Internet Social Interaction vs. Mood & Self-Esteem

Answers to the Prompt: Internet Social Interaction vs. Mood & Self-Esteem

State the alternative and null hypothesis (H1 and Ho)

• Null Hypothesis (H₀): There is no significant difference in mood and self-esteem between individuals who are ostracized and those who are accepted in an Internet social interaction.
• Alternative Hypothesis (H₁): Individuals who experience ostracism in an Internet social interaction will exhibit poorer mood and lower self-esteem compared to those who are accepted.

Experimental Design

Identify the most appropriate experimental design (e.g., single-factor or factorial) and explain how exactly it qualifies as that type of design.

• The most appropriate experimental design for this study would be a single-factor experimental design.
• This is because the study is primarily investigating the impact of one independent variable (social interaction condition) on two dependent variables (mood and self-esteem).

Independent Variable

Specify precisely what the independent variable(s) will be, and how they will be manipulated. Also, specify the number of levels of each independent variable if appropriate.

1. Independent Variable: Social interaction condition (ostracism vs. acceptance).
2. Manipulation: Participants will be randomly assigned to either the ostracism or acceptance condition during an online social interaction simulation.

Dependent Variables

Specify exactly what the dependent variable(s) will be, and the operational definition for the variable as well as how it will be quantified.

1. Dependent Variables: Mood and self-esteem.
2. Operational Definitions:
   • Mood: Participants’ emotional states will be assessed using a standardized mood assessment scale, measuring factors such as happiness, sadness, and anxiety.
   • Self-esteem: Participants’ self-esteem will be measured using a validated self-esteem scale, assessing their overall evaluation of self-worth and confidence.

Procedures

Specify the procedures that will be followed (e.g., how participants will be obtained, where the experiment will be run, and what exactly will take place). This should be detailed enough to clearly illustrate what the manipulation is in the experiment and exactly how the experiment would work.

1. Participants:
   1. Recruitment: Participants will be recruited through online platforms known for diverse user demographics. Inclusion criteria will include age, internet usage frequency, and general mental health status to ensure a varied yet psychologically stable sample.
   2. Informed Consent: Participants will provide informed consent before participating, clearly outlining the nature of the study, potential risks, and their right to withdraw.
2. Experiment Location: The experiment will be conducted on a secure online platform specifically designed for the study. This platform will simulate a social environment where participants can interact with avatars controlled by the experimenters.
3. Procedure:
   1. Random Assignment: After providing informed consent, participants will be randomly assigned to either the ostracism or acceptance condition. This randomization will be done using a computer-generated algorithm to ensure an unbiased distribution.
   2. Baseline Assessment: Before the social interaction, participants will complete baseline measures of mood and self-esteem to establish a starting point.
   3. Social Interaction Simulation:
      • Ostracism Condition: Participants in this condition will experience simulated ostracism during an online group activity. Avatars controlled by the experimenters will exclude the participant from the group conversation or activities, mimicking social rejection.
      • Acceptance Condition: Participants in this condition will experience a supportive and inclusive online group interaction. Avatars will engage with the participant, providing positive feedback and inclusion.
   4. Post-Interaction Measures: Immediately after the social interaction, participants will complete measures of mood and self-esteem again to capture the immediate impact of the online interaction.
   5. Debriefing: Participants will be fully debriefed, informed about the purpose of the study, and provided with resources for psychological support if needed.
   6. Data Analysis: Collected data will be anonymized and subjected to statistical analysis to determine any significant differences between the ostracism and acceptance conditions.
4. Controlling Extraneous Variables:
   1. Standardized Procedure: The online platform will ensure a standardized and controlled environment for both conditions.
   2. Random Assignment: Participants will be randomly assigned to conditions to control for individual differences.
   3. Inclusion Criteria: Clear criteria will be set during recruitment to minimize variability in participant characteristics.
5.  Ethical Considerations: The study will adhere to ethical guidelines, ensuring the well-being of participants throughout the process. Confidentiality and privacy will be maintained, and participants will have the option to withdraw at any point without consequences.

Controlling Extraneous Variables and Eliminating Confounding Variables

Indicate what, if anything, would be done to control extraneous variables and eliminate confounding variables.

1. Random Assignment: Participants will be randomly assigned to either the ostracism or acceptance condition. This randomization helps distribute extraneous variables evenly across the two groups, reducing the likelihood of confounding variables influencing the results.
2. Inclusion Criteria: Clear inclusion criteria will be established during participant recruitment. This will help control for relevant individual differences and ensure a more homogeneous sample, minimizing the impact of extraneous variables.
3. Standardized Procedure: The online platform and the procedures for the social interaction simulation will be standardized for both conditions. This consistency ensures that any observed effects can be attributed to the manipulation (ostracism or acceptance) rather than variations in the procedure.
4. Blinding: Experimenters involved in data collection and analysis will be kept blind to participants’ assigned conditions. This helps prevent unintentional biases that might influence the results.
5. Pilot Testing: Before the main study, a pilot test will be conducted to identify and address any unforeseen issues. This can include refining the experimental procedures, clarifying instructions, or adjusting the simulation to enhance ecological validity.
6. Counterbalancing (if applicable): If there are concerns about order effects in a within-subjects design, counterbalancing the order of conditions will be implemented. This involves presenting the conditions in different orders to different participants to balance out any potential order-related biases.
7. Controlled Environment: The online platform used for the study will provide a controlled environment, minimizing external influences that could introduce extraneous variables. Any factors outside the experiment’s scope will be accounted for and documented.

By implementing these measures, the study aims to isolate the effects of the independent variable (social interaction condition) and enhance the internal validity of the findings, making them more robust and generalizable.

Experimental Design Type

Indicate if the experiment could be run as a within-subjects or matched-groups design. If so, what would the matching variables be and why? For within-subjects designs, indicate what you would do to address the problems of carryover effects, participant fatigue, habituation, etc.

1. Within-Subjects Design:
   1. If the experiment is designed as within-subjects, each participant would experience both the ostracism and acceptance conditions. This design could provide a direct comparison of the individual’s responses to both conditions.
   2. Matching Variables: To control for individual differences, potential matching variables could include:
      • Baseline Mood and Self-esteem: Participants’ initial mood and self-esteem levels could be measured and used as matching variables to ensure that individuals experiencing both conditions are comparable at the start of the study.
      • Internet Usage Habits: The frequency and nature of participants’ internet usage could be matched to control for variations in online behavior.
   3. Addressing Problems in Within-Subjects Design:
      • Counterbalancing: To address potential order effects, the order in which participants experience the ostracism and acceptance conditions will be counterbalanced. This means that half the participants will experience ostracism first, while the other half will experience acceptance first.
      • Controlled Rest Periods: To mitigate issues of carryover effects, participant fatigue, and habituation, there will be controlled rest periods between the two conditions. This allows participants to return to a baseline state before the next condition.
2. Matched-Groups Design:
   1. If the experiment is designed as a matched-groups design, participants would be carefully matched based on certain criteria before being assigned to either the ostracism or acceptance condition.
   2. Matching Variables: Potential matching variables could include:
      • Demographic Characteristics: Participants could be matched based on demographic factors such as age, gender, and socioeconomic status to control for these variables.
      • Personality Traits: Matching participants based on personality traits related to social sensitivity or resilience could enhance the comparability of the groups.
   3. Addressing Problems in Matched-Groups Design:
      • Random Assignment within Matched Groups: Even in a matched-groups design, random assignment will be used within each matched pair to ensure that individuals within a matched pair are randomly assigned to either the ostracism or acceptance condition.
      • Monitoring Confounding Variables: Throughout the study, potential confounding variables will be closely monitored and controlled for in the analysis.

Ultimately, the choice between within-subjects and matched-groups design depends on the research goals, logistical considerations, and the potential impact of order effects in within-subjects designs. Both designs aim to enhance the control of extraneous variables and improve the internal validity of the study.