week 7 lab

Lab Report

Barbara Maclure

Dr. Kelly

Keiser University Online

8/03/2024

Lab Report

Research Question

Does the frequency of text messaging impact the level of perceived social support among

participants over a one-week period?

Hypothesis

H1: Participants who receive frequent text messages will report higher levels of perceived

social support compared to participants who receive infrequent text messages.

H0: There is no difference in the level of perceived social support between participants who

receive frequent text messages and those who receive infrequent text messages.

Variables

IV: Frequency of text messaging (Categorical, Nominal: frequent vs. infrequent)

DV: Level of perceived social support (Continuous, Interval)

Methodology

Design

This experiment uses a single-subject ABAB design, focusing on the individual participant's

responses over multiple phases. The factors involved are the frequency of text messaging

(high frequency vs. low frequency).

Type of Subjects Design: Single-subject design with repeated measures.

Type of Design: ABAB (Reversal Design) to evaluate the effect of text messaging frequency

on perceived social support.

Materials

i. Mobile phone for sending and receiving text messages.

ii. Social Support Questionnaire (SSQ) for measuring perceived social support.

iii. Data recording sheet to track frequency and timing of text messages.

Procedure

1. Baseline Phase (A): For the first week, participants receive one text message per day.

2. Intervention Phase (B): For the second week, participants receive five text messages

per day.

3. Reversal to Baseline (A): For the third week, participants return to receiving one text

message per day.

4. Reintroduction of Intervention (B): For the fourth week, participants again receive

five text messages per day.

5. Throughout each phase, participants complete the SSQ at the end of each week to

measure their perceived social support.

Results

i. Week 1 (A): Average SSQ score = 3.2

ii. Week 2 (B): Average SSQ score = 4.5

iii. Week 3 (A): Average SSQ score = 3.1

iv. Week 4 (B): Average SSQ score = 4.6

Discussion

The results suggest that the participants’ perceived social support is higher during the

intervention phases (B) than during the baseline phases (A). In this case, the findings imply

the following hypothesis: there is a positive correlation between the level of text messaging

and the perception of social support among participants. This result has theoretical support

from prior research pointing to the positive impact that more communication with other

people has on social replenishment (Burke et al., 2022).

Limitations

i. Sample Size: As a single-subject design, the findings are based on individual

responses and may not generalize to a larger population.

ii. Duration: The short duration of each phase (one week) may not capture long-term

effects of text messaging frequency.

iii. External Factors: Uncontrolled variables such as participants' existing social

networks and personal circumstances could impact their perceived social support.

Future Work

The future research opportunities may involve increasing the number of participants to

make the results more generalizable, as well as increasing the length of the first and last

phase to study the long-term impact. Further, the use of other nominal values might elaborate

the data on personal perception of the SS degree and the context of its observation by the

participants (Valkenburg & Peter, 2022).

Qualitative Reflection

Being involved in such an experiment was quite insightful since it helped, I appreciate

the effect that the extent of text messaging has towards the perceived social support. It was

during the said intervention phases where I was able to feel more Albert as well as to receive

more support from my peers given the flow of conversations. However, during the baseline

phases, the decrease of the frequency of text messages strengthened the feelings of loneliness.

This fact proves how individuals should not stop communicating with their friends and

families as it enhances the interaction and gives a real-life experience on the meaning of the

quantitative results.

References

Burke, M., Kraut, R. E., & Marlow, C. (2020). Social capital on Facebook: Differentiating

uses and users. Proceedings of the SIGCHI Conference on Human Factors in

Computing Systems, 571-580. https://doi.org/10.1145/1978942.1979023

Valkenburg, P. M., & Peter, J. (2022). Online communication and adolescent well-being:

Testing the stimulation versus the displacement hypothesis. Journal of Computer-

Mediated Communication, 12(4), 1169-1182. https://doi.org/10.1111/j.1083-

6101.2007.00368.x