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Nursing Research

Sources of Data

  • Primary Sources (Preferred) – data originate from the research itself; are factual and not subject to interpretation by others.
  • Secondary Sources – data are interpreted or analyzed by another person (not the original researcher); these are “secondhand” accounts.

Ethical Issues in Nursing Research

  • Institutional Review Boards (IRBs)
    • Ensure the rights, safety, and welfare of human research subjects in their institution, hospital, or clinic.
    • Authority to approve or reject research proposals submitted to their institution/hospital (per FDA guidelines).
    • If an IRB member has a conflict of interest, they must recuse themselves from deliberation and abstain from voting.
  • Committee Members
    • IRB members are affiliated with the institution.
    • Physicians, clinicians, or retail pharmacists who are not affiliated are generally not included unless hired as consultants.
    • Prefer experienced staff members, not recent graduates.
    • Size of the IRB and number of members depend on the type of institution.
  • Vulnerable Populations
    • Almost all biomedical/behavioral research in the United States requires informed consent.
    • Special protections and consent requirements for vulnerable populations:
    • Infants and children younger than 18
    • Pregnant patients
    • Fetuses
    • Prisoners
    • Refugees, ethnic minorities
    • Persons with mental or physical disabilities, visual or hearing impairment
    • Persons who are economically disadvantaged

Belmont Report

  • A foundational document outlining ethical principles for research with human subjects.
  • Issued in 1979 by the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research.

Tuskegee Syphilis Experiment

  • Infamous study of 600 African American sharecroppers (1932–1972) in Alabama.
  • Men were tested for syphilis; those with positive results were never informed or treated.
  • This led to laws protecting human subjects’ rights and mandating informed consent.

Informed Consent of Human Subjects

  • Subjects must be informed that they have the right to withdraw at any time without adverse consequences.
  • Additional requirements for minors and vulnerable subjects:
    • Describe the study.
    • Inform what they are expected to do (e.g., questionnaires, labs).
    • Describe risks or discomfort present now and in the future (if applicable).
    • Describe benefits now and in the future (if applicable).
    • Discuss alternatives to the study.
    • Allow enough time for questions.
    • Discuss compensation or rewards for participation.
    • Discuss confidentiality and data security to protect identity.
    • Provide number and/or email address of a contact for concerns or problems with the study.
  • Minors
    • Anyone younger than 18 years.
    • Emancipated Minor Criteria: legal court document declaring emancipation; active duty in the U.S. military; legally binding marriage (or divorce from a legally binding marriage).

Consent Versus Assent

  • Consent may be given only by individuals aged 18 years or older.
  • A minor (not emancipated) can give assent from age 7 to 17 and cannot legally give consent.
  • The child should be assured they can withdraw after discussing with parents.
  • The parent or legal guardian must consent to the minor’s participation.
  • The researcher needs parental permission to speak with the minor to obtain assent (the child signs a separate assent form).

Research-Related Terms

  • Statistical Significance
    • α: Significance level or p-value; usually set as p < 0.05 or p < 0.01.
    • A significance level of p < 0.05 means a 5% probability results are due to chance.
    • A significance level of p < 0.01 means a 1% probability results are due to chance; therefore, an ext{α} = p < 0.01 is considered better than p < 0.05.
  • Control group: Subjects in an experiment who do not receive treatment.
  • N: Total size of the population.
  • n: Number of subjects in the subpopulation.
  • Significance level: Also known as the “α” or the “p-value.” The p-value is usually set at p < 0.05 or p < 0.01.
  • Independent variable: Variable that is being manipulated to influence the dependent variable; the researcher has control over it in experimental studies.
  • Dependent variable: The outcome or response resulting from the manipulation of the independent variable.
  • Hypothesis: An idea (or supposition) that can be tested and refuted.
    • Null hypothesis (H0): The opposite of the hypothesis being studied.
    • Example: If the hypothesis is “Corn plants grow faster when exposed to sunlight,” the null is “Corn plants will not grow faster when exposed to sunlight.” If the data meet the set p-value threshold, the results are significant and the null hypothesis can be rejected; if not, there is no demonstrated relationship, and results may be due to chance.

Normal Curve and Measures of Distribution

  • Normal curve: A bell-shaped curve.
  • Measures of distribution:
    • Mean: The average; ext{mean} = rac{ ext{sum of scores}}{n} = rac{ rac{}{ } ext{sum}}{n}. For example, with values 5, 5, 5, 10, 10, the mean is ext{mean} = rac{5+5+5+10+10}{5} = 7. (sums shown for clarity)
    • Median: The middle value when data are ordered.
    • Example: 1, 3, 4, 5, 7, 10, 14 → median is 5.
    • Mode: The most frequently occurring value.
    • Example: 3, 5, 7, 7, 7, 8, 9, 10, 10 → mode is 7.
    • Range: Difference between the largest and smallest values.
    • Example: 2, 3, 5, 7, 10, 15 → range is 15 − 2 = 13.

Research Designs

  • Prospective: Studies done in the present or future; data are obtained now and measured in the future. Longitudinal studies are a type of prospective study.
  • Retrospective: Studies done on events that have already occurred (e.g., chart reviews, recall of events); also called ex post facto.
  • Longitudinal: Long-term studies that follow the same group (cohort) over many years to observe and measure variables; observational (no manipulation).
    • Example: Framingham Heart Study – tracked the same subjects (N = 5{,}029) to study cerebrovascular disease risk factors.
  • Cohort: Groups sharing a common characteristic (e.g., gender, age, job, ethnicity); useful for studying causative or risk factors.
    • Example: Nurses’ Health Study – longitudinal cohort studying oral contraceptives and lifestyle factors.
  • Cross-sectional: Compares differences and similarities between two or more groups at one point in time.
  • Case Study: In-depth investigation of a single person, group, or phenomenon.
  • Descriptive: Observational studies; researchers observe and collect information without manipulating the environment.
  • Correlational: Evaluates relationships between at least two variables; mechanisms of association rather than causation.
    • Positive correlation: Variables move in the same direction.
    • Negative correlation: One variable increases while the other decreases.
    • No correlation: Variables are not related.
  • Experimental: Random sampling and random assignment; at least one control group and one or more treatment groups; manipulation; causality can be inferred if A + B leads to C.
  • Quasi-Experimental: Similar to experimental design but without randomization; subjects recruited by convenience sampling.

Deductive Versus Inductive Reasoning

  • Deductive Reasoning (top-down logic): Start with a theory and derive specific hypotheses; used in quantitative studies.
  • Inductive Reasoning (bottom-up logic): Start with specific observations to develop generalizations and theory; used in qualitative studies.

Qualitative Versus Quantitative Studies

  • Qualitative Studies
    • Data: Words, narratives, subjective opinions.
    • Number of subjects: Usually few.
    • Subject recruitment: Small, not randomized.
    • Data gathering: In-depth interviews, focus groups, observations; audio/video recorded and transcribed.
    • Logic: Inductive; specific data generalized to broader themes.
    • Design: Flexible and may evolve with the situation or subjects.
    • Statistical Testing: Interprets themes and patterns; uses limited statistics (e.g., hi^2).
    • Notes: Researcher is a participant and observer to varying degrees.
  • Quantitative Studies
    • Data: Numerical and measurable.
    • Number of subjects: Large; may involve databases.
    • Subject recruitment: Randomization possible in experimental designs.
    • Data gathering: Questionnaires, instruments, measurements, surveys.
    • Logic: Deductive.
    • Design: Systematic and predefined before research begins.
    • Statistical Testing: ext{Pearson correlation}, ext{ paired } t ext{-test}, ext{ simple/multiple regression}, ext{ ANOVA}, etc.
    • Notes: Researcher aims to be objective; biases and funding sources should be disclosed.

Research Process

  • Phase I — Conception: Formulate research question/problem; review literature; develop hypotheses.
  • Phase II — Design and Planning: Select design; identify population/sample; determine protocols, resources, and ethical considerations; prepare proposal; submit to IRB for approval.
  • Phase III — Implementation: Recruit participants (obtain consent); implement design; collect data.
  • Phase IV — Analysis: Organize, analyze, and interpret data.
  • Phase V — Dissemination: Prepare final report; publish and disseminate findings (e.g., journal articles, poster presentations, lectures).

Human Genetic Symbols

  • Exam questions may include genetic symbols (Table 29.2):
    • Healthy male: empty square ☐
    • Diseased/affected male: filled square ■
    • Healthy female: empty circle ○
    • Diseased/affected female: filled circle ●
    • Death: diagonal slash across symbol
  • Legend:
    • Healthy male - empty square
    • Diseased male - filled square
    • Healthy female - empty circle
    • Diseased female - filled circle
    • Death - diagonal slash across symbol