Note.

Generally, in quantitative studies, reviewers expect hypotheses rather than research questions. However, both research questions and hypotheses serve different purposes and can be beneficial when used together.

Research Questions

Clarify the research’s aim (Farrugia et al., 2010)

• Research often begins with an interest in a topic, but a deep understanding of the subject is crucial to formulate an appropriate research question.
• They identify the problem or issue the research seeks to address. The nature of the research question (descriptive, comparative, or relationship-based) specifies the research’s purpose.
  • Examples include:
    • Descriptive: “What factors most influence the academic achievement of senior high school students?”
    • Comparative: “What is the performance difference between teaching methods A and B?”
    • Relationship-based: “What is the relationship between self-efficacy and academic achievement?”
• It is important to know the boundary between existing knowledge and ignorance.
  • Increasing knowledge about a subject can be achieved through systematic literature reviews, in-depth interviews with patients (and proxies), focus groups, and consultations with field experts.
• Some funding bodies, like the Canadian Institute for Health Research, recommend conducting a systematic review or a pilot study before seeking grants for full trials.
• Extensive subject knowledge can lead to multiple research questions, necessitating a decision on whether they can be addressed in one or multiple studies.
  • The presence of multiple research questions in a study can complicate the design, statistical analysis, and feasibility.
  • It’s advisable to focus on a single primary research question for the study.
  • The primary question, clearly stated at the end of a grant proposal’s introduction, usually specifies the study population, intervention, and other relevant factors.
• Hulley and colleagues (2007) advocate for the FINER criteria in developing a strong research question.
  • The FINER criteria underscore aspects that can enhance the chances of a successful research project, including specifying the population of interest, aligning with scientific and public interest, clinical relevance, and contribution to the field, while complying with ethical and national research standards.

  • F	Feasible	Adequate number of subjects Adequate technical expertise Affordable in time and money Manageable in scope
    I	Interesting	Getting the answer intrigues investigator, peers and community
    N	Novel	Confirms, refutes or extends previous findings
    E	Ethical	Amenable to a study that institutional review board will approve
    R	Relevant	To scientific knowledge To clinical and health policy To future research

• While the FINER criteria highlight the essential elements of a research question in a broader sense, the PICOT format serves as a practical framework for formulating a more detailed and specific research question.
  • The PICOT approach is crucial in developing the study’s framework and protocol, influencing inclusion and exclusion criteria and identifying patient groups for inclusion.

  • P	Population (patients)	What specific patient population are you interested in?
    I	Intervention (for intervention studies only)	What is your investigational intervention?
    C	Comparison group	What is the main alternative to compare with the intervention?
    O	Outcome of interest	What do you intend to accomplish, measure, improve or affect?
    T	Time	What is the appropriate follow-up time to assess outcome

  • Defining the specific population, intervention, comparator, and outcome helps in selecting the right outcome measurement tool.
  • The more precise the population definition and stricter the inclusion and exclusion criteria, the more significant the impact on the interpretation, applicability, and generalizability of the research findings.
  • A restricted study population enhances internal validity but may limit the study’s external validity and generalizability to clinical practice.
  • A broadly defined study population may better reflect clinical practice but could increase bias and reduce internal validity.
• An inadequately formulated research question can negatively impact study design, potentially leading to ineffective outcomes and affecting publication prospects.

Checklist: Good research questions for social science projects (Panke, 2018)

Research Hypotheses

Present the researcher’s predictions based on specific statements

• These statements define the research problem or issue and indicate the direction of the researcher’s predictions.
• The primary research question should originate from the hypothesis, not the data, and be established before starting the study.
  • Formulating the research question and hypothesis from existing data (e.g., a database) can lead to multiple statistical comparisons and potentially spurious findings due to chance.
• The research or clinical hypothesis, derived from the research question, shapes the study’s key elements: sampling strategy, intervention, comparison, and outcome variables.
• Hypotheses can express a single outcome or multiple outcomes.
• Statistical significance testing involves formulating a null hypothesis (e.g., no difference between techniques) and an alternate hypothesis (e.g., a difference exists).
  • After statistical testing, the null hypothesis is either rejected or not rejected based on whether the study’s findings are statistically significant.
  • Hypothesis testing helps determine if observed findings are due to true differences and not chance.
  • Hypotheses can be 1-sided (specific direction of difference) or 2-sided (presence of a difference without specifying direction).
  • 2-sided hypotheses are generally preferred unless there’s a strong justification for a 1-sided hypothesis.
• A solid research hypothesis, informed by a good research question, influences the research design and paves the way for defining clear research objectives.

Types of Research Hypothesis

• Y- and X-Centered Research Designs
  • Y-Centered Research Design Hypothesis
    • In a Y-centered research design, the focus is on the dependent variable (DV) which is specified in the research question. Theories are then used to identify independent variables (IV) and explain their causal relationship with the DV.
    • Example: “An increase in teacher-led instructional time (IV) is likely to improve student reading comprehension scores (DV), because extensive guided practice under expert supervision enhances learning retention and skill mastery.”
    • Hypothesis Explanation: The dependent variable (student reading comprehension scores) is the focus, and the hypothesis explores how changes in the independent variable (teacher-led instructional time) affect it.
  • X-Centered Research Design Hypothesis
    • In X-centered research designs, the independent variable is specified in the research question. Theories are used to determine potential dependent variables and the causal mechanisms at play.
    • Example: “Implementing technology-based learning tools (IV) is likely to enhance student engagement in the classroom (DV), because interactive and multimedia content increases student interest and participation.”
    • Hypothesis Explanation: The independent variable (technology-based learning tools) is the focus, with the hypothesis exploring its impact on a potential dependent variable (student engagement).
• Deterministic and Probabilistic Hypotheses
  • Probabilistic Formulated Hypotheses
    • Probabilistic hypotheses suggest that changes in the independent variable are likely to lead to changes in the dependent variable in a predictable manner, but not with absolute certainty.
    • Example: “The more teachers engage in professional development programs (IV), the more their teaching effectiveness (DV) is likely to improve, because continuous training updates pedagogical skills and knowledge.”
    • Hypothesis Explanation: This hypothesis implies a probable relationship between the extent of professional development (IV) and teaching effectiveness (DV).
  • Deterministic Formulated Hypotheses
    • Deterministic hypotheses state that a specific change in the independent variable will lead to a specific change in the dependent variable, implying a more direct and certain relationship.
    • Example: “If the school curriculum changes from traditional lecture-based methods to project-based learning (IV), then student collaboration skills (DV) are expected to improve because project-based learning inherently requires teamwork and peer interaction.”
    • Hypothesis Explanation: This hypothesis presumes a direct and definite outcome (improvement in collaboration skills) resulting from a specific change in the teaching method.
• Descriptive Hypothesis
  • A descriptive hypothesis is a statement that suggests a potential answer to a research question, focusing on describing the characteristics, behaviors, or properties of a particular group, situation, or phenomenon. It does not imply a causal relationship but rather aims to identify and describe specific attributes or patterns.
    • Example: “Students who identify as visual learners will score higher on tests that are presented in a visually rich format compared to tests presented in a text-only format.”
    • Explanation: This hypothesis aims to describe the potential difference in test scores between visual learners taking visually rich tests and text-only tests, without implying a direct cause-and-effect relationship.
• Comparative Hypothesis
  • A comparative hypothesis involves comparing two or more groups or conditions to determine if there are differences between them. It typically predicts a difference in outcomes based on varying conditions, treatments, or classifications.
    • Example: “Teaching method A will improve student performance more than method B.”
    • Explanation: This hypothesis compares the effectiveness of two different teaching methods, suggesting that one will lead to better student performance than the other. It implies a direct comparison but does not necessarily establish a causal mechanism.

• Relationship-Based Hypothesis
  • A relationship-based hypothesis predicts a relationship between two or more variables. It suggests that changes in one variable will correspond to changes in another, indicating a potential correlation or association.
    • Example: “Students with higher self-efficacy will show higher levels of academic achievement.”
    • Explanation: This hypothesis predicts a relationship between the variable of self-efficacy and academic achievement. Unlike a causal hypothesis, it does not necessarily suggest that one variable causes changes in the other, but rather that they are related in some way.

Tips for developing research questions and hypotheses for research studies

1. Perform a systematic literature review (if one has not been done) to increase knowledge and familiarity with the topic and to assist with research development.
2. Learn about current trends and technological advances on the topic.
3. Seek careful input from experts, mentors, colleagues, and collaborators to refine your research question as this will aid in developing the research question and guide the research study.
4. Use the FINER criteria in the development of the research question.
5. Ensure that the research question follows PICOT format.
6. Develop a research hypothesis from the research question.
7. Ensure that the research question and objectives are answerable, feasible, and clinically relevant.

If your research hypotheses are derived from your research questions, particularly when multiple hypotheses address a single question, it’s recommended to use both research questions and hypotheses. However, if this isn’t the case, using hypotheses over research questions is advised. It’s important to note these are general guidelines, not strict rules. If you opt not to use hypotheses, consult with your supervisor for the best approach.

References

Farrugia, P., Petrisor, B. A., Farrokhyar, F., & Bhandari, M. (2010). Practical tips for surgical research: Research questions, hypotheses and objectives. Canadian journal of surgery. Journal canadien de chirurgie, 53(4), 278–281.

Hulley, S. B., Cummings, S. R., Browner, W. S., Grady, D., & Newman, T. B. (2007). Designing clinical research. Philadelphia.

Panke, D. (2018). Research design & method selection: Making good choices in the social sciences. Research Design & Method Selection, 1-368.