In academic programs, individuals are frequently tasked with conducting research, often as a partial fulfillment of course requirements crucial for program completion. In moments of uncertainty, a despondent student might question, “Does this constitute a proper title for research?” or express uncertainty about developing a hypothesis for their idea. Health Science Research Methods offers guidance to initiate this process. While the concepts covered extend beyond health and biomedical research, they provide applicable insights for research across various disciplines. This resource aims to assist individuals in crafting effective research titles and developing robust hypotheses, fostering a foundation for successful academic inquiry.
Health Sciences Research Methods encompass systematic approaches to investigate, understand, and contribute to knowledge in the diverse field of health. These methods aim to answer questions, solve problems, and advance scientific understanding within various health-related disciplines, including medicine, nursing, pharmacy, public health, and more.
By the end of this content, you will be able to:
Formulate clear and relevant research questions or hypotheses that address gaps in current knowledge or practical issues within health science disciplines.
Select appropriate research designs, whether experimental, observational, qualitative, or quantitative, base on the nature of the research question and available resources.
Implement effective methods for data collection, which may include surveys, interviews, experiments, clinical trials, observations, or the analysis of existing data sets.
Integrate ethical principles into the research process, ensuring the protection of participants’ rights, confidentiality, and adherence to ethical guidelines governing health sciences research.
Apply suitable statistical or qualitative analysis techniques to interpret data and draw meaningful conclusions.
Employ statistical software, coding qualitative data, and deriving evidence-based interpretations.
Effectively communicate research findings through scholarly publications, presentations, or reports. Disseminate results to relevant stakeholders, contributing to the collective knowledge in health sciences.
Embrace a commitment to lifelong learning, staying informed about emerging research methods, technological advancements, and changes in ethical standards. Adapt research approaches to incorporate new knowledge and methodologies.
Define Search
Search refers to the deliberate and systematic activity of examining or exploring a subject, location, or information resource with the specific intent of finding or discovering something. It involves a careful and thorough inspection, reading, or inquiry, often directed towards uncovering information, exploring potential places, or examining public records. The process of search may encompass various methods and strategies to ensure a comprehensive and detailed examination, with the ultimate goal of obtaining relevant or sought-after results (Merriam-Webster Dictionary).
Common Errors in Non-Scientific Inquiry
- Inaccurate observations
- Overgeneralization
- Selective observation
- Illogical reasoning
- Premature closure
- Halo effect
- Personal experience
- Ecological fallacy
Research is empirical, rooted in the concept of empiricism where knowledge is derived from experiences.
The information resulting from these experiences takes various forms, such as test scores, field notes, or responses to questionnaires.
The researcher engages in a systematic process of examining and organizing data, generating hypotheses, and testing them. Educational research follows the scientific method within a broad framework, yet there is flexibility in how the steps are implemented across different types of studies.
Critical Thinking
Critical thinking stands out as a highly coveted skill among employers across diverse industries when evaluating potential job candidates. It encompasses the capability to objectively analyze information and arrive at reasoned judgments. In essence, critical thinking entails the skillful evaluation of various sources, including data, facts, observable phenomena, and research findings. Exceptional critical thinkers possess the ability to draw sound conclusions from a pool of information, skillfully discerning between relevant and extraneous details. This proficiency proves invaluable when tackling problems or navigating decision-making processes (Doyle, 2017).
Planning for Research
Definition Research
Research is the methodical process of collecting and analyzing information to increase our understanding of the phenomenon under study. Research is a cyclic and systematic investigation involving the study of a specific population or a subset (sample) within that population. Its purpose is to gain understanding, collect data, or measure outcomes related to a particular problem or topic of interest (Creswell, 2017).
Every research should address: a problem statement or hypothesis construction, data collection, analysis and interpretation of results. Engaging in research involves careful planning and consideration of various factors. These will be discussed in detail, but let us first take a look at the two major types of research: basic research and applied research.
Basic research, also known as pure or fundamental research, is conducted primarily to enhance scientific knowledge and understanding. Researchers in basic research explore theoretical concepts and principles without a specific practical application in mind. The primary goal is to expand our understanding of the natural world, uncover fundamental laws and theories, and answer fundamental scientific questions. Basic research often forms the foundation for applied research and technological advancements but doesn’t have immediate or direct practical applications. Scientists in basic research may investigate phenomena, conduct experiments, or develop theories, contributing valuable knowledge to their respective fields.
Experimental Research
Experimental research involves manipulating variables to observe the effects and establish cause-and-effect relationships. This method often includes a control group and an experimental group, allowing researchers to compare outcomes between them. Experimental research is particularly valuable for testing hypotheses, evaluating interventions, and determining the effectiveness of social programs or policies. In social sciences, experiments can be designed to assess the impact of specific interventions on social behaviors, attitudes, or perceptions. By conducting experiments, researchers can identify strategies that effectively address social problems, leading to evidence-based solutions and informed decision-making.
Applied research aims to solve specific, practical problems or address practical questions. It involves the application of scientific principles and theories to real-world issues. Researchers in applied research focus on developing solutions, products, or interventions that have direct relevance and usefulness in various fields, including medicine, engineering, technology, and social sciences. Applied research is goal-oriented and often conducted in specific contexts, with the intention of solving immediate problems, improving processes, or creating new technologies. The remaining content on this page will focus on applied research.
Basic research and applied research are two fundamental types of scientific inquiry, each serving distinct purposes and methodologies. The key difference between basic and applied research lies in their objectives and outcomes. Basic research seeks to expand knowledge and theories, often without immediate practical applications, while applied research aims to address specific problems and create tangible solutions that can be directly applied to real-world situations. While both types of research are valuable, they serve different purposes in the scientific community, contributing to the overall progress of knowledge and the betterment of society. The remaining content on this page will focus on applied research.
Action research is a form of applied research that directs its attention toward identifying solutions to localized issues within a specific setting.
For instance, a teacher may engage in action research to examine the effectiveness of a newly adopted spelling program on her students’ achievement scores. This approach emphasizes a hands-on, problem-solving methodology that empowers practitioners to address challenges directly within their immediate context (Mills, 2003, as cited in Leedy and Ormrod, 2005, p. 108).
A collective effort where a group identifies a problem, takes proactive steps to address it, evaluates the success of their interventions, and, if unsatisfied with the outcomes, persists in refining and reattempting solutions. This iterative process allows for continuous learning and adaptation, emphasizing a dynamic and responsive approach to problem-solving within a collaborative framework.
Research Based of Extent of Work on Area of Study.
Exploratory Research
Exploratory research is typically undertaken in areas where there is limited prior investigation. It serves as an initial fact-finding endeavor, aiming to clarify and define the nature of a problem. This form of research is crucial for uncovering patterns and ideas that can be further investigated in depth. The primary goal is to pave the way for more comprehensive studies by shedding light on areas that lack prior exploration.
Descriptive Research
Descriptive research seeks to portray the characteristics of a population or phenomenon without exerting any influence. Utilizing methods such as surveys, case studies, and observations, researchers collect data to answer key questions regarding the subject—namely, who, what, when, where, and how. In social sciences, descriptive research proves valuable for understanding demographic features, attitudes, behaviors, or opinions within a specific societal group.
The outcomes of descriptive research, including identified patterns and correlations, contribute significantly to policy-making, program development, and addressing broader societal issues.
Explanatory Research
Explanatory research is fundamentally designed to unravel the intricacies of phenomena, delving into the ‘why’ behind observed occurrences. In contrast to descriptive research, which addresses questions of ‘what,’ ‘when,’ ‘where,’ and ‘how,’ explanatory research aims to uncover the underlying reasons or causal relationships.
For instance, while reporting the voting intentions of the Jamaican public for the next Digicel Rising Star is considered descriptive, shifting the focus to understand why individuals plan to vote for competitor A versus competitor B transforms the inquiry into an explanatory pursuit. Explanatory research goes beyond surface-level observations, seeking to provide deeper insights into the driving forces and motivations behind human behaviors or phenomena of interest.
Historical Research
Historical research explores past events, processes, or behaviors to uncover patterns, causes, and effects within a specific historical context. Researchers use historical documents, records, artifacts, and oral accounts to reconstruct events and understand their significance. This type of research helps scholars and policymakers analyze historical trends, identify the roots of social issues, and gain insights into the development of societies over time. By understanding historical contexts, social scientists can draw connections between past events and contemporary issues, aiding in decision-making, policy formulation, and societal change.
Research Based on Aim of Study.
It is crucial to note that the purpose of the research, rather than the technique employed, determines whether a study falls into the categories of exploratory, descriptive, or causal research. This emphasizes the importance of aligning research goals with the appropriate methodological approach, ensuring that the chosen research type is well-suited to meet the intended objectives.
Causal Research
Causal research endeavors to uncover the underlying reasons behind specific patterns, seeking to identify cause-and-effect relationships among variables. This methodological approach is particularly useful when the objective is to understand the driving forces behind observed phenomena and the interconnectedness of various factors.
- To Explore Effects (Prospective Study)
Start with a suspected cause and attempt to identify effects on some variables [Effects of gender on achievement in research methods courses].
- TO Explore Causes (Retrospective Study)
Start with an effect and look for factors that might have caused it [Factors that contribute to poor performance in examinations].
- To Explore Consequences
How do teachers who are trained before entering the classroom feel about using constructivist approaches in teaching?
Causal-comparative research endeavors to unravel the causes behind the current state of a phenomenon, delving into cause-and-effect relationships. In this investigative approach, the term “cause” refers to treatments or conditions believed to have instigated observed differences, while the “effect” pertains to the resulting disparities. This type of research can be retrospective or prospective. Importantly, causal-comparative studies involve the measurement, rather than manipulation, of variables, either after the fact or when variables are inherently unchangeable.
Despite its quest to establish causal relationships, it is crucial to approach findings from causal-comparative research with caution, recognizing that these relationships are often “tenuous and tentative.” Unlike experimental studies that can confidently establish cause-effect connections, causal-comparative research is observational in nature. The researcher observes disparities between groups and seeks to understand the potential causes, effects, or consequences without manipulating the variables. In essence, causal-comparative research offers valuable insights into potential relationships, shedding light on the intricacies of observed differences without directly intervening in the variables under investigation.
Predictive Research
Predictive research aims to leverage insights obtained from prior analytical research to anticipate outcomes in specific scenarios. Drawing on information gathered through rigorous analysis, this type of research helps forecast potential developments or trends, making it a valuable tool for decision-makers anticipating future circumstances.
Evaluation Research
Evaluation research is a type of research that focuses on assessing the merit and worth of a particular practice within a specific context. The primary goal of evaluation research is to provide insights into the effectiveness, efficiency, and overall impact of programs, interventions, policies, or practices. This form of research aims to answer questions related to the success or failure of a program, how well it meets its objectives, and whether it has achieved the desired outcomes. Evaluation Research and its application in health policy development was discussed here.
Importance of Research
- Knowledge Enhancement
Research serves as a continual process of knowledge expansion, actively addressing gaps and replicating existing knowledge. By incorporating diverse voices and perspectives, it contributes to a richer, more comprehensive understanding of various subjects.
- Practice Improvement
Beyond theoretical contributions, research plays a pivotal role in enhancing practical applications. For educators, it serves as a source of new ideas and insights, fostering continuous improvement in teaching approaches. Additionally, it facilitates collaboration among educators, promoting the exchange of innovative practices and methodologies.
- Informed Policy Debates
Research acts as a cornerstone in shaping well-informed policy debates. By presenting a spectrum of perspectives on critical issues, research enables individuals to weigh different viewpoints. Moreover, it empowers decision-makers with the knowledge needed to make informed choices in the development and evaluation of policies.
The research process will be discussed in terms of chapters. Click on the respective tab below to review detailed content on the components and considerations of each chapter.
Research Methodology Chapter One- Introduction
Chapter 1 establishes the foundation for the research endeavor by situating the study within existing knowledge and outlining the research background. The chapter articulates a clear statement of the problem, identifying the specific issue or gap in understanding that the research aims to address. It formulates research questions or hypotheses to guide the investigation, offering a roadmap for inquiry. Additionally, it elucidates the purpose and significance of the study, highlighting the potential contributions and relevance of the research to the academic or practical domain. The chapter also discusses the study's scope and limitations, outlining the boundaries and constraints within which the research operates. Finally, it presents the organization of the study, providing readers with a preview of the structure and flow of subsequent chapters, ensuring clarity and coherence in the research narrative. Click the Icon to Go to Chapter One.
A conceptual framework in research is a foundational structure that assists researchers in understanding, analyzing, and interpreting a research problem. A conceptual framework is essentially defined as a system of concepts, theories, or ideas that forms the basis for investigating a research problem. It acts as a lens through which researchers view their study, providing a conceptual map for understanding the relationships between key variables. The primary purpose is to delineate the central concepts, variables, and relationships relevant to the research problem. It helps organize thoughts and provides a roadmap for developing research questions, ensuring clarity and coherence in the study. By establishing a logical flow, it aids in making connections between different elements of the research.
Conceptual framework is broader and more general compared to specific research theories or models. Often, it encompasses guiding principles or perspectives that shape the overall research design, offering a holistic view of the research problem. Researchers enjoy flexibility in constructing and adapting conceptual frameworks to align with the unique needs and characteristics of their study. This adaptability allows researchers to integrate relevant theories or concepts, providing a framework that best suits the nature of the research. Let us review the common conceptual frameworks in health and social science research:
Health Belief Model
The Health Belief Model (HBM) is a psychological model that explains and predicts health behaviors by examining individuals’ beliefs and perceptions. Developed in the 1950s by social psychologists Hochbaum, Rosenstock, and Kegels, the HBM posits that an individual’s likelihood of taking health-related action is determined by their perception of a health threat and the value they place on reducing that threat.
Perceived Susceptibility refers to an individual’s belief regarding their vulnerability or likelihood of experiencing a particular health issue. A person might assess their susceptibility to developing diabetes based on factors like family history, lifestyle choices, and overall health.
Perceived Severity focuses on an individual’s belief about the seriousness of a health problem and the potential consequences if the issue is not addressed. Perceiving obesity as a severe health issue may involve considering the risks of cardiovascular diseases, diabetes, and reduced quality of life associated with it.
Perceived Benefits involves the individual’s belief in the effectiveness of a recommended health action to reduce the perceived threat. Believing that regular exercise and a balanced diet can effectively reduce the risk of obesity-related health problems.
Perceived Barriers involves the assessment of obstacles and costs associated with taking a health-related action. Barriers to adopting a healthier lifestyle might include time constraints, financial costs, or the perceived difficulty of making significant dietary changes.
Cues to Action are factors that prompt or stimulate individuals to take health-related action. Receiving information about the health benefits of physical activity, observing others’ positive health changes, or a health scare in the community could serve as cues to action.
Self-Efficacy reflects an individual’s belief in their ability to successfully execute a health-related action. Having confidence in one’s ability to stick to a new exercise routine or maintain a healthier diet despite challenges.
Importance of the Health Belief Model in Research
The HBM guides the development of health interventions by identifying factors that influence health behaviours. It helps researchers design strategies that consider individuals’ perceptions and beliefs.
Researchers use the HBM to understand why individuals may or may not adopt health-promoting behaviours. This understanding is crucial for designing effective interventions.
HBM aids in tailoring interventions to address specific barriers and motivators identified through individuals’ perceptions, increasing the intervention’s relevance and effectiveness.
By understanding how individuals perceive health threats and interventions, policymakers can develop more targeted and impactful public health policies.
Advantages and Disadvantages of the Health Belief Model
Some positives with the HBM include its: applicability, individual focus, predictive power, and practical application.
- The model is applicable across a wide range of health behaviours and populations.
- Emphasizes individual perceptions, making interventions more personalized.
- Effectively predicts and explains health behaviors in many contexts.
- Easy to use in designing health education and communication campaigns.
However, there are some shortcomings associated with the use of the HBM. These include its simplistic nature, limited scope, variable importance, and a lack of consideration for emotions.
- Critics argue it oversimplifies health behavior by focusing on individual perceptions.
- May not fully capture the complexity of social, environmental, and cultural influences.
- The importance of model components may vary across different behaviours.
- Does not explicitly consider emotional factors in health decision-making.
Health Promotion Model (HPM)
Developed by Nola Pender, the Health Promotion Model (HPM) is grounded in the belief that individuals seek to regulate their behaviour to achieve and maintain health. The HPM offers a comprehensive framework for understanding and promoting health behaviours. The key principles of HPM include:
Personal factors, including biological, psychological, and socio-cultural influences, shape health behaviours.
Cognitive factors such as perceived benefits, barriers, self-efficacy, and emotions influence health-related decision-making.
Health-promoting behaviours are the result of a dynamic interaction between individual characteristics, cognitions, and the environment.
Social support and interpersonal relationships impact individuals’ health behaviours.
External factors such as the environment, available resources, and situational constraints affect health behaviors.
Advantages of HPM
HPM considers individual, interpersonal, and environmental factors, providing a comprehensive understanding of health behavior.
The model has been successful in predicting and explaining various health behaviors across diverse populations.
The model provides a framework for designing interventions to promote health behaviors by addressing relevant determinants.
Disadvantages of HPM
The model’s multi-dimensional nature may be challenging for some researchers to operationalize and apply effectively.
While socio-cultural influences are acknowledged, the model may not fully capture the nuances of cultural diversity.
The model places significant emphasis on individual decision-making, potentially underestimating the role of external factors.
Research Process Implications of HPM
HPM is versatile and applicable across various health-related contexts. Researchers can design targeted interventions based on identified determinants within the model. The model encourages researchers to explore the interconnectedness of individual, interpersonal, and environmental factors influencing health behaviors.
Social-Ecological Model
The Social-Ecological Model (SEM) is a conceptual framework that recognizes the multi-level influences on health behaviours and outcomes.
It encompasses various levels: individual, interpersonal, community, and societal:
- Intrapersonal/Individual Factors influence behaviour, encompassing aspects like knowledge, attitudes, beliefs, and personality.
Interpersonal Factors involve interactions with other people, serving either as sources of social support or creating barriers that hinder interpersonal growth, subsequently impacting healthy behavior.
Community and Organizational Factors category includes rules, regulations, policies, and informal structures within institutions or organizations. Community Factors encompass formal or informal social norms existing among individuals, groups, or organizations. Such norms can either limit or enhance healthy behaviours.
Public Policy Factors involves local, state, and federal policies and laws. These regulations either control or support health actions and practices, especially for disease prevention, early detection, control, and management.
Importance of the Social-Ecological Model in Research
SEM provides a comprehensive view, acknowledging that health issues are complex and influenced by multiple factors. It informs the development of interventions by recognizing that changes at different levels can impact behaviour. SEM encourages researchers to consider the broader context in which health-related behaviours occur.
Advantages and Disadvantages of the Social-Ecological Model
Advantages
SEM considers a range of factors, providing a holistic understanding through the integration of multiple perspectives.
It can be applied to various health issues and behaviours.
SEM guides the development of interventions that target multiple levels.
Disadvantages
The model’s multi-level nature can make it challenging to navigate.
Implementing interventions across multiple levels may require extensive resources.
Critics argue that SEM may not give sufficient attention to individual agency.
Critical Theory
Critical Theory, rooted in the works of philosophers such as Karl Marx and developed further by the Frankfurt School, offers a distinctive lens for examining social structures, power dynamics, and societal inequalities. This theoretical framework is grounded in the premise that social issues are deeply intertwined with power imbalances and structural injustices. Critical Theory encourages researchers to scrutinize the underlying assumptions and norms that perpetuate inequality, oppression, and marginalization within society. This approach challenges the status quo and aims to unveil hidden power structures that influence individuals and groups.
Tenets of Critical Theory
At its core, Critical Theory emphasizes the importance of questioning dominant ideologies and exposing the ways in which societal structures contribute to the reproduction of inequality. It encourages a reflexive stance, urging researchers to be aware of their own biases and positionality. Critical theorists argue that research should not merely describe social phenomena but should actively engage in social critique, advocating for social change. The framework prompts researchers to investigate not only what is visible but also what is hidden or suppressed within social systems.
Importance in Research
Critical Theory holds particular relevance in fields that aim to address social justice issues, including sociology, education, and cultural studies. By foregrounding power relations and critiquing established norms, researchers utilizing this framework contribute to a deeper understanding of social problems and potential pathways for transformative change. Critical Theory is instrumental in shedding light on the intersections of race, class, gender, and other axes of identity, fostering a nuanced analysis of the complexities within societal structures.
Research Process Implications
Researchers employing Critical Theory engage in a reflexive and participatory research process. They often collaborate with communities affected by social issues, valuing their perspectives and lived experiences. Data collection methods may include interviews, participant observation, and content analysis aimed at uncovering hidden power dynamics. The findings of research guided by Critical Theory often have implications for activism and social advocacy, as they seek to disrupt and transform oppressive structures. While powerful in its potential for societal critique, Critical Theory demands a heightened ethical awareness to navigate the complexities of research involving vulnerable populations and contested power dynamics
Theory of Planned Behaviour (TPB)
The Theory of Planned Behaviour (TPB) is a psychological model that aims to predict and understand human behaviour. It was developed by Icek Ajzen and builds upon the earlier Theory of Reasoned Action. TPB posits that individual intention is the key predictor of behaviour, and intention is influenced by three main factors:
Attitude Toward Behaviour (AB)- This component refers to an individual’s evaluation of a particular behaviour. It assesses whether the person perceives the behaviour as positive or negative.
Subjective Norms (SN)- Subjective norms involve the perceived social pressure or expectations from significant others regarding the performance or non-performance of a behaviour.
Perceived Behavioural Control (PBC)- Perceived behavioural control reflects an individual’s belief in their ability to perform a specific behaviour successfully, considering perceived obstacles and resources.
Behavioural Intention- The three components—Attitude Toward Behaviour, Subjective Norms, and Perceived Behavioural Control—combine to shape an individual’s behavioral intention. Behavioral intention, in turn, is a strong predictor of actual behavior.
While the main focus is on the three components, TPB acknowledges the influence of external variables, such as demographic factors, personality traits, and situational factors, that may impact the relationship between intention and behaviour.
Application of the TPB in Research
TPB is widely used in various fields, including health psychology, marketing, and social sciences, to understand and predict behaviors like adopting a healthy lifestyle, purchasing decisions, and adherence to specific practices.
- TPB helps predict and understand behaviors based on attitudes, subjective norms, and perceived control.
- It guides the development of interventions by identifying key factors influencing behaviour.
Advantages include:
- TPB has been successful in predicting various behaviours.
- It is versatile and applicable to a range of behaviours.
- Interventions informed by TPB can lead to effective behaviour change.
Disadvantages
While TPB provides valuable insights into behavioural prediction, it oversimplifies complex human behaviours and does not fully account for emotional and cultural factors.
- It has been critiqued for potentially oversimplifying the complexity of human behaviour.
- TPB may not adequately address the role of emotions in decision-making.
- The model may not fully consider cultural nuances impacting behaviour.
Despite these limitations, TPB remains an influential model in understanding the cognitive determinants of behaviour.
Social Cognitive Theory (SCT)
Social Cognitive Theory is a versatile framework that provides a nuanced understanding of behaviour, allowing researchers to predict, explain, and intervene in various contexts. SCT, developed by Albert Bandura, emphasizes the reciprocal interaction between personal factors, behaviour, and the environment. It introduces key concepts such as observational learning, self-efficacy, and self-regulation.
Observational Learning- people can learn by observing others and imitating their behaviours.
Self-Efficacy- belief in one’s capability to execute actions that will produce desired outcomes.
Self-Regulation- individuals can control their own behaviour through processes like goal-setting and self-monitoring.
Social Cognitive Theory- Research Application
SCT provides a holistic understanding of human behavior by considering cognitive, behavioral, and environmental factors. It is applicable to various fields, including education, psychology, health, and communication. The SCT can guide the design of interventions to change behaviour by addressing factors such as role modeling and self-efficacy.
Advantages of Social Cognitive Theory
Behavioral Predictions- SCT allows for the prediction of behavior by considering cognitive and environmental influences.
Practical Application- Its emphasis on observational learning provides practical insights for designing interventions.
Individual-Centered- Recognizes the role of individual factors, allowing for tailored interventions.
Disadvantages of Social Cognitive Theory
Complexity- SCT can be intricate, making it challenging to apply in some research contexts.
Limited Emphasis on Emotion- The theory may not extensively address emotional factors influencing behavior.
Not All-Encompassing- While comprehensive, SCT may not cover all aspects of behavior, necessitating integration with other theories.
Feminist Theory
Feminist theory is a multidisciplinary perspective that critically examines and challenges traditional assumptions, structures, and practices related to gender and power. Emerging from social, political, and cultural contexts, feminist theories seek to understand, critique, and transform societal norms that perpetuate gender-based inequalities. The primary focus is on dismantling patriarchal systems and advocating for the rights and experiences of women.
Principles of Feminist Theory
Feminist theories encompass a range of perspectives, but they share common principles. These include critiquing and challenging gender roles, examining power dynamics, promoting inclusivity and intersectionality, and advocating for social justice. Feminist frameworks often emphasize the importance of recognizing diverse experiences, acknowledging historical and systemic oppressions, and promoting equity in various spheres, such as education, the workplace, and interpersonal relationships.
Importance in Research
Feminist theory plays a crucial role in informing research by providing a lens through which scholars can analyze and interpret social phenomena. In research, a feminist framework prompts researchers to consider how gender intersects with other social categories, influencing experiences and outcomes. It encourages the exploration of power imbalances, marginalized voices, and the impact of gender norms on knowledge production. By employing feminist theory, researchers contribute to a more nuanced and equitable understanding of social issues, fostering positive social change and advocating for inclusive policies and practices
Grounded Theory
Grounded Theory is a robust and widely used conceptual framework, particularly in qualitative research. Its inductive nature allows for the exploration of new phenomena. Grounded Theory, developed by Glaser and Strauss, is an inductive research approach aiming to generate theories from data rather than testing pre-existing hypotheses. The following principles guide Grounded Theory:
Open Coding is the initial coding of data to identify concepts and categories.
Axial Coding organizes and connects codes to find relationships and patterns.
Constant Comparison is the process of continuously comparing data to refine concepts and categories.
Theoretical Sampling involves selecting data sources based on emerging theories.
Theoretical Saturation is the point where no new information is obtained, indicating theoretical completeness.
Grounded Theory is employed when researchers seek to develop a theory grounded in data rather than testing existing theories. It is widely used in qualitative research across disciplines, particularly in social sciences, education, and healthcare.
Advantages of Grounded Theory
Grounded Theory allows for the discovery of patterns and theories directly from data, suitable for exploring new phenomena through it inductive approach.
It is adaptable and applicable to various research contexts and disciplines adding to its flexibility.
The method provides detailed and contextually rich descriptions of phenomena.
Disadvantages of Grounded Theory
Conducting Grounded Theory research can be time-intensive due to the iterative nature of data collection and analysis.
Interpretation is influenced by researchers, introducing potential bias.
The constant comparative method and theoretical sampling can be challenging for novice researchers.
Ecological Systems Theory
Developed by Urie Bronfenbrenner, the Ecological Systems Theory offers a holistic perspective on human development, emphasizing the interconnectedness between individuals and their environments. This theoretical framework posits that an individual’s development is influenced by multiple systems, each nested within the other. Bronfenbrenner delineates these systems into microsystem, mesosystem, exosystem, macrosystem, and chronosystem. The microsystem consists of immediate, direct influences on an individual, such as family and peer relationships. The mesosystem involves interactions between components of the microsystem. The exosystem includes external environments indirectly impacting an individual, like parental workplace policies. The macrosystem encompasses broader cultural values and societal norms, while the chronosystem incorporates the temporal dimension, considering changes over time.
Tenets of Ecological Systems Theory
At the heart of the Ecological Systems Theory is the recognition that human development is shaped by dynamic interactions within and across various environmental contexts. It underscores the reciprocal relationships between individuals and their environments, highlighting the bidirectional influence of each system. The theory underscores the importance of considering the multiple layers of influence, acknowledging that developmental outcomes are the result of intricate interplays at various ecological levels.
Importance in Research
Ecological Systems Theory has been widely employed in developmental psychology, education, and social sciences to explore the multifaceted influences on individuals across the lifespan. Researchers using this framework examine how various ecological factors contribute to developmental trajectories, resilience, and well-being. The theory is particularly relevant in understanding the impact of diverse contexts on individuals from different cultural, socioeconomic, and demographic backgrounds. By considering the intricate web of influences, Ecological Systems Theory provides a nuanced understanding of human development that extends beyond individual attributes.
Research Process Implications
Researchers utilizing Ecological Systems Theory often employ mixed-method approaches to capture the complexity of the environments shaping individuals’ lives. They may conduct qualitative interviews, surveys, and observations to explore the dynamics within various systems. Longitudinal studies are valuable for tracking changes over time, aligning with the chronosystem concept. Ecological Systems Theory encourages interdisciplinary collaboration, fostering a comprehensive exploration of how different fields intersect to influence human development. The framework prompts researchers to recognize the interconnectedness of systems and to consider the implications of interventions or policies on various levels of the ecological hierarchy
Bioecological Model
The bioecological model is a subtype or a specialized aspect of the broader ecological systems theory. Often associated with the ecological systems theory but places a specific emphasis on the biological aspects of human development. The Bioecological Model, conceptualized by Urie Bronfenbrenner, stands as a prominent theoretical framework in the field of developmental psychology and human behaviour. At its core, this model articulates the significance of examining an individual’s development in the context of multiple, nested environmental systems. These systems collectively contribute to shaping an individual’s experiences, behaviour, and overall development. The Bioecological Model encompasses five key environmental systems, each representing a different level of influence, thereby facilitating a comprehensive understanding of human development.
Components of the Bioecological Model
The five environmental systems include the Microsystem, Mesosystem, Exosystem, Macrosystem, and Chronosystem. The Microsystem involves the immediate, direct interactions of an individual within their surroundings, such as family, school, and peers. The Mesosystem highlights the interconnections between different microsystems, providing insights into how relationships in one setting can impact another. The Exosystem extends the analysis to external settings that indirectly influence the individual, such as the workplace. The Macrosystem delves into the broader cultural and societal context, considering cultural values and norms. Lastly, the Chronosystem emphasizes the dimension of time, recognizing that development is influenced by historical events and evolving contexts.
Importance in Research
Researchers find the Bioecological Model invaluable due to its holistic approach to understanding human development. Its multilevel perspective allows for a nuanced analysis of the complex interplay between individual and environmental factors. By acknowledging the significance of different systems and their dynamic interactions, the model aids researchers in uncovering the intricacies of behavior within various contexts.
Advantages and Disadvantages
The Bioecological Model’s strengths lie in its comprehensive perspective and flexibility, accommodating diverse research areas. However, its complexity can pose challenges in operationalizing and determining causal relationships. While it identifies influential factors, it may not provide explicit guidance on causality, requiring researchers to navigate the intricate relationships within the model.
Research Process Implications
Researchers applying the Bioecological Model can conduct multidimensional analyses, exploring the impact of various environmental factors concurrently. Longitudinal research becomes essential, aligning with the Chronosystem, to capture the evolving nature of individuals and their environments over time. The model also informs intervention design, guiding researchers to consider and address multiple levels of influence for more effective outcomes. In essence, the Bioecological Model contributes significantly to the depth and breadth of research in understanding the complexities of human development and behavior
In summary, a conceptual framework is a vital tool that not only defines the key components of a study but also contributes to the coherence, organization, and logical development of the research. Its flexibility makes it a dynamic tool that researchers can tailor to their specific research contexts.
Research Methodology Chapter Two- Literature Review
Chapter 2, the literature review, is a critical component of a research thesis or dissertation. It serves to systematically review, analyze, and synthesize existing scholarly works relevant to the research topic. The chapter begins by defining the scope and context of the literature review, highlighting its purpose in establishing the foundation for the study. The review progresses to identifying key themes, theories, and concepts in the literature, addressing any existing debates or controversies. It also critically examines methodological approaches used in previous studies and evaluates their strengths and limitations. Throughout the chapter, the researcher showcases their understanding of the current state of knowledge on the topic and identifies gaps or unresolved issues that the present study aims to address. The literature review sets the stage for the research methodology, providing a rationale for the chosen approach and guiding the overall structure of the research. Click the Icon to go to Chapter Two.
A conceptual framework is a broader, more general structure that guides the overall understanding of a research problem. The conceptual framework guides the entire study. A research model, on the other hand, is a specific plan outlining the structure and components of a study, while a theory provides a systematic explanation for observed phenomena. A research model focuses on the specific methodology and design, and a theory provides a broader explanation for observed patterns.
Theories and models contribute to the research process in various ways:
The selection of a theory or model helps formulate research questions by providing a theoretical foundation.
The chosen framework influences the design of the study, including the selection of variables, data collection methods, and analysis techniques.
The theoretical framework guides the interpretation of study findings, allowing researchers to contextualize and understand observed patterns.
These theories inform the development of interventions and strategies by identifying key factors influencing behavior.
Theoretical frameworks often incorporate ethical considerations, ensuring that research respects the rights and well-being of participants.
The research design is the overarching plan or blueprint that outlines the systematic approach and structure of a research study. It serves as a methodological framework guiding the researcher in addressing research questions or hypotheses, collecting and analyzing data, and drawing valid conclusions. The design encompasses crucial elements such as the study’s population, sample size, sampling techniques, data collection methods, and data analysis procedures. Research designs also involve considering ethical considerations, potential biases, and limitations inherent in the chosen approach. It outlines the systematic steps taken to ensure the study’s internal validity, reliability, and overall methodological soundness.
A well-defined research design is essential for achieving the study’s objectives and contributes to the credibility of research findings. It helps researchers make informed decisions about the methods they employ, ensuring that the chosen approach aligns with the nature of the research problem. Different research designs, such as experimental, observational, correlational, or mixed-methods designs, offer varying strengths and weaknesses, allowing researchers to tailor their approach to the specific requirements of their study. Overall, the research design is the foundational structure that shapes the entire research process, providing clarity, coherence, and a systematic pathway for conducting a robust and rigorous investigation.
Types of Research Designs
Several types of research designs are commonly used in the field of research, each serving specific purposes and addressing distinct research questions. Listed above are just a few examples, and researchers may choose or combine designs based on their specific research questions, goals, and constraints. Research designs in health sciences help address questions related to disease prevention, treatment effectiveness, healthcare policies, and public health interventions. Health science research often employ a combination of these designs to gain a comprehensive understanding of complex health-related issues.
Research Methodology Chapter Three- Research Design and Methodology
Chapter 3 in a research dissertation is a critical section dedicated to the research methodology. It meticulously details the systematic approach employed in addressing research questions or hypotheses. This chapter outlines the research design, population, and sampling methods, shedding light on data collection techniques, research instruments, and data analysis methods. Ethical considerations, validity, reliability, and limitations are also thoroughly addressed. Serving as a roadmap, Chapter 3 ensures transparency and credibility in the chosen methods, acting as a foundational guide for the entire research project. It provides readers with a comprehensive understanding of the study's methodology, essential for interpreting and trusting the research findings. Click the Icon to go to Chapter three.
Research paradigms are overarching frameworks that guide researchers in understanding and approaching the nature of knowledge, inquiry, and the research process. There are several research paradigms, and they align with Chapter 3 (Methodology) by influencing the researcher’s worldview and choice of research methods. Here are some common research paradigms: (Click on each tab to review the content).
Positivism asserts an objective reality that can be studied using empirical observation and measurement. Common in quantitative research, positivism seeks to identify causal relationships and general laws.
Principle- Empirical observation and measurement lead to objective knowledge.
Interpretivism focuses on understanding subjective meanings and interpretations within social contexts. Predominant in qualitative research, interpretivism seeks to uncover the complexity of human experiences and behaviors.
Principle- Subjective meanings and interpretations are essential for understanding.
Pragmatism combines positivist and interpretivist elements, choosing methods based on practical utility. Pragmatism is flexible, adapting research approaches to the specific needs and goals of the study.
Principle- Practical utility guides methodological choices.
Critical Theory critiques and transforms social structures, aiming to address power imbalances and promote social justice. Common in social sciences, it explores issues of inequality, oppression, and societal transformation.
Principle- Critical examination of power structures and pursuit of social justice.
Constructivism recognizes multiple realities and the active role of individuals in constructing their understanding. Often seen in qualitative research, constructivism explores how individuals create meaning and knowledge.
Principle- Knowledge is actively constructed by individuals.
Research paradigms are typically discussed in the early stages of planning to inform the choice of research methods. Paradigms are elaborated in the methodology section, explaining the philosophical underpinnings. If the chosen research approach does not explicitly align with a particular paradigm, it may not need extensive discussion. In some cases, the paradigm may have minimal impact on the overall study design, making it less central to the discussion.
Research philosophies represent the fundamental beliefs about the nature of reality, knowledge, and the researcher’s role. They guide the choice of research methods and the overall research approach. Here are some common research philosophies: (Click on each tab to review the content).
Positivist Ontology
Positivism, as an ontological stance, assumes that there is an objective and independent reality that exists external to individuals. Reality is considered to be stable, measurable, and observable. Positivist researchers often seek to uncover universal laws and causal relationships through empirical observation and measurement.Constructivist Ontology
In contrast, constructivism posits that reality is subjective and socially constructed. Individuals actively create their understanding of reality based on their experiences, perceptions, and interactions. Constructivist researchers acknowledge multiple, context-dependent realities, recognizing the role of individuals in shaping their own perspectives.Strength and Weaknesses
Strengths of Positivist Ontology- Positivism emphasizes the objective study of an external reality, promoting objectivity and replicability.
- Positivist ontology aligns well with quantitative research methods, allowing for precise measurements and statistical analyses.
- Positivism aims to uncover general laws and principles, contributing to predictive power in certain contexts.
- Critics argue that positivism oversimplifies complex social phenomena by reducing them to quantifiable variables.
- Positivism may neglect the subjective and interpretive aspects of human experiences.
- The positivist emphasis on objectivity raises concerns about the researcher’s ability to remain value-neutral.
- Constructivism allows for a rich understanding of complex social phenomena, emphasizing context and subjectivity.
- Aligns well with qualitative research methods, providing insights into individuals’ perspectives and experiences.
- Acknowledges the dynamic and changing nature of reality, allowing for adaptability in research approaches.
- Critics argue that a strong emphasis on subjectivity may lead to relativism, making it challenging to establish shared understandings.
- Findings from constructivist studies may have limited generalizability due to the emphasis on context-specific understanding.
- Qualitative research associated with constructivism can be time-consuming and resource-intensive.
Positivist Epistemology
- Positivism asserts that knowledge is objective, observable, and can be discovered through empirical observation and measurement.
- Strengths- Positivism is associated with rigor and objectivity. It often employs quantitative methods, allowing for statistical analysis and generalizability.
- Weaknesses- Critics argue that positivism may oversimplify complex social phenomena by reducing them to measurable variables. It might neglect the subjective and context-dependent nature of certain aspects.
Constructivist Epistemology
- Constructivism holds that knowledge is subjective, context-dependent, and shaped by the social and cultural context of individuals.
- Strengths- Constructivism acknowledges the importance of context and the interpretive nature of human experiences. It is well-suited for studying complex and context-dependent phenomena.
- Weaknesses- Constructivist approaches may be criticized for lacking the same level of objectivity as positivism. Some argue that the emphasis on interpretation can introduce bias.
General Strengths and Weaknesses of Epistemological Perspectives
Strengths- Researchers can choose an epistemological stance that aligns with the nature of their research questions.
- Epistemological perspectives guide the selection of research methods, allowing for a diverse range of methodologies.
- The debate between subjective and objective knowledge remains a challenge, with no universally accepted resolution.
- Extremes in either direction (overemphasis on objectivity or subjectivity) may lead to potential blind spots in understanding certain phenomena.
Axiology, in the context of research philosophy, is concerned with the nature, types, and criteria of values. It explores questions related to the ethical and moral aspects of research, including the values that guide the researcher’s choices and the impact of these choices on the research process. Axiology encompasses both ethics (moral values) and aesthetics (aesthetic values). Researchers adopting an axiological stance are attentive to the ethical implications of their work, emphasizing transparency, integrity, and respect for participants. While there might be challenges associated with the subjective nature of values, addressing these challenges is seen as crucial for maintaining the ethical integrity of the research process.
Axiology posits that values, including ethical considerations and aesthetic judgments, are inherent in the research process. Researchers must acknowledge and navigate these values.
Strengths and Weaknesses
Strengths
- Axiology encourages researchers to explicitly address ethical considerations, ensuring the responsible conduct of research.
- Recognizing the role of values provides a more holistic perspective, acknowledging that research is not value-neutral.
Weaknesses
- Critics argue that axiology introduces subjectivity into the research process, potentially leading to biased interpretations.
- Different researchers may interpret values differently, making it challenging to establish a universally agreed-upon set of ethical guidelines.
Integration with Epistemology and Ontology
Epistemological Connection- Axiology is closely connected to epistemology, influencing how researchers interpret and understand knowledge.
Ontological Connection- It also intersects with ontology, as the values guiding research may relate to the researcher’s ontological assumptions about the nature of reality.
Scoping Review Methodology
A scoping review is a type of literature review that seeks to map the existing literature on a broad topic, identifying key concepts, theories, evidence sources, and research gaps. Scoping reviews aim to explore the breadth of literature on a broad subject, providing an overview of the available evidence without necessarily assessing the quality of individual studies. Scoping reviews are particularly useful when a research area is complex, diverse, or not well-defined, helping researchers identify the key themes and gaps in existing literature.
Qualitative, quantitative, and mixed methods are different research methodologies. These methodologies represent distinct approaches to conducting research, each with its unique set of principles, techniques, and philosophies. Philosophical orientations inform the design, data collection, and analysis strategies in each type of research, shaping the researchers’ perspectives and approaches to knowledge creation. Researchers select a specific methodology based on the nature of the research questions, the type of data required, and the research objectives.
Quantitative Research
Quantitative research is characterized by its reliance on numerical data, which is often collected through structured questionnaires, checklists, and measurement scales. The main objective of quantitative research is to explain, predict, or control phenomena. Analysis in quantitative research is typically statistical, and this approach often involves a limited number of variables studied within large sample sizes. Quantitative research is closely associated with deductive reasoning, where hypotheses are tested based on existing theories or concepts. This approach is highly structured and aims for precision, allowing researchers to draw specific conclusions about the relationships between variables.
Qualitative Research
Qualitative research emphasizes narrative data and seeks to describe phenomena in depth. Qualitative methods include open-ended interviews, document examination, and participant observation, where researchers immerse themselves in the environment to gather rich, context-specific data. The results of qualitative research are primarily used to describe phenomena and gain a deep understanding of complex social contexts. Qualitative research is inductive in nature, allowing theories to emerge from the data rather than testing predefined hypotheses. It often explores diverse perspectives, offering nuanced insights into human experiences, beliefs, and behaviors.
Mixed Method Research
A mixed methods approach combines both qualitative and quantitative methodologies, allowing researchers to capitalize on the strengths of both techniques. This approach acknowledges the complexity of research questions that may benefit from a holistic understanding. By integrating quantitative data for statistical analysis and qualitative data for in-depth exploration, researchers can provide a more comprehensive and nuanced perspective on the phenomena under investigation. The mixed methods approach offers a balanced and triangulated view, enriching the research findings and providing a deeper understanding of the research topic. Researchers employing this approach often use qualitative data to illuminate the context and quantitative data to establish patterns, providing a more holistic and robust interpretation of research outcomes.
The population in a research study constitutes the core group under investigation. Clarity in defining this group, encompassing factors like age, gender, location, socioeconomic status, and other relevant demographics, is imperative. For instance, the population could be as specific as “primary school teachers,” “children from middle-class families,” or even “10-year-old girls with diabetes.” This defined group serves as the foundation upon which research questions are built and findings are generalized. Provide as much details as possible.
Additionally, researchers need to be mindful of the accessible population, which refers to the subset of the population the researcher can feasibly reach. The sampling frame, acting as a guide for actual sample selection, must be comprehensive and representative. It ensures the study’s findings align with the intended population. Identifying this accessible population is vital, as it impacts the study’s feasibility, ethical considerations, and the practicality of data collection methods.
Determining the sample size is a critical aspect of research planning, directly impacting the study’s statistical power and reliability. Several factors influence this decision, including the desired confidence level, margin of error, and the variability inherent within the population. The supporting evidences, literature(s) or protocol guiding the sample size selection must be made clear. A larger sample size enhances the study’s reliability, ensuring that the findings can be generalized more confidently (Cohen, 1988). Careful consideration of these factors is essential for the study to yield meaningful and accurate results, reflecting the characteristics of the broader population from which the research questions emerge.
Sampling Techniques
At the heart of research lies the concept of sampling, a practice where insights are gleaned from a subset of the entire population with the aspiration that findings are universally applicable. This methodology, underscores the essence of extrapolating results from a fraction of the whole to the larger population. Various sampling techniques underpin this process, each offering distinct advantages.
Probability sampling
A sample is selected in such a way that each member of the population has a non-zero chance of being selected and the probability of being selected is known. When probability sampling is used, statistical procedure can be used to make inferences about the population.
Non-probability sampling
The probability of a member of the population being selected is unknown. Statistical inferences about the population cannot be made.
The sampling techniques also have impact on internal and external validity of the research. Lets us explore these further.
Each member of the sample is chosen at random; each member of the population has an equal chance of being selected for the sample. At its simplest, all the names of those in the population can be put in a container and the sample selected by drawing names one at a time. Selected names must be returned to the container before the next name is drawn. Alternatively, each member is assigned a number and a table of random numbers can be used to select.
Random sampling ensures every member of the population has an equal chance of being selected, promoting unbiased representation by ensuring equal chances for each member to be included. However, it requires a complete list of the population, which might not always be available, making it challenging to implement. Random sampling enhances both internal and external validity by minimizing biases and ensuring generalizability to the entire population.
The population is divided into subgroups (STRATA) of members who share some characteristic(s) and then members of each stratum are randomly selected. There is equal allocation; equal numbers from each strata are selected. Proportionate sampling or Proportional allocation; each group is represented in the sample in the same proportion as it exists in the population. Sampling fraction which is the ratio of sample size to population size (n/N) is considered.
Stratification into subgroups based on specific criteria, promotes comprehensive coverage of diverse characteristics. This ensures representation from specific subgroups of the population, making it useful when studying diverse groups. It requires accurate classification of the population into strata, which can be complex and time-consuming. This technique enhances internal validity by ensuring representation from various subgroups, improving the study’s accuracy. It also improves external validity by allowing for comparisons across different strata, increasing the study’s applicability to similar populations.
Population is arranged in some order, and every nth member selected. The stating point is randomly chosen. The starting point determines the sample (n = population size / sample size). Employs a systematic pattern for selection, providing an organized approach.
It provides a balance between randomness and simplicity, often easier to implement than simple random sampling. It has the disadvantage of being susceptible to periodic patterns in the population list, which might lead to biased samples if the pattern aligns with the sampling interval. There is moderate impacts on internal validity due to its systematic nature. External validity can be affected if the periodic patterns align with specific characteristics of the population, leading to limited generalizability.
Groups or clusters of members of the population are randomly selected. The exact size of the sample is not known until after the sample is selected. How many clusters? Decide on the sample size (e.g. 100 employees). Ascertain the mean size of the clusters (approximately 25 in each department). Divide the sample size by the mean size of the clusters to decide how many clusters to select (100/25 = 4 departments). Randomly select 4 clusters.
This is convenient when a complete list of the population is unavailable, as it involves sampling clusters (groups) rather than individual elements. It is good to note, this can lead to higher sampling error, especially if the clusters are not heterogeneous. This technique can impact internal validity if clusters are not well-designed, leading to biased results. External validity might be compromised if the clusters do not represent the population adequately.
Convenience Sampling
Members of the sample are selected based on their availability. It is easy and quick to implement, especially for preliminary or exploratory research. A disadvantage is that it is highly susceptible to selection bias, as it involves choosing the most readily available individuals or groups. Convenience sampling often compromises both internal and external validity. Internal validity is affected due to selection bias, while external validity is limited because the sample might not accurately represent the broader population.
Purposive Sampling
Members of the sample are selected based on their possession of specific characteristics that are critical to the research. They are information-rich. Purposive sampling is valuable when studying specific subgroups or rare phenomena, allowing researchers to gain in-depth insights. However, researchers must be cautious about potential biases and limitations, ensuring that the chosen participants adequately represent the intended characteristics or expertise. Some examples of purposive techniques include:
- Maximal Variation Sampling
- Extreme Case Sampling
- Typical Sampling
- Theory or Concept Sampling
- Homogenous Sampling
- Critical Sampling
Advantage of purposive sampling- it allows researchers to select specific individuals or groups deliberately, ensuring the inclusion of experts, key informants, or participants with unique characteristics. This method is useful for studies focusing on specific traits or experiences. A disadvantage is that it is prone to researcher bias, as the selection is based on the researcher’s judgment. This could lead to overlooking certain perspectives or characteristics, limiting the diversity of the sample. It might also be challenging to generalize findings to broader populations. Purposive sampling can impact both internal and external validity. Internal validity might be influenced if the chosen participants do not represent the diversity of opinions or experiences within the defined criteria. External validity could be limited as findings might not apply to the larger population due to the specific and selective nature of the sample.
Snowballing
The researcher identifies one member of the population with the desired characteristics. After this person is interviewed, he/she is used as an informant to identify other persons and so on. Often used when the persons of interest are not easily identified or prefer not to be identified. Snowball sampling is especially valuable in qualitative and exploratory research, where in-depth insights from specific social networks or communities are necessary.
Particularly useful for accessing hard-to-reach or hidden populations, where traditional methods might fail. It leverages social networks, allowing participants to refer others, providing access to unique groups. A disadvantage- prone to bias, as initial participants might refer others who share similar characteristics or opinions, leading to a lack of diversity in the sample. Additionally, the sample size can be challenging to control, making it difficult to calculate statistical measures accurately. Snowball sampling can impact both internal and external validity. Internal validity might be compromised due to the potential bias introduced by participants’ referrals. External validity could be affected if the initial participants do not accurately represent the target population, limiting the generalizability of the findings.
Quota Sampling
Representatives from various groups in the population are sought. The researchers has guidelines to help them identify members of the various categories, and a quota for each category. The researchers then use various ways and means of finding such persons, and continue until they have satisfied their quota. Example- visit offices, homes, stop passers-by, intercept shoppers in car parks, etc. Associated biases- certain members of the population are excluded and not represented in the sample, examples- homes with big dogs; offices with mean-looking security guards; unfriendly-looking shoppers.
Sampling Errors on Reliability and Validity
Non-Random Sampling Error (Sampling Bias)- This type of sampling error occurs when the sample selected is not representative of the population due to flaws in the sampling design. It can lead to a lack of external validity, as the findings may not generalize to the broader population. For example, if a researcher only samples participants from urban areas, the results may not be valid for rural populations.
Random Sampling Error– While random sampling is intended to minimize bias, there is still inherent variability in selecting one sample from many possible samples. This variability is known as random sampling error. Larger random sampling errors indicate a greater deviation between the sample and the population. To enhance reliability, researchers can increase the sample size, reducing the impact of random variation and improving the accuracy of the study’s outcomes.
Sampling errors, comprising non-random and random sampling errors, significantly impact the reliability and validity of research outcomes. Non-random sampling errors, leading to flaws that cannot be measured post-data collection. Identifying and rectifying these biases is crucial to prevent skewed results and enhance the external validity of the study. However, random sampling errors arise naturally due to variability in the selection process and can be estimated. While sampling biases hinder generalization, understanding and effectively managing random sampling errors ensure the validity and reliability of research outcomes.
Ensuring Reliability and Validity During Sampling
Internal validity refers to the degree to which an experiment or research study accurately measures what it intends to measure. It assesses the extent to which the observed effects or changes in the dependent variable can be confidently attributed to the manipulation of the independent variable, rather than to other factors. Internal validity is essential for drawing accurate cause-and-effect conclusions from experimental or research findings.
Matched Designs
Matched designs involve pairing participants based on specific characteristics deemed relevant to the study. This helps control for potential confounding variables, enhancing internal validity by creating comparable groups.
In a study examining the impact of a new teaching method on academic performance, participants could be matched based on prior academic achievement to ensure that the groups are equivalent in terms of baseline academic abilities.
Counterbalancing
Counterbalancing is a technique where the order of experimental conditions is randomly varied across participants. This helps control for order effects, such as learning or fatigue, contributing to internal validity by minimizing the influence of these confounding variables.
In a memory experiment, half of the participants might first study a list of words and then solve math problems, while the other half does the tasks in the reverse order. This ensures that any observed effects are not due to the order of tasks.
Pilot Testing
Pilot testing involves conducting a small-scale version of the study to identify and address potential issues before the main study. It helps refine procedures, identify ambiguities, and enhance the internal validity of the final study.
Before implementing a large-scale survey on a new psychological measure, researchers might conduct a pilot study with a small group to identify unclear questions or potential response biases, ensuring the reliability and validity of the instrument.
External validity refers to the extent to which the results of a study can be generalized beyond the specific conditions, participants, and settings used in the research. It assesses the degree to which the findings can be applied to or have relevance for populations, situations, or contexts other than those directly examined in the study. Population Validity considers the extent to which the study’s results can be generalized to other populations. Ecological Validity assesses the generalizability of the study’s results to different settings or environments.
Ecological Validity
Ecological validity refers to the extent to which study conditions and settings resemble real-world situations. It ensures that the findings can be generalized to and have relevance for everyday, natural contexts.
In a psychological study on the effects of workplace stress, researchers might design the experiment to closely mimic the actual conditions of a typical office environment. This approach enhances the ecological validity of the study by reflecting the complexities and dynamics of real workplace situations.
Population Validity
Population validity, also known as external validity, involves using diverse samples that represent the broader population. This improves the generalizability of study results beyond the specific sample used in the study.
If a study aims to investigate the effectiveness of a new educational intervention, researchers might ensure diversity in the sample by including participants from various socio-economic backgrounds, ethnicities, and geographical locations. This enhances the population validity of the study, allowing for broader generalization of findings.
Replication
Replication involves conducting the study multiple times in different settings or with different populations. This contributes to external validity by assessing the consistency and robustness of the observed effects.
A psychological experiment on memory retention might be replicated in various locations, such as different universities or cultural contexts. If similar results are consistently obtained across replications, it strengthens the external validity of the study, suggesting that the findings are applicable beyond the specific conditions of the original experiment.
Test-Retest Reliability
Test-retest reliability involves administering the same test to the same participants on different occasions to assess the stability and consistency of measurements over time. It is commonly used in quantitative studies to ensure that measurements yield consistent results.
In a psychological study measuring anxiety levels, participants may take the anxiety assessment, and the same test is readministered to them after a certain period. If the scores are highly consistent between the two administrations, it indicates good test-retest reliability.
Inter-Rater Reliability
Inter-rater reliability assesses the consistency of judgments or assessments made by different raters or observers. In situations involving subjective judgments, having multiple raters independently assess the same data enhances the reliability of the study.
In a qualitative study using interviews, different researchers might independently analyze and code the interview transcripts. If their interpretations and coding decisions align closely, it demonstrates high inter-rater reliability.
Standardized Procedures in Qualitative Research
Ensuring standardized procedures in qualitative research involves maintaining consistency and reliability in data collection and analysis. Methods of verification, such as trustworthiness, authenticity, and dependability, contribute to the rigor of qualitative studies.
In an ethnographic study, multiple methods of verification may be employed, including extended periods of observation, triangulation through various data sources, peer review and debriefing, analysis of negative cases, clarification of researcher bias, member checking with participants, and providing rich, thick descriptions of the studied phenomena. These strategies enhance the reliability and validity of qualitative research.
Internal Validity
Random allocation of participants into experimental and control groups helps control for potential confounding variables. It ensures that, on average, both groups are similar at the beginning of the study, making it easier to attribute any differences in outcomes to the intervention. By eliminating or minimizing the influence of extraneous variables, randomization strengthens internal validity. It enhances the researcher’s confidence that the observed effects are due to the intervention rather than other factors.
External Validity
Randomization increases the likelihood that the study results can be generalized beyond the sample to the larger population. When participants are randomly selected, the study sample is more likely to be representative of the larger population. This enhances the external validity of the study, allowing researchers to generalize their findings to a broader context.
Randomization plays a crucial role in enhancing the validity of research studies. It positively impacts construct validity by ensuring accurate measurement of intended concepts, aligning operationalization closely with theoretical definitions. In terms of content validity, while randomization itself does not directly affect it, a well-designed study considering appropriate interventions and control groups contributes to content validity by representing the entire content domain accurately. Randomization also enhances internal validity by controlling for confounding variables, ensuring unbiased group assignments and strengthening the overall validity of research studies.
In intervention studies, control groups are crucial for determining the true effects of an experimental intervention. In essence, controls are essential to ensure valid and reliable results. There are different types of controls, each with specific characteristics and impacts on study validity.
Placebo Control
Placebo controls involve administering a placebo, which is an inactive substance that has no therapeutic effect, to the control group. Participants in the placebo group believe they are receiving the active intervention, allowing researchers to assess the psychological and physiological effects of the belief in treatment without the actual intervention. Placebo controls are essential for determining the specific effects of the experimental intervention beyond the placebo effect, which is the improvement observed due to the participant’s belief in the treatment.
Example- In a clinical trial testing a new antidepressant medication (experimental group), the placebo control group receives identical-looking placebo pills. By comparing the outcomes between the experimental group and the placebo group, researchers can assess the antidepressant’s efficacy beyond the placebo effect.
Active Control
Active control refers to a control group in which participants receive an existing, established intervention or treatment rather than a placebo or no treatment. This type of control helps compare the new intervention’s effectiveness against an already proven standard. Active controls enhance internal validity by reducing the risk of placebo effects and ensuring that observed effects are more likely due to the new intervention.
Example- In a study comparing a new pain relief medication (experimental group) to an established pain reliever (active control group), participants in the active control group receive a widely used pain medication like ibuprofen.
Passive Control
Passive control refers to a control group that does not receive any intervention, placebo, or active treatment. Passive controls are essential for determining the baseline or natural progression of the condition under study. While they are cost-effective and straightforward to implement, they may raise ethical concerns, especially if there is an effective known treatment available.
Example- In a study evaluating the effectiveness of a mindfulness-based stress reduction program (experimental group) for anxiety, the passive control group consists of participants who receive no specific intervention, allowing researchers to assess the natural course of anxiety symptoms.
Self-Control
Self-control, also known as within-subject control, involves using the same participants as both the experimental and control groups at different times or conditions. Each participant serves as their own control, which can reduce inter-individual variability. Self-control designs are commonly used in crossover trials.
Example- In a study examining the impact of a dietary supplement on cognitive function, participants receive the supplement for a specific period (experimental condition) and then a placebo for another period (control condition). By comparing the participants’ performance within themselves, researchers can assess the supplement’s effects while accounting for individual differences.
Blinding, also known as masking, is a method used in research to prevent bias by ensuring that participants, researchers, or both are unaware of the treatment assignments in a study. Blinding helps maintain the integrity and validity of the study by reducing the potential influence of biases on the outcomes. There are different levels of blinding in research:
Single-Blinded
In a single-blinded study, either the participants or the researchers are unaware of the treatment assignments. For example, in a single-blinded clinical trial, participants do not know whether they are receiving the experimental treatment or a placebo. The researchers, however, are aware of the assignments. Single-blinded studies reduce participant bias but can still be influenced by researcher bias.
Double-Blinded
In a double-blinded study, both the participants and the researchers involved in the study are unaware of the treatment assignments. The actual treatments (experimental and control) are concealed, and neither the participants nor the researchers know who is receiving which treatment. Double-blinded studies minimize both participant and researcher biases, enhancing the study’s validity and reliability.
Triple-Blinded
Triple-blinded studies extend blinding to include not only participants and researchers but also individuals involved in data analysis and interpretation. This means that the statisticians or data analysts are unaware of the treatment assignments while analyzing the study results. Triple-blinded studies provide an additional layer of protection against bias, ensuring that the data analysis remains objective and unbiased.
Internal Validity– Blinding, especially double-blinding and triple-blinding, enhances internal validity by minimizing biases. Participants are less likely to modify their behavior or responses based on their knowledge of the treatment, and researchers are less likely to unintentionally influence the outcomes or interpret results in a biased manner.
External Validity– Blinding does not directly impact external validity, which refers to the generalizability of the study results to broader populations or real-world settings. However, by improving internal validity and minimizing biases, blinding indirectly contributes to the trustworthiness of the study findings, increasing the likelihood that the results can be applied to diverse populations.
An instrument refers to a tool or device used to collect data or measure variables in a systematic and standardized way. Instruments can take various forms depending on the nature of the research and the type of data being collected. Examples of research instruments include surveys, questionnaires, interviews, tests, scales, checklists, and observational protocols. The primary purpose of an instrument is to ensure that data collection is consistent, reliable, and valid. Researchers carefully design and validate instruments to gather accurate and meaningful information that can be analyzed to address research questions or test hypotheses. The characteristics and features of an instrument depend on the specific requirements of the study and the type of data needed for analysis.
The researcher must comprehensively outline all data collection methods employed in the study. These methods may include questionnaires, interviews, observations, video and audio recordings, cameras, and field notes. Each method warrants a detailed description, encompassing aspects such as the number of items, what they measure, and other relevant details. A list of research designs and applicable data collection instrument are presented below:
Instrumentation, such as apparatus or tests, should also be meticulously described, elucidating their purpose and functionality. In quantitative research, a table summarizing each research question and its corresponding data collection method(s) can enhance clarity and organization. Additionally, a well-constructed timeline is essential for depicting the research development period, outlining various activities and their tentative dates. Presented in table format, the timeline serves as a visual guide to the progression of the study.
Furthermore, the researcher is obligated to furnish a comprehensive description of the procedural steps involved in data collection. This entails elucidating the methodology for experiments, the administration process for questionnaires, the conduct of interviews, the protocol for observations, and other pertinent details. Clarity in these descriptions is crucial for ensuring the rigor and replicability of the study.
Pilot Testing
Your research instrument may be new or was modified from a previous study; to ensure reliability of the instrument, it must be pilot tested. Pilot testing, also known as a pilot study or feasibility study, involves conducting a small-scale trial or test of a research project before the main study is implemented. This trial run allows researchers to identify and address potential issues, refine methodologies, and assess the practicality of the research design.
Purpose of Pilot Testing
The primary purpose of pilot testing is to uncover and rectify any flaws or challenges in the research plan before committing to a full-scale study. It helps researchers evaluate the feasibility of their methods, assess the clarity of instructions, refine data collection tools, and identify any unexpected issues that may arise during the actual study. Pilot testing contributes to the overall improvement of the research design and enhances the reliability and validity of the study. Pilot testing is recommended in various scenarios:
- When implementing a new research design or methodology.
- Before using specific instruments or tools for data collection.
- When testing a novel intervention or treatment.
- In situations where the research involves complex procedures.
- Before conducting a large-scale study to ensure efficiency.
Research Instrument and Levels of Measurement
The analysis of data hinges on the meticulous design of items within the research instrument. A profound understanding of the various levels of measurement and the corresponding statistical operations applicable to these measurements is imperative. This understanding is integral for ensuring the validity of the conclusions drawn from the study results.
Measurement is intricately linked to operationalization, which involves defining and translating abstract concepts into observable and measurable terms. Operationalization serves as the bridge connecting the conceptual or theoretical realm with the empirical or observational level. More precisely, measurement is a systematic procedure wherein a researcher assigns numerical values to empirical properties, enabling the transformation of abstract ideas into quantifiable data.
- Numerals are symbolic representations without inherent quantitative meaning. They serve as labels or identifiers for phenomena, objects, or entities. For instance, using numerals like 1, 2, 3 or Roman numerals I, II, III can help categorize and distinguish elements.
- When numerals are endowed with quantitative meaning, they transform into numbers. This quantitative aspect empowers researchers to leverage mathematical and statistical techniques for purposes such as description, explanation, and prediction.
- Assignments involve mapping numerals onto specific events, properties, or entities. It is the act of associating numerical values with observable characteristics.
Rules are the guiding principles or procedures that dictate how a researcher assigns numerals or numbers to objects or events. These rules are pivotal as they determine the quality of measurement. The careful formulation and application of rules ensure that the assigned numbers accurately and meaningfully represent the reality they intend to measure. It is through these rules that numbers gain significance and contribute to rigorous and meaningful analyses. Let us explore the types of items that may be incorporated into a questionnaire and the levels of measurement that can be applied to these items during the coding and subsequent analysis
Ethics in research encompasses a broad spectrum of principles and considerations aimed at protecting the welfare, rights, and dignity of individuals and communities involved in the research process. This multidimensional framework includes aspects such as respect for autonomy, beneficence, non-maleficence, justice, honesty, integrity, and accountability. Clarifying the dimensions relevant to the research being conducted is essential as it ensures that ethical principles are appropriately applied to address the specific challenges, risks, and impacts inherent in the research context. By identifying direct, indirect, or potential ethical dimensions, researchers can anticipate and mitigate ethical dilemmas, conflicts of interest, power imbalances, and unintended consequences that may arise during the course of the study. Moreover, articulating these dimensions promotes transparency, accountability, and ethical reflexivity, fostering trust among stakeholders and enhancing the credibility and validity of the research outcomes. Thus, a comprehensive understanding of the ethical dimensions relevant to the research is foundational for conducting ethical research and promoting the well-being of all involved parties. Ethics in Research were discussed here.
Ethics and the Role of the Institution
Institutional entities, such as universities, research organizations, and ethics review boards, play a pivotal role in ensuring ethical practices in research. These institutions often establish guidelines, policies, and procedures to govern the conduct of research involving human subjects, animal subjects, or sensitive data. Ethics review boards, commonly known as Institutional Review Boards (IRBs) or Research Ethics Committees (RECs), evaluate research proposals to assess the ethical implications and ensure compliance with ethical standards and regulations. They provide oversight to safeguard the welfare and rights of research participants, ensuring that studies are conducted with integrity, respect, and fairness. Additionally, institutions may offer training programs, workshops, and resources to educate researchers about ethical principles and best practices, fostering a culture of ethical conduct within the research community.
Ethics and the Research Team
The composition and dynamics of the research team can significantly influence the research process and outcomes due to the diverse axiological perspectives of team members. Axiology refers to the philosophical study of values, including ethical, moral, and epistemological beliefs, which shape researchers’ perceptions, attitudes, and decision-making processes. Research teams often comprise individuals with varying backgrounds, disciplines, cultural norms, and personal values, leading to a multiplicity of perspectives on research objectives, methodologies, and interpretations of findings. These diverse perspectives can enrich the research process by encouraging critical dialogue, challenging assumptions, and fostering innovative approaches. However, they can also introduce biases, conflicts, and ethical dilemmas that require careful navigation and resolution. Effective communication, mutual respect, and a shared commitment to ethical conduct are essential for research teams to navigate axiological differences constructively and uphold the integrity and validity of the research endeavor.
Ethical Dilemma in Research
An ethical dilemma in research refers to a situation where researchers encounter conflicting moral principles or values that make it challenging to determine the most appropriate course of action. These dilemmas often arise when researchers must navigate competing interests, responsibilities, or obligations while conducting their studies. Ethical dilemmas in research can involve complex considerations related to participant autonomy, beneficence, justice, privacy, confidentiality, and integrity.
Examples of ethical dilemmas in research include issues related to informed consent, privacy and confidentiality, conflicts of interest, research misconduct, data management and sharing, and the equitable treatment of research participants. Resolving ethical dilemmas requires careful consideration of ethical principles, consultation with relevant stakeholders, adherence to ethical guidelines and regulations, and a commitment to upholding the rights and welfare of research participants while maintaining the integrity and credibility of the research.
In circumventing ethical dilemmas these strategies, can effectively identify, address, and mitigate ethical issues in research endeavours, thereby upholding ethical standards and promoting the integrity and credibility of the research process.
Summary
Research, marked by a systematic approach, originates from a pivotal question or problem, propelling the investigation forward.
It necessitates a well-defined goal, providing a clear direction for inquiry, guided by a conceptual framework, research philosophies, and pertinent theories and models that shape the design and implementation.
The research process demands a strategic plan, often involving breaking down the primary problem into manageable sub-problems for a structured analysis.
Aligned with the specific research problem, question, or hypothesis, research operates on critical assumptions foundational to the chosen methodology.
At its core, the research process follows a cyclical or helical nature, involving continuous iterations, from problem formulation to data collection and interpretation. In essence, research embodies a dynamic and evolving journey, purposefully and iteratively exploring to resolve the identified problem.
References
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doi:10.1093/ije/dys049
Published: 2024-1-15, Last Updated: 2024-3-25