Mastering APA Statistical Reporting and Research Design Principles
APA Statistical Reporting Examples
This section demonstrates how to report key statistical findings and sample characteristics using proper APA format.
Sample Size and Demographics
- Total Participants: The total sample size was reported as N = 98. (Note: The capitalized N represents the full sample; a lowercase n represents a subset.)
- South Asian Identification: 9.20% of the sample identified as South Asian.
- Male Participants: 50.00% of the sample was identified as men.
- Non-Respondents for Age: Six participants did not report their age (92 respondents out of 98 total).
- Average Age: The sample was made up of college-aged students (M = 20.12, SD = 1.29).
Correlation Reporting (Film Aggression Study)
Correlation Between Critic Reviews and Aggression
There is no significant correlation between critic reviews and the total amount of aggression in a film (*r* = -.18, *p* = .07).
Correlation Between Critic Reviews and Audience Reviews
There is a strong significant correlation between critic reviews and audience reviews (*r* = .66, *p* < .001).
Requirements for Full Statistical Reporting Credit
The following components are required when reporting correlations in APA format:
- The strength (e.g., strong) and direction (e.g., positive) of the relationship are included.
- Both variable names are mentioned.
- The statistical values are placed at the end of the sentence after a comma and within parentheses.
- The statistical notations (*r* and *p*) are italicized, but the actual numbers are not.
- Values are rounded properly as instructed (e.g., *r* to two decimal places, *p* to two or three).
Aggression Study: Variables and Group Differences
- Independent Variable (IV): Type of character.
- Levels of the IV: Human, non-human.
- Dependent Variable (DV): Total amount of aggression.
- Operationalization of DV: Different types of aggressive behavior.
There is a significant difference between the groups in terms of the amount of aggressive behavior, *t*(70) = 1.70, *p* = .047. Films that had human main characters had significantly higher aggression scores (*M* = 93.54) than those whose main character was non-human (*M* = 80.04).
Core Research Concepts: Stress and Life Satisfaction
Several studies focus on the relationship between stress and life satisfaction, utilizing specific conceptual and operational definitions.
Conceptual Definitions
- Variable 1 (Stress): The body’s response to challenges.
- Variable 2 (Life Satisfaction): A person’s overall assessment of their happiness.
Examining the link between stress and life satisfaction helps us better understand how stress affects general well-being. This research can inform mental health practitioners in creating effective stress-reduction plans and educate legislators and businesses on the need for stress-relieving settings, leading to happier and healthier communities.
Demographic Variables Chosen
Two additional demographic variables were chosen for analysis:
- Relationship Status: Helps determine how personal relationships affect stress and life happiness (e.g., married, divorced, single, or in a relationship).
- Income Level: Might reveal how one’s financial situation impacts stress and life happiness, facilitating the discovery of relationships between financial stress and general well-being.
Operational Definitions
- Stress (Operational Definition 1): Cortisol levels tested using hair samples. Higher cortisol is correlated with more stress, providing an objective indicator beyond self-reports.
- Life Satisfaction (Operational Definition 1): Ecological Momentary Assessment (EMA). Participants share their emotions in real-time via a smartphone app, offering a dynamic perspective on life satisfaction.
Research Studies on Stress and Well-being
Study 1: Stress Hormones and Biological Aging
Focus and Rationale
The study’s primary focus is how stress hormones and psychological stress affect individuals’ biological systems. Earlier studies linked chronic stress, particularly from childhood, to chronic/long-term health problems. Scientists deemed this study necessary to further understand the biological processes in action.
Hypothesis and Predictions
The research question hypothesized that stress hormones like adrenaline and epinephrine, which are related to biological aging indicators, would increase in response to rising levels of psychological stress. The scientists predicted that individuals with a history of long-term stress would show high levels of inflammation and DNA damage, indicating accelerated aging.
Methodology and Sample
This study used a mixed-method approach. They employed biological techniques to measure stress hormones and biological aging, and questionnaires to measure psychological stress. Participants were randomly chosen adults, mainly neither young nor old, with a range of backgrounds to ensure accurate representation.
Measures
Researchers used blood samples to test stress hormones. They also evaluated levels of inflammation and DNA damage as indicators of biological aging, allowing them to examine the connection between stress and aging.
Study 2: Healthcare Professionals’ Well-being
Focus and Rationale
The overall topic focuses on healthcare professionals’ stress levels and life happiness/satisfaction. Earlier studies identified high levels of stress, but lacked specific details on their mental health and general well-being. The purpose of this study was to provide insight for improving support for these individuals.
Hypothesis
The hypothesis was to understand the connection between healthcare professionals’ stress levels and their happiness. The authors hypothesized a negative correlation between life satisfaction and stress levels, predicting that stressed professionals would report lower levels of life satisfaction, emphasizing the need for mental health interventions.
Methodology and Sample
The study used a survey method, gathering self-reported data from healthcare workers to measure life satisfaction and stress levels. The sample included healthcare workers from different locations and regions categorized into color zones, allowing the study to measure regional differences in life satisfaction.
Results
The hypotheses were supported by the results. There were no significant differences in stress across the demographic characteristics and variables, showing consistency across these factors. However, healthcare workers in the orange zone reported higher life satisfaction than those in the yellow zone, indicating a regional difference. Overall, stress levels were similar among healthcare workers.
Study 3: Social Support and Resilience
Focus and Rationale
The overall topic of this study is how social support and resilience can influence the effects of stress on life satisfaction. The researchers believed this study was important because prior research has shown that stress significantly affects overall well-being.
Hypothesis
The research question hypothesized that higher levels of social support would result in greater life satisfaction, even when stress is a factor. The authors thought that people with strong social connections would experience fewer negative impacts from stress on their life satisfaction.
Methodology and Sample
The method was a survey. Participants completed questionnaires that measured stress, social support, and life satisfaction. The sample included people of all backgrounds.