Research analysis

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Task8.4.docx

Running head: Community and political service and social media use 1

Community and political service and social media use 5

Community and political service and social media use

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Comment from Professor:

I appreciate your effort on this first attempt but several things are missing which I will detail in turn. I would recommend reviewing the sample research paper in your course resources which is a good model to follow for an APA-style research paper. The main thing is to follow a standard format with appropriate subheadings, such as participants, procedures, and measures. This submission doesn't tell us who is being recruited (adults age 18+) or by whom (students in a graduate psychology class). It doesn't tell us where the survey will be conducted (Survey Monkey), how participants will be recruited (using social media), or that they will be consented. It also doesn't go into any detail about the key measures (CSAS) such as how many items it has, a sample item, response options, or include an in-text citation for the measure. All of these details would be relevant for your methods section and should be incorporated into your final submission.

*The latter is the only thing really missing here--future directions. A discussion section typically addresses where research can make up for limitations of our work, which is also addressed in the discussion. Adding those elements will round this out nicel

Literature review

According to (Fenn et al, 2022), community service, or unpaid activity that aims to improve the lives of others, is often linked to a better quality of life. However, little attention has been paid to the process of starting and maintaining community service engagement. The Trans-theoretical Model (TTM) of behavior modification was used to investigate young individuals' preparation for community service. Self-efficacy and the relevance of positives increased across preparedness groups, while the value of negatives declined. This is consistent with past TTM uses. It is possible to use the findings of this study to guide readiness-targeted community service interventions. Longitudinal research on community service preparation beyond the college context might be beneficial in this field of study.

Dana et al (2021) conducted a similar study with an aim to design and evaluate a 10-item 'attitudes to formal volunteering' scale for retired older individuals that may be used to guide intervention efforts because favorable attitudes to volunteering are connected with support for volunteering and individual engagement. Two components (the overall attitude toward volunteerism and the attitude toward participation in volunteerism) accounted for 64% of the variance in attitude scores, according to principal component analysis. In a confirmatory factor analysis, the two-factor model was shown to match the data perfectly. The proposed scale could be a valuable tool for gauging the attitudes of retired older individuals to volunteering.

An experiment of students within animal science curriculum service-learning was used as a platform to bring together participants whose attitude towards community service was assessed (Smith, 2020). The goal of the study was to see if a term project focused on community service influenced student attitudes on volunteering in the field of animal research. There were two groups of students in a beef cattle production class, and the term project was administered by dividing them into those two groups. For the control group (CON), they were given a normal farm and business plan development assignment. Beef producers face several obstacles to adopting best management practices, and the treatment group (TRT) was tasked with developing educational materials to help them. CSAS, a measure of attitudes toward community service, was used both before and after the projects were completed. SAS v. 9.4 was used to analyze the data. CON answered more favorably (P 0.05) to CSAS questions when modifications existed before and after the test, but attitude domains did not alter (P 0.11). Students' attitudes on community service are not changed by a service-oriented term project, according to the data. According to the report, religious beliefs are the most commonly cited reasons for volunteering. Motivating motivations include the desire to promote national connection, the want to fill leisure time, and the desire to get work experience. There was a consensus among students that they wanted to observe the impact of their volunteer work, and some opted for projects that allowed them to do just that. Personal development, skills, and job prospects are all cited as favorable outcomes for students who volunteer. Time constraints due to schoolwork are the most common impediment to students volunteering. In addition to the findings, the study made a number of recommendations and proposals aimed at increasing the involvement of university students in community service. The study also confirmed the effectiveness of Community Service Attitude Scale (CSAS) in evaluating participant’s attitude towards community or political service.

Perceived organizational support (POS) and role clarity were examined in this study to see if they had any effect on the satisfaction of mandatory volunteers (Kim et al, 2021). Attitudes toward volunteering played a mediating role in the relationship between volunteer satisfaction and attitudes toward civic participation, and self-efficacy for service served as a moderator in the relationship between POS, role clarity, and volunteer satisfaction. Results from a significant event in Wuhan, China, indicated that POS and job clarity impacted volunteer happiness. Positive attitudes toward volunteering and civic participation are intertwined because of the impact that volunteers have on their own well-being. Participant self-efficacy was found to be a key mediator in the relationship between volunteer satisfaction and organizational climate characteristics such as POS, role clarity, and self-efficacy toward service. Our research shows that organizations have an essential role in boosting mandatory volunteers' happiness, which has a favorable impact on volunteerism and civic engagement.

Research gap

The literature proved the effectiveness of Community Service Attitude Scale (CSAS in determining participant’s attitude towards community service. However, there is none of the scholars who explored the social media aspect and the data that can be collected from social media use ad trends in relation to the engagement in community service. Therefore, there is a need to explore the attitude towards community service and political service in the era of increased use of social media services and platforms which act as a channel of influence where the members of society use social media in influencing others on behavioral and attitude patterns towards various areas in the community including community service or political service. In exploring the research gap, data from social media platforms will be relied upon to give a more defined and purpose-oriented data for better results.

Methods section

This study follows a mixed research methodology. This refers to a situation where both qualitative and quantitative data is used in developing insight on the research topic and discussion. Quantitative data will be derived from the Community Service Attitude Scale which measures participant’s attitudes towards community service. The data will be cross-referenced with qualitative data from other sources such as documents and journals. Quantitative data is considered appropriate for the study as it brings in the ability to assess the validity and consistency of data through the use of statistical tests. This eliminates potential bias that may rise as a result of subjective approach towards the study.

To ensure the validity and trustworthiness of the findings, the qualitative approach, which draws on data from a variety of theoretical sources, is deemed the most appropriate method for this study.  Qualitative data can be equally as helpful as quantitative data when it comes to providing context and explanation. Qualitative research is considered appropriate for this study as it is easy for researchers to make changes if they do not have access to the information they need.  Monitoring participants' behavior and asking them probing questions might help the researcher get insight into the issue at hand (Gilad, 2021).

Participants must be 18 years and above and recruited through the social media network such as Facebook, Instagram, Twitter, other online platforms that could be used include emails, blogs, mobile diaries, and communities. Potential participants would be sent an ad describing the study with a link to Survey Monkey. To ensure there is pure representation of the population, the convenience sampling method would be used in selecting participants and subjecting the participants to a CSAS measuring tool after which data is collected and analyzed.

This study follows a mixed research methodology. This refers to a situation where both qualitative and quantitative data is used in developing insight on the research topic and discussion. Quantitative data will be derived from the Community Service Attitude Scale which measures participant’s attitudes towards community service. The data will be cross-referenced with qualitative data from other sources such as documents and journals. Quantitative data is considered appropriate for the study as it brings in the ability to assess the validity and consistency of data through the use of statistical tests. This eliminates potential bias that may rise as a result of subjective approach towards the study.

To ensure the validity and trustworthiness of the findings, the qualitative approach, which draws on data from a variety of theoretical sources, is deemed the most appropriate method for this study.    Qualitative data can be equally as helpful as quantitative data when it comes to providing context and explanation. Qualitative research is considered appropriate for this study as it is easy for researchers to make changes if they do not have access to the information they need.  Monitoring participants' behavior and asking them probing questions might help the researcher get insight into the issue at hand (Gilad, 2021).

Participants would be recruited through the social media network such as Facebook, Instagram, Twitter, other online platforms that could be used include emails, blogs, mobile diaries, and communities. Potential participants would be sent an ad describing the study with a link to Survey Monkey. To ensure there is pure representation of the population, the convenience sampling method would be used in selecting participants and subjecting the participants to a CSAS measuring tool after which data is collected and analyzed.

RQ1: What are participants’ attitudes towards community service, as measured by the Community Service Attitude Subscales (CSAS)?

            H10: There is no relationship between the CSAS subscales

            H1A: There is a relationship between the CSAS subscales

Analysis: Correlation between the CSAS Subscales: Awareness, Connectedness, Normative Helping Behavior, Costs, Benefits, Career Benefits, Seriousness, Intention, Future Plans

RQ2: What are some predictors of attitudes to community service (as measured by CSAS subscales): Demographics: age, gender, race/ethnicity, education?

            H10: There are no demographic predictors of community service (using CSAS subscales)

            H1A: There are demographic predictors of community service (using CSAS subscales)

            Analysis: Multiple regressions with subscales and demographics

RQ3: What is the relationship between community service and social media?

            H10: There is no relationship between community service and social media

            H1A: There is a relationship between community service and social media

Analysis: Correlation between community service and social media

RQ4: What is the relationship between political participation and social media?

            H10: There is no relationship between political participation and social media

            H1A: There is a relationship between political participation and social media

Analysis: Correlation between political participation and social media

RQ5: What are predictors of use of social media related to community service: Demographics: age, gender, race/ethnicity, education?

            H10: There are no demographic predictors for use of social media related to community service

            H1A: There are demographic predictors for use of social media related to community service

            Analysis: Multiple regressions with use of social media related to community service

RQ6: What are predictors of use of social media related to political service: Demographics: age, gender, race/ethnicity, education?

            H10: There are no demographic predictors for use of social media related to political service

            H1A: There are demographic predictors for use of social media related to political service

            Analysis: Multiple regressions with use of social media related to political service

RQ7: What is the relationship between attitudes toward community service (as measured by the CSAS) and use of social media?

            H10: There is no relationship between CSAS subscales and social media

            H1A: There is a relationship between CSAS subscales and social media

Analysis: Correlation between CSAS subscales and social media

RQ8 Open ended question: What is the experience of engaging in community service participation?

            Analysis: coding and correlation with community service

RQ9 Open ended question: What is the experience of engaging in political participation?

            Analysis: coding and correlation with political service

RQ10 Open ended question: What are the reasons given for people not to participate in community service or political service?

            Analysis: coding and correlation with community service/political service

Results

Demographics

I utilized SPSS to conduct a descriptive statistics analysis. For race, education and marital status I utilized frequencies and for age I utilized descriptive stats. I also picked the community service questions and utilized frequency stats. For the demographic race. 64.1% identified as Caucasian, 23.9% African American, 6% Hispanic, 1.3% Asian American, 0.7 American Indian, 3.3 % Pacific Islander, and 0.7% declined to disclose their race. Looking at this I would say that the participant pool was not that diverse. This also makes me wonder when it comes to the actual community service question, would there be one or more races that were more active in community services than other races.

The next demographic is education. 6.6% of the respondents held a Doctorate, 43.2% held a master’s degree, 21.9% held a bachelor's degree, 19.9% held an associate degree, 7.6% completed high school and 0.7% chose other but unsure what other options were available. This data is important because at first glance it appears that the respondents with higher degrees were more willing to take part in the research than those without.

The last demographic is marital status. 59.5% of the respondents were married, 28.6% were single, 9.3% divorced, 1% widowed and 1.7% chose not to answer. This makes me wonder since the marital status percent was higher was it due to partner influence by chance.

Lastly when looking at age, I ran descriptive statistics, and the mean age was 43.34. 18 years old was the minimum and 76 was the maximum.

Community Service Questions

In the past year, did you participate in community service (e.g., for nonprofit)?

For this question 43.5% of the respondents made donations and contributions while 39.5% went out and volunteered their time. The other 16.9% made a social media post about community service but did not engage in the actual activity. This shows that more individuals were willing to make monetary contributions instead of going out in the community and engaging in the activity.

How often do you post about a community or nonprofit issue?

Some of the respondents (24.4%) reported that they rarely post about a community issue and next are 17.8% who post several times a year and 13.3% that post more than once a week. I am somewhat surprised with the popularity of social media that the percentage of those who rarely post was higher among the respondents.

How often did you participate in community service in the past year?

31.7% of the respondents reported that they participate several times a year, followed by 18.6% that reported they rarely participate and 12.4% that reported that they participate weekly. This is intriguing because this plays into the question about the type of contribution that is being made, whether it’s a financial contribution or if they are contributing their time.

So far it looks as though more respondents want to contribute money, rather than going out and engaging in community service. Also, it shows that even though social media is a popular avenue for communication it is rarely being used to bring light to some community issues or service.

The first RQ I analyzed utilizing a correlation for is RQ3, “What is the relationship between community service and social media”? The two variables that were analyzed were how often do you post about community or nonprofit issues and how often did you participate in community service in the past year. When looking at the correlation matrix, the Pearson correlation is 499 which shows that there is a strong correlation and also indicates that there is a relationship between the variables. This also tells us that there is a relationship between community service and social media because those individuals that post about community issues are more likely to participate in community service and those who may actively participate in community service are more likely to post community issues to their social media accounts. I can conclude that there is a relationship between community service and social media. 

The second RQ I analyzed utilizing a correlation for is RQ4, “What is the relationship between political participation and social media”? The two variables that were analyzed were how often do you post about a political issue and how often did you participate in political service in the past year? This one was unable to produce any analysis because one of the variables is constant. I think this means that there is no correlation or not a strong correlation between the two variables. I conclude that there is no relationship between political participation and social media.

 

The RQ I analyzed utilizing a multiple regression for is RQ5, “What are predictors of use of social media related to community service: Demographics: age, gender, race/ethnicity, education”? My dependent variable is “how often do you post about a community or nonprofit issue” and the independent variables are age, gender, race/ethnicity and education. When looking at the Anova box the sig. it is 0.729 which is higher than 0.05 conventional threshold so the model overall does not have statistical significance. Next we will look at the coefficients table. If the sig. is >0.05 then the null hypothesis is not rejected and this means that there is no impact to the dependent variable (Warner, 2013).For the demographic predictor of age the sig. it is 0.373 which is higher than 0.05 conventional threshold so this means that there is no relationship between age and how often an individual posts a community issue on social media. For the demographic predictor of gender the sig. it is 0.791 which is higher than 0.05 conventional threshold so this means that there is no relationship between gender and how often an individual posts a community issue on social media. For the demographic predictor of race/ethnicity the sig. it is 0.459 which is higher than 0.05 conventional threshold so this means that there is no relationship between race/ethnicity and how often an individual posts a community issue on social media. For the demographic predictor of education the sig. it is 0.882 which is higher than 0.05 conventional threshold so this means that there is no relationship between education and how often an individual posts a community issue on social media. What I would conclude from this data analysis is that there are no demographic predictors for use of social media related to community service. 

The RQ8 that I utilized for the coding was “what is the experience of engaging in community service participation?

First, I created coding categories of rewarding, sense of community, personal satisfaction, meeting like-minded people and other. This first thing did was run a frequency on my coding variable. This resulted in showing that 12.5 % of the respondents described the experience of engaging in community service as rewarding, 45.8 % of the respondents described the experience of engaging in community service as feeling a sense of community, 20.8 % of the respondents described the experience of engaging in community service as having a sense of personal satisfaction, 4.2 % of the respondents described the experience of engaging in community service as positive due to meeting like-minded people and 16.7 % of the respondents described the experience of engaging in community service as other reasons that were not coded.

When looking at the pearson correlation, which in .111, this shows that there is a weak correlation between the variables. The data suggests that social media use doesn’t play a role in whether an individual chose to engage in community service.

Discussion

Based on the data collected, there are several ways and means through which people tend to work for the community. Community development works in several ways, and it is tough to assess the nature of operations, especially on matters to work for the community. Several participants stated that they had donated, while others directly volunteered their time. This raises the question of whether there is any difference between a donation and now participating. Participation in community service is mainly a calling, and several people will feel comfortable donating while others will push themselves and contribute their time and presence to the community (Drury et al., 2021). There is a sense of relief when someone does not disclose what they undertake in public. This has been evidenced by the many participants who rarely post about the community issue.

Some participants perceived that the best way to ensure proper care for the community is by doing things in-house. Of those that post about the issues in the community, very few does it continuously. People have embraced social media positively by not advertising the problems in the community. A number of those that participate in the community service do it several times a year. Those that contribute most of the time are the smallest of the proportion. This indicates the contributory power of the participants is more financial than physical. Based on the information above, it is evident that several people do not want to be seen working for the community as they hardly address the issues they face in society (Ozdemir et al., 2022).

Based on the analysis, it is evident that the persons who apply social media in addressing community issues have a significant impact, as evidenced by the strong correlation. Social media brings to light some of the community members' problems. Some people are willing to donate and participate, but they do not know the issue at hand. It is up to the community members to ensure all the regional problems are addressed and that applying social media is not as adverse as it seems (Drury et al., 2021). Those who use social media are more likely to participate in community service, which benefits the community.

Politics is very ambiguous, and one cannot tell the actual impact it has on addressing issues in the community. Applying social media in the community has driven several political forces which work to ensure that the community's needs are addressed. It isn't easy to know whether it is the drive of the political persons or whether social media has something to do with political participation. All in all, social media applies to addressing all policies that seem to affect an organization. Issues within the community are for all members despite their age, gender, education or race. Several people use social media, and applying the changes in the community may result from a child or an older adult posting the issues on social media platforms (Ozdemir et al., 2022). With social media, one does not factor in items such as age and gender if all the facts presented on the platform are verified.

For some people, engaging in community service is about fulfilling inner satisfaction. Some people feel that some of the issues in the present moment will succeed if they participate. A number of them will feel wonderful when all operations within an organization have been satisfied by the works of their hands. Others think the opportunities presented to them are gifts and should return to the community. All in all, different persons have different objectives for engaging in community service (Ozdemir et al., 2022).

Reference

Bang, H., Lee, C., Won, D., Chiu, W., & Chen, L. (2022). Exploring Attitudes of Mandatory Volunteers: The Role of Perceived Organizational Support, Role Clarity, and Self-Efficacy Toward Service. Nonprofit and Voluntary Sector Quarterly, 08997640221093797.

Dana, L. M., Jongenelis, M. I., Jackson, B., Newton, R. U., & Pettigrew, S. (2021). Development of a scale assessing retired older adults’ attitudes to volunteering. Australasian journal on ageing40(3), e254-e261.

Drury, J., Carter, H., Ntontis, E., & Guven, S. T. (2021). Public behaviour in response to the COVID-19 pandemic: understanding the role of group processes. BJPsych open7(1).

Fenn, N., Reyes, C., Monahan, K., & Robbins, M. L. (2022). How Ready Are Young Adults to Participate in Community Service? An Application of the Transtheoretical Model of Behavior Change. American Journal of Health Promotion36(1), 64-72.

Gilad, S. (2021). Mixing qualitative and quantitative methods in pursuit of richer answers to real-world questions. Public Performance & Management Review44(5), 1075-1099.

Ozdemir, S., Ng, S., Chaudhry, I., & Finkelstein, E. A. (2022). Adoption of preventive behaviour strategies and public perceptions about COVID-19 in Singapore. International Journal of Health Policy and Management11(5), 579-591

Smith, W. B. (2020). Attitudes Toward Community Service Using a Targeted Term Project in a Beef Production. NACTA Journal65.