Introduction to Research Levels

Opening Remarks

• José Supo introduces the seminar on research levels, welcoming participants and mentioning the presence of Héctor Zacarías from the Hispanic Society of Scientific Researchers.

• Héctor expresses his happiness to discuss the topic and notes that they usually meet on Saturdays but have rescheduled due to a contingency.

Seminar Logistics

• The seminars are typically held on Saturdays at 6 PM (Bogotá/Lima time), with adjustments made as necessary.

• Participants are encouraged to confirm their attendance by commenting in the chat, indicating their location for audio verification.

Engagement with Participants

Participant Interaction

• Acknowledgment of participants like Gabriel Ortega and Carolina Rendón who greet the hosts.

• Various attendees introduce themselves from different locations, including Puebla, Guatemala, El Salvador, and Argentina.

Understanding Research Levels

Importance of Research Taxonomy

• The discussion emphasizes that understanding research taxonomy is crucial for developing effective methodological strategies.

• The foundational knowledge of research levels is essential for constructing viable research ideas.

Structure of Research Levels

• José suggests starting the seminar while continuing to acknowledge new participants throughout.

• There will be a Q&A session where previously prepared questions will be addressed alongside live queries from attendees.

Exploring Different Levels of Research

Framework for Understanding

• The seminar will focus on six proposed levels of research, although some authors suggest fewer levels (four or five).

• Emphasis is placed on understanding differences between these levels rather than debating their exact number.

Qualitative vs. Quantitative Approaches

• Discussion begins about Dr. Dan Dan's classification from 1986 regarding four levels of research; however, there’s an acknowledgment that various frameworks exist.

• Héctor illustrates the concept using a pyramid structure representing different research stages or moments in investigation.

Research Methodology Insights

Basic Division in Research

• The most fundamental division in scientific inquiry is into qualitative and quantitative approaches.

• This distinction highlights two phases: one without statistical tools (qualitative), followed by one requiring mathematical methods (quantitative).

Flexibility in Classification

Research Strategies and Taxonomy

Types of Research

• The best strategies for conducting studies involve dividing them into two main types: prospective and retrospective. This division is akin to the two sides of a coin.

• There are studies where researchers collect their own data, and others that utilize existing data from measurements in which they did not participate. This highlights the importance of understanding different research methodologies.

Hierarchical Structure of Research

• When discussing levels of research, there exists a hierarchical structure where qualitative research precedes quantitative research. Understanding this hierarchy is crucial for structuring effective studies.

• Within quantitative research, it can be further divided into descriptive and analytical studies, with analytical studies being those that do not yield definitive results but rather explore relationships among variables.

Importance of Precedent Studies

• The concept of "economy of research" emphasizes using previous researchers' experiences to inform new strategies. For instance, if one study uses data from a medical campaign registry, another study can leverage similar methodologies based on shared characteristics in their data collection processes.

• Identifying common conditions between studies allows researchers to use prior work as a precedent effectively; the more shared characteristics there are, the stronger the precedent becomes for future investigations.

Levels of Research Taxonomy

• There are six proposed levels within this taxonomy; however, depending on perspective (qualitative vs quantitative), one might argue there are only two primary levels. The classification system helps clarify how various types of research relate to each other and their respective methodologies.

• While some authors have identified four distinct levels in their frameworks, it's essential to recognize that these classifications may vary across different publications and contexts within scientific literature. Each level serves a unique purpose in guiding researchers through their inquiries.

Specific Levels Explained

• The predictive level is often less studied compared to others like applied or pure research as defined by Mario Bunge's framework; it appears in specific Venezuelan government methodology texts but remains underexplored overall.

Understanding Research Levels and Variables

The Importance of Research Levels

• The discussion begins with the significance of understanding how we learn, emphasizing that researchers often focus on specific areas within educational research, leading to a concentration in their studies.

• It is noted that while some researchers conduct explanatory studies, others like sociologists engage in exploratory research, highlighting the diversity in pedagogical approaches.

• The speaker mentions the existence of six levels of research, contrasting different authors' classifications which range from four to six levels.

• A request is made for clarification on terminology regarding categorical (qualitative) and numerical (quantitative) variables to avoid confusion among students and researchers alike.

• The distinction between categorical and numerical variables is crucial; categorical variables represent categories while numerical variables are defined by numbers with units.

Clarifying Variable Types

• Categorical variables include values such as gender or marital status, whereas numerical variables are identified by measurable quantities like weight or temperature.

• There’s a common misconception where categorical variables are labeled as qualitative and numerical ones as quantitative; this can lead to misunderstandings in research contexts.

• It's important to differentiate between types of research (qualitative vs. quantitative studies) and types of variables (categorical vs. numerical), as conflating these terms can cause significant errors in academic settings.

• An anecdote illustrates the potential pitfalls when educators mislabel their studies based on variable types, stressing the importance of accurate terminology in teaching environments.

Understanding Research Hierarchies

• The conversation shifts towards the hierarchy of research levels; no level is inherently superior—each serves its purpose within a broader investigative framework.

• Each level—from exploratory to predictive—is essential for comprehensive understanding; neglecting foundational levels undermines higher-level investigations.

• The speaker compares research levels to segments of a journey: each segment must be traversed sequentially for effective exploration and understanding of phenomena.

Conclusion on Research Methodology

Exploratory and Descriptive Research in Diabetes

Understanding the Levels of Research

• The discussion begins with the importance of quantifying how diabetes affects the population, emphasizing that while diabetes is already discovered, new studies can quantify its impact.

• It is suggested that researchers should not repeat previous studies but rather build upon them. If prior exploratory studies exist, one can conduct descriptive or applied research based on those findings.

• The speaker explains that different levels of research (exploratory, descriptive, applied) are not inherently better than others; they represent stages in a research journey towards understanding and solving health issues.

• A pyramid metaphor is introduced to illustrate the progression from exploratory studies to applied interventions aimed at improving public health conditions.

• The abundance of descriptive studies on diabetes is highlighted, noting various demographics studied (children, pregnant women, obese patients), which contribute to a comprehensive understanding of the disease.

Advancing Research Towards Solutions

• Few studies focus on treatment efficiency; however, there’s an ongoing quest for definitive solutions to diabetes management as represented by the apex of the pyramid metaphor.

• Each level of research contributes to a chain-like structure where each study builds upon previous knowledge leading towards potential solutions for health problems like diabetes.

• A question arises regarding whether relational-level studies qualify as basic research. The response affirms this classification aligns with Mario Bunge's taxonomy in epistemology.

Purpose and Application of Research

• Mario Bunge's perspective emphasizes that research aims to produce knowledge beneficial for society; studying diseases like diabetes must ultimately aim at reducing mortality rates associated with these conditions.

• The necessity for research focused on practical applications is stressed—studies should aim to improve patient outcomes rather than merely accumulating knowledge without purpose.

• Applied research seeks improvements in living conditions related to specific health issues such as chronic complications from diabetes or traffic accidents.

Foundations of Applied Research

• To effectively apply findings from basic research into practice requires foundational theoretical support; thus, pure/basic research precedes applied efforts in healthcare contexts.

• Basic or pure research serves as a preliminary phase where concepts are defined before moving onto quantitative assessments like prevalence rates in diseases such as diabetes.

• If sufficient background exists from earlier basic studies, researchers may directly engage in applied investigations without needing further foundational work.

Cognitive Purpose in Research

• Relational-level studies are confirmed as basic due to their goal being knowledge acquisition. This aligns with historical concepts referring to cognitive purposes behind scientific inquiry.

Understanding Applied vs. Basic Research

The Nature of Research

• The discussion begins with a distinction between pure (basic) research and applied research, referencing Mario Dulce's classification.

• Applied research is not primarily about knowledge acquisition; its main goal is to improve human conditions and environments.

• A critical question arises in thesis defense: "What problem does your study solve?" This highlights the expectation for applied research to address real-world issues.

Personal Anecdote on Research Focus

• The speaker shares their passion for numbers and statistics from an early age, leading to a focus on epidemiology and public health during their studies.

• A professor challenges the speaker by asking what problem they aim to resolve with their thesis, emphasizing the need for practical outcomes in research.

Clarifying Research Objectives

• The speaker reflects on their initial misunderstanding; their prevalence study was merely quantifying data rather than solving a specific problem.

• Examples are provided where applied research directly addresses problems, such as vaccination campaigns reducing disease prevalence or surgeries resolving medical issues.

The Importance of Problem-Solving in Research

Defining Applied Research

• Any field can engage in applied research if it aims to solve problems; this includes engineering solutions like bridge construction or algorithm development for faster internet searches.

• Historical context is given regarding the evolution of search engines, illustrating how technological advancements stem from applied research addressing user needs.

Lines of Investigation

• The concept of a line of investigation is introduced as a sequence of studies that collectively aim to solve problems or improve conditions over time.

• Each study within a line contributes to building knowledge that ultimately leads to practical solutions, reinforcing the importance of structured inquiry.

Research Levels: Relational vs. Explanatory

Distinguishing Between Study Types

• A question arises regarding the difference between relational and explanatory levels in research, suggesting that many authors conflate these terms without clear distinctions.

• The speaker recalls past literature that grouped relational studies together but later differentiated them based on dependency relationships among variables.

Understanding Variable Relationships

Understanding Causality and Correlation in Research

Levels of Relationship Between Variables

• The discussion begins with the distinction between categorical and numerical variables, emphasizing that relationships can be established probabilistically rather than causally. For instance, obesity and diabetes often occur together but do not imply one causes the other.

• It is clarified that explanatory studies aim to demonstrate causal relationships, while relational studies focus on associations without establishing causation.

• A key point made is that for a causal relationship to exist, there must first be a demonstrated correlation between the two variables being studied.

Criteria for Establishing Causality

• The speaker introduces temporal criteria as essential for establishing causality; an example given is smoking leading to lung cancer, where smoking precedes the disease.

• This temporal relationship serves as a criterion for causality in explanatory studies, contrasting with relational studies which only seek to establish probabilistic connections.

• Various scenarios are presented regarding the relationship between two variables:

• Variable A causing Variable B

• Variable B causing Variable A

• Both being influenced by a third variable (C)

• No causal link despite correlation (spurious relationship).

Statistical Analysis in Research

• In explanatory research, statistical analysis aims to rule out spurious relationships before confirming any causal links. This involves multivariate analysis unlike relational studies which typically use bivariate analysis.

• Case-control studies are mentioned as examples where researchers identify correlations but must be cautious not to infer direct causation from these findings.

Differentiating Research Levels

• The speaker notes differences between relational and explanatory levels of research. Some authors combine these levels into new taxonomies but emphasize clear differentiation remains crucial.

• There’s mention of Bradford Hill's criteria for causality being primarily applicable in health contexts but raises questions about their relevance in other fields like education.

Application of Causality Criteria Across Fields

• The speaker confirms that Bradford Hill's criteria can indeed apply across various disciplines beyond health, suggesting broader applicability of these principles.

• Key criteria discussed include:

• Statistical association

• Dose-response relationship

• Temporal precedence

• Argumentative reasoning supporting hypotheses

• Specificity of cause through experimental manipulation.

Understanding Research Mechanisms and Exploratory Levels

General Concepts of Damage Mechanisms

• The discussion begins with the broad term "mechanisms of action," which encompasses various damage mechanisms. An update on this topic is expected to be published soon, highlighting ongoing research efforts.

Scientific Evidence and Deduction

• The speaker emphasizes the importance of scientific evidence, noting that once a concept is established, deductions can be made for specific cases based on general conclusions. This approach is often absent in biological contexts.

Qualitative Research Exploration

• A question arises regarding investigational purposes at an exploratory level. The speaker notes that exploratory research is the least systematized methodologically and serves as the foundation for new lines of inquiry.

Defining Research Intentions

• The speaker explains that a purpose in research reflects an intention expressed through intentional actions or objectives. In exploratory research, intentions are crucial for framing studies.

Historical Context in Qualitative Research

• The conversation shifts to historical perspectives, illustrating how qualitative research seeks to understand phenomena from their origins—such as cancer or traffic accidents—before they were formally recognized.

Identifying Phenomena

• To conduct qualitative research effectively, one must first identify and become aware of phenomena (e.g., bullying). Recognition precedes study; without it, issues may persist unaddressed.

Importance of Definition in Research

• Defining concepts is essential before studying them. An anecdote about defining "ghost" illustrates how vague definitions hinder scientific inquiry. Clear definitions enable focused discussions and investigations.

Interpretation and Rule Establishment

• After identifying phenomena like bullying or auroras, researchers should interpret why these occur and establish rules or criteria for diagnosis (e.g., diabetes), ensuring replicability in science.

Understanding Exploratory vs. Descriptive Research

Transition from Descriptive to Exploratory Research

• The discussion highlights the shift of certain research objectives from a descriptive level to an exploratory one, emphasizing the need for deeper analysis beyond mere description.

• An example is provided regarding diagnosing conditions like anorexia nervosa, illustrating how specific measurements (like temperature) can be taken as part of a diagnostic process.

• The speaker clarifies that "determining" relates to a single unit of study, contrasting it with descriptive studies that require multiple units for comprehensive analysis.

• Determining individual conditions (e.g., depression or weight) is emphasized as exploratory, while describing characteristics of groups (e.g., post-cholecystectomy patients) falls under descriptive research.

• The distinction between determining prevalence in populations versus individuals is made clear; prevalence pertains to broader groups rather than singular cases.

Clarifying Misconceptions in Research Terminology

• A common confusion arises when researchers use terms like "determine" inappropriately within descriptive contexts, leading to misinterpretation of study types.

• The speaker suggests replacing "determine" with "calculate" when discussing population-level studies to avoid ambiguity and clarify the nature of the research being conducted.

Objectives in Descriptive Research

• A question arises about whether there are more objectives within descriptive research beyond those previously mentioned; this opens up a discussion on potential additional goals in such studies.

• The speaker acknowledges that their presentation has focused primarily on health and social sciences but notes that other fields may have different terminologies and objectives.

Key Terms and Their Applications

• Common terms used in health and social science research include "describe," "estimate," and "verify," which serve distinct purposes within various studies.

• Examples illustrate how these terms apply: describing characteristics of individuals without gallbladders or estimating prevalence rates among populations.

Role of Methodologists in Research Design

• Methodologists play a crucial role in defining research objectives and guiding students through thesis seminars and methodology courses, ensuring clarity in terminology usage.

• There’s an acknowledgment that educational resources evolve over time; past literature suggested using infinitive verbs for objectives but may not encompass current best practices.

Importance of Learning Portfolios

• The necessity for developing descriptive parts within relational results is discussed, indicating its relevance across various levels of research design.

Understanding Statistical Estimation and Research Variables

Importance of Descriptive Statistics

• To make accurate estimations, one must first obtain absolute and relative frequencies along with measures of central tendency and dispersion based on the type of variable.

• Estimation requires description; verification necessitates both estimation and description to understand the phenomenon being studied.

Relationship Between Objectives and Data

• All objectives developed in research should complement results from lower hierarchical levels.

• For example, when investigating smoking as a risk factor for lung cancer, prior knowledge about the prevalence of both smoking habits and lung cancer is essential.

Defining Key Concepts

• Clear definitions are crucial in research; understanding what constitutes "lung cancer" or "smoking habits" supports the validity of presented results.

• Results should be relationally analyzed while being supported by descriptive data and well-defined concepts.

Exploring Independent and Dependent Variables

Clarifying Research Lines

• In explanatory research, independent variables typically influence a dependent variable, which is often singular but can sometimes include multiple factors.

• The dependent variable represents the outcome being studied—in this case, osteoporosis.

Transforming Research Lines into Variables

• A line of investigation can also serve as a variable. For instance, studying osteoporosis among postmenopausal women involves identifying those with and without the condition.

• The transformation from a line of inquiry (e.g., academic performance in medical students) to an analytical variable (e.g., low academic performance due to specific risk factors).

The Role of Theoretical Framework in Research

Conceptualizing Theoretical Framework

• The theoretical framework varies according to research levels but should not be viewed as external; it serves as an internal guide for structuring research projects or theses.

• A conceptual framework acts like a map that helps researchers navigate their study's context—essential for clarity in presenting findings.

Example Application

Understanding Theoretical Frameworks in Research

Importance of Defining Prevalence

• The theoretical framework must focus on the concept of prevalence, which is essential for understanding research studies. It is crucial to explain what prevalence means, especially for first-year students who may not be familiar with the term.

• There is a common confusion between prevalence and incidence; thus, it’s important to define these terms clearly before delving into the study of osteoporosis.

Osteoporosis and Its Context

• A clear definition of osteoporosis should be provided, particularly in relation to postmenopausal women. Understanding menopause is vital as it influences the prevalence rates among this demographic compared to the general population.

• This study is descriptive because there is a suspicion that the prevalence of osteoporosis differs from that in the general population. This context forms part of the theoretical framework.

Conceptual Framework Development

• When conducting relational studies on osteoporosis, additional variables must be included and developed within the conceptual framework.

• The theoretical framework serves as a foundational support for understanding results; it should clarify concepts so that interested parties can comprehend both results and underlying theories.

Distinction Between Theory and Opinion

• The theoretical framework should not merely reflect personal opinions or new essays but rather provide established theories relevant to the study at hand.

• In qualitative studies, interpretations are valid; however, they differ from quantitative studies where results are paramount without personal bias influencing conclusions.

Role of Results in Research Interpretation

• If findings indicate an increased prevalence, researchers can then interpret why this might be happening based on their results—this leads to new hypotheses for future studies.

• The essence of a theoretical framework lies in its role as a supportive structure for ongoing research efforts rather than an opinion piece.

Exploratory vs Applied Research

Identifying Levels of Research

• In civil engineering contexts such as soil studies or material quality assessments, exploratory research plays a critical role prior to project development.

• Once designs or budget evaluations begin, this shifts into applied research territory where interventions are actively being tested or implemented.

Classifying Verbs by Research Level

• Common verbs like "optimize," "design," "improve," etc., can be classified according to different levels of research: exploratory, explanatory, or applied depending on their context within projects.

Examples:

• Optimize: Considered applicable at an applied level since it aims at improving existing processes.

• Design: Establishes strategies but lacks certainty about effectiveness; categorized under explanatory.

• Evaluate: Assesses existing interventions indicating an applied level approach.

General Insights on Verb Classification

Understanding Language and Research Methodology

The Role of Language in Communication

• An expert highlights that Spanish speakers often adapt English terms, emphasizing mutual understanding as the core of effective communication.

• The importance of translating verbs into other languages is discussed, noting the need to assess their utility and compatibility within different contexts.

Research Ideas and Objectives

• The speaker explains that research begins with an idea expressed through sentences, which are essential for conveying thoughts effectively.

• A statement serves as the foundation of a study, reflecting the researcher’s intent and evolving into a more concrete objective.

Strategies for Achieving Research Goals

• Behind every research objective lies a strategy detailing how to achieve it; this includes statistical procedures or causal criteria.

• The discussion emphasizes that objectives alone do not encompass all necessary details; they must be supported by methodological strategies.

Addressing Questions in Epidemiology

• A question arises regarding epidemiological studies focusing solely on descriptive rather than relational approaches, prompting a broader discussion about knowledge fields.

• The speaker suggests exploring methodology literature outside one’s field to gain diverse perspectives on research practices.

Variations Across Disciplines

• A comparison is made between medical theses requiring project execution versus engineering projects where theoretical reports suffice without practical implementation.

• This illustrates the necessity for researchers to broaden their understanding across disciplines when developing methodologies.

Taxonomy of Bloom in Research Levels

• The potential application of Bloom's taxonomy in determining research levels is explored, suggesting its hierarchical nature aligns with research progression.

• It is noted that while Bloom's classifications are foundational, they can inform various aspects of research design and objectives.

Understanding Research Strategies and Interventions

Defining Objectives in Research

• When setting a research objective, such as determining the prevalence of caries, the choice of verbs like "determine" does not impose a rigid structure on the methodology. Flexibility in strategy is essential.

• The method can vary; for instance, one might calculate or estimate prevalence without being constrained by the verb used. The strategic approach is defined later in the research process.

Classification of Studies

• A question arises regarding intervention levels: both explanatory and relational/applicative studies can be classified as experimental. This stems from an older classification system by Lyon and Baylor.

• In the 1950s, there was a surge in causal relationship studies leading to a clearer taxonomy between observational and experimental studies.

Characteristics of Experimental Studies

• Explanatory studies are categorized based on their ability to demonstrate causal relationships through either experiments or observational methods.

• Experimental studies must include manipulation and control; manipulation refers to intentional interventions that differentiate these studies from others.

Types of Interventions

• Campaigns like vaccination programs are interventions aimed at improving health outcomes rather than testing efficacy, which would classify them as explanatory experiments.

• Predictive studies may also involve interventions but differ from traditional experiments due to their focus on forecasting outcomes rather than establishing causality.

Designing Instruments for Research

• In industrial engineering, when creating instruments (like surveys), it’s crucial first to define constructs such as productivity and continuous improvement clearly.

• Developing effective questionnaires requires understanding what constitutes quality in specific contexts (e.g., emergency service quality).

Data Collection Techniques

• Interviewing and surveying techniques are primarily applicable to human subjects; they cannot be directly applied to objects unless using human perceptions about those objects as data sources.

• For example, studying cement quality involves gathering user perceptions through interviews or surveys rather than assessing the object itself directly.

Conclusion of Discussion

Upcoming Academic Sessions and Participant Engagement

Acknowledgment of Participants

• The speaker expresses gratitude to all participants for their attention and involvement in the session, indicating a strong community engagement.

Future Plans for Transmissions

• It is announced that the next academic session will take place on Saturday, emphasizing the continuation of these informative meetings.

Encouragement for Questions

• Participants are encouraged to leave questions in the comments section of recorded sessions, which will be used as input for future topics. This approach fosters an interactive learning environment.

Collaboration with Experts

• The speaker acknowledges Hector Zacarías, a member of the Hispanic Society of Scientific Researchers, highlighting collaboration and expertise within the seminar series.

Continuation of Live Seminars