

Findings revealed that bullying on teenagers results in mental health issues such as anxiety, depression, and lack of sleep (Moore et al. 2017; Zhu et al., 2021). On the same note, Liu et al. (2014) urge that bullying victimization leads to poorer psychological adjustment. According to Yin et a. (2017), mental health issues resulting from bullying have been proven to have considerable unfavorable consequences on welfare, function, and development in adolescents and are connected with poorer academic achievement, unemployment, poor social functioning, and substance addiction. This detrimental influence can extend well after adolescence, establishing a cycle of continuous dysfunction and loss. Zhu et al. (2021) further add that bullying among teenagers results in lower fluid intelligence, thus limited problem-solving ability. Research also established that bullying increases the risk of illicit drug use two years later (Liu et al., 20214). On a different note, Cuesta et al. (2021) urge that bullying victims tend to be weak or insecure, shy, and emotionally vulnerable, thus making them easy targets for bullies in the future. In one of the materials covered in class, Cook (2005), reveals that individuals who are exposed to childhood trauma experience long-lasting problems that place them at an higher risk of additional trauma exposure.

Other effects of bullying among adolescents, according to Nurlia and Suardiman (2020), include impediment of normal personality growth and personal development within the society, negative social academic, school dropout, and poor academic performance. On a different note, Fullchange and Furlong (2016) reveal that people who have been bullied during their childhood between 7 and 1 years of age experience various diminished quality-of-life outcomes into their adulthood up to when they are 50 years of age. These negative life outcomes include suicidal thoughts, alcohol dependency, poorer general health, depression, psychological distress, reduced cognitive functioning, anxiety disorders, fewer social relationships, lower socio-economic circumstances, and diminished well-being. Alao, in one of the YouTube videos shared as a class reading material, Harris (2015) revealed that childhood trauma affects health across a lifetime.

Bullying is also associated with teenagers’ physical health, such as headache, nausea, and fatigue (Zhou et al., 2017). Bullying was also found to adversely impact the development of personal identity (Salmivalli et al., 2021). Only one positive effect of bullying among teenagers was established. Findings revealed that bullying is linked with increased motivation for higher education (Liu et al., 2014).

RQ3: What are some of the practical solutions for Reducing bullying among teenagers?

Findings revealed that the role of parents is crucial in protecting children against bullying. For instance, open, active communication and parent-child relationship were found to minimize the experiences of cyberbullying and penetration (Zhu et al., 2021). The author further added that parental guidance and monitoring of their children’s online activities and internet use minimizes children’s tendency to engage in some negative activities associated with cyberbullying. The authoritative parental style also assists in protecting youths from cyberbullying. Supporting this statement, Charalampous et al. (2018) urge that authoritative parenting is a protective factor for cyber and conventional forms of bullying. Zhu et al. (2021) further urge that when parental monitoring attains a balance between openness and control, it becomes a significant protective factor against cyberbullying.

The development of school-based programmes also contributes significantly towards minimizing bullying in schools. Schools are recognized as one of the areas where bullying among teens is prevalent. Supporting these findings, Hall (2017) urges that anti-bullying school policies are effective in reducing bullying. Menesini and Salmivalli (2017) further added that school-based programmes for reducing bullying are effective, accounting for about 20-23% decrease in bullying others and a 17-20% decrease for those being bullied. Another practical solution for reducing bullying among teenagers is the implementation of social-emotional learning programs during the adolescence stage. According to Swearer et al. (2017), to effectively combat bullying during teenage, social-emotional learning programs should be focused on restorative practices and positive behavioral development. Also, to minimize bullying in schools, intervention strategies may include expelling and suspending the bullies, teaching respect and empathy to students through classroom lessons, collaborating with parents on student behavior, maintaining constant adult supervision, and training teachers on intervening in bullying cases (Hall, 2017).

CONLUSION AND RECOMMENDATIONConclusion

This study’s main goal was to determine the risk factors of bullying on teenagers. Findings established that personal factors such as gender, age, health conditions, and online behavior place teenagers at a higher risk of bullying victimization. Besides, socio-family-related factors including parental abuse, family dysfunction, parental neglect, authoritarian parental style, communication issues, inadequate monitoring, parental miscommunication, lack of support, domestic violence, family dysfunction, and single-parent family contribute to increased risk of being abused.

Another goal of the study was to determine the effects of bullying on teenagers. Bullying was found to result in mental health issues such as depression, anxiety, and loss of sleep. These mental issues were found adversely affect welfare, function, and development in adolescents and are connected with poorer academic achievement, unemployment, poor social functioning, and substance addiction. Furthermore, bullying among teenagers was found to result in lower fluid intelligence, which limits teenagers’ ability to solve problems. Also, bullying on teenagers increases the risk of illicit drugs and leaves bullying victims insecure, shy, and emotionally vulnerable, thus making them easy targets for bullies in the future. Other effects of bullying among adolescents are impediment of normal personality growth and personal development within the society, negative social academic, school dropout, and poor academic performance. Despite the many negative effects of bullying, it was found that bullying increases motivation for higher education.

Lastly, this study sought to uncover practical solutions for reducing bullying among teenagers. Some of the identified interventions for bullying prevention include promotion of open and active communication between teenagers and parents, parental guidance and monitoring of their children’s online activities and internet use, adoption of authoritative parental style, implementation of school-based anti-bullying programs, and implementation of social-emotional learning programs during the adolescence stage. Also, expelling and suspending the bullies, teaching respect and empathy to students through classroom lessons, collaborating with parents on student behavior, maintaining constant adult supervision, and training teachers on intervening in bullying cases can help reduce bullying in schools.

Limitations of the Study

This study was faced with a few limitations. Firstly, the study was limited to the use of secondary data, limiting the researcher from collecting primary data to supplement the findings obtained using secondary data. Also, since the study relied on the researcher for data extraction, analysis, and interpretation, this increased the risk of the researcher’s bias.

Recommendations

Parents are recommended to adopt an authoritative parental style to minimize bullying among teenagers. Also, parents should closely monitor children’s online activities and internet use. Furthermore, parents should openly discuss with their children the issue of bullying and inform them of the bullying preventive interventions. Another pertinent recommendation is that schools establish support groups to equip bullying victims with empowerment skills.

REFERENCESAizenkot, D., & Kashy-Rosenbaum, G. (2021). Cyberbullying victimization in WhatsApp classmate groups among Israeli elementary, middle, and high school students. Journal of interpersonal violence, 36(15-16), NP8498-NP8519. https://doi.org/10.1177%2F0886260519842860Álvarez-García, D., Núñez, J. C., García, T., & Barreiro-Collazo, A. (2018). Individual, family, and community predictors of cyber-aggression among adolescents. European journal of psychology applied to legal context, 10(2), 79-88.

Ang, R. P. (2015). Adolescent cyberbullying: A review of characteristics, prevention, and intervention strategies. Aggression and violent behavior, 25, 35-42. https://doi.org/10.1016/j.avb.2015.07.011Bakar, A. Y. A. (2021). A systematic literature review on the effects of bullying at school. SHOULD: Indonesian Journal of School Counseling, 6(1), 35-39.

Baldry, A. C., Farrington, D. P., & Sorrentino, A. (2015). “Am I at risk of cyberbullying”? A narrative review and conceptual framework for research on the risk of cyberbullying and cyber victimization: The risk and needs assessment approach. Aggression and Violent Behavior, 23, 36-51. https://doi.org/10.1016/j.avb.2015.05.014Bennett Esq, B. (2013). Cyberbullying Among School-Aged Adolescents and Teens: A Policy Review and Recommendations for Georgia.

Bradshaw, J., Crous, G., Rees, G., & Turner, N. (2017). Comparing children’s experiences of school-based bullying across countries. Children and Youth Services Review, 80, 171-180. https://doi.org/10.1016/j.childyouth.2017.06.060Capurso, S., Paradžik, L., & Čale Mratović, M. (2017). Cyberbullying among children and adolescents–an overview of epidemiological studies and effective preventive programs. Kriminologija & socijalna integracija: časopis za kriminologiju, penologiju i poremećaje u ponašanju, 25(1), 127-137. http://dx.doi.org/10.31299/ksi.25.1.5Charalampous, K., Demetriou, C., Tricha, L., Ioannou, M., Georgiou, S., Nikiforou, M., & Stavrinides, P. (2018). The effect of parental style on bullying and cyberbullying behaviors and the mediating role of peer attachment relationships: A longitudinal study. Journal of adolescence, 64, 109-123.

Cuesta, I., Montesó‐Curto, P., Metzler Sawin, E., Jiménez‐Herrera, M., Puig‐Llobet, M., Seabra, P., & Toussaint, L. (2021). Risk factors for teen suicide and bullying: An international integrative review. International journal of nursing practice, 27(3), e12930. https://doi.org/10.1111/ijn.12930Festl, R. (2016). Perpetrators on the internet: Analyzing individual and structural explanation factors of cyberbullying in the school context. Computers in Human Behavior, 59, 237-248.

Fullchange, A., & Furlong, M. J. (2016). An exploration of effects of bullying victimization from a complete mental health perspective. Sage Open, 6(1), 2158244015623593. https://doi.org/10.1177%2F2158244015623593Hall, W. (2017). The effectiveness of policy interventions for school bullying: A systematic review. Journal of the Society for Social Work and Research, 8(1), 45-69.

Hellström, L., & Lundberg, A. (2020). Understanding bullying from young people’s perspectives: An exploratory study. Educational Research, 62(4), 414-433. https://doi.org/10.1080/00131881.2020.1821388Hong, J. S., Kim, D. H., Thornberg, R., Kang, J. H., & Morgan, J. T. (2018). Correlates of direct and indirect forms of cyberbullying victimization involving South Korean adolescents: An ecological perspective. Computers in Human Behavior, 87, 327-336. https://doi.org/10.1016/j.chb.2018.06.010Hudson, S. (2018). The Impact of Cyber-Bullying on Adolescents’ Georgia Milestones Scores. Liberty University.

Katz, I., Lemish, D., Cohen, R., & Arden, A. (2019). When parents are inconsistent: Parenting style and adolescents’ involvement in cyberbullying. Journal of Adolescence, 74, 1-12.

Lindfors, P. L., Kaltiala-Heino, R., & Rimpelä, A. H. (2012). Cyberbullying among Finnish adolescents–a population-based study. BMC public health, 12(1), 1-5. https://doi.org/10.1186/1471-2458-12-1027Liu, M. C. C., Lan, C. C., Hsu, J. W., Huang, K. L., & Chen, Y. S. (2014). Bullying victimization and conduct problems among high school students in Taiwan: Focus on fluid intelligence, mood symptoms, and associated psychosocial adjustment. Children and youth services review, 47, 231-238. https://doi.org/10.1016/j.childyouth.2014.09.011Menesini, E., & Salmivalli, C. (2017). Bullying in schools: the state of knowledge and effective interventions. Psychology, health & medicine, 22(sup1), 240-253. https://doi.org/10.1080/13548506.2017.1279740Moore, S. E., Norman, R. E., Suetani, S., Thomas, H. J., Sly, P. D., & Scott, J. G. (2017). Consequences of bullying victimization in childhood and adolescence: A systematic review and meta-analysis. World journal of psychiatry, 7(1), 60. https://dx.doi.org/10.5498%2Fwjp.v7.i1.60Newman, M., & Gough, D. (2020). Systematic reviews in educational research: Methodology, perspectives, and application. Systematic reviews in educational research, 3-22. https://library.oapen.org/bitstream/handle/20.500.12657/23142/1007012.pdf?sequence=1#page=22Nurlia, A., & Suardiman, S. P. (2020). The phenomenon of bullying in junior high school students nowadays. International Journal of Education and Learning, 2(1), 7-13.

Olweus, D. (1978). Aggression in the schools: Bullies and whipping boys. Hemisphere.

Patchin, J. W., & Hinduja, S. (2015). Measuring cyberbullying: Implications for research. Aggression and Violent Behavior, 23, 69-74. https://doi.org/10.1016/j.avb.2015.05.013Rao, J., Wang, H., Pang, M., Yang, J., Zhang, J., Ye, Y., … & Dong, X. (2019). Cyberbullying perpetration and victimisation among junior and senior high school students in Guangzhou, China. Injury prevention, 25(1), 13-19.

Salmivalli, C., Laninga‐Wijnen, L., Malamut, S. T., & Garandeau, C. F. (2021). Bullying prevention in adolescence: solutions and new challenges from the past decade. Journal of research on adolescence, 31(4), 1023-1046. https://doi.org/10.1111/jora.12688Simsek, N., Sahin, D., & Evli, M. (2019). Internet addiction, cyberbullying, and victimization relationship in adolescents: a sample from Turkey. Journal of addictions nursing, 30(3), 201-210. https://doi.org/10.1097/JAN.0000000000000296.

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of busin

Investigating Brand Solidarity

Investigating Brand Solidarity

Student’s Name

Institution Affiliation

Course Name and Code

Professor’s Name

Date

Investigating Brand Solidarity

Starbucks aimed to increase its workforce diversity and offer chances to specific groups of people. It has pledged to hire 25,000 military spouses and veterans by 2025 as part of its attempts to be socially accountable. The company reached this milestone six years ahead of expectations and now employs more than five thousand active-duty military personnel’s families and veterans each year. Starbucks has just announced the creation of a leadership program that would connect black, indigenous, and other people of color (BIPOC) with top leaders to promote investment in collaboration opportunities and further the company’s commitment to racial and social equity. Furthermore, by 2030, the chain hopes to have 20% of its corporate workforce comprise BIPOC and 30% of its retail and manufacturing workforce comprise BIPOC. In addition, they do not discriminate based on race or gender at any of their locations. In addition, they extend friendly services and pleasantries to every member of society.

Starbucks is a firm that adheres to the notion of corporate solidarity, which is currently the method that is used to achieve a good standard practice within the company as well as to achieve their survival in the market. The organization fulfills its ethical and social responsibilities inside and outside of the business. In point of fact, there is usually a seminar held once a year for workers on how to properly use their time, how to treat other employees and customers successfully, and how they can resolve disagreements between employees and customers. Indeed, their platform generates common benefits for everyone, and I maintain that it doesn’t matter why you believe this; as long as you do, the business will endure for a longer period of time.

Introductory speech

Introductory speech

Greetings to you all present today. As you all know, we have been dealing with drug addictions affecting many students within the campus, and we have been trying to help them through all that we can. However, it is a challenging part of our studies and our lives even though it is fully paying, not in financial ability but through the satisfaction of saving a soul from going too deep into drugs where they cannot be redeemed. Therefore today we have a special speaker with us. She will take us through what she has experienced as she has dealt with people affected by drug addiction and how it is possible to get out of that hook that seems difficult to deal with.

I am glad to introduce Brenda Browne, the director division of mental health and addiction services. She is also the addictions administrator in Passaic County within the department of human resources. She is very resourceful, and her presence here today will enable us to get more insights and more information on what is meant by being fully addicted and which addiction level is safe. She will inform us of how to deal with our friends who are addicted and how to help them realize that they can change. Therefore let us all welcome her and listen carefully to her wisdom which she has got from dealing with all types of addiction patients up to now. Welcome to our group; we are happy to have you in our presence.

Introductory Psychology Writing Assignment

Introductory Psychology Writing Assignment

Assignment Overview

All Introductory Psychology students are required to complete an Introductory Psychology Writing Assignment. There are many beliefs about psychology that are commonly held by the general public, despite the fact that they are not generally supported by scientific research. Often, people evaluate how likely these claims are to be true based upon their personal experience, anecdotes or stories, and how well the claims match their intuitions about human behavior, thoughts, and feelings. Scientists test the accuracy of these claims by systematically collecting and analyzing these observations (i.e., data) to make determinations about what is true.

In this assignment, you are going to be a psychological detective. Listed below are five common beliefs that have been questioned by many psychologists. You will pick ONE of the questionable claims listed below. Your job is to find two empirical research articles that scientifically test some aspect of your chosen claim, and to use that evidence to evaluate the claim’s support (or lack thereof). For each of the claims, some suggested keywords to begin your search are provided (you likely will need to search other terms, as well), along with a sample empirical research article addressing this claim. You may not use this article as one of your two sources.

Challenged psychological beliefs:

1. Children raised by gay parents are likely to experience negative life outcomes.

Some Suggested Keywords for PsycInfo: (“gay parent*” OR “homosexual parent*”) AND (“outcome*” OR

“well-being” OR “disorder*” OR “health”)

Sample empirical research article addressing this topic:

Farr, R. H., & Patterson, C. J. (2013). Coparenting among lesbian, gay, and heterosexual couples:

Associations with adopted children’s outcomes. Child Development, 84(4), 1226-1240. doi:http://dx.doi.org.aurarialibrary.idm.oclc.org/10.1111/cdev.120462. Most autistic individuals exhibit savant abilities.

Some Suggested Keywords: (“autism” OR “autistic” ) AND savant*

Sample empirical research article:

Scheuffgen, K., Happé, F., Anderson, M., & Frith, U. (2000). High “intelligence,” low “IQ”? speed of

processing and measured IQ in children with autism.Development and Psychopathology, 12(1), 83-90. doi:http://dx.doi.org.aurarialibrary.idm.oclc.org/10.1017/S095457940000105X3. Eyewitness testimony is an accurate and trustworthy form of evidence in the justice system.

Some Suggested Keywords: (“eyewitness” OR “witness testimony”) AND (“accurate” OR “accuracy”)

Sample empirical research article:

Wells, G. L., Ferguson, T. J., & Lindsay, R. C. (1981). The tractability of eyewitness confidence and its

implications for triers of fact. Journal of Applied Psychology, 66(6), 688-696. doi:http://dx.doi.org.aurarialibrary.idm.oclc.org/10.1037/0021-9010.66.6.6884. Thinking positive thoughts reduces the chances of suffering from serious illnesses, such as cancer.

Some Suggested Keywords: (“positive thinking” OR “optimism” ) AND (“health outcomes” OR “cancer”) Sample empirical research article:

De Moor, J. S., De Moor, C. A., Basen-Engquist, K., Kudelka, A., Bevers, M. W., & Cohen, L. (2006).

Optimism, distress, health-related quality of life, and change in cancer antigen 125 among patients with ovarian cancer undergoing chemotherapy. Psychosomatic Medicine, 68(4), 555-562. doi:http://dx.doi.org.aurarialibrary.idm.oclc.org/10.1097/01.psy.0000222379.713895. Students perform better when under pressure, such as when they procrastinate until last minute.

Some Suggested Keywords: “procrastinat*” AND “performance”

Sample empirical research article:

Michinov, N., Brunot, S., Le Bohec, O., Juhel, J., & Delaval, M. (2011). Procrastination, participation, and

performance in online learning environments.Computers & Education, 56(1), 243-252. doi:http://dx.doi.org.aurarialibrary.idm.oclc.org/10.1016/j.compedu.2010.07.025Assignment Details

Writing Guidelines

Try to avoid sharing personal experiences and/or personal opinions.

Paraphrase. DO NOT use quotes.

Please be careful not to plagiarize. To receive credit for this paper, you must review the articles in your own words.

Make sure that you clearly cite your sources.

You are expected to write effectively and thoughtfully. You’re encouraged to use the Writing Center’s free services to help you achieve these goals: https://msudenver.edu/writectr/Formatting Guidelines

The paper should be 3-4 pages (not including title page and references) in length and should be typed.

The entire paper should be double-spaced with 12-point font size.

All margins should be one inch.

Paper Outline

Include an APA-formatted title page.

Introduce the topic and explain the purpose of the paper

Identify which claim you are investigating.

Explain why the topic is important and interesting.

II. Summarize the two empirical research articles that you read.

Briefly (no more than a few sentences) describe how you located your sources.

Selecting your articles: BE SURE THAT YOU SELECT EMPIRICAL STUDY ARTICLES FROM SCHOLARLY JOURNALS. Empirical study articles present research conducted by the authors (i.e. not literature reviews or editorials). To ensure that you’re selecting empirical study articles, check the abstract for references to participants, procedure, and results. If the abstract does not clearly indicate that this article is empirical search, you can check the text of the article for a “Methods” section. Your instructor will explain how to find empirical articles in scholarly journals.

Your instructor will specify how you should make paper submissions. You should submit online through Launchpad. In addition, you should submit the two full-text articles you’re citing in your paper. Your instructor will provide instructions for how these sources should be submitted.

Evaluate the sources—do these sources appear credible/trustworthy (i.e. How was the research funded; What was the review process for publication)? Why or why not? (Note: You will need to read the entire article in order to do this – not just the abstract.)

Describe what the researchers did in their study.

State who was in the study (participants).

Include the number of men, women, ages, ethnicities, etc.

State how the participants were asked to be in the study (recruited)

State what the participants were asked to do.

In addition to naming the questionnaires or tasks, also explain what the questionnaires are measuring and what the tasks are. Describe them well enough so that the reader has an idea of what kinds of questions the participants answered or what kinds of tasks they completed.

In what ways were the results consistent with the hypotheses/predictions? Any surprising findings? Do not worry about trying to understand the statistics; the author will explain the statistics in the “Discussion” section of the article.

What did you perceive as being the strengths of these studies? What were their limitations?

III. Addressing the Claim

Draw a conclusion about your claim. Does the claim seem accurate or inaccurate?

Be sure to support your answer.

When were your articles published? Would you expect the findings to still hold true? Why?

Which groups of people do these articles help you better understand? Do these articles help you understand all people, or only certain subgroups (i.e. are there populations for whom you think you’d find different results than those found in the articles – generations, nationalities, race, etc.?). You’re NOT being ask who would be interested in this research, but to whom the findings apply.

IV. Reference Page

You need a complete reference for the article that you reviewed. Be sure that your references are in the most current APA style.(Your instructor will cover this style, or you can go to http://owl.english.purdue.edu/owl/ and visit the “Research and Citation” section.)

CITATIONS:

Representing someone else’s research and/or words as your own is considered plagiarism. Plagiarism is a serious offense, and can result in failing the course. In order to avoid plagiarism, you must give credit to the author(s) whose work you are citing. APA (American Psychological Association) format is used for citations made within the text. Below are examples of sentences and how they should be cited.

Citations include the author’s last name and the year of publication.

One author: Cite the author’s last name and the year the article was published. Example: In a recent study of reaction times (Rogers, 2012)…or Rogers (2012) compared reaction times…

Multiple authors: When a work has two authors, always cite both names every time the reference occurs in the text. Example: (Smith & Smith, 2009). When a work has three or more authors, include only the surname of the first author followed by et al. Example: (Wasserstein et al., 2012).

Citation of a work discussed in another source: If a work is cited in your article, and you did not read the original work cited, you should use the following citation format: (Siedenberg, 2011 as cited in Coltheart, 2013)…

Important: Any portion of your paper that contains information from the article needs to be cited. Since you will reference the article you read for this assignment multiple times, you will end up citing that article in your paper multiple times. If you are in doubt about whether you should cite it then cite it! Better to be safe than sorry.

-205740614045References

Geenen, N. Y. R., Hohelüchter, M., Langholf, V., & Walther, E. (2014). The beneficial effects of prosocial spending on happiness: Work hard, make money, and spend it on others? The Journal of Positive Psychology, 9(3), 204-208. doi:http://dx.doi.org/10.1080/17439760.2014.891154

00References

Geenen, N. Y. R., Hohelüchter, M., Langholf, V., & Walther, E. (2014). The beneficial effects of prosocial spending on happiness: Work hard, make money, and spend it on others? The Journal of Positive Psychology, 9(3), 204-208. doi:http://dx.doi.org/10.1080/17439760.2014.891154

REFERENCES: You will probably have only two references on your reference page. List them in alphabetical order. The reference page should be on a separate page. The following APA format should be used for your reference page:

literature review on Logistic Regression

IntroductionIn this part, a form of bankruptcy calculation provisional on financial statements is tendered. Despite giving an argument on the recommended variables, the subject of functional form is presented. The condition most frequently applied for the bankruptcy calculation model denotes that the extent at which two variables have the capability to replace another holding projected risk unaffected will be continuous. If the feature confined by sole financial ratios is believed less a replacement for any other feature as this proportion grows, this restraint might not be suitable. Particularly, the configuration of constant compensation will instigate calculations susceptible to noncredible outliers. A requirement of the logit model that permits flexible rates of reparation is aggravated. The model is projected along with the regression effects are reported.

Second; by querying the direct associations flanked by financial ratios as well as the meticulous result of bankruptcy, a model configuration that establishes a higher bound on probability estimation is investigated. By reference to an easy model of errors, the specification differentiates between the likelihood of bankruptcy along with the likelihood of insolvency. While the forecasted likelihoods of bankruptcy could be assessed empirically, the occurrence of bankruptcy is not apparent. However, provisional on the model configuration, chances can be obtained for this occurrence, as well. An appraisal is tendered on the capability of the model to gauge the overall growth in credit dangers for the limited company liability sectors. Individual chances of bankruptcy are proliferated with the company’s debt to create a calculation of expected loss in deficiency of improved values. This computation is then collected and fixed with entire loan losses for the limited company liability sector over its existence. Lastly, the likelihood of reviewing the outcome of macro variables in a small panel of companies are discovered. With indication to aggregation possessions of a probit model, a proposal is tendered on how to approximate time-definite consequences on collective data as a way to make out macro coefficients that could be comprised in the micro-level representation.

Financial ratios reproduce key connections amid financial variables and give basic principles for financial preparation and study. Ratios are regularly employed as a foundation for construing a firm’s performance patterns, its trade, fiscal and market risk patterns, and a variety of commercial, strategic judgments, for example, unifications, consolidations and insolvency. Even though ratios have been productively employed in multiple discriminant analysis (MDA) to categorize unsuccessful and non failed companies, the procedure used in choosing ratios has been condemned. Numerous researchers have experimented in their appraisal of bankruptcy researches that a brute empiricism is characteristically employed to choose the financial percentages for their representations. Previous insolvency forecasting analysis did not encompass a theory of financial breakdown on which to center the selection of definite ratios; consequently, the empirical judgments cannot be simplified to designate the most probable forecasters of financial malfunction. In attempting to comprehend the failure course and distinguishing that financial worth is centered on future cash information current and flow, cash centered subsidize flow model established by Helfcrt as well as proposed in the FASB.

Logistic Regression

In the untimely periods, Cornfield (2000, 97) was the foremost researcher to employ logistic regression (LR). They were followed by other researchers who employed this method to approximate the likelihood of happening of a course as a purpose of additional variables. The deployment of LR augmented in the 1980s, plus currently it comprises one of the mainly extensively used techniques in the study in, Finance, and particularly in accounting. Among the intentions in accounting is to study those features that at a specified instance influence the survival of an accounting difficulty, and to direct the element of the latter, plus to make models with prognostic capability that can review the stipulated Finance problem (Menard 2011, 7). The logistic regression representation is extremely suitable for addressing subjects of this category, offered an adequately copious and well-distributed model is obtainable. Additionally, in scheming the study, and trailing an adequate writing investigation and with excellent familiarity of the topic, all the imperative variables for clarifying the reaction variable ought to be considered (Diaz-Quijano 2012, 9).

Logistic Regression is a trendy and useful system for modeling resounding results as a function of both permanent and clear-cut variables. The issue is: how forceful is it? Or rather: how forceful are the general executions? Even a comprehensive reference for instance scrutinizing clear-cut data, instigates an experimental observation. From a hypothetical perspective, the logistic general linear model is a basic difficulty to solve. The optimized measure is log-concave, which in turn denotes that there is an exclusive global limit and no confined limits to get cornered (El-Habil 2012, 78). Gradients usually imply bearings that are continually improving. Nevertheless, the standard techniques of resolving the logistic universal linear model are the Newton-Raphson technique or the directly correlated iteratively reweighted technique that uses least squares (Allison 2012, 34). Furthermore, these techniques, while characteristically extremely fast, do not certify convergence in all situations. If Newton-Raphson methods are not appealing, numerous other optimization systems could be employed:

•Stochastic gradient descent

•Conjugate gradient

A controlling dilemma with logistic regression emerges from an attribute of training data: divisions of results that are split or quasi split by divisions of the varying aspects.

The Logistic Regression Model

Logistic regression study scrutinizes the manipulation of various aspects on a dichotomous effect by approximating the likelihood of the event’s happening. This is implemented by investigating the connection between one or more sovereign variables as well as the dichotomous result log odds by calculating the log odds alterations of the dependable aspects rather than the individual dependent variable. The ratio of log odds ratio is that of two odds plus it is a synopsis computation of the association of two variables. The employment of the log odds relation in logistic regression gives a more unsophisticated account of the probabilistic connection of the changeable aspects and effect in contrast to a linear regression from which linear associations and further rich statistics can be inferred.

There exist two representations of logistic regression, which are binomial logistic regression in addition to multinomial logistic regression. Binominal logistic regression is characteristically used in the event the dependent aspect that is varying is dichotomous while the autonomous variables are either permanent or definite variables. Logistic regression is majorly employed in this circumstance. In the event, the dependent variable is never dichotomous in nature and consists of over two instances; a multinomial logistic regression could be utilized. It is as well known as logit regression, whereas multinomial logistic regression encompasses truly comparable consequences to binominal logistic regression.

Data

Dependent variable dichotomous (clear cut) (bearing a seatbelt or avoiding to bear a seatbelt). If this is not the case then, multinomial (logit) regression is supposed to be employed;

Dependent or Autonomous variables: interval or clear cut

Suppositions:

Presumes a linear connection stuck between the logit of the IVs along with DVs

Nevertheless, it does not presume a liner connection between the clear-cut dependent along with independent variables

2. The example is great- dependability of estimation reduces or goes down when there are merely a handful of cases

3. Ivs are never considered as linear functions of one other

4. Customary distribution is not essential for the dependent aspect or variable.

5. Homoscedasticity is never essential for every level of the autonomous variables.

6. Generally distributed accounts of mistakes are not presupposed.

7. The independent variables require not being in the levels of intervals

Logistic Regression is considered to be a category of the analytical model, which can be employed when the intended variable is a definite variable having two levels – for instance live/die, having an ailment or not having the ailment, buying a product or not buying, winning a race or not winning and many more. A logistic regression representation never not entail judgment trees and is further similar to nonlinear regression, for example, fixing a polynomial to a collection of statistics and values. Logistic regression could be employed primarily with two categories of the intended target variables:

1. A clear-cut target variable, which has precisely two levels (for example a binominal or dichotomous variable).

2. A constant target variable, which has significances in the degrees of 0.0 to 1.0 in lieu of possibility values or percentages.

As an instance of logistic regression, a person should reflect on a research whose intention is to form the reply to a drug as a purpose of the dosage of the medicine given. The intended (dependent) variable, reaction, has a degree 1 if the patient is productively given medication through the drug while 0 if the medicine is not thriving.

The Logistic Model Formula 

This formula calculates the likelihood of the selected reaction being functional figures of the forecaster variables. If a forecaster variable is clear-cut variable having two significances, then one distinct variable the values is assigned the price 1 while the other is allocated the 0 price. It should be noted that DTREG permits a person to employ any figure for clear-cut variables for instance “Male” and “Female”, plus it exchanges these figurative names into 0/1 standards. Therefore, a person does not need being apprehensive of recoding clear-cut values (Consentino & Claeskens 2011, 13). If a forecaster variable is a definite variable having over two levels, then a disconnected model variable is engendered to symbolize every of the levels except for one that is prohibited. The significance of the model variable is 1 on stipulations that the variable is of that class, and the significance is 0 on the stipulations that the variable is of any additional category. Therefore, not an excess of one model variable will be given level 1. On stipulations that the variable encompasses the value of the barred class, after that all of the model variables created for the variable are given the level 0 (Yu-Pin et al 2011, 67). DTREG repeatedly engenders the model variables for clear-cut forecaster variables; all a person requires doing is to select variables as being conditional and clear-cut. In conclusion, the logistic principle has every constant predictor variable, every dichotomous forecaster variable having a 0 or 1 value, and a model variable for each sort of forecaster variables having over two groups minus one group. The outline of the logistic representation principle and rule is: P = 1/(1+exp(-(B0 + B1*X1 + B2*X2 + … + Bk*Xk)))

Where B0 is an invariable while Bi are forecaster variables coefficients (or model variables in the instance of multicategory forecaster variables). The calculated value, P, is a probability in the assortment 0 to 1. The exp () role and function is e elevated to a power.

Maximum Likelihood (ML)

Maximum likelihood, as well termed as the ML technique, is the system of establishing the worth of one or additional constraints for a known marker that makes the acknowledged probability distribution a limit. The greatest likelihood approximate for a limit is denoted. Maximum Likelihood Estimation (MLE)

With this information, a person is in a situation to bring in the idea of the likelihood. If the likelihood, of an occurrence X being reliant on representation parameters p is articulated as

P (X | p)

Therefore, he or she could now discuss the likelihood

L (p | X)

That is to state, the probability of the limits given the statistics.

For nearly all reasonable models, people are capable of finding and establishing certain data that are additionally probable than others. The intention of maximum likelihood evaluation is to unearth the limit value(s) that creates the scrutinized data most probably. This is since the probability of the limits given the data is described to be comparable to the likelihood of the data provided the limits (in principle, they are comparative to one other, other than this does not influence the opinion). If this was done in the trade of making forecasts centered on a position of solid suppositions, then probability interests would be developed – the likelihood of certain results happening or not happening. Nevertheless, in the instance of data study, the moment they have been scrutinized they are preset, there exists no probability part to them any longer (the expression data emerges from the Latin expression denoting given). More interest is in the probability of the representation limits that underlie the preset data.

In CDMA, a key feature that bounds system efficiency is the multiuser intrusion instigated by the user’s nonorthogonality autographed waveforms. Multiuser recognition is an influential tool for fighting the consequences of this multiuser intrusion. Under a number of typical assumptions, the ML multiuser sensor is best in the logic that it offers the minimum fault likelihood in mutually denoting the data signs of all users. Regrettably, to execute the ML sensor, it is essential to resolve a risky combinatorial optimization (A simple method for estimating relative risk using logistic regression 2012, 54).

An Easy Case of MLE

To repeat, the easy theory of maximum likelihood limit view is this: get the parameter values, which create the scrutinized data most probably. How would person carry out this in an easy coin toss try out? Specifically, before assuming that p is a definite value (0.5) the researcher might desire to discover the MLE of p, provided with a dataset. Further than parameter inference, the probability framework permits a researcher to create trials of parameter values. For instance, the researcher might desire to inquire whether or not the predicted p is different considerably from 0.5 or it does not (Kline 2011, 89). This experiment is fundamentally inquiring if there is proof that the coin is unfair. There are further examples of the way such experiments can be carried out with the introduction of the theory of a probability ratio test.

On an assumption that the experimenter tosses a coin 100 occasions and the result appears to be 56 heads along with 44 tails. In place of supposing that p is 0.5, the researcher’s intention is to get the MLE value for p (Sason & Shamai 2006, 76). After that, the researcher will want to inquire if this value varies notably from 0.50. There is a way how this is done. First of all, the p value is established, which makes the scrutinized data most probably. As stated, the scrutinized data are currently set. They will be invariables that are inserted into the binomial likelihood model:-

•n = 100 the whole amount of throws)

•h = 56 the whole amount of heads)

In psychosomatic science, researchers seek out to discover general rules and principles that direct the conduct under study. As these rules and codes are not openly apparent, they are devised in aspects of theories. In mathematical formation, such theories about the formation and internal operation of the behavioral course of significance are affirmed in aspects of parametric relations of likelihood deliveries termed as models. The objective of the formation is to infer the outline of the basic course by checking the feasibility of such formations.

Once a formation is stated with its parameters, as well as, the collection of data, a person is in a position to assess its integrity of fit, specifically, how well it has the capability to fit in the scrutinized data. Integrity of fit is reviewed by establishing parameter figures of a representation that excellently suits the data—a process called parameter inference (Gould et al 2006, 56). There exist two universal techniques of parameter inference. These are LSE and MLE methods of inference. The former has primarily been a well-liked option of model suitability in Finance and is joined to many recognizable arithmetical perceptions, for example, linear regression, summation of squares faults, ratio variance explain, as well as the root mean squared variation (Skiadas 2010, 54). LSE that unlike MLE needs no or negligible distributional suppositions is practical for finding an expressive calculation for the rationale of summarizing experiential data, other than it has no foundation for experimenting hypotheses or making confidence periods (Hosmer & Lemeshow 2000, 67).

Conversely, MLE is never as extensively distinguished among modelers in Finance; however it is a typical progression to parameter inference and suggestion in values. MLE has lots of best properties in inference: satisfactoriness (total information regarding the parameter of concern enclosed in its MLE estimator); uniformity (accurate parameter figure that created the data retrieved asymptotically, for example, statistics of satisfactorily large trials); effectiveness (lowest-possible variation of parameter approximations attained asymptotically); as well as parameterization invariance. On the contrary, no such aspects can be articulated concerning LSE (Wesołowski 2009, 90). Per se, most researchers would not perceive LSE as a common process for parameter inference, but somewhat as a technique that is principally employed with linear regression formations. Additionally, a preponderance of the inference techniques in statistics is established centering on MLE. For instance, MLE is a precondition engulfing the chi-square experiment, the Gsquare experiment, Bayesian techniques, assumption with missing statistics, modeling of arbitrary consequences, and lots of model selection principles, for example, the Akaike statistics criterion, as well as, the Bayesian information principles (Chatterjee & Hadi 2006, 23).

Bibliography

Allison, P. D. (2012). Logistic Regression Using SAS Theory and Application. Cary, NC, SAS

Institute. http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=450974.

A Simple Method for Estimating Relative Risk Using Logistic Regression 2012, BMC Medical

Research Methodology, 12, 1, pp. 14-19, Academic Search Complete, EBSCOhost, viewed 26 August 2012.

Chatterjee, S., & Hadi, A. S. (2006). Regression Analysis by Example. Hoboken (N.J.), Wiley-

Interscience.Cornfield J, Gordon T, Smith WN (2000). Quantal Response Curves for Experimentally

Uncontroled Variables. Bull Int Stat Inst.

Consentino, F, & Claeskens, G 2011, ‘Missing covariates in logistic regression, estimation and

distribution selection’, Statistical Modelling: An International Journal, 11, 2, pp. 159-183, Academic Search Complete, EBSCOhost, viewed 26 August 2012.

Diaz-Quijano, F 2012, ‘A simple method for estimating relative risk using logistic regression’,

BMC Medical Research Methodology, 12, p. 14, MEDLINE with Full Text, EBSCOhost, viewed 26 August 2012.

El-Habil, AM 2012, ‘An Application on Multinomial Logistic Regression Model’, Pakistan

Journal Of Statistics & Operation Research, 8, 2, pp. 271-291, Academic Search Complete, EBSCOhost, viewed 26 August 2012.

Gould, W., Pitblado, J., & Sribney, W. (2006). Maximum likelihood estimation with stata.Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression. New York, Wiley.Kline, R. B. (2011). Principles and practice of structural equation modeling. New York,

Guilford Press. Menard, S 2011, ‘Standards for Standardized Logistic Regression Coefficients’, Social Forces,

89, 4, pp. 1409-1428, Academic Search Complete, EBSCOhost, viewed 26 August 2012.

Sason, I., & Shamai, S. (2006). Performance Analysis of Linear Codes under Maximum-

Likelihood Decoding: A Tutorial. Boston, Mass. [u.a.], Now Publ.Skiadas, CH 2010, ‘Exact Solutions of Stochastic Differential Equations: Gompertz, Generalized

Logistic and Revised Exponential’, Methodology & Computing In Applied Probability, 12, 2, pp. 261-270, Business Source Complete, EBSCOhost, viewed 26 August 2012.

Wesołowski, K. (2009). Introduction to Digital Communication Systems. Chichester, U.K., J.

Wiley.Yu-Pin, L, Hone-Jay, C, Chen-Fa, W, & Verburg, P 2011, ‘Predictive ability of logistic

regression, auto-logistic regression and neural network models in empirical land-use change modeling – a case study’, International Journal Of Geographical Information Science, 25, 1, pp. 65-87, Academic Search Complete, EBSCOhost, viewed 26 August 2012.

student influx. There has been an influx of international students in the Australian universities

Introduction

There has been an influx of international students in the Australian universities (Government of South Australia, 2011). Given that most of these students come from different countries with diverse cultural backgrounds, it becomes inevitable that they have to face a lot of challenges in the course of their studies in this nation. One of the major challenges faced is diet. This means that when they come here, they find a new diet which may be strange to them. However, this leaves them with no choice rather that striving to adapt (Misner B, 2006).

The first thing they should do is to understand the feeding habits in this country. They are obliged to carry out an extensive research to find out the types of foods popular with the Australians. This will enable them to have a deeper understanding of these meals before coming up with the right decision on exactly what to do about it (Simon S, 2003). Making a right decision will be of a great benefit to them since it will give them an opportunity to choose what fits them. Hence, it can be possible for them to continue living a healthy life despite the change (Wojtaszek CA, et al. 2005).

However, before settling on such a decision, these international students should seek the support of dieticians. Since the universities are universal organizations which serve the interest of international communities, it is imperative that they employ full time dieticians (Woods M, et al. 2009). They should be given the responsibility to offer advisory services to the international students on the right type of food to adopt. Their services are necessary because they can be instrumental in guiding these students on the available diets in Australia. Moreover, they can use such opportunities to sensitize them on the foods which can be appropriate for their consumption (McMahon K & Brown JK, 2007).

This paper reports that the most recommended meal for these international students should be aimed at enabling them to continue leading a healthy life as they used to do before. In this consumerism society, people are fond of consuming meals which expose them to lots of health risks (Puckett R, 2004). In this regard, this review suggests that the chosen set of diet should be based on Atkins theory. Meaning, they should be encouraged to consume foods rich in limited contents of carbohydrates. This can be instrumental in protecting them from contracting dangerous diet related ailments such as diabetes and obesity. Moreover, a modification in the diet can be undertaken so that it can address the medical issues that presents with the intake of specific diets. There is need for international students to take artificial foods that have a high proportion of nutrients (Houtzager L, 2009). A proper diet will protect the students from nutritional related diseases.

To conclude this literature review, the students should ensure that they satisfy the recommended dietary intake targets as outlined by the dieticians. Besides, they should learn about all varieties of nutritional foods including their aroma, taste, appearance, food colour, and texture. Briefly, international students in Australia must ensure that they learn about Australian foods and quickly adapt to the diets so that they can continue living a healthy lifestyle. This will enable them to fit into this country and enjoy their studies without any problem.

Research objective and questionThe main objective of the research was to find out how well the foreign students adapt their nutritional needs to the food and the eating habits of the host country. To achieve this, the research aimed at getting an answer to the following questions

How well do foreign students adapt to the food types of the host country and does the food meet their expectations?

What kind of support are these students offered by the administration so as to be able to cope better?

MethodologyStudy design:Qualitative research is a technique of enquiring in-depth understanding of human behaviour in their social environment and the factors leading to such behaviour. This study used the Grounded Theory approach. This theory aims at shaping a certain desire which is discovered in social and psychological processes (Creswell, 2009). Moreover, this method comes with a number of merits such as development of new theories that will be accepted in the research when the research questions cannot be accurately answered. However, it also suffers from the following demerits; in that it requires a lot of labour as well as resources, the scope is also limited due to in-depth approach and it results to the procedural technicalities due to its subjectivity (Babbie, 2011).

This research aimed at studying how international students around Flinders University manage their nutritional needs. As an assistant director in the Ministry of Health and Nutrition, this is a research the researcher carried out as a requirement in his workplace.

Data collectionThe study adopted a one on one interview approach which enabled the researcher to probe deeper on answers that were vague. The researcher constructed an interview guide (Appendix 1) to help him in structuring the interview and collect data (Grbich, 1999). The interview guide was made with the objective of the research in mind so that it could collect data that was as relevant as possible. The questions were all open ended to aid the researcher get a variety of answers.

Pilot interviews were carried out among the peers of the researcher to aid in identifying areas that would present difficulties during the actual interviews and iron them out (Mantri, 2009)

Ethical issuesEthical implications regarding issues on privacy and confidentiality arose in the formulation of the study. Many students felt that the information they give when data is collected may be exposed with their identity and this makes many to decline being recruited as respondents. The respondents were therefore assured of the confidentiality of the data collected. A consent form was presented to the participants and they were required to sign it before any interviewing could be done. The study has received all applicable approvals from all relevant authorities (Appendix 2: Ethics form).

ParticipantsThe research involved participant sampling which involves use of a portion of the population to investigate the behaviour or the characteristics of the entire population (Creswell, 2009). This strategy assists in the cutting down on the time to be spent in the research process, energy, and financial resources. A more precise and efficient sampling strategy was the Stratified sampling where the population is divided into sub-sets of specific size and similar characteristics, where the subsets (or strata) make different quantities of the entire population. The use of sub-sets enhances comparisons and correlation to be made between them making the technique flexible in regard to geographical enquiries. (Kothari, 2008)

This sampling was carried out around restaurants and eating places around the university as these are convenient places to meet with target population of the research study.

Since a qualitative research involves more research input, this required recruiting a number of participants. The sub set was made of international students who are over 18 years old and who hang around the eating places. The participants were also required to be residing around the university and be willing to participate in the exercise.

References

Pribis; Pencak; Grajales. 2010. Beliefs and Attitudes toward Vegetarian Lifestyle across Generations. Nutrients; Volume 2; Issue 5; Pages 523-531. Molecular Diversity Preservation International. http://dx.doi.org/10.3390/nu2050523.

Puckett R 2004, Food service manual for health care institutions, 3rd ed. Jossey-Bass: San Francisco CA.

Simon S, 2003, A survey of the nutritional adequacy of meals served and eaten by patients, Nursing Practice 2001, vol. 4, no. 2 , pp.7-11.

Wojtaszek CA, et al. 2005, Nutrition impact symptoms in the oncology patient, OncolIss, vol. 17, no. 1, pp.15-7.

Woods M, et al. 2009, Effect of a dietary intervention and n-3 fatty acid supplementation on measures of serum lipid and insulin sensitivity in persons with HIV, American Journal of Clinical Nutrition, vol. 90, no. 6, pp.1566–78.

study designs and Data Collection

Introduction

The study design involved the use of a cross-sectional survey and this provided a simplified design and expedited the collection and analysis of the data (Creswell 2009). Kraus (2005) defines a cross sectional study as one where the researcher identifies a subset of the whole population under study and collects data at a single point in time. This subset must be well representative of the whole population. The cross sectional survey questionnaires interviews were conducted on one day again with an emphasis on time and expedience. The data collection and analysis was quantitive in nature, this approach was favoured as it would eventually produce data that was systematically arranged and that was easy to logically analyse (Creswell, Trout and Barbuto, 2004). The data hence collected was easy to analyse through various methods and mediums and help the researcher come to a deductive conclusion.

Participants and Sampling

The population was a convenience sample drawn from 100 international paramedic students who were given an opportunity to participate and from this n=30 participants completed the survey. A clustering technique was used so as to offer a notification to participate in several meetings as it is impossible to ascertain a sample without a list (Creswell 2009). Since surveys were handed out to only those who were international paramedic students and were available to participate it was a convenience sample (Babbie 1990, in Creswell 2009). Convenience sampling involves picking respondents from among those who are easily available, this helps ease the rigours involved in searching for respondents from a large sample. The major shortcoming of this approach though is that the data collected might not be representative of the whole population (Creswell 2009). There was no stratification, only male participants were invited to participate (Creswell 2009). With 100 surveys and an estimated 10% response sample the calculated margin of error is 4.9% with a confidence rating of 90% (Relevant Insights 2012).

Data Collection

Data collection was done from the self-administered questionnaires (Appendix 1) that were designed using a five point Likert scales, multiple choice and yes/no questions this enables participants to rank responses (Huck 2008). The questions were closed and answers were from a limited population that enabled generalization of findings for comparison (Creswell 2009). I was able to make estimates of attributes from a small group and thereby, make assertions about a larger population (Fowler 1998; Babbie 1990, in Charema 2004). From this it was possible to make generalisations about behavioural characteristics of the population.

The survey was sectionalised first section addressed demographic information, the second discussed experience and the third directly as to stress predictors. The researcher looked at previous studies in the field of job related stress for paramedics and narrowed down the questions from these studies to suit his research question and hypotheses. The researcher was fortunate to have had the input of the course supervisor who has also written extensively on the topic of job stress previously. The quantitative data collected from the questionnaires was time efficient and enabled the researcher to rapidly turn around the data and evaluate the information to publish findings (Creswell 2009).

References

Blau, G, Chapman, S & Gibson, G 2011, ‘Exploring the Importance of Different Items as Reasons for Leaving Emergency Medical Services Between Fully Compensated, Partially Compensated, and Non-Compensated/Volunteer Samples’, Journal of Allied Health, vol. 40, no. 3, pp.e33-e37.

Blumenfield, M, & Byrne, D 1997, ‘Development of Posttraumatic stress disorder in urban Emergency medical Service workers’, Medscape Mental Health e-Journal, vol.2, no.9.

Boudreaux, E, Mandry, C & Brentley, P 1997, ‘Stress, job satisfaction, coping, and psychological distress among emergency medical technicians’, Prehospital and Disaster Medicine, vol.12, vol. 4, pp.242-249.

Bryman, A., and Cramer, D. (2008), Quantitative Data Analysis with SPSS 14, 15, 16, Routledge, London.

Similarities are based on the geographic settings, the portrayal of racism, and the specifics of the court case

Introduction

Similarities are based on the geographic settings, the portrayal of racism, and the specifics of the court case

Body

Geographical setting

Similarity in Portrayal of racism

Similarity in the specifics of the court cases

Conclusion

What entails moral courage and the summation of Tom Robinson and Scottsboro boys’ case