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Impact on the Behavior of Students due to Online technology Gaming and Its Effect on their Academic Performance

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Influence of online computer games on the academic achievement of nontraditional undergraduate students

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• https://doi.org/10.1080/2331186X.2018.1437671

1. Introduction

2. theoretical framework, 3. literature review, 4. formulating the problem, 5. data evaluation and analysis, 6. results of analysis, 7. discussion and conclusions, additional information.

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Technological advances have provided educational institutions the capability to explore various online teaching strategies such as digital games in the classroom. Though games can be used to engage various learning styles and behaviors, the platform is mainly practiced at the secondary educational grade level with traditional-aged students. Little research literature exists that explores the influence of digital game-based learning on the academic achievement of nontraditional undergraduate students. An extensive literature review of 77 articles was conducted using the procedure developed in Cooper’s Taxonomy (1998) for analyzing and synthesizing literature. Cooper’s system involved (a) formulating the problem, (b) collecting data, (c) evaluating data appropriateness, (d) analyzing and interpreting relevant data, and (e) organizing and presenting the results. This scoping literature review explores how digital games can be used in the educational environment to support the learning of nontraditional students.

• nontraditional students
• computer games
• academic achievement
• higher education
• part-time student
• post-secondary education
• gamification
• game-based learning

Public Interest Statement

Many US college and university leaders need to construct ways to engage and retain non-traditional students who make up 75% of student enrollment. During the Obama administration, the US was tied for 12th position with 39% of adults having a minimum of an associate degree. Digital game-based learning, when aligned with the learning objectives of a course or curriculum has been shown to provide a hands-on, interactive, and real-life application learning experience. Learners are engaged through the cognitive, psychomotor and affective domains which increase the opportunity for retention, persistence, and graduation. If the United States is to once again lead worldwide in college degree attainment, the percent rate of successful college graduates needs to raise to 56% by the year 2020. Finding ways to engage the largest but most vulnerable population of learners on campus is vital to the US global position and workforce development.

Though 75% of nontraditional or adult learners enroll in a colleges or universities in the United States, only 33.7% complete college with a degree or certificate (New, Citation 2014 ). The US Department of Education ( Citation 2002 ) defines non-traditional students as learners over the age of 24 who are not only balancing work, life, and family but also returning to school after a pause in educational pursuit. A study of 4.5 million non-first-time students conducted by the National Student Clearinghouse Research Center reported only a third of nontraditional students completed college compared to 60.7% of traditional learners (New, Citation 2014 ). Finding instructional strategies that engage, motivate, and retain nontraditional learners are not only critical to the academic success of this population of students, but also to the continued development of workforce talent in the United States.

Digital game-based learning is an instructional method that has shown promise in adult education and learning (Anderson, Anderson, & Taylor, Citation 2009 ). Digital game-based learning combines educational content with the use of video games. The digital games are explicitly designed for educational purposes and have the capability to engage a diverse of learning styles and behaviors. Learning can take place in both formal and informal environments, one-on-one or in groups. Game-based learning has shown to increase various abilities related to cognition such as perception, reasoning, critical-thinking, spatial navigation, and memory retention (Granic & Lobel, Citation 2013 ).

Unfortunately, current empirical research conducted on digital game-based learning mainly focuses on adolescents (Ding, Guan, & Yu, Citation 2017 ). Though some research examines the effectiveness of using digital games-based learning on traditional college students (Ding et al., Citation 2017 ), a limited number of studies are dedicated to explore the influence of digital game-based learning on undergraduate non-traditional students. The integration of digital games in the educational environment has shown positive results in enhancing the learning process (Trybus, Citation 2014 ). Strategically designed and integrated, digital games have the potential to increase academic and learning effectiveness. This scoping literature review examines the research on digital game-based learning for non-traditional students enrolled in postsecondary education and the implication games can have on achievement and learning outcomes.

The framework for the scoping literature review is supported by two theoretical models: Adult Learning (Knowles, Citation 1984 ) and Situated Cognition (Brown, Collins, & Duguid, Citation 1989 ). The focus of a scoping study is to place knowledge regarding a particular topic in a conceptual framework, map relevant literature, and present what is known and unknown (Anderson, Allen, & Peckham, Citation 2008 ). The broad range of data can be inclusive of both material from empirical and non-research materials (2008). The objective is to generate meaningful discussion around a specified topic.

Knowles ( Citation 1984 ), one of the leading teachers, scholars, and practitioner of adult-learning and education was considered the father of andragogy. After extensive research, Knowles outlined four principles related to adult learning that applied to non-traditional students. These principles are: adult learners must be included in the assessment and planning of their learning; adult learners’ experiences and mistakes form the foundation for learning; adult students are interested in subjects that are immediately connected to their lives or employment; and learning is more meaningful when problem-based as opposed to theoretical or ambiguous (Kearsley, Citation 2010 ).

Situated Cognition theory, the second theory, is based on the premise that knowledge is formed and supported by the cultural, social, and physical experiences and situations of an individual (Brown et al., Citation 1989 ). Learning occurs in the everyday life experiences of an individual and the theoretical model emphasizes an authentic context for skill acquisition (Brown et al., Citation 1989 ). Learning is organic, meaningful, and effective when materials are rooted in personal connections and reflect real-life experiences (Herrington & Oliver, Citation 1995 ). Students persist academically when course lessons and materials are made relevant to the lived experience (Park & Choi, Citation 2009 ).

Digital game-based learning aligned with many of the suggested parameters outlined by theories of Situated Cognition and Adult Learning promotes effective adult learning (Kearsley, Citation 2010 ). The digital gaming experience provides learning within a specific problem-solving context which allows adult learners to use their experiences and errors as a gage for learning. In many cases, the games are related to real life experiences or careers skills found in the work environment. Digital game-based learning provides nontraditional learners with more authentic context for skill acquisition (Trybus, Citation 2014 ). Important features connecting adult learning and digital games are: (1) genuine context which mirrors how information is utilized in real-life, (2) presents authentic activities, (3) numerous points of view and roles, (4) games can give linked assessment of the learning, (5) can scaffolding learning or instruction at decisive points (Herrington & Oliver, Citation 1995 ).

The use of digital game-based learning as supplementary aids at the university level is in the early stages of development (Herro & Clark, Citation 2016 ; Holmes & Gee, Citation 2016 ; Kanthan & Senger, Citation 2011 ; Moylan, Burgess, Figley, & Bernstein, Citation 2015 ). College and university leaders hesitate to use digital games at the postsecondary level because of insufficient data on learning outcomes, assessments, and academic performance directly linked to digital game-based interventions (Kanthan & Senger, Citation 2011 ; Vandercruysse, Vandewaetere, Cornillie, & Clarebout, Citation 2013 ). Ding et al. ( Citation 2017 ) stated, “due to difficulties in defining, constructing, and measuring complex variables as well as the subsequent results, rigorous empirical research on the effectiveness of gamification in education or game-based learning has been limited” (p. 148). However, technology savvy students seek an engaging hands-on interactive learning experience that is available in game-based learning. To increase teaching effectiveness, instructors must develop an understanding of the internal structure of digital game design as well as the limitations of technology (Kanthan & Senger, Citation 2011 ). Research is lacking in the design aspects of digital games and the related learning to non-traditional students (Tham & Tham, Citation 2014 ). The lack of research and comprehension deter the use of digital gaming for instructional purposes.

Indications of interest in digital game-based learning are noted in research studies across many disciplines. For example, significant gains over traditional teaching methods for both male and female students were reported when a 3D game-based learning system for teaching engineering content was assessed (Su & Cheng, Citation 2013 ). The display of a positive attitude and engagement were higher for engineering students who used digital games, compared to the engineering students who learned via traditional teaching methods (Boeker, Andel, Vach, & Frankenschmidt, Citation 2013 ). The use of digital game-based learning resulted in increased cognition for medical students over script-based instruction (Boeker et al., Citation 2013 ; Rondon, Chiarion, & Furquim de Andrade, Citation 2013 ). Digital games often provide a safe environment for students’ learning a second language thereby reducing anxiety and increasing willingness to communicate which directly affects language learning (Reinders & Wattana, Citation 2015 ).

Alternatively, digital games were not always found to inspire students in higher education. A group of college students in Singapore who were found to possess a high level of intrinsic motivation showed no increase in motivation or engagement due to the use of games (Tham & Tham, Citation 2014 ). In fact, the Singapore students who were unfamiliar with digital games-based learning experienced feelings of apprehension. Further assessments on student learning indicated the continued need to use a combination of lecture with digital learning (Rondon et al., Citation 2013 ). Familiarizing students with the technology requires extensive time, which further delays learning. Adjusting for these differences presents challenges for instructors (Holmes & Gee, Citation 2016 ). Another factor that affects student acceptance of digital games in learning is the mindset of students accustomed to a passive style of learning through the lecture format (Herro & Clark, Citation 2016 ).

Digital games-based learning has been used to increase student retention, build teamwork skills, and communication (Bodnar, Anastasio, Enszer, & Burkey, Citation 2016 ). Furthermore, digital gaming technology provides the option to measure students’ progress over extended periods of time due to the prolonged interaction and play with the games. To be effective at the university level, digital games must align with the course content and course objectives (Moylan et al., Citation 2015 ).

Few studies examined the relationship between digital games and achievement for non-traditional students (Burgess, Stermer, & Burgess, Citation 2012 ; Young et al., Citation 2012 ). In fact, the National Research Council suggested research be conducted on games and learning while also admitting that little evidence exist to support digital games as a tool for achievement (Clark, Tanner-Smith, & Killingsworth, Citation 2014 ). Recommendations on how best to employ digital games to improve learning outcomes are available, however, a broader understanding of the possible influence on diverse learners or subject matters is required (Kim & Chang, Citation 2010 ).

The stated problem is that although extensive literature is available on the influence of digital game-based learning on traditional students, scant research exists that explores the use of digital game-based learning specifically on the academic achievement of nontraditional undergraduate students.

To examine the problem, the following questions guided the review:

Research Question 1 : How is digital game-based learning used as a supplemental tool to engage nontraditional students in classroom instruction and coursework?

Research Question 2 : How is digital game-based learning used to build learning and work-related skills for nontraditional undergraduate students?

Research Question 3: In what subjects are digital game-based learning used to engage nontraditional students in classroom instruction and coursework.

The purpose of this scoping literature review was to frame the discussion surrounding digital game based learning as pertains to nontraditional students, create meaningful dialog, identify existing gaps, map out relevant literature, and synthesis findings from various studies.

4.1. Method

An in-depth understanding of a topic, such as digital game-based learning for nontraditional students, is achieved through identification of what has already been researched and areas needing further exploration. To provide a comprehensive understanding of a particular topic, a systematic review of the literature is required (Booth, Papaioannou, & Sutton, Citation 2012 ). To address the research problem the researchers conducted a literature review using the systematized procedure developed by Cooper ( Citation 1998 ) for synthesizing the literature. The Cooper organizational structure outlined how to (a) formulate the problem, (b) collect data, (c) evaluate the appropriateness of the data, (d) analyze and interpret relevant data, and (e) organize and present the results. Results were compared with issues existing in large higher education institutions where digital games were being used as an instructional tool. Use of a structure such as Copper, increases the study objectivity, constructs a contextual framework, and clarifies the objectives of the review for the reader (Cooper, Citation 1988 ). Cooper’s taxonomy has been shown to be a reliable method for conducting a review.

4.2. Data collection

A search was conducted to find empirical studies including quantitative, qualitative, mixed method, comparative and theoretical analyses, and literature reviews to answer the research questions. Key search words included non-traditional students, non-traditional learners, games, and game-based learning. Other keywords included adult learners, GameScape, Toolwire, gamification, and for-profit universities. Search engines used for the literature research included Google Scholar, ProQuest, and EBSCO HOST. Databases included Education Sources, Educational Resources Information Center (ERIC), Computers and Applied Sciences Complete, Cochranes. Database searches were conducted individually after checking thesaurus terms to ensure a comprehensive search. Additionally, searches were conducted in multiple database packages. Search terms derived from thesaurus searches included: non-traditional students, older students, working adults, part-time undergraduates and games, gamification, simulations, and classroom technologies. These terms were used alone or together in multiple combinations. A sample of 77 articles was collected for analysis. Although many articles could be used to provide background and context, based on the outlined procedure, 14 articles were studied intensively for RQ 1, 2 and 3 (Tables 1 , 2 , and 3 ). The search also included articles pertaining to digital games incorporated in the curriculums of for-profit universities. For-profit universities serve non-traditional undergraduate students as a primary population. The emerging data on the current practice of using DGBL are incorporated into Table 3 . A third research question was developed in response to emerging data. Articles that included varied learners fitting one or more criteria for a non-traditional undergraduate student in higher education were included. Documents indicating a primary focus on traditional undergraduate students were excluded from the research.

Table 1. Ways that digital game-based learning are used to engage nontraditional students

Table 2. learning and work-related skills developed by using digital game based learning, table 3. subjects that digital game based learning are used to teach them in higher education.

The scoping study review included articles that were empirical studies related to digital games as a strategy for increasing learning and could be used to answer the research questions. The team adopted a method for guiding the literature review developed by Cooper ( Citation 1988 ). An extensive search for literature was conducted using the terms and search strategies described above. A broad-based definition of nontraditional students was adopted that included those who study part time, work full time or at part time jobs that require many hours, students aged over 24, ESL learners and those enrolled in distance learning, particularly enrolled at for-profit universities that primarily serve nontraditional students. US Department of Education definitions for nontraditional students were used and individuals needed to meet only one of these criteria to be considered a nontraditional student (Zawacki-Richter, Müskens, Krause, Alturki, & Aldraiweesh, Citation 2015 ).

Some limitation of the study were articles that did not include specified search terms might have been overlooked because of scant research on the topic. Each team member assumed responsibility for reviewing specific articles related to a research question. The entire team checked and counter checked each other’s work and reviewed the analyses to ensure accuracy and validity.

RQ1: How is digital game-based learning used as a supplemental tool to engage nontraditional students in classroom instruction and coursework.

The following descriptions are presented as derived from an analysis of each article identified as related to findings for research question 1. The themes in this section are: (a) Design and Motivation, (b) Feedback and Alignment, (c) Finance Achievement, and (d) English Language Learning Achievement. The summary presents key findings. Table 1 provides key information for the response to RQ1 from each article including the topic, authors, design, and results. A discussion follows Table 1 and implications of the research are indicated in the final section before the responses for RQ2 and 3.

6.1. Design and motivation

Flores ( Citation 2015 ) conducted an extensive analysis of related literature and existent digital games for teaching a second language. Digital games for every age group, including non-traditional adult learners, were analyzed using a literature-based framework of theory and research. The digital games promote a learner-centered approach, which relies on and supports intrinsic motivation when compared to traditional teaching methods that often undermine learning and decrease motivation. More empirical research is needed on games as a learning strategy for acquisition of a second language.

In a large lab setting, where students ranged in age from 18–41, digital games were shown to increase the level of participation and engagement in the learning content that was not related to age or gender, therefore providing motivation even for diverse learners (Nadolny & Halabi, Citation 2016 ). No association was found between the final grade and age, gender, gaming experience, or learning style. Designing the digital game-based course took a great deal of time particularly related to assessment and feedback. Further, students responded to open-ended questions at the end of class indicating they preferred the digital game-based experience in class.

Postgraduate students working with theory in a digital game-based business module reported the experience engaging and enjoyable (Brady & Devitt, Citation 2016 ). The reflective experiences were more meaningful than winning or losing a game but also supported continued participation even after losing. Course content must be aligned with the context for the digital game to be effective for learning.

Using a theoretical framework drawn from the literature, Trybus ( Citation 2014 ) analyzed the qualities of traditional, game based, and hands on training. Digital game based and hands on training offer the opportunity to be experiential learners and serve as active participants in the learning process to develop higher order thinking skills. Students found the challenge of digital games enjoyable, which led to increased motivation. However, digital game challenges can have a negative effect on learner motivation (Brady & Devitt, Citation 2016 ) indicating the need for support for students who are learning to navigate the digital gaming architecture.

6.2. Real life experience

RQ 2: How is digital game based learning used to build learning and work-related skills for nontraditional undergraduate students?

The following descriptions are derived from an analysis of articles that indicated digital game-based learning aids in the development of work-related skills and abilities in 2017. The themes in this section are: (a) Building Competencies, (b) Building Employment Competencies, (c) In the Military, (d) Collaborative Learning, and (e) Math. Research question 2 also allowed the research team to explore postsecondary institutions and disciplines where computer games have been integrated into courses that serve and support non-traditional undergraduate students. The following descriptions are presented as derived from an analysis of university documentation where games were used as a part of the curriculum. These are displayed in Table 3 . The themes are: (a) Critical Thinking, (b) Psychology, (c) Writing, (d) Environment Science, (e) Nutrition, (f) Adaptable Games, have been studied.

Table 2 provides key information about each article including the topic, authors, design, and results. A discussion follows Table 2 and implications of the research are indicated in the final section.

6.3. Building competencies

A contemporary society requires that students think-critically, collect, synthesize data, and use that information to solve complex problems (Anderson et al., Citation 2009 ). Students must be able to modify and integrate new methods in reaction to new requirements or dynamic situations. Also, can use technology to generate new knowledge. Digital games provide learners the opportunity for a hands-on and real-life application which can lead to increase knowledge and awareness of issues, actions, and resolutions surrounding complicated issues.

Digital games are incorporated into a course for undergraduate nontraditional learners to allow students to auto-assess whether they have learned the material. When nontraditional students play games, they become involved in intricate changing worlds. Within the digital game play, students are made aware of details, come to conclusions, and take prompt action. If unsuccessful, students do the same task again, so knowledge is gained from errors as they progress toward mastery (Carroll & Borge, Citation 2007 ). Digital skills have changed the way we express and communicate in the twenty-first century, (McFarlane, Citation 2003 ) are mirrored in digital gaming, and may be essential to nontraditional student achievement.

6.4. Building employment competencies

Digital games are used in a course for nontraditional learners to help build employment competencies and skills for nontraditional students (Snow, Citation 2016 ). The National Adult Learners Satisfaction-Priorities Report examined trends in satisfaction of adult learners, as well as how likely adult learners were to recommend the program to other adults. Findings related to enrollment factors for adult learners showed that at four-year institutions, 85% of the adult learners enrolled based on a requirement for a current or future job. Learning with digital games gives the non-traditional learner an opportunity to develop new abilities and expertise which they might use in employment and achievement (Levy & Pliskin, Citation 2012 ).

6.5. In the military

Online programs enroll a large percentage of students are active military because of the accessibility and flexibility of the course offering. The military has advocated for the use of games for teaching since 1997 (Kearney & Pivec, Citation 2007 ). The military recommends adopting computer games as learning tools (Mead, Citation 2013 ). Digital games are also used by the military to re-acclimate soldiers to civilian activities (real-world activities), as well as dealing with PTSD (Mead, Citation 2013 ).

6.6. Collaborative learning

RQ3: In what subjects are digital game-based learning used to engage nontraditional students in classroom instruction and coursework

In addition, the research team investigated how universities that primarily serve non-traditional students might be using DGBL with non-traditional students. We researched for profit universities because they primarily serve non-traditional students. Table 3 displays findings for this search.

A new digital game was recently published by a university professor at Texas A&M (Tate, Citation 2017 ). The game, Variant, launched in January of 2017, is designed to help students learn math while enjoying the learning experience. Variant uses an avatar to help learners solve calculus-based equations. During the launch period, the digital game was requested by 400 university faculty in over 300 universities, which indicates the interest in digital game based learning programs.

6.8. English language learning achievement

A block-clearing digital game was developed to provide vocabulary practice in an English course for students in their first year at a Taiwan university. Researchers Ting-Ting and Yueh-Min ( Citation 2017 ) studied the implementation of the digital game in classroom instruction for students majoring in information management. Participants for the study consisted of three classes totaling 94 students. The same instructor taught all three groups. An ANOVA was used to compare student achievement for those who used the digital gaming program as part of the course instruction and those who were taught using traditional means. Results of the study indicated that students who used the games achieved at higher levels and were more interested in learning.

6.8.1. Develop critical thinking

Some of the leading for-profit and state colleges and universities use digital games to engage and teach critical-thinking skills to non-traditional students who make up a large percentage of their enrollment. University of Phoenix uses “Critical Thinking in Everyday Life”, a GameScape by Toolwire in HUM/115, to help nontraditional students develop critical thinking skills (Toolwire Games, Citation 2016 ) through a computerized, storytelling, experiential learning experience using the latest gaming technology. Students use investigative techniques in scenarios that connect theory to real-life concepts. Student are forced to assume certain characters, use interactive objects and connect previous knowledge to create new understanding to solve mysteries. Learning through digital games can help nontraditional students to think in novel or unusual ways about abstract ideas or knowledge. Digital game-based learning has been thought to be more successful than traditional teaching methods regarding constructing thinking related to memory skills and learning (Kolb & Lewis, Citation 1986 ). Better memory skills and learning can lead to better achievement for nontraditional students.

Digital game-based learning teaches ideas by involving students in experience by devising arenas in which information is used for a practical purpose (Squire, Giovanetto, Devane, & Durga, Citation 2005 ). By demonstrating authoritative problem solving and integrating situations that enable students to construct meaning based on previous comprehension, digital games provide practical experiences for non-traditional learners. These aspects create an ideal environment for the acquisition of knowledge or skill building. Building academic skills in a positive manner is one area in which computer games help nontraditional students reach learning goals (Snow, Citation 2016 ).

6.8.2. Reinforcing content in psychology

Digital games are used in courses for non-traditional students to reinforce content and real-world application. University of Phoenix uses “What Happened to Uncle Bob? a GameScape Mystery” to help teach psychology in PSY201. The first episode involves Scientific Inquiry. The other subsequent episodes involve Human Development, Emotions and Motivation, Individual Differences, and Abnormal Psychology. Students learn skills such as the steps in the scientific method, collecting evidence, and examining pieces of information that lead to solutions.

6.8.3. Skill building in writing

To teach writing skills, University of Phoenix uses, “University Writing Essentials: Live! News” in ENG 147 University Writing Essentials. After completing each episode students save their responses to a PDF file and send it to their instructor. The digital game covers areas such as paragraph building, quoting/paraphrasing activity, fixing paragraphs, and essay construction kit.

6.9. Environmental science

Every module in the Sparksville 25 game program corresponds to learning objectives. Included is a point system for performance measurement and competition. Modules within the game are: Balancing Ecosystems, Managing Population Growth, Maintaining Terrestrial and Atmospheric Resources, Controlling Energy Systems, and Building a Positive Environmental Agency. Digital game-based learning provides a means for operative learning, transfer of the application of knowledge, theory to realistic activity and experience (Anderson et al., Citation 2009 ).

6.10. Nutrition

The University of Phoenix uses a Toolwire GameScape episode, “Nutrition—A Key to Health” in SCI 220, Human Nutrition. This online game allows non-traditional students to explore the following modules in a game format: a key to health, nutrient sources and significance, energy balance, vitamins, minerals and water, fitness and food safety, and a focus on life stages. Another nutrition GameScape that may be used in a Nutrition course for non-traditional learners is “Where Health Happens”. Likewise, “Health and Wellness: The Game Show Where Wellness Wins!” may also be used in health courses.

6.11. Adaptable games

Toolwire Games are educational games with assessments and tasks that include realistic video. The digital games are grouped into subject areas that contains several games. The Toolwire games are used in face to face, blended, or online courses. The following universities use the Toolwire games: University of Phoenix, Arizona State University, Capella University, Kaplan University, Columbus State Community College, and Strayer University (Toolwire Games, Citation 2016 ). These universities enrollment consist of a large population of nontraditional students. Using the Toolwire educational games assist students’ achievement in the given curriculum areas.

7.1. Significance

Limited research literature exists on the impact of digital game-based learning on non-traditional students. As a result, some of the research articles referenced include participants who are categorized as traditional students but also qualify as nontraditional under the stated definition. Only a few such studies exist including: Hayes and Ohrenberger ( Citation 2013 ), on the effect of digital games and gaming for pre-service teacher education; Hanson-Smith ( Citation 2016 ), on motivation; and Foss et al. ( Citation 2014 ) on the effects of a digital game for nursing students on administering proper dosages of medications. Jabbar, Azita, and Felicia ( Citation 2015 ) conducted a review of games-based learning and developed a series of recommendations for the future design of educational games. The concept of digital game-based learning in instruction is international in scope and interest. For example, Chik ( Citation 2014 ) examined the use of digital games to stimulate second language learners in East Asia. The present study examines literature for the effects of gaming on learning for the fast-growing population of nontraditional undergraduate students. The study has both national and international implications that leads to providing comprehensive understanding of the influence digital game-based learning has on the learning outcomes of nontraditional students when integrated into a university course or curriculum.

7.2. Contributions, implications of the study, and results

Digital games, when used as a supplemental tool have a positive influence on the academic achievement of nontraditional students pursuing an undergraduate degree. As the number of nontraditional students enrolled in colleges courses and online classes increase, post-secondary institutions are pressured to develop effective strategies to not only engage but promote academic success for this population of students. As a result, the demand for digital games in education for nontraditional undergraduate students will continue to grow because of the potential role in academic achievement and student engagement. However, if digital games are to be effective, course learning objectives must be related and directly connected to the game. A direct alignment is required between the game, feedback, learning outcomes, and assessment.

Digital games have been found to promote students’ confidence, satisfaction, interest, and effort (Keller, Citation 2008 ). These types of digital games provide an authentic context for skill acquisition, and connect theoretical in-class lessons to real-life application which is supported by the situated learning theory (Brown et al., Citation 1989 ). Colleges and universities must develop a better understanding of the optimal circumstances and systems that best accommodates the learning needs and behavior of nontraditional students taking online courses.

Nontraditional students’ needs are unique and different from those of traditional students. Additional attention is required by institutions to ensure this population of students feel supported and successful in their academic endeavors. Leveraging the use of technology, specifically digital games, increase student retention and decrease the attrition rate resulting in increased graduation rate. Positive results have been found in such areas as English as a Second Language (ESL), nursing, mathematics, military, and engineering. Students experienced increased levels of engagement, motivation, academic success, problem solving, and critical thinking. Further, digital games used as a learning resource and tool provide non-traditional students access to a quality education and meaningful learning experience.

Technology has had a great influence on every aspect of society and is constantly evolving. Higher education institutions still struggle with how to effectively integrate electronic devices in the classroom to increase student engagement, development, performance, and learning outcomes. The lack of guidance is apparent by the existing gap in research literature that addresses the topic of the use of digital games to engage nontraditional students. This literature review attempts to bridge the gap by providing an overview of the existing problem, methods, benefits, challenges, and possible solutions. The hope is that educational administrators, policy-makers, instructors, and decision-makers better understand the complex issues surrounding the educational needs of nontraditional students and how digital games support efforts to improve persistence, access, equity, retention, and persistence to obtain a quality education.

7.3. Results and conclusions

Nontraditional students possess different learning behaviors and levels of motivation (Knowles, Citation 1984 ; Pelletier, Citation 2010 ). However, incorporating the principles derived from the literature on traditional students, allows instructors to adapt and use digital games to support the nontraditional learners. For example, digital games, were used in computer science programs to enhance student learning for traditional learners (Angel, Caudell, & Whitmore, Citation 2017 ). Other fields where traditional students have experienced positive outcomes include medical education, particularly in preparing nursing students (Blakely, Skirton, Cooper, Allum, & Nelmes, Citation 2008 ). Business is another area where simulations are incorporated to model real-life situations that traditional students may encounter in their discipline (Davis, Citation 2011 ; Tanner, Stewart, Totaro, & Hargreave, Citation 2012 ). Digital games are used in many disciplines including: Cartography, Corporate Training, Mathematics, Microbiology and Electromagnetic Theory (Beylefeld & Struwig, Citation 2007 ; Chen, Liao, Cheng, Yeh, & Chan, Citation 2012 ; Feeney, Citation 2007 ; Kumer & Lightner, Citation 2007 ; Thomas & Mead, Citation 2008 ).

Learning by way of active participation and drawing inferences from that experience is a core idea of the constructivist theories of learning (Facer, Citation n.d. ; Rogoff, Citation 1994 ; Vygotsky, Citation 1980 ). Digital games in education provide an interactive and hands-on learning experience, especially when experiential learning is used to engage adult learners (Knowles, Citation 1984 ). The digital games and simulations take students into another world and let them experience life in another dimension (Nkonyane & Van Wyk, Citation 2015 ).

When used as a supplemental tool in online courses, digital games have a positive influence on the motivation, academic achievement, and retention of nontraditional students pursuing an undergraduate degree (Snow, Citation 2016 ). The use of digital games as supplemental learning aids promotes students’ confidence, satisfaction, interest, and effort (Keller, Citation 2008 ). Digital games provide an authentic context for skill acquisition, and help relate what students learn to their everyday life which is supported by the situated learning theory of Brown et al. ( Citation 1989 ).

The study was designed to provide information on digital game-based learning for nontraditional learners that will enable educational administrators, leaders, policymakers, instructors, and decision-makers to better understand the complex issues surrounding the educational needs of nontraditional students. A second purpose was to show how digital games support efforts to improve learner persistence, access, equity, retention, and persistence. The goal is to enable educators in providing a higher quality education for nontraditional students.

7.4. Recommendations

The findings indicate that using digital games in courses for nontraditional undergraduate students have benefits in areas of academic achievement. The use of digital games is recommended in undergraduate programs for promoting and developing problem-solving, critical-thinking skills (Trybus, Citation 2014 ), and achieving the learning goals of instruction (Adachi & Willoughby, Citation 2013 ). Using digital games as supplemental tools in courses for nontraditional students are recommended to improve cognitive skills such as memory and reasoning (Granic & Lobel, Citation 2013 ). Since digital games have the potential to increase student success, Ma, Jain, and Anderson ( Citation 2011 ) recommend educational game developers consider these factors in game design. A further recommendation is that course designers and educators incorporate games aligned with the course content (Brady & Devitt, Citation 2016 ), and that digital games are selected which target instructional goals to maximize learning. Another recommendation is to include digital games as supplemental tools to increase class relevance and learning engagement (Park & Choi, Citation 2009 ). A final recommendation is that digital games be related to learners’ career, job or life to develop transferable and marketable skills to the workforce (Park & Choi, Citation 2009 ). The sparse number of articles found that explored or assessed the experiences of nontraditional students for this study exposed a gap in the literature. In the first decades of the twenty-first century, nontraditional undergraduates are entering undergraduate programs in greater numbers (New, Citation 2014 ). The purpose of this scoping literature review was to frame the discussion surrounding digital game-based learning as it pertains to nontraditional students, create meaningful dialog, identify existing gaps, map out relevant literature, and synthesize findings from various studies.

The authors received no direct funding for this research.

Notes on contributors

Patrick e. turner.

The authors are both researchers and practitioners in the field of education who are either faculty members or administrators at a post-secondary institution serving both traditional and non-traditional students. The team lead, Patrick Turner is the Director of Student Support Center-Helena College at the University of Montana whose research focus is student retention and persistence. Elizabeth Johnston currently serves as Senior Research Fellow for the Center for Educational and Instructional Technology Research (CEITR). Mansureh Kebritchi is the Chair of CEITR in the School of Advanced Studies. David Heflich is a researcher in the (CEITR), mentors doctoral students for UOP and for Nova Southeastern University. Sally Evans is a researcher in CEITR who serves as a Doctoral Chair and on candidate committees. All members have an active research agenda in the field of education and scholarship is presented at both national and international conferences.

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How to Write a Statement of the Problem in Research

Table of Contents

The problem statement is a foundation of academic research writing , providing a precise representation of an existing gap or issue in a particular field of study.

Crafting a sharp and focused problem statement lays the groundwork for your research project.

• It highlights the research's significance .
• Emphasizes its potential to influence the broader academic community.
• Represents the initial step for you to make a meaningful contribution to your discipline.

Therefore, in this article, we will discuss what is a statement of the problem in research and how to craft a compelling research problem statement.

What is a research problem statement?

A research problem statement is a concise, clear, and specific articulation of a gap in current knowledge that your research aims to bridge. It not only sets forth the scope and direction of your research but also establishes its relevance and significance.

Your problem statement in your research paper aims to:

• Define the gap : Clearly identify and articulate a specific gap or issue in the existing knowledge.
• Provide direction : Serve as a roadmap, guiding the course of your research and ensuring you remain focused.
• Establish relevance : Highlight the importance and significance of the problem in the context of your field or the broader world.
• Guide inquiry :  Formulate the research questions or hypotheses you'll explore.
• Communicate intent : Succinctly convey the core purpose of your research to stakeholders, peers, and any audience.
• Set boundaries : Clearly define the scope of your research to ensure it's focused and achievable.

When should you write a problem statement in research?

Initiate your research by crafting a clear problem statement. This should be done before any data collection or analysis, serving as a foundational anchor that clearly identifies the specific issue you aim to address.

By establishing this early on, you shape the direction of your research, ensuring it targets a genuine knowledge gap.

Furthermore, an effective and a concise statement of the problem in research attracts collaborators, funders, and supporters, resonating with its clarity and purpose. Remember, as your research unfolds, the statement might evolve, reflecting new insights and staying pertinent.

But how do you distinguish between a well-crafted problem statement and one that falls short?

Effective vs. ineffective research problem statements

Imagine a scenario where medical researchers aim to tackle a new strain of virus. Their effective problem statement wouldn't merely state the existence of the virus. Instead, it would delve into the specifics — the regions most affected, the demographics most vulnerable, and the current limitations in medical interventions.

Whereas an ineffective research problem statement is vague, overly broad, or ambiguous, failing to provide a clear direction for the research. It may not be rooted in existing literature, might lack clarity on its significance, or could be framed in a way that makes the research objectives unachievable or irrelevant.

To understand it better, let's consider the topic of “Remote work and employee productivity.”

Effective problem statement

“Over the past decade, there has been a 70% increase in organizations adopting remote work policies. While some studies suggest remote work enhances employee productivity, others indicate potential declines due to distractions at home.

However, there’s a lack of comprehensive research examining the specific factors in a remote environment that influence productivity. This study aims to identify and analyze these factors, providing organizations with actionable insights to optimize remote work policies.”

Why is this statement of a problem in research effective?

• Specificity : The statement provides a clear percentage to highlight the rise in remote work.
• Context : It acknowledges existing research and the conflicting findings.
• Clear gap identification : It points out the lack of comprehensive research on specific factors affecting productivity in remote work.
• Purpose : The statement concludes with a clear aim for the research.

Ineffective problem statement

"People are working from home a lot now, especially since there are so many internet tools. Some say it's good; others say it's not that great. This research will just look into the whole work-from-home thing and see what's up."

Why is this statement of a problem in research ineffective?

• Informal language : Phrases like "what's up" and "the whole work-from-home thing" are not suitable for academic writing.
• Vagueness : The statement doesn't provide any specific data or context about the rise of remote work.
• Lack of clear focus : It's unclear what aspect of remote work the research will address.
• Ambiguous purpose : The statement doesn't specify the research's objectives or expected outcomes.

After gaining an understanding of what an effective research problem statement looks like, let's dive deeper into how to write one.

How to write a problem statement in research?

Drafting your research problem statement at the onset of your research journey ensures that your research remains anchored. That means by defining and articulating the main issue or challenge you intend to address at the very beginning of your research process; you provide a clear focus and direction for the entire study.

Here's a detailed guide to how you can write an effective statement of the problem in research.

Identify the research area : Before addressing a specific problem, you need to know the broader domain or field of your study. This helps in contextualizing your research and ensuring it aligns with existing academic disciplines.

Example: If you're curious about the effects of digital technology on human behavior, your broader research area might be Digital Sociology or Media Studies.

Conduct preliminary literature review : Familiarize yourself with existing research related to your topic. This will help you understand what's already known and, more importantly, identify gaps or unresolved questions in the existing knowledge. This step also ensures you're advancing upon existing work rather than replicating it.

Example: Upon reviewing literature on digital technology and behavior, you find many studies on social media's impact on youth but fewer on its effects on the elderly.

Read how to conduct an effective literature review .

Define the specific problem : After thoroughly reviewing the literature, pinpoint a particular issue that your research will address. Ensure that this chosen issue is not only of substantial importance in its field but also realistically approachable given your resources and expertise. To define it precisely, you might consider:

• Highlighting discrepancies or contradictions in existing literature.
• Emphasizing the real-world implications of this gap.
• Assessing the feasibility of exploring this issue within your means and timeframe.

Example: You decide to investigate how digital technology, especially social media, affects the mental well-being of the elderly, given the limited research in this area.

Articulate clearly and concisely : Your problem statement should be straightforward and devoid of jargon. It needs to convey the essence of your research issue in a manner that's understandable to both experts and non-experts.

Example: " The impact of social media on the mental well-being of elderly individuals remains underexplored, despite the growing adoption of digital technology in this age group. "

Highlight the significance : Explain why your chosen research problem matters. This could be due to its real-world implications, its potential to fill a knowledge gap or its relevance to current events or trends.

Example: As the elderly population grows and becomes more digitally connected, understanding the psychological effects of social media on this demographic could inform digital literacy programs and mental health interventions.

Ensure feasibility : Your research problem should be something you can realistically study, given your resources, timeframe, and expertise. It's essential to ensure that you can gather data, conduct experiments, or access necessary materials or participants.

Example: You plan to survey elderly individuals in local community centers about their social media usage and perceived mental well-being, ensuring you have the means to reach this demographic.

Seek feedback : Discuss your preliminary problem statement with peers, mentors, or experts in the field. They can provide insights, point out potential pitfalls, or suggest refinements.

Example: After discussing with a gerontologist, you decide to also consider the role of digital training in moderating the effects of social media on the elderly.

Refine and Revise : Based on feedback and further reflection, revise and improve your problem statement. This iterative process ensures clarity, relevance, and precision.

Example: Your refined statement reads: Despite the increasing digital connectivity of the elderly, the effects of social media on their mental well-being, especially in the context of digital training, remain underexplored.

By following these detailed steps, you can craft a research problem statement that is both compelling and academically rigorous.

Having explored the details of crafting a research problem statement, it's crucial to distinguish it from another fundamental element in academic research: the thesis statement.

Difference between a thesis statement and a problem statement

While both terms are central to research, a thesis statement presents your primary claim or argument, whereas a problem statement describes the specific issue your research aims to address.

Think of the thesis statement as the conclusion you're driving towards, while the problem statement identifies a specific gap in current knowledge.

For instance, a problem statement might highlight the rising mental health issues among teenagers, while the thesis statement could propose that increased screen time is a significant contributor.

Refer to the comparison table between what is a thesis and a problem statement in the research below:

Common mistakes to avoid in writing statement of the problem in research

Mistakes in the research problem statement can lead to a domino effect, causing misalignment in research objectives, wasted resources, and even inconclusive or irrelevant results.

Recognizing and avoiding these pitfalls not only strengthens the foundation of your research but also ensures that your efforts concede impactful insights.

Here's a detailed exploration of frequent subjective, qualitative, quantitative and measurable mistakes and how you can sidestep them.

Being too broad or too narrow

A problem statement that's too broad can lack focus, making it challenging to derive specific research questions or objectives. Conversely, a statement that's too narrow might limit the scope of your research or make it too trivial.

Example of mistake: "Studying the effects of diet on health" is too broad, while "Studying the effects of eating green apples at 3 pm on heart health" is overly narrow.

You can refine the scope based on preliminary research. The correct way to write this problem statement will be "Studying the effects of a high-fiber diet on heart health in adults over 50." This statement is neither too broad nor too narrow, and it provides a clear direction for the research.

Using unnecessary jargon or technical language

While academic writing often involves academic terms, overloading your problem statement with jargon can alienate readers and obscure the actual problem.

Example of Mistake: "Examining the diurnal variations in macronutrient ingestion vis-à-vis metabolic homeostasis."

To ensure it’s not complicated, you can simplify and clarify. "Examining how daily changes in nutrient intake affect metabolic balance" conveys the same idea more accessible.

Not emphasizing the "Why" of the problem

It's not enough to state a problem; you must also convey its significance. Why does this problem matter? What are the implications of not addressing it?

Example of Mistake: "Many students are not engaging with online learning platforms."

You can proceed with the approach of highlighting the significance here. "Many students are not engaging with online learning platforms, leading to decreased academic performance and widening educational disparities."

Circular reasoning and lack of relevance

Your problem statement should be grounded in existing research or observed phenomena. Avoid statements that assume what they set out to prove or lack a clear basis in current knowledge.

Example of Mistake: "We need to study X because not enough research has been done on X."

Instead, try grounding your statement based on already-known facts. "While several studies have explored Y, the specific impact of X remains unclear, necessitating further research."

Being overly ambitious

While it's commendable to aim high, your problem statement should reflect a challenge that's achievable within your means, timeframe, and resources.

Example of Mistake: "This research will solve world hunger."

Here, you need to be realistic and focused. "This research aims to develop sustainable agricultural techniques to increase crop yields in arid regions."

By being mindful of these common mistakes, you can craft a problem statement that is clear, relevant and sets a solid foundation for your research.

Over-reliance on outdated data

Using data that is no longer relevant can mislead the direction of your research. It's essential to ensure that the statistics or findings you reference are current and pertinent to the present scenario.

Example of Mistake: "According to a 1995 study, only 5% of the population uses the internet for daily tasks."

You always cross-check the dates and relevance of the data you're using. For a contemporary study on internet usage, you'd want to reference more recent statistics.

Not specifying the sample size or demographic

A problem statement should be clear about the population or sample size being studied, especially when making generalizations or claims.

Example of Mistake: "People prefer online shopping to in-store shopping."

Here, you would benefit from specifying the demographic or sample size when presenting data to avoid overgeneralization. " In a survey of 1,000 urban residents aged 18-35, 70% expressed a preference for online shopping over in-store shopping. "

Ignoring conflicting data

Cherry-picking data that supports your hypothesis while ignoring conflicting data can lead to a biased problem statement.

Example of Mistake: "Research shows that all students benefit from online learning."

You’ve to ensure a balanced view by considering all relevant data, even if it contradicts your hypothesis. " While many studies highlight the advantages of online learning for students, some research points to challenges such as decreased motivation and lack of face-to-face interaction. "

Making unsubstantiated predictions

Projecting future trends without solid data can weaken the credibility of your problem statement.

Example of Mistake: "The demand for electric cars will increase by 500% in the next year."

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• Published: 10 December 2020

Effect of internet use and electronic game-play on academic performance of Australian children

• Md Irteja Islam 1 , 2 ,
• Raaj Kishore Biswas 3 &
• Rasheda Khanam 1  

Scientific Reports volume  10 , Article number:  21727 ( 2020 ) Cite this article

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This study examined the association of internet use, and electronic game-play with academic performance respectively on weekdays and weekends in Australian children. It also assessed whether addiction tendency to internet and game-play is associated with academic performance. Overall, 1704 children of 11–17-year-olds from young minds matter (YMM), a cross-sectional nationwide survey, were analysed. The generalized linear regression models adjusted for survey weights were applied to investigate the association between internet use, and electronic-gaming with academic performance (measured by NAPLAN–National standard score). About 70% of the sample spent > 2 h/day using the internet and nearly 30% played electronic-games for > 2 h/day. Internet users during weekdays (> 4 h/day) were less likely to get higher scores in reading and numeracy, and internet use on weekends (> 2–4 h/day) was positively associated with academic performance. In contrast, 16% of electronic gamers were more likely to get better reading scores on weekdays compared to those who did not. Addiction tendency to internet and electronic-gaming is found to be adversely associated with academic achievement. Further, results indicated the need for parental monitoring and/or self-regulation to limit the timing and duration of internet use/electronic-gaming to overcome the detrimental effects of internet use and electronic game-play on academic achievement.

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Introduction.

Over the past two decades, with the proliferation of high-tech devices (e.g. Smartphone, tablets and computers), both the internet and electronic games have become increasingly popular with people of all ages, but particularly with children and adolescents 1 , 2 , 3 . Recent estimates have shown that one in three under-18-year-olds across the world uses the Internet, and 75% of adolescents play electronic games daily in developed countries 4 , 5 , 6 . Studies in the United States reported that adolescents are occupied with over 11 h a day with modern electronic media such as computer/Internet and electronic games, which is more than they spend in school or with friends 7 , 8 . In Australia, it is reported that about 98% of children aged 15–17 years are among Internet users and 98% of adolescents play electronic games, which is significantly higher than the USA and Europe 9 , 10 , 11 , 12 .

In recent times, the Internet and electronic games have been regarded as important, not just for better results at school, but also for self-expression, sociability, creativity and entertainment for children and adolescents 13 , 14 . For instance, 88% of 12–17 year-olds in the USA considered the Internet as a useful mechanism for making progress in school 15 , and similarly, electronic gaming in children and adolescents may assist in developing skills such as decision-making, smart-thinking and coordination 3 , 15 .

On the other hand, evidence points to the fact that the use of the Internet and electronic games is found to have detrimental effects such as reduced sleeping time, behavioural problems (e.g. low self-esteem, anxiety, depression), attention problems and poor academic performance in adolescents 1 , 5 , 12 , 16 . In addition, excessive Internet usage and increased electronic gaming are found to be addictive and may cause serious functional impairment in the daily life of children and adolescents 1 , 12 , 13 , 16 . For example, the AU Kids Online survey 17 reported that 50% of Australian children were more likely to experience behavioural problems associated with Internet use compared to children from 25 European countries (29%) surveyed in the EU Kids Online study 18 , which is alarming 12 . These mixed results require an urgent need of understanding the effect of the Internet use and electronic gaming on the development of children and adolescents, particularly on their academic performance.

Despite many international studies and a smaller number in Australia 12 , several systematic limitations remain in the existing literature, particularly regarding the association of academic performance with the use of Internet and electronic games in children and adolescents 13 , 16 , 19 . First, the majority of the earlier studies have either relied on school grades or children’s self assessments—which contain an innate subjectivity by the assessor; and have not considered the standardized tests of academic performance 16 , 20 , 21 , 22 . Second, most previous studies have tested the hypothesis in the school-based settings instead of canvassing the whole community, and cannot therefore adjust for sociodemographic confounders 9 , 16 . Third, most studies have been typically limited to smaller sample sizes, which might have reduced the reliability of the results 9 , 16 , 23 .

By considering these issues, this study aimed to investigate the association of internet usage and electronic gaming on a standardized test of academic performance—NAPLAN (The National Assessment Program—Literacy and Numeracy) among Australian adolescents aged 11–17 years using nationally representative data from the Second Australian Child and Adolescent Survey of Mental Health and Wellbeing—Young Minds Matter (YMM). It is hypothesized that the findings of this study will provide a population-wide, contextual view of excessive Internet use and electronic games played separately on weekdays and weekends by Australian adolescents, which may be beneficial for evidence-based policies.

Subject demographics

Respondents who attended gave NAPLAN in 2008 (N = 4) and 2009 (N = 29) were removed from the sample due to smaller sample size, as later years (2010–2015) had over 100 samples yearly. The NAPLAN scores from 2008 might not align with a survey conducted in 2013. Further missing cases were deleted with the assumption that data were missing at random for unbiased estimates, which is common for large-scale surveys 24 . From the initial survey of 2967 samples, 1704 adolescents were sampled for this study.

The sample characteristics were displayed in Table 1 . For example, distribution of daily average internet use was checked, showing that over 50% of the sampled adolescents spent 2–4 h on internet (Table 1 ). Although all respondents in the survey used internet, nearly 21% of them did not play any electronic games in a day and almost one in every three (33%) adolescents played electronic games beyond the recommended time of 2 h per day. Girls had more addictive tendency to internet/game-play in compare to boys.

The mean scores for the three NAPLAN tests scores (reading, writing and numeracy) ranged from 520 to 600. A gradual decline in average NAPLAN tests scores (reading, writing and numeracy) scores were observed for internet use over 4 h during weekdays, and over 3 h during weekends (Table 2 ). Table 2 also shows that adolescents who played no electronic games at all have better scores in writing compared to those who play electronic games. Moreover, Table 2 shows no particular pattern between time spent on gaming and NAPLAN reading and numeracy scores. Among the survey samples, 308 adolescents were below the national standard average.

Internet use and academic performance

Our results show that internet (non-academic use) use during weekdays, especially more than 4 h, is negatively associated with academic performance (Table 3 ). For internet use during weekdays, all three models showed a significant negative association between time spent on internet and NAPLAN reading and numeracy scores. For example, in Model 1, adolescents who spent over 4 h on internet during weekdays are 15% and 17% less likely to get higher reading and numeracy scores respectively compared to those who spend less than 2 h. Similar results were found in Model 2 and 3 (Table 3 ), when we adjusted other confounders. The variable addiction tendency to internet was found to be negatively associated with NAPLAN results. The adolescents who had internet addiction were 17% less and 14% less likely to score higher in reading and numeracy respectively than those without such problematic behaviour.

Internet use during weekends showed a positive association with academic performance (Table 4 ). For example, Model 1 in Table 4 shows that internet use during weekends was significant for reading, writing and national standard scores. Youths who spend around 2–4 h and over 4 h on the internet during weekends were 21% and 15% more likely to get a higher reading scores respectively compared to those who spend less than 2 h (Model 1, Table 4 ). Similarly, in model 3, where the internet addiction of adolescents was adjusted, adolescents who spent 2–4 h on internet were 1.59 times more likely to score above the national standard. All three models of Table 4 confirmed that adolescents who spent 2–4 h on the internet during weekends are more likely to achieve better reading and writing scores and be at or above national standard compared to those who used the internet for less than 2 h. Numeracy scores were unlikely to be affected by internet use. The results obtained from Model 3 should be treated as robust, as this is the most comprehensive model that accounts for unobserved characteristics. The addiction tendency to internet/game-play variable showed a negative association with academic performance, but this is only significant for numeracy scores.

Electronic gaming and academic performance

Time spent on electronic gaming during weekdays had no effect on the academic performance of writing and language but had significant association with reading scores (Model 2, Table 5 ). Model 2 of Table 5 shows that adolescents who spent 1–2 h on gaming during weekdays were 13% more likely to get higher reading scores compared to those who did not play at all. It was an interesting result that while electronic gaming during weekdays tended to show a positive effect on reading scores, internet use during weekdays showed a negative effect. Addiction tendency to internet/game-play had a negative effect; the adolescents who were addicted to the internet were 14% less likely to score more highly in reading than those without any such behaviour.

All three models from Table 6 confirm that time spent on electronic gaming over 2 h during weekends had a positive effect on readings scores. For example, the results of Model 3 (Table 6 ) showed that adolescents who spent more than 2 h on electronic gaming during weekdays were 16% more likely to have better reading scores compared to adolescents who did not play games at all. Playing electronic games during weekends was not found to be statistically significant for writing and numeracy scores and national standard scores, although the odds ratios were positive. The results from all tables confirm that addiction tendency to internet/gaming is negatively associated with academic performance, although the variable is not always statistically significant.

Building on past research on the effect of the internet use and electronic gaming in adolescents, this study examined whether Internet use and playing electronic games were associated with academic performance (i.e. reading, writing and numeracy) using a standardized test of academic performance (i.e. NAPLAN) in a nationally representative dataset in Australia. The findings of this study question the conventional belief 9 , 25 that academic performance is negatively associated with internet use and electronic games, particularly when the internet is used for non-academic purpose.

In the current hi-tech world, many developed countries (e.g. the USA, Canada and Australia) have recommended that 5–17 year-olds limit electronic media (e.g. internet, electronic games) to 2 h per day for entertainment purposes, with concerns about the possible negative consequences of excessive use of electronic media 14 , 26 . However, previous research has often reported that children and adolescents spent more than the recommended time 26 . The present study also found similar results, that is, that about 70% of the sampled adolescents aged 11–17 spent more than 2 h per day on the Internet and nearly 30% spent more than 2-h on electronic gaming in a day. This could be attributed to the increased availability of computers/smart-phones and the internet among under-18s 12 . For instance, 97% of Australian households with children aged less than 15 years accessed internet at home in 2016–2017 10 ; as a result, policymakers recommended that parents restrict access to screens (e.g. Internet and electronic games) in children’s bedrooms, monitor children using screens, share screen hours with their children, and to act as role models by reducing their own screen time 14 .

This research has drawn attention to the fact that the average time spent using the internet, which is often more than 4 h during weekdays tends to be negatively associated with academic performance, especially a lower reading and numeracy score, while internet use of more than 2 h during weekends is positively associated with academic performance, particularly having a better reading and writing score and above national standard score. By dividing internet use and gaming by weekdays and weekends, this study find an answer to the mixed evidence found in previous literature 9 . The results of this study clearly show that the non-academic use of internet during weekdays, particularly, spending more than 4 h on internet is harmful for academic performance, whereas, internet use on the weekends is likely to incur a positive effect on academic performance. This result is consistent with a USA study that reported that internet use is positively associated with improved reading skills and higher scores on standardized tests 13 , 27 . It is also reported in the literature that academic performance is better among moderate users of the internet compared to non-users or high level users 13 , 27 , which was in line with the findings of this study. This may be due to the fact that the internet is predominantly a text-based format in which the internet users need to type and read to access most websites effectively 13 . The results of this study indicated that internet use is not harmful to academic performance if it is used moderately, especially, if ensuring very limited use on weekdays. The results of this study further confirmed that timing (weekdays or weekends) of internet use is a factor that needs to be considered.

Regarding electronic gaming, interestingly, the study found that the average time of gaming either in weekdays or weekends is positively associated with academic performance especially for reading scores. These results contradicted previous literatures 1 , 13 , 19 , 27 that have reported negative correlation between electronic games and educational performance in high-school children. The results of this study were consistent with studies conducted in the USA, Europe and other countries that claimed a positive correlation between gaming and academic performance, especially in numeracy and reading skills 28 , 29 . This is may be due to the fact that the instructions for playing most of the electronic games are text-heavy and many electronic games require gamers to solve puzzles 9 , 30 . The literature also found that playing electronic games develops cognitive skills (e.g. mental rotation abilities, dexterity), which can be attributable to better academic achievement 31 , 32 .

Consistent with previous research findings 33 , 34 , 35 , 36 , the study also found that adolescents who had addiction tendency to internet usage and/or electronic gaming were less likely to achieve higher scores in reading and numeracy compared to those who had not problematic behaviour. Addiction tendency to Internet/gaming among adolescents was found to be negatively associated with overall academic performance compared to those who were not having addiction tendency, although the variables were not always statistically significant. This is mainly because adolescents’ skipped school and missed classes and tuitions, and provide less effort to do homework due to addictive internet usage and electronic gaming 19 , 35 . The results of this study indicated that parental monitoring and/ or self-regulation (by the users) regarding the timing and intensity of internet use/gaming are essential to outweigh any negative effect of internet use and gaming on academic performance.

Although the present study uses a large nationally representative sample and advances prior research on the academic performance among adolescents who reported using the internet and playing electronic games, the findings of this study also have some limitations that need to be addressed. Firstly, adolescents who reported on the internet use and electronic games relied on self-reported child data without any screening tests or any external validation and thus, results may be overestimated or underestimated. Second, the study primarily addresses the internet use and electronic games as distinct behaviours, as the YMM survey gathered information only on the amount of time spent on internet use and electronic gaming, and included only a few questions related to addiction due to resources and time constraints and did not provide enough information to medically diagnose internet/gaming addiction. Finally, the cross-sectional research design of the data outlawed evaluation of causality and temporality of the observed association of internet use and electronic gaming with the academic performance in adolescents.

This study found that the average time spent on the internet on weekends and electronic gaming (both in weekdays and weekends) is positively associated with academic performance (measured by NAPLAN) of Australian adolescents. However, it confirmed a negative association between addiction tendency (internet use or electronic gaming) and academic performance; nonetheless, most of the adolescents used the internet and played electronic games more than the recommended 2-h limit per day. The study also revealed that further research is required on the development and implementation of interventions aimed at improving parental monitoring and fostering users’ self-regulation to restrict the daily usage of the internet and/or electronic games.

Data description

Young minds matter (YMM) was an Australian nationwide cross-sectional survey, on children aged 4–17 years conducted in 2013–2014 37 . Out of the initial 76,606 households approached, a total of 6,310 parents/caregivers (eligible household response rate 55%) of 4–17 year-old children completed a structured questionnaire via face to face interview and 2967 children aged 11–17 years (eligible children response rate 89%) completed a computer-based self-reported questionnaire privately at home 37 .

Area based sampling was used for the survey. A total of 225 Statistical Area 1 (defined by Australian Bureau of Statistics) areas were selected based on the 2011 Census of Population and Housing. They were stratified by state/territory and by metropolitan versus non-metropolitan (rural/regional) to ensure proportional representation of geographic areas across Australia 38 . However, a small number of samples were excluded, based on most remote areas, homeless children, institutional care and children living in households where interviews could not be conducted in English. The details of the survey and methodology used in the survey can be found in Lawrence et al. 37 .

Following informed consent (both written and verbal) from the primary carers (parents/caregivers), information on the National Assessment Program—Literacy and Numeracy (NAPLAN) of the children and adolescents were also added to the YMM dataset. The YMM survey is ethically approved by the Human Research Ethics Committee of the University of Western Australia and by the Australian Government Department of Health. In addition, the authors of this study obtained a written approval from Australian Data Archive (ADA) Dataverse to access the YMM dataset. All the researches were done in accordance with relevant ADA Dataverse guidelines and policy/regulations in using YMM datasets.

Outcome variables

The NAPLAN, conducted annually since 2008, is a nationwide standardized test of academic performance for all Australian students in Years 3, 5, 7 and 9 to assess their skills in reading, writing numeracy, grammar and spelling 39 , 40 . NAPLAN scores from 2010 to 2015, reported by YMM, were used as outcome variables in the models; while NAPLAN data of 2008 (N = 4) and 2009 (N = 29) were excluded for this study in order to reduce the time lag between YMM survey and the NAPLAN test. The NAPLAN gives point-in-time standardized scores, which provide the scope to compare children’s academic performance over time 40 , 41 . The NAPLAN tests are one component of the evaluation and grading phase of each school, and do not substitute for the comprehensive, consistent evaluations provided by teachers on the performance of each student 39 , 41 . All four domains—reading, writing, numeracy and language conventions (grammar and spelling) are in continuous scales in the dataset. The scores are given based on a series of tests; details can be found in 42 . The current study uses only reading, writing and numeracy scores to measure academic performance.

In this study, the National standard score is a combination of three variables: whether the student meets the national standard in reading, writing and numeracy. Based on national average score, a binary outcome variable is also generated. One category is ‘below standard’ if a child scores at least one standard deviation (one below scores) from the national standard in reading, writing and numeracy, and the rest is ‘at/above standard’.

Independent variables

Internet use and electronic gaming.

In the YMM survey, owing to the scope of the survey itself, an extensive set of questions about internet usage and electronic gaming could not be included. Internet usage omitted the time spent in academic purposes and/or related activities. Playing electronic games included playing games on a gaming console (e.g. PlayStation, Xbox, or similar console ) online or using a computer, or mobile phone, or a handled device 12 . The primary independent covariates were average internet use per day and average electronic game-play in hours per day. A combination of hours on weekdays and weekends was separately used in the models. These variables were based on a self-assessed questionnaire where the youths were asked questions regarding daily time spent on the Internet and electronic game-play, specifically on either weekends or weekdays. Since, internet use/game-play for a maximum of 2 h/day is recommended for children and adolescents aged between 5 and 17 years in many developed countries including Australia 14 , 26 ; therefore, to be consistent with the recommended time we preferred to categorize both the time variables of internet use and gaming into three groups with an interval of 2 h each. Internet use was categorized into three groups: (a) ≤ 2 h), (b) 2–4 h, and (c) > 4 h. Similar questions were asked for game-play h. The sample distribution for electronic game-play was skewed; therefore, this variable was categorized into three groups: (a) no game-play (0 h), (b) 1–2 h, and (c) > 2 h.

Other covariates

Family structure and several sociodemographic variables were used in the models to adjust for the differences in individual characteristics, parental inputs and tastes, household characteristics and place of residence. Individual characteristics included age (continuous) and sex of the child (boys, girls) and addiction tendency to internet use and/or game-play of the adolescent. Addiction tendency to internet/game-play was a binary independent variable. It was a combination of five behavioural questions relating to: whether the respondent avoided eating/sleeping due to internet use or game-play; feels bothered when s/he cannot access internet or play electronic games; keeps using internet or playing electronic games even when s/he is not really interested; spends less time with family/friends or on school works due to internet use or game-play; and unsuccessfully tries to spend less time on the internet or playing electronic games. There were four options for each question: never/almost never; not very often; fairly often; and very often. A binary covariate was simulated, where if any four out of five behaviours were reported as for example, fairly often or very often, then it was considered that the respondent had addictive tendency.

Household characteristics included household income (low, medium, high), family type (original, step, blended, sole parent/primary carer, other) 43 and remoteness (major cities, inner regional, outer regional, remote/very remote). Parental inputs and taste included education of primary carer (bachelor, diploma, year 10/11), primary carer’s likelihood of serious mental illness (K6 score -likely; not likely); primary carer’s smoking status (no, yes); and risk of alcoholic related harm by the primary carer (risky, none).

Statistical analysis

Descriptive statistics of the sample and distributions of the outcome variables were initially assessed. Based on these distributions, the categorization of outcome variables was conducted, as mentioned above. For formal analysis, generalized linear regression models (GLMs) 44 were used, adjusting for the survey weights, which allowed for generalization of the findings. As NAPLAN scores of three areas—reading, writing and numeracy—were continuous variables, linear models were fitted to daily average internet time and electronic game play time. The scores were standardized (mean = 0, SD = 1) for model fitness. The binary logistic model was fitted for the dichotomized national standard outcome variable. Separate models were estimated for internet and electronic gaming on weekends and weekdays.

We estimated three different models, where models varied based on covariates used to adjust the GLMs. Model 1 was adjusted for common sociodemographic factors including age and sex of the child, household income, education of primary carer’s and family type 43 . However, the results of this model did not account for some unobserved household characteristics (e.g. taste, preferences) that are unobserved to the researcher and are arguably correlated with potential outcomes. The effects of unobserved characteristics were reduced by using a comprehensive set of observable characteristics 45 , 46 that were available in YMM data. The issue of unobserved characteristics was addressed by estimating two additional models that include variables by including household characteristics such as parental taste, preference and inputs, and child characteristics in the model. In addition to the variables in Model 1, Model 2 included remoteness, primary carer’s mental health status, smoking status and risk of alcoholic related harm by the primary carer. Model 3 further included internet/game addiction of the adolescent in addition to all the covariates in Model 2. Model 3 was expected to account for a child’s level of unobserved characteristics as the children who were addicted to internet/games were different from others. The model will further show how academic performance is affected by internet/game addiction. The correlation among the variables ‘internet/game addiction’ and ‘internet use’ and ‘gaming’ (during weekdays and weekends) were also assessed, and they were less than 0.5. Multicollinearity was assessed using the variance inflation factor (VIF), which was under 5 for all models, suggesting no multicollinearity 47 .

p value below the threshold of 0.05 was considered the threshold of significance. All analysis was conducted in R (version 3.6.1). R-package survey (version 3.37) was used for modelling which is suited for complex survey samples 48 .

Data availability

The authors declare that they do not have permission to share dataset. However, the datasets of Young Minds Matter (YMM) survey data is available at the Australian Data Archive (ADA) Dataverse on request ( https://doi.org/10.4225/87/LCVEU3 ).

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Acknowledgements

The authors would like to thank the University of Western Australia, Roy Morgan Research, the Australian Government Department of Health for conducting the survey, and the Australian Data Archive for giving access to the YMM survey dataset. The authors also would like to thank Dr Barbara Harmes for proofreading the manuscript.

This research did not receive any specific Grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Research Article

The Development of the Problematic Online Gaming Questionnaire (POGQ)

* E-mail: [email protected] (ZD); [email protected] (MG)

Affiliation Eötvös Loránd University, Institute of Psychology, Budapest, Hungary

Affiliations Eötvös Loránd University, Institute of Psychology, Budapest, Hungary, Doctoral School of Psychology, Eötvös Loránd University, Budapest, Hungary

Affiliation Nottingham Trent University, Psychology Division, Nottingham, United Kingdom

• Zsolt Demetrovics, 
• Róbert Urbán, 
• Katalin Nagygyörgy, 
• Judit Farkas, 
• Mark D. Griffiths, 
• Orsolya Pápay, 
• Gyöngyi Kökönyei, 
• Katalin Felvinczi, 
• Attila Oláh

• Published: May 10, 2012
• https://doi.org/10.1371/journal.pone.0036417
• Reader Comments

Online gaming has become increasingly popular. However, this has led to concerns that these games might induce serious problems and/or lead to dependence for a minority of players. Aim: The aim of this study was to uncover and operationalize the components of problematic online gaming.

A total of 3415 gamers (90% males; mean age 21 years), were recruited through online gaming websites. A combined method of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was applied. Latent profile analysis was applied to identify persons at-risk.

EFA revealed a six-factor structure in the background of problematic online gaming that was also confirmed by a CFA. For the assessment of the identified six dimensions – preoccupation, overuse, immersion, social isolation, interpersonal conflicts, and withdrawal – the 18-item Problematic Online Gaming Questionnaire (POGQ) proved to be exceedingly suitable. Based on the latent profile analysis, 3.4% of the gamer population was considered to be at high risk, while another 15.2% was moderately problematic.

Conclusions

The POGQ seems to be an adequate measurement tool for the differentiated assessment of gaming related problems on six subscales.

Citation: Demetrovics Z, Urbán R, Nagygyörgy K, Farkas J, Griffiths MD, Pápay O, et al. (2012) The Development of the Problematic Online Gaming Questionnaire (POGQ). PLoS ONE 7(5): e36417. https://doi.org/10.1371/journal.pone.0036417

Editor: Jerson Laks, Federal University of Rio de Janeiro, Brazil

Received: January 26, 2012; Accepted: March 31, 2012; Published: May 10, 2012

Copyright: © 2012 Demetrovics et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was supported by the Hungarian Scientific Research Fund (grant number: 83884) ( http://otka.hu ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The popularity of online gaming has spread at an increasing rate since its introduction [1] . However, given the increasing number of studies on the phenomenon of problematic gaming [2] , [3] , [4] , [5] , [6] , there have been growing concerns about negative consequences for a small minority. These gamers spend more time with gaming than planned while ignoring other important activities causing negative effects on their performance [4] , [7] , social relationships [8] , [9] , and withdrawal symptoms [10] , [11] . There are different names present regarding this phenomenon in scientific literature. The phenomenon is referred to as addiction [11] , [12] , problematic use [13] , [14] , excessive game use [10] or engagement [15] . However, all these authors – irrespective of the name – agree in that there exists an excessive form of online gaming that shows a problematic pattern and that is related to behavioral addictions [16] , [17] . The present authors propose to use the name problematic gaming. This term describes both the quintessence of the phenomenon (i.e., that the behavior is not only excessive but gaming-related problems are also expected to be present), while avoiding the notion of dependency (as the exact definition and diagnostic criteria have not yet been clarified or agreed).

The issues outlined above also suggest that precise assessment and screening of the phenomenon is an urgent matter. In order to measure the problematic nature of gaming, some authors have developed questionnaires based on the general phenomenon of internet addiction [11] , while others have attempted to operationalize the behavioral addiction model of Griffiths [16] , [18] . However, the limitation of these current questionnaires is that many of them typically target users of Massively Multiplayer Online Role-Playing Games (MMORPG) [4] , [9] , [13] , [14] , [19] . Though this type of game is the most popular among online games, the total population of gamers is more diverse and it is therefore necessary to develop a measure that is suitable for the assessment of other genres and gamer populations such as those who play online Real-Time Strategy (RTS) games and online First Person Shooter (FPS) games.

The aim of our study was therefore twofold. Firstly, to explore what components comprise problematic online gaming. Secondly, to make these dimensions measurable, to develop such a scale on which the identified dimensions can be assessed. Contrary to earlier studies, the objective here was to create a questionnaire suitable for all types of Massively Multiplayer Online Games. A further intention was to carry out an empirical based analysis to ensure that all components of problematic gaming remain in focus.

The study was approved by the Institutional Review Board of the Eötvös Loránd University. Informed consent was obtained via our online system from all subjects. After introducing the goals of the study in details the subjects were asked to tick into a box if they agreed to continue and participate in the study.

Sample, Procedure and Participants

All Hungarian websites that facilitate the playing online games were identified (n = 18). All 18 sites were contacted by the research team and were asked information about the number of visitors, and requested their cooperation in the planned study. All sites responded. Based on this information, the number of (ever) registered users was estimated to be approximately 30,000. However, many of these users may have simultaneously registered on multiple sites. Furthermore, it is likely that many formerly registered users were not currently active. All sites agreed to publish a call for participation in the present study on their home sites or via a newsletter. In the call for participation, gamers were asked to visit the study website, to sign in with a password provided by the researchers, and to complete a questionnaire. A total of 4390 questionnaires were started but not everyone completed the whole survey. This left 3415 completed questionnaires. In addition to answering the general questions regarding online gaming habits, the respondents were asked about online gaming problems.

Major socio-demographic characteristics of the gamers (gender, age, qualification, marital status, school, work) and characteristics regarding their online gaming activities were recorded. Additionally, the survey contained a 26-item questionnaire that listed several problems regarding online gaming. The 26 items were created by means of (i) a comprehensive literature review supplemented with (ii) interviews with online gamers. Firstly, in relation to the literature review, a full search was carried out in the databases Web of Science, Science Direct, PsycINFO, and Medline using the following keywords: online gam*, MMO, MMORPG, multiplayer, FPS, First Person Shooter, RTS, Real Time Strategy. A total of 199 hits were found. However, 115 was excluded because they were irrelevant regarding specific aspects and characteristics of online gaming. The remaining 84 papers were read carefully and all items were listed out that could be considered as reflecting problematic aspects of online gaming. A total of 42 characteristics were identified this way. Secondly (and concurrently with the literature review), 15 online gamers were asked to list problems they had noticed in themselves and/or others as result of online gaming. These gamers listed 32 problems. Following exclusion of duplicates and similar items, the list was reduced to 26 items.

Statistical Analysis

Statistical analysis comprised an exploratory factor analysis (EFA) with robust maximum-likelihood estimation (MLR) in MPLUS 6.0. The goodness of fit was assessed by the root-mean-square error of approximation (RMSEA) and its 90% confidence interval (90% CI), and p value smaller than 0.05 for test of close fit (Cfit>.05). The factor solution was selected based on fit statistics and interpretability of factors.

The factor structure based on EFA was confirmed through confirmatory factor analyses (CFA) with independent samples. CFA was performed with robust maximum-likelihood estimation (MLR) in MPLUS 6.0. The goodness of fit was evaluated using RMSEA and its 90% confidence interval (90% CI), p value smaller than 0.05 for test of close fit, standardized root-mean-square residual (SRMR), comparative fit index (CFI), and Tucker-Lewis Fit Index (TLI). As Brown (2006) and Kline (2005) recommended, multiple indices were selected in order to provide different information for evaluating model fit.

To carry out the above analyses, four non-overlapping groups from the sample were randomly selected. Sample 1 (n = 600) was used to perform an initial EFA on the original 26 items. Sample 2 (n = 600) was used to conduct a separate EFA to cross-validate the factor structure found in the first analysis. Sample 3 (n = 600) was used to conduct CFA analysis. After the inspection of modification indices, we also cross-validated the final CFA model with sample 4 (n = 1615).

In order to identify the groups of users with high risk of problematic use of online gaming a person-oriented statistical framework was selected, seeking subtypes of gamers that exhibited similar patterns of symptoms of problematic use. Therefore a latent profile analysis was performed with 1 to 6 classes with the full sample (n = 3415). The latent profile analysis [23] , [24] is a latent variable analysis with a categorical latent variable – in this case problematic gamers – and continuous manifest indicators such as factor scores of POGQ. In the process of determining the number of latent classes, the Bayesian information criteria parsimony index was used, alongside the minimization of cross-classification probabilities, entropy and the interpretability of clusters. In the final determination of the number of classes, the likelihood-ratio difference test (Lo-Mendell-Rubin Adjusted LRT Test) was also used. This compares the estimated model with a model having one less class than the estimated model [25] . A low p value (<.05) indicates that the model with one less class is rejected in favor of the estimated model.

To determine the cut-off point for POGQ a sensitivity analysis based on membership in the most problematic group in the latent profile analysis was carried out. Considering membership in this group as a gold standard, the sensitivity and specificity values for all POGQ cut-off points was calculated. Thus, the accuracy of the POGQ by calculating the proportion of participants classified as being at high risk for problematic gaming versus other gamers could be assessed. The sensitivity (i.e., the proportion of true positives belonging to the most problematic group based on LPA) and specificity (i.e., the proportion of true negatives) was defined as suggested by Altman and Bland [26] and Glaros and Kline [27] . In order to explore the probability that the POGQ would give the correct “diagnosis”, the positive predictive values (PPV), the negative predictive values (NPV), and the accuracy values for each possible POGQ cut-off points was calculated. PPV was defined as the proportion of participants with positive test results who are correctly diagnosed [27] , [28] . The NPV was defined as the proportion of patients with negative test results who are correctly diagnosed [27] , [28] .

Descriptive Statistics

90% of our sample (n = 3072) was male. Mean age was 21 years (SD = 5.85 years). Slightly more than one-tenth of the participants had graduate education, while 39.4% had secondary education. The majority (61.9%) were primarily students, but approximately one-quarter worked full time (24.3%). Almost two-thirds of the participants were single (64.9%), and a further 24.3% were in a relationship but did not live with their partner (see Table 1 ).

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https://doi.org/10.1371/journal.pone.0036417.t001

Slightly more than one-third (35.7%) played a maximum 14 hours per week and approximately the same number played between 15 and 28 hours per week. One in ten played more than 42 hours a week (6 hours per day on average) ( Table 1 ). Approximately a half spent money on gaming, although most did not spend more than $25(US) per month. The majority of the sample participants were individual gamers (38.6%) but there was also a relatively high ratio of different level organized gamers ( Table 1 ).

Exploratory Factor Analyses

An exploratory factor analysis was performed with maximum-likelihood estimation which is robust to non-normality and promax rotation to evaluate the factor structure of 26 items on Sample 1 (n = 600). Acceptability of the factor solution was based on goodness of fit index (RMSEA <0.08, Cfit (90% CI) <0.08, pclose >0.05), the interpretability of the solution and salient factor loadings (>0.30). A total of 1–8 factor solutions was examined. The six-factor solution provided the first adequate RMSEA value based on the criteria (χ 2  = 409.8, df = 184 p<0.0001; RMSEA = 0.045 [0.039–0.051] pclose >0.90). The exploratory factor analysis on Sample 2 (n = 600) was repeated. As in Sample 1, a six-factor solution also provided the first adequate and interpretable factor solution (χ2 = 457.7 df = 184 p<0.0001; RMSEA = 0.050 [0.044–0.056] Cfit = 0.514). Factor loadings are presented in Table 2 .

https://doi.org/10.1371/journal.pone.0036417.t002

For the further development of this scale, items with the following rules were selected. First, items were excluded that had factor loadings lower than 0.40 at least in one of the two analyses. Second, items with salient cross loadings were excluded. If a cross loading only in one of the two parallel EFAs was identified, the cutoff 0.50 was used. In case of more than two cross-loadings, a 0.30 as a cutoff was used to exclude items from further analyses. The excluded items are crossed out in Table 2 . As result of the above criteria, 18 of the original 26 items were retained (see Appendix S1 ).

Confirmatory Factor Analysis

Based on the previous analyses on the samples 1 and 2, a six-factor solution was tested on Sample 3 (n = 600) with confirmatory factor analysis. This model provided an optimal fit to the data (χ2 = 256.0 df = 120 p<0.0001; CFI = 0.965; TLI = 0.956; RMSEA = 0.043 [0.036–0.051] Cfit>0.90; SRMR = 0.037). We cross-validated this model with Sample 4 (n = 1615) and found adequate level of fit (χ2 = 512.8 df = 120 p<0.0001; CFI = 0.962; TLI = 0.952; RMSEA = 0.045 [0.041–0.049] Cfit>0.90; SRMR = 0.036). The factor loadings, factor reliabilities, internal consistencies, means, and SDs are presented in Table 3 .

https://doi.org/10.1371/journal.pone.0036417.t003

Professional vs. Non-professional Gamers

The possible bias stemming from the inclusion of professional gamers in the total sample was checked. The level of fit of the measurement models without professional gamers (N = 2857) was satisfactory (χ2 = 763.5 df = 120 p<0.0001; CFI = 0.965; TLI = 0.956; RMSEA = 0.043 [0.040–0.046]; SRMR = 0.034). The level of fit of the measurement models only among professional gamers (N = 528) was also satisfactory (χ2 = 290.0 df = 120 p<0.0001; CFI = 0.948; TLI = 0.934; RMSEA = 0.052 [0.044–0.059]; SRMR = 0.034). Furthermore, a multi-group analysis with non-professional (N = 2857) and professional (N = 528) gamers was performed. In this analysis, the factor loadings and intercepts were set equal in both groups. The level of fit was satisfactory (χ2nonprofessional = 758.6, χ2professional = 302.4 df = 264, p<0.0001; CFI = 0.963; TLI = 0.957; RMSEA = 0.042 [0.040–0.045]; SRMR = 0.036) and the means of latent variables were not statistically different in either group.

Labels of Factors

In the first factor, two items belonged that referred to obsessive thinking and daydreaming on the online game. This dimension was named preoccupation. The second factor contained items concerning the excessive use of online games. The three items belonging here referred to noticing gaming related problems, elongated gaming time, and the difficulties in controlling time spent on gaming. This factor was named overuse. The third factor was named immersion as these four items indicated dealing excessively with online games, immersion in gaming, and losing track of time. The fourth factor indicated damage to social relationships, and the preference of gaming over social activities. This three-item dimension was named social isolation. The two items of the fifth factor referred to the comments of the player’s social environment on overuse of online games and the related conflicts, so this factor was named interpersonal conflicts. Finally, the four items of the sixth factor concerned the appearance of withdrawal symptoms in cases when players experienced difficulties in gaming as much as they wanted. This dimension got the name withdrawal.

Latent Profile Analysis

A latent profile analysis was performed on the dimensions of problematic online gaming, and, a four-class solution was found according to the decision criteria. As Table 4 demonstrates that the AIC, BIC and sample-size adjusted BIC continued to decrease as more latent classes were added. However, a leveling-off after the four-latent-class solution was noted. In inspection of entropy, the two-class solution reached the maximum level, but the four-class solution also provided also an adequate level of entropy. Based on the L-M-R test, the four-class solution was accepted.

https://doi.org/10.1371/journal.pone.0036417.t004

The features of each class are presented in Figure 1 . The first class represents those gamers (47.8% of the total sample) that scored on dimensions of problematic use below the average. The second class of gamers (33.7%) represents the low risk of problematic use. The third class (15.2%) represents the medium risk of problematic use. Finally, the fourth class (3.4%) represents the high risk of problematic use. In this latter group, the ‘social isolation’ factor and ‘withdrawal symptoms’ factor especially showed an elevated level compared to other dimensions.

. The latent profile analysis resulted four classes. The first class represents those gamers that scored on POGQ below the average, while the second class represents the low risk, the third class represents medium risk of problematic use. The fourth class (3.4%) represents the high risk of problematic use.

https://doi.org/10.1371/journal.pone.0036417.g001

Determination cut-off score to be classified a problematic gamer: Sensitivity and specificity analyses.

Based on membership in the fourth class (i.e., being at high risk for problematic gaming) as a “gold standard”, the sensitivity, specificity, PPV as well as NPV, and accuracy of the POGQ at all possible cut-off points ( Table 5 ) were calculated.

https://doi.org/10.1371/journal.pone.0036417.t005

Based on this analysis, a cut-off score of 65 points is suggested as an ideal cut-off to be classed as problematic gamer. In this case, specificity is 100%, while sensitivity is 96%. This means that practically none of the negative (i.e., non-problematic) cases are considered as problematic, while only 4% of the true problematic cases are not recognized. Accuracy, as well as NPV in this case is 100%, while PPV is 90%. Increasing of the cut-off score would result in the growing number of the false negative cases, whereas decreasing would lead to more false positive cases.

Due to the growing number of indicated problems concerning online gaming it has become an absolute necessity to develop a tool with adequate psychometric characteristics for the measurement of the extent of gaming-related problems. The Problematic Online Gaming Questionnaire (POGQ) developed in this study, based on the results of the analyses, appears to fulfill those requirements that are expected from a measure like this. The POGQ was created in a way that it is applicable for all types of online games and its empirical basis makes it possible to cover all problems experienced by the players.

The results of these empirically-based analyses are at the same time very much supported by the fact that the six dimensions identified in the background of problematic online gaming fit closely to the available theoretical frameworks. Griffiths [18] proposed a “components” model for addictions that assumes the six classical symptoms for addiction behaviors in general that is salience, mood modification, tolerance, withdrawal, conflict, and relapse. The withdrawal and preoccupation components can be identified with our equally named factors, while conflict dimension is partly covered by the interpersonal conflicts factor and partly by the factor overuse (intrapersonal conflicts). It is interesting though that items explicitly representing salience dimension fell out during analysis (see item 2, 5, 11 in Table 2 .), but the component is still present in overuse, preoccupation, and social isolation factors. The relapse component appears in the overuse dimension while mood modification dimension is primarily present in the withdrawal factor (item 13 in Table 2 ).

In another approach, the DSM-IV criteria for psychoactive substance use dependence by the American Psychiatric Association [29] that are generally regarded as the definitional basis of behavioral addictions can be considered. These dimensions – withdrawal, lack of control (unsuccessful attempt to quit), much time spent on the activity, behavior continues despite knowledge of adverse consequences, more intensive use and for longer period than intended – are all clearly reflected in the POGQ. The more than adequate psychometric properties of the POGQ and the wide empirical content it is based on, is reassuring regarding the future use of the scale. However, further tasks include the cross-cultural validation of the POGQ and clinical validation of the scale.

It is an issue in relation to all behavioral addictions not present in DSM-IV-TR whether those individuals who engage in a specific behavior excessively should be regarded as having a disorder, and with which criteria we should identify individuals functioning on other pathologic levels. Considering the lack of consensus regarding definitions, the authors of the present study insisted on using the expression ‘problematic gaming’ instead of the more ambiguous gaming dependence. However, the latent profile analysis performed also indicated that a segment of the online gaming population (3.4% in this study) significantly exceeded the whole population and characteristically showed more problems than others. A further 15.2% of the population also showed moderately elevated level of problems. One of the most important tasks in future research is the detailed analysis of this at-risk population and to explore which background factors may carry high risk concerning problematic gaming. For forthcoming studies, the results here highlight two significant dimensions, withdrawal and social isolation, that showed elevated levels in case of these gamers, while obsession and overuse seemed to be the less indicative dimensions. Therefore, it seems that intensive actual (overuse) or imaginary (obsessive) gaming is less indicative of problematic gaming in itself. These results coincide with the results observed concerning problematic internet use [30] . In contrast, neglecting social relationships and especially the presence of withdrawal symptoms (feeling depressed or irritable, getting restless, anxious or upset when not able to game) appear to carry the highest risks. Furthermore, it is important to note that both dimensions include reducing or neglecting other activities which are key characteristics of addictions according to the results of many other studies.

One limitation of the present study is that it was carried out among Hungarian gamers thus results should be cautiously generalized for other cultures. However, it is hoped that future studies can confirm the findings presented here in other cultures. Another important issue is that current results were based on self-report data. It is again a challenge for future studies to investigate and confirm the identified problem-dimensions in clinical and/or observational studies. In conclusion, and based on all these assumptions, it is hoped that creation of the POGQ will facilitate and enhance further research, and that the instrument will serve as a valid and reliable tool in future studies.

Supporting Information

Appendix s1..

Problematic Online Gaming Questionnaire (POGQ).

https://doi.org/10.1371/journal.pone.0036417.s001

Author Contributions

Conceived and designed the experiments: ZD. Performed the experiments: ZD KN JF OP KF GK. Analyzed the data: RU AO. Wrote the paper: ZD UR KN JF MDG KF.

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" The effects of online games on the academic performance of male students " Statement of the Problem

The main purpose of the study was to gather information for the male students concerning the effects of online games on the academic performance in order to find out solutions for the existing problems enumerated below based on the interview conducted:

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The objective of this research was to findout the effect of online gaming habits on student,s learning outcomes in class X of social sciences in economics subject at SMA Negeri 1 Tapa, Bone Bolango Regency, It employed a quantitative method with a sample of 66 students. At the sama time, the data analysis used in this research was a simple linear regression analysis assisted by IBM Statistics SPSS 26.0 program. The research findings signified that the variable of online gaming habits partially had a negatif and significant effect on students’ learning outcomes in class X of social Sciences at SMA Negeri 1 Tapa, the results of this research obtainet a coefficient of determination (R2) of 0.169, meaning that the effect of online gaming habbits variabel on students’ learning outcomes at SMA Negeri 1 Tapa was 16.9%. in contrast, the remaining 83.1% was affected by other variables that contribute to students’ learning outcomes at SMA Negeri 1 Tapa, which were not examinet in this research.

KnE Social Sciences

Computer and video game has gain enough popularity among teenagers also in children which is alarming and raised concern about the impact it may have on the youngsters. The games have violent themes, coupled with their interactive nature, have led to accusations that they may be worse than televised violence in affecting children's antisocial behaviour. Addiction is one of the reason it might hamper the effect on health. Other allegations are that they have an addictive quality and that excessive playing results in a diminished social contact and poorer school performance. But how bad are video games? There are strong methodological reasons for not accepting the evidence for video games effects at face value This research focuses on what are the views of people towards the computer gaming and to identify the actual effects of computer games on high school students. This paper covers earlier studies on the same topic and their findings in literature survey To reach to the objective, responses from significant no of people taken with systematic design of questionnaire. At the end it covers and conclude the relation of different variables & the effect of games on students.

Psychology and Education: A Multidisciplinary Journal, 2024

In modern society, computers have become almost a non-negotiable part of every individual's life. Then this is bound to have both positive and negative consequences on people. Because of this many young children and individuals anywhere can become addicted to playing such games online and offline gaming. It became a huge distraction to the academic performance of the learners by being addicted to computer games. The main goal of this study was to determine the level of understanding on playing in computer games and academic performance of learners in Sultan Palao Ali Memorial Elementary School, SPAMES (127217), Tagoloan District, Division of Lanao del Norte. The study used descriptive-correlational research design. Descriptive research determined the profile of elementary learners of Sultan Palao Ali Elementary School located at Barangay Inagonan, Tagoloan Lanao, Del Norte and the level of understanding on playing in computer games and the academic performance of the respondents. Based on the results of the study, most of the learners at Sultan Palao Ali Elementary School, Tagoloan District, Division of Lanao del Norte, were age ranges from 11-13, females and in satisfactory level as to their academic performance. In the level of understanding of playing computer games of the respondents, among the indicators of the level of understanding, the indicator "Playing computer games can enhance the accuracy/speed of my hands), got the highest mean score which can also be interpreted in the agreed level, while the indicator "Playing computer games can increase my empathy and supports my mental well-being) garnered the lowest mean of 1.80, which can be interpreted in the disagreed level in which the respondents believed that playing computer games negatively impacted their health. Further, in correlation, the null hypothesis, which states that there is no significant relationship between academic performance and profile in terms of age, was not rejected, while sex was rejected. At the same time, the null hypothesis, which states that there is no significant relationship between academic performance and the level of understanding of playing computer games, was also rejected. Furthermore, in the regression analysis, the null hypothesis stating that "there is no variable/s best predict the academic performance" was rejected.

There are many factors that correlated with students' academic performance. Some people believe that video game is one of the factors that affect students' academic performance negatively. Thus, the purpose of this study was to investigate the relationship between video games and student academic performance among male and female students of IIUM. A questionnaire was used to collect data about students' gaming frequency and students' academic performance. 30 students were selected randomly from each kulliyyah as the sample of the study. The result of the research indicated that there is no relationship between video games and students' academic performance of IIUM University. From this findings, it can be concluded that being non-gamer does not guarantee a student to have high academic performance. In contrast, being frequent gamer also does not guarantee student to perform bad in academic. There are many factors that correlated with academic performance other than video games.

There are many factors that correlated with students' academic performance. Some people believe that video game is one of the factors that affect students’ academic performance negatively. Thus, the purpose of this study was to investigate the relationship between video games and student academic performance among male and female students of IIUM. A questionnaire was used to collect data about students' gaming frequency and students' academic performance. 30 students were selected randomly from each kulliyyah as the sample of the study. The result of the research indicated that there is no relationship between video games and students’ academic performance of IIUM University. From this findings, it can be concluded that being non-gamer does not guarantee a student to have high academic performance. In contrast, being frequent gamer also does not guarantee student to perform bad in academic. There are many factors that correlated with academic performance other than video games

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• How to Write a Problem Statement | Guide & Examples

How to Write a Problem Statement | Guide & Examples

Published on November 6, 2022 by Shona McCombes and Tegan George. Revised on November 20, 2023.

A problem statement is a concise and concrete summary of the research problem you seek to address. It should:

• Contextualize the problem. What do we already know?
• Describe the exact issue your research will address. What do we still need to know?
• Show the relevance of the problem. Why do we need to know more about this?
• Set the objectives of the research. What will you do to find out more?

Table of contents

When should you write a problem statement, step 1: contextualize the problem, step 2: show why it matters, step 3: set your aims and objectives.

Problem statement example

Other interesting articles

Frequently asked questions about problem statements.

There are various situations in which you might have to write a problem statement.

In the business world, writing a problem statement is often the first step in kicking off an improvement project. In this case, the problem statement is usually a stand-alone document.

In academic research, writing a problem statement can help you contextualize and understand the significance of your research problem. It is often several paragraphs long, and serves as the basis for your research proposal . Alternatively, it can be condensed into just a few sentences in your introduction .

A problem statement looks different depending on whether you’re dealing with a practical, real-world problem or a theoretical issue. Regardless, all problem statements follow a similar process.

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The problem statement should frame your research problem, giving some background on what is already known.

Practical research problems

For practical research, focus on the concrete details of the situation:

• Where and when does the problem arise?
• Who does the problem affect?
• What attempts have been made to solve the problem?

Theoretical research problems

For theoretical research, think about the scientific, social, geographical and/or historical background:

• What is already known about the problem?
• Is the problem limited to a certain time period or geographical area?
• How has the problem been defined and debated in the scholarly literature?

The problem statement should also address the relevance of the research. Why is it important that the problem is addressed?

Don’t worry, this doesn’t mean you have to do something groundbreaking or world-changing. It’s more important that the problem is researchable, feasible, and clearly addresses a relevant issue in your field.

Practical research is directly relevant to a specific problem that affects an organization, institution, social group, or society more broadly. To make it clear why your research problem matters, you can ask yourself:

• What will happen if the problem is not solved?
• Who will feel the consequences?
• Does the problem have wider relevance? Are similar issues found in other contexts?

Sometimes theoretical issues have clear practical consequences, but sometimes their relevance is less immediately obvious. To identify why the problem matters, ask:

• How will resolving the problem advance understanding of the topic?
• What benefits will it have for future research?
• Does the problem have direct or indirect consequences for society?

Finally, the problem statement should frame how you intend to address the problem. Your goal here should not be to find a conclusive solution, but rather to propose more effective approaches to tackling or understanding it.

The research aim is the overall purpose of your research. It is generally written in the infinitive form:

• The aim of this study is to determine …
• This project aims to explore …
• This research aims to investigate …

The research objectives are the concrete steps you will take to achieve the aim:

• Qualitative methods will be used to identify …
• This work will use surveys to collect …
• Using statistical analysis, the research will measure …

The aims and objectives should lead directly to your research questions.

Learn how to formulate research questions

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You can use these steps to write your own problem statement, like the example below.

Step 1: Contextualize the problem A family-owned shoe manufacturer has been in business in New England for several generations, employing thousands of local workers in a variety of roles, from assembly to supply-chain to customer service and retail. Employee tenure in the past always had an upward trend, with the average employee staying at the company for 10+ years. However, in the past decade, the trend has reversed, with some employees lasting only a few months, and others leaving abruptly after many years.

Step 2: Show why it matters As the perceived loyalty of their employees has long been a source of pride for the company, they employed an outside consultant firm to see why there was so much turnover. The firm focused on the new hires, concluding that a rival shoe company located in the next town offered higher hourly wages and better “perks”, such as pizza parties. They claimed this was what was leading employees to switch. However, to gain a fuller understanding of why the turnover persists even after the consultant study, in-depth qualitative research focused on long-term employees is also needed. Focusing on why established workers leave can help develop a more telling reason why turnover is so high, rather than just due to salaries. It can also potentially identify points of change or conflict in the company’s culture that may cause workers to leave.

Step 3: Set your aims and objectives This project aims to better understand why established workers choose to leave the company. Qualitative methods such as surveys and interviews will be conducted comparing the views of those who have worked 10+ years at the company and chose to stay, compared with those who chose to leave.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

All research questions should be:

• Focused on a single problem or issue
• Researchable using primary and/or secondary sources
• Feasible to answer within the timeframe and practical constraints
• Specific enough to answer thoroughly
• Complex enough to develop the answer over the space of a paper or thesis
• Relevant to your field of study and/or society more broadly

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

Your research objectives indicate how you’ll try to address your research problem and should be specific:

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McCombes, S. & George, T. (2023, November 20). How to Write a Problem Statement | Guide & Examples. Scribbr. Retrieved September 23, 2024, from https://www.scribbr.com/research-process/problem-statement/

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Quantitative Games: Problem Statement and Examples, New Geometric Aspects

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In view of discussing games involving stochastic state equations, delays, partial differential equations and other functional dependence, we shall return to the definition of a quantitative game and try to extend an earlier statement of the problem [1]. We shall consider the case of N players, J a , α=1,2,…N.

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Control Theory Centre, Department of Engineering, University of Warwick, CV4 7AL, Coventry, England

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© 1975 D. Reidel Publishing Company, Dordrecht-Holland

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Blaquière, A. (1975). Quantitative Games: Problem Statement and Examples, New Geometric Aspects. In: Grote, J.D. (eds) The Theory and Application of Differential Games. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-1804-3_10

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