Walden University Wk 6 Socioe

5 days ago

Joseph Senesie

RE: Week 6


Explanation for whether or not socioeconomic status should be used to allocate resources for public health financing

Socioeconomic status should determine the allocation of resources in public health. According to Levi, Juliano and Richardson (2007), the allocation of resources to support public health should be based on population distribution, risk factors, and disease burden. The distribution of resources based on need contributes to the reduction of inequity in healthcare. As indicated by Lee (2021), equity is one of the ethical requirements in the distribution of healthcare services. Distributing resources in public health without standards and a transparent process is counterproductive as marginalized populations will suffer the ramifications of such an irrational process. For instance, the lack of transparency and standards of resources allocation in public health at both federal and state-level promote the continued imbalance in the health system in the United States (Levi, Juliano & Richardson, 2007). Furthermore, in the era of scarcity of resources, it makes sense to distribute the limited resources based on need, hence, ensuring overall efficiency (Olsen Øystein, 2010).

Explain how the socioeconomic status of communities drives the financing need for public health initiatives

Socioeconomic factors drive the need for public health investment. The World Health Organization recommends investing a minimum of $40 per capita in healthcare results in meeting basic health, water, and sanitation needs (Anyangu-Amu, 2010). Investing sufficient resources per capita contributes to the development of the healthcare system. Based on a nutrition study in Indonesia, negative socioeconomic factor such as low income is associated with high stunting levels in children under-five (Utami, Setiawan, & Fitriyani, 2019). Thus, meeting the financial gaps brings about positive change and improvement in the health status of a community. According to the World Health Organization (2004), increased income reduces the disease burden. Therefore, socioeconomic status of individuals, households, and communities are linked to public health needs.


Anyangu-Amu, S. (2010). Financing Public Health in Africa. Retrieved from


Lee, L. M. (2012). Public Health Ethics Theory: Review and Path to Convergence. Journal of Law, Medicine &

Ethics, 40(1), 85–98. Retrieved from


Levi, J., Juliano, C., & Richardson, M. (2007). Financing Public Health: Diminished Funding for Core Needs and State-by-State Variation in Support. Journal of Public Management and Practice, 13(2), 97 – 102. Retrieved from


Olsen Øystein E. (2010). The impact of global health initiatives on trust in health care provision under extreme resource scarcity: presenting an agenda for debate from a case study of emergency obstetric care in Northern Tanzania. Health Research Policy and Systems, 8(1), 14. Retrieved from


Utami, R., Setiawan, A., & Fitriyani, P. (2019). Identifying causal risk factors for stunting in children under five years of age in South Jakarta, Indonesia. Retrieved from


World Health Organization. (2004). Poverty: Assessing the distribution of health risks by socioeconomic position at national and local levels. Retrieved from


4 days ago

Dominique Morgan

RE: Discussion – Week 6


Whether or not socioeconomic status should be used to allocate resources for public health financing

Socioeconomic status refers to the social standing of someone and is often calculated as a combination of occupation, income, and education (American Psychological Association [APA], n.d.). Socioeconomic status can expose inequities in access to resources, privileges of some groups over others, who holds power, and who controls access (APA, n.d.). In the case of resource allocation for public health financing, socioeconomic status should be used. When assessing public health financing needs, socioeconomic status is a critical factor (Laureate Education, 2012). In order to adequately allocate resources, the socioeconomic status of the population being served must not only be considered but also included as a factor in deciding how to distribute those resources. Blindly allocating resources without accurately assessing the population’s current needs can lead to inequitable dissemination. The instability and variation of public health financing warrants evaluating all factors impacting public health funding from health insurance coverage, state and federal funding sources to the population’s socioeconomic status (Levi et al., 2007).

How the socioeconomic status of communities drives the financing need for public health initiatives to provide for underserved populations

Socioeconomic status is a critical indicator for advocating for funding for public health initiatives to provide for underserved populations. Lower socioeconomic status is associated with adverse health and social outcomes, limiting financial resources and opportunities (Santiago et al., 2011). The limited financial resources and opportunities of underserved populations then lead to inequities and inequalities in distributing resources, health, and social services, impacting the quality of life (APA, 2010). Public health’s goal is to improve health outcomes of populations through a variety of means like initiatives, education, promotion, advocacy, and more (Bloland et al., 2012). It would be a societal benefit for public health initiatives to receive the funding and financing necessary for all communities regardless of socioeconomic status. The benefits would include efforts to reduce gaps in socioeconomic statuses, more equal access to funding and services, and an overall improvement in quality of life (APA, 2010).


American Psychological Association. (n.d.). Socioeconomic status. https://www.apa.org/topics/socioeconomic-status

American Psychological Association. (2010). Children, youth, families and socioeconomic status. https://www.apa.org/pi/ses/resources/publications/children-families

Bloland, P., Simone, P., Burkholder, B., Slutsker, L., & De Cock, K.M. (2012). The role of public health institutions in global health system strengthening efforts: The US CDC’s perspective. PLoS medicine, 9(4), e1001199. https://doi.org/10.1371/journal.pmed.1001199

Laureate Education. (2012). Multi-media PowerPoint: Financing public heath [PowerPoint]. Walden University Blackboard. https://class.waldenu.edu

Levi, J., Juliano, C., & Richardson, M. (2007). Financing public health: Diminished funding for core needs and state-by-state variation in support. Journal of Public Health Management and Practice, 13(2), 97–102

Santiago, C. D., Wadsworth, M. E., & Stump, J. (2011). Socioeconomic status, neighborhood disadvantage, and poverty-related stress: Prospective effects on psychological syndromes among diverse low-income families. Journal of Economic Psychology, 32(2), 218–230. https://doi-org.ezp.waldenulibrary.org/10.1016/j.joep.2009.10.008

4 days ago

Joy Garba

RE: Discussion – Week 6 Attachment


The study selected for this week’s discussion is Islamic parents’ attitudes and beliefs towards school-based sexual and reproductive health education programs in Oman (Al Zaabi et al., 2019).

Which is the research design used by the authors?

The authors used quantitative research using a two-phase sequential explorative design conducted in the large urban district of Saham, Oman. The researchers used a district with a large population and more public schools (n = 30) than other districts (Oman MOE 2018; Oman NCSI 2018), including 15 public secondary schools (8 boys’ schools and 7 girls’ schools). Each school has one female school nurse, approximately 8 to 14 science teachers, and an average of 350 to 400 students in grades 7 to 9 (Oman MOE 2018).

Why did the authors use this t-test?

The authors asked parents to indicate the extent to which they were comfortable with their children receiving comprehensive sexuality education from different sources. During the study, both mothers and fathers rated parents, school nurses, school teachers, and religious leaders as important sources of information. An independent-samples t-test showed that there was only a significant difference between the comfort of mothers (M = 4.43, SD = 0.81) and fathers (M = 4.10, SD = 0.99) towards parent as a source of comprehensive sexuality education (t (237) = −2.87, p= 0.004). An independent-samples t-test indicated that mothers rated parents as an essential source of comprehensive sexuality education significantly more than fathers did.

However, the results of a one-way analysis of variance (ANOVA) showed that there was a significant difference between the attitudes of parents with higher and lower education levels towards the importance of CSE in school (F(4, 234) = 4.097, p = .003) and the appropriate age to start teaching it (F(4, 234) = 2.991, p = .020). Parents with higher education were more supportive of introducing CSE in school and wanted it to be introduced earlier in grades 1 to 4. In addition, a one-way ANOVA found a significant difference between age groups regarding the appropriate age to start teaching sexual education (F(3,235) = 3.36, p = .019) such that young parents preferred that CSE be introduced earlier in grades 1 to 4.

Do you think it is the most appropriate choice? Why or why not?

The t-test and ANOVA were used to show significant difference between variables which was appropriate to knowing various attitudes of parents towards sexual and health education.

Did the authors display the data?

The Authors displayed data as shown below in Table 1 to Table 4

Table 1

Parental rating by the source of Comprehensive Sexual Education

Table 2

Showing importance parents assigned to possible topics within the Comprehensive Sexual Education curriculum

Table 3

Grade level at which parents thought specific topics should be introduced within the school curriculum

Table 4

Characteristics of the total sample

Do the results stand alone? Why or why not?

The overall response rate to the questionnaires was 95.6% (n = 125 mothers; n = 116 fathers). Around 52.3% of participants were female, and 47.7% were male and had boys or girls aged 12–14 years. In this study, most parents were 30–39 years of age (60.3%), followed by 40–49 (28.9%), 50 or older (5.9%) and under 30 (5%). All participating parents were of Islamic faith and Omani citizens and generally had high levels of education. The results stood alone, showing the various categories of respondents who participated in the study and results displayed in the data tables.

Did the authors report effect size? If yes, is this meaningful?

A statistical power analysis was performed for sample size estimation. The study’s effect size was 0.3, which is considered medium and meaningful (Cohen 1988). With an alpha = 0.05 and power = 0.95, the projected sample size was N = 147.


Al Zaabi, O., Heffernan, M., Holroyd, E., & Jackson, M. (2019). Islamic parents’ attitudes and beliefs towards school-based sexual and reproductive health education programs in Oman. Sex Education, 19(5), 534–550. https://doi-org.ezp.waldenulibrary.org/10.1080/14681811.2018.1553708

Cohen, J. 1988. Statistical Power Analysis for the Behavioral Sciences. New York: Erlbaum Associates. Collier-Harris, C. A., and J. D. G. Goldman. 2017. “What Educational Contexts Should Teachers Consider for Their Puberty Education Programs?” Educational Review 69 (1): 118–133. DeJong, J., R. Jawad, I. Mortagy, and B. Shepard. 2005. “The Sexual and Reproductive Health of Young People in the Arab Countries and Iran.” Reproductive Health Matters 13 (25): 49–59.

Oman CDSC (Communicable Disease Surveillance and Control). (2018). HIV/AIDS Control Program. Oman: Ministry of Health. http://www.cdscoman.org/hivandaids-control.html

Oman MOE (Ministry of Education). (2018). Education System in Oman. Oman: MOE. http://home. moe.gov.om/english/module.php?module=InfoCenter

Oman MOH (Ministry of Health) and WHO (World Health Organization). Oman Global school-based Student Health Survey 2010. Oman: WHO and MOH. http://www.who.int/chp/gshs/oman/en/ Oman MOH (Ministry of Health), and WHO (World Health Organization). 2018. Country Cooperation Strategy for World Health Organization and Oman 2018–2022. Oman: MOH and WHO. HTTP:// www.who.int/countryfocus/cooperation_strategy/ccs_omn_en.pdf

Oman NCSI (National Center for Statistics and Information). 2018. Monthly Statistical Bulletin: February 2018. Oman: National Center for Statistics and Information. https://www.ncsi.gov.om/

3 days ago

Sharnia Lashley
RE: Discussion – Week 6
Background of Research and Measures
From 06/01/2015 to 02/28/2016, Damares et al. (2018) utilized a cross-sectional, correlational study to assess the existence of compulsive overeating disorder and to look at the disorder’s relationship with anxiety and depression symptoms and clinical and sociodemographic data through a sample (n=111) of overweight or obese, adult cardiovascular disease (CVD) patients of a São Paulo hospital. The researchers used the Hospital Anxiety and Depression Scale (HADS) to collect anxiety and depressive data, a Likert scale instrument called Escala de Compulsão Alimentar Periódica ECAP (Binge Eating Scale – BES) to evaluate compulsive overeating anxiety and a specific tool to collect clinical (i.e., BMI and other data) and sociodemographic data to assess relationships between this data (Damares et al., 2018).
Research Analysis Methods
Data processing and analysis ensued through SPSS, with mean, median, and standard deviation, measures of effect size utilized in the descriptive analysis. The researchers set a 0.05 level of significance (Damares et al., 2018). Researchers used Cronbach’s Alpha, at 0.85, to measure internal consistency for the BES, the chi-square test with the qualitative and the independent samples t-test to compare data, ANOVA, and two other tests (Kruskall-Wallis and Mann-Whitney) with the quantitative data (Damares et al., 2018).
Results, T-test, and Meaningfulness
The authors appropriately reported the average (mean) score across participants for the scale variables as continuous, using the variables as dependent in the t-test as a result (Walden University, n.d.). Table 1, also shared below, displays means, medians, and standard deviation measurement data for body mass index and anxiety symptom variables by participant’s compulsive overeating information (Damares et al., 2018). A figure displayed the Pearson correlation analysis of the depression and anxiety variables (Damares et al., 2018). The results do not seem to stand alone with sociodemographic outcomes described and other variable data displayed. Table 1 (Damares et al., 2018) exhibits that most patients did not have compulsive overeating disorder (n=91 of 111 or 82%), leaving 18% that did. There was an association of higher BMI (p=0.010) with compulsive overeating (Damares et al., 2018). The results indicate no significant correlation with compulsive overeating levels (p=0.053). However, in the presence or absence of compulsive overeating, an association surfaced (p=0.017, Damares et al., 2018)). Other results included weak to moderate correlation between “anxiety with age (r=-0.260, p=0.005) and depression (r=0.506; p=<0001”, Damares et al., 2018). The reported effect size is meaningful to evaluating CVD patients when it comes to physical and mental characteristics.
Table 1 Measurements of body mass index and anxiety symptoms variables according to participants’ compulsive overeating (n = 111). São José do Rio Preto, SP, Brazil, 2015-2016
Body Mass Index
Anxious Symptoms
Mean [SD* (Median)]
Mean [SD* (Median)]
Compulsive overeating
Absent (n=91)
30.00 [3.50 (29.390)]
8.34 [4.44 (8.00)]
Moderate (n=15)
33.28 [4.10 (33.590)]
11.33 [5.38 (12.00)]
Severe (n=5)
31.92 [4.49 (32.540)]
10.2 [3.76 (11.00)]
Compulsive overeating
Absent (n=91)

8.34 [4.44 (8.00)]
Present (n=20)

11.05 [4.95 (11.5)]

*standard deviation; †Analysis of Variance Test (ANOVA); ‡Kruskal-Wallis test
Reprinted from “Relationship between anxiety, depressive symptoms and compulsive overeating disorder in patients with cardiovascular diseases, by Damares Garcia, G., Alcalá Pompeo, D., Palota Eid, L., Bernardi Cesarino, C., Pinto, M. H., & Paiva Gonçalves, L. W., 2018, Revista Latino-Americana de Enfermagem (RLAE), 26, 1–9. https://doi-org/10.1590/1518-8345.2567.3040
Damares Garcia, G., Alcalá Pompeo, D., Palota Eid, L., Bernardi Cesarino, C., Pinto, M. H., & Paiva Gonçalves, L. W. (2018). Relationship between anxiety, depressive symptoms and compulsive overeating disorder in patients with cardiovascular diseases. Revista Latino-Americana de Enfermagem (RLAE), 26, 1–9. https://doi-org/10.1590/1518-8345.2567.3040
Walden University. (n.d.). Skill builders – Skill builder 14: Hypothesis Testing for Independent Samples t-test. Walden University Blackboard.

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