Infer More, Describe Less: More Powerful Survey Conclusions through Easy Inferential Tests.

Hightower, Christy; Scott, Kerry

doi:10.29173/istl1550

Cited by 7 publications

(3 citation statements)

References 2 publications

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“…An online sample size calculator was used to determine the sample size (Raosoft, 2020). The Raosoft calculator was recommended by Hightower and Kelly (2012) for calculating sample size and margins of error in survey data. For assuming 5% margin of error, 95% confidence level, and response distribution of 50%, the minimum sample size was 385 participants.…”

Section: Methodsmentioning

confidence: 99%

Changes in oral home care and smoking habits during COVID‐19 pandemic: A cross‐sectional study

Atieh,

Aldhanhani,

Shah

et al. 2024

Clinical & Exp Dental Res

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ObjectivesThe coronavirus disease‐19 (COVID‐19) pandemic has caused disruption in the health behavior in many aspects of life. While hand hygiene was promoted as one of the precautionary measures to mitigate and contain COVID‐19, oral health and smoking might have received less attention in the media campaigns. The aim of this study was to examine health behavioral changes in terms of oral home care habits, smoking, and perception of dental care during the COVID‐19 pandemic.Material and MethodsAn online survey was designed to assess oral home care, smoking habits, and attitude toward dental services of participants aged 18 years and older. The data were collected between September and November 2021. The strength of association between changes in oral home care habits, smoking, and attitude toward invasive/long dental procedures and each variable was measured by χ2 analysis. Estimates of relative risk were also calculated for all variables. Predictors of avoiding dental procedures were estimated by a binary logistic regression.ResultsA total of 532 participants, based in the United Arab Emirates, took part in this online survey with a response rate of 88.7%. The age of the participants ranged between 18 and 67 with mean age of 34.9 ± 9.0 years. The majority of the participants have adopted changes in their routine oral home care habits, with 82.1% of them changing the toothbrush more frequently. Participants who changed their oral home care habits were more likely to have received sufficient information on the importance of maintaining oral health. Likewise, the changes in smoking habits were significantly associated with receiving information on the relationship between smoking and the severity of the COVID‐19 (p < 0.001).ConclusionsThe findings showed that positive behavior toward oral home care and smoking was noticed during the pandemic particularly when public receives sufficient and up‐to‐date information.

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Section: Methodsmentioning

confidence: 99%

Changes in oral home care and smoking habits during COVID‐19 pandemic: A cross‐sectional study

Atieh,

Aldhanhani,

Shah

et al. 2024

Clinical & Exp Dental Res

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“…We used a validated Rao soft sample size calculator suitable for calculation of sample sizes in surveys [60] to estimate a minimum representative sample size for school children. Considering the combined population size of approximately 70,000 from the Education Management Information System for both Gauteng and Mpumalanga 2017/2018, and a 95% confidence level, a minimum representative sample size of 383 was calculated to achieve the objective of this study, and a final sample of 903 school children was obtained: MRS = 390 and GUS = 513.…”

Section: Sample Size and Sampling Techniquementioning

confidence: 99%

Comparison of Malnutrition Indicators and Associated Socio-Demographic Factors among Children in Rural and Urban Public Primary Schools in South Africa

Hlahla,

Kunene,

Mphekgwana

et al. 2023

Children

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Most children in South Africa attending public schools are predisposed to malnutrition due to poor infrastructure and social inequality. This is despite the implementation of the National School Nutrition Programme to address barriers to learning associated with hunger and malnutrition and the National Development Plan to reduce child malnutrition through provision of social grants. In view of this, we compared malnutrition indicators and associated socio-demographic factors among children in rural Mpumalanga and urban Gauteng in South African public primary schools selected using a multistage cluster random sampling. A validated researcher-administered questionnaire was used to collect socio-demographic data of caregivers, along with primary school children data collected on age, sex, learning grade, and anthropometric measures. Malnutrition indicators, which are stunting (low height-for-age z-scores), underweight (low weight-for-age z-scores), thinness (low body-mass-index-for-age z-scores), and overweight/obesity (high body mass index) were computed using WHO Anthro Plus 1.0.4 and data were analyzed using Stata 18. A total of 903 children (rural = 390 and urban = 513) with a mean age of 10 ± 2 years in the foundation phase (learning grades one to three) and the intermediate learning phase (learning grades four to seven) participated with their caregivers (mean age: 39 ± 8 years). Significant levels of poor socio-demographic status were observed among caregivers living in the rural setting compared to in the urban setting. Overall, thinness (18%), stunting (12%), underweight (10%), and overweight/obesity (24%) were observed among school children. Children in the rural schools had a significantly higher prevalence of stunting (20% vs. 3%; p < 0.0001), underweight (17% vs. 2%; p < 0.0001) and thinness (28% vs. 7%; p < 0.001) than their urban counterparts. In the urban, the odds of stunting, underweight and thinness were less among school children, while overweight/obesity was twice as likely in the urban setting. The multivariate final model showed lower odds of underweight [adjusted odds ratio (AOR) = 0.16; 95% confidence interval (CI): 0.06–0.42] and stunting [AOR = 0.33; 95% CI: 0.13–0.87] in the urban compared to the rural schools. The association of stunting with sex [AOR =0.53; 95% CI: 0.30–0.94] and the intermediate learning phase [AOR = 7.87; 95% CI: 4.48–13.82] was observed in the rural setting, while thinness was associated with living in households with an income of USD 52.51 to USD 262.60/month [AOR = 2.89; 95% CI: 1.01–8.24] and receiving the child social grant [AOR = 2.49; 0.90–6.86] in the urban setting. Overweight/obesity was associated with living in a household with an income of USD 52.51 to USD 262.60/month [AOR = 1.80; 95% CI: 1.02–3.10]. The findings suggest nutritional intervention approaches that are accustomed to the context of settings to effectively tackle malnutrition.

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“…According to data obtained from RDTC (2018b) the study consisted sample of 101 persons with albinism which was calculated using the Raosoft Sample Size Calculator using confidence interval at 95%, margin of error of 5% and skewness level (response distribution) 50%. Raosoft sample size calculator was used because it is the best and modern way to illustrate the interconnectedness of the margin of error, sample size and confidence level (Hightower & Scott, 2012).…”

Section: Sample Sizementioning

confidence: 99%

Factors That Affect Access to Sunscreens: A Study of Persons with Albinism in Moshi Municipal, Tanzania

Fabian¹

2022

JSS

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People with albinism are particularly vulnerable to sunburn and skin cancer because of the reduction or absence of melanin in the body. The aim of the research was to analyze the factors that affect persons with albinism access to sunscreens. The study took a form of a cross-sectional design and it was conducted in Moshi municipality. Simple random sampling was used to select the population of 101 PWA who belong to Moshi Municipality but only 79 PWA manage to return questionnaires well enough to be used in the study. This study collected both primary and secondary data whereas household survey using self-administered questionnaire was used. Data were analyzed using descriptive analysis where frequencies and percentages were calculated and interpreted. Moreover, multiple regression analysis was applied to analyze the factors affecting PWA access to sunscreens. The study revealed that PWA are aware of sunscreen and they are knowledgeable about the methods used to protect skin from harmful sunrays. Furthermore, distance was revealed to be one of social factors that affect persons with albinism access to sunscreen but to those who live beyond Moshi Municipal. On the other hand income and price significantly affect persons with albinism on access to sunscreen. The study concluded that people with albinism are aware of the need to protect themselves from the effects of sunrays and are knowledgeable about the methods of protection, whereas travel distance, income and price of sunscreen were the main factors that affect persons with albinism access to sunscreen. The study recommended that government should provide sunscreen products for free or lower the price so that sunscreens would be accessible to persons with albinism. Moreover, it was recommended that distribution centers should be located near residential areas of persons with albinism.

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Infer More, Describe Less: More Powerful Survey Conclusions through Easy Inferential Tests.

Cited by 7 publications

References 2 publications

Changes in oral home care and smoking habits during COVID‐19 pandemic: A cross‐sectional study

Changes in oral home care and smoking habits during COVID‐19 pandemic: A cross‐sectional study

Comparison of Malnutrition Indicators and Associated Socio-Demographic Factors among Children in Rural and Urban Public Primary Schools in South Africa

Factors That Affect Access to Sunscreens: A Study of Persons with Albinism in Moshi Municipal, Tanzania

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