Manipulating the data

Pallant, Julie

doi:10.4324/9781003117445-11

Cited by 195 publications

(296 citation statements)

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“…The parental health‐seeking behavior relating to the use of CAM before seeing the medical officer was another factor increasing the risk of patient delays. In this study, the use of CAM was found to be a strong predictor of patient delay, as in previous studies in Indonesia and other LMICs or even high‐income countries 16,32–48 . CAM is very popular, and a systematic review of CAM prevalence surveys worldwide found a prevalence of 23%–62%, and for over‐the‐counter CAM 25%–46%, and also commonly used for children, with prevalence estimates from 12% to 51% in the United States, Canada, Australia, and the United Kingdom 49 .…”

Section: Discussionsupporting

confidence: 78%

“…Quantitative Bivariable analyses were performed using chi-square analyses, and multivariable analyses were carried out using a logistic regression model. 36 Variables with p < .25 in the bivariate analysis and relevant…”

Section: Discussionmentioning

confidence: 99%

“…In this study, the use of CAM was found to be a strong predictor of patient delay, as in previous studies in Indonesia and other LMICs or even high-income countries. 16,[32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48] CAM is very popular, and a systematic review of CAM prevalence surveys worldwide found a prevalence of 23%-62%, and for over-the-counter CAM 25%-46%, and also commonly used for children, with prevalence estimates from 12% to 51% in the United States, Canada, Australia, and the United Kingdom. 49 As per the Indonesia Family Life Survey in 2014-2015, from 15,739 children (0-14 years), the proportion who found prevalence of traditional or herbal medicines use was 6.2%, the use of traditional health practitioners was 3.4%, and the use of traditional medicines and/or traditional practitioners was 8.8%.…”

Section: Discussionmentioning

confidence: 99%

“…Descriptive statistics included percentages and measurements of the central tendency (median and interquartile range [IQR]) for age, birth order, number of children, and distance to the first health facility. Bivariable analyses were performed using chi‐square analyses, and multivariable analyses were carried out using a logistic regression model 36 . Variables with p < .25 in the bivariate analysis and relevant were included in the multivariate analysis.…”

Section: Methodsmentioning

confidence: 99%

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Type of cancer and complementary and alternative medicine are determinant factors for the patient delay experienced by children with cancer: A study in West Java, Indonesia

Sari

Devansyah

Modjaningrat

et al. 2023

Pediatric Blood & Cancer

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Introduction Most pediatric cancer patients in developing countries present at an advanced stage due to delayed diagnosis, being an important barrier to effective care. The objective of this study was to evaluate the associated factor of patient delay and explore significant parental practice‐associated risk factor to patient delay. Methods This was a sequential mixed methodology, utilizing data from the Indonesian Pediatric Cancer Registry for clinical variables and completed interviews with parents using structured questionnaires to obtain their sociodemographic data. A binary logistic regression analysis model was fitted to identify factors associated with patient delay. Additional semi‐structured interviews related to parental practice of using complementary and alternative medicine (CAM) were administered to 30 parents. Thematic framework analysis was performed on qualitative data to explore determinant factors of parental practice of using CAM. Results We interviewed 356 parents with children with cancer. The median patient delay was 14 days (interquartile range [IQR]: 6–46.5 days). The most extended delay was in patients with malignant bone tumors (median 66, IQR: 14–126). In multivariable logistic regression analysis, solid cancer (odds ratio [OR] = 5.22, 95% confidence interval [CI]: 2.79–9.77, p < .001) and use of CAM (OR = 1.86, 95% CI: 1.13–3.08, p = .015) were associated with patient delay. Qualitative interviews highlighted key issues relative to determinant parental factors using CAM, including vague initial childhood cancer symptoms, parental health‐seeking behavior, CAM availability and accessibility, also barriers of healthcare facilities. Conclusion Type of cancer and use of CAM are essential factors that cause patient delay. It should be addressed in the future childhood cancer awareness and childhood cancer diagnosis pathway.

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Section: Discussionsupporting

confidence: 78%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Type of cancer and complementary and alternative medicine are determinant factors for the patient delay experienced by children with cancer: A study in West Java, Indonesia

Sari

Devansyah

Modjaningrat

et al. 2023

Pediatric Blood & Cancer

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“…Prior to data analysis, Cronbach's alpha was used to examine internal consistency of the 23 factors. Alpha values greater than 0.7 are regarded as sufficient (Pallant, 2010). The results of the consistency test gave 0.873 for the 23 factors providing evidence that all factors have high internal consistency and therefore are reliable.…”

Section: Brief Description Of Multiple Regression Analysis (Mra)mentioning

confidence: 93%

Barriers to BIM for facilities management adoption in Nigeria: a multivariate analysis

Ikediashi

Ansa

Ujene

et al. 2022

IJBPA

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PurposeBuilding information modelling (BIM) has been established in the literature as a successful platform that creates an intelligent virtual model for processing data from conceptual design through construction to operational stage of a facility. However, its adoption for facilities management (FM) provision in Nigeria has been slow due to inherent barriers. The aim of this paper is to (1) assess and categorise using factor analysis BIM for FM barriers and (2) model the barriers using stakeholders' personal/professional attributes.Design/methodology/approachAnchored on quantitative research design, 205 copies of structured questionnaire were distributed to key stakeholders and facilities managers in Nigeria's three strategic cities while 135 valid responses were received giving a response rate of 65.8%. Data collected were analysed using descriptive statistics while multiple regression analysis was used to model the barriers. Kruskal Wallis test was used to test the only hypothesis postulated for the study.FindingsThe study established lack of awareness of BIM for FM, poor supporting infrastructure for Internet services, and lack of education and training as the top three rated barriers militating against adoption of BIM for FM in Nigeria while corruption, widespread mistakes and errors and cultural issues were established as the three least rated barriers. Besides, findings also established eight underlying factors that explained 23 barrier factors used for the study which were subsequently used to develop eight regression models. In effect, gender, professional affiliation, organisation, experience, education, expertise, BIM for FM project type, and location were found to statistically predict the 8 extracted factors driving perceived barriers of BIM for FM adoption in Nigeria.Practical implicationsThe study has provided a framework of barrier factors to help stakeholders identify specific barriers for which appropriate measures can be taken to ameliorate consequences of the perceived barriers. Meanwhile, an improved and rejuvenated advocacy on inherent benefits of BIM for facilities management by frontline stakeholders could potentially steer up interests and increased participation of stakeholders on BIM for FM.Originality/valueThe unique study developed the first ever regression model that links BIM for FM barriers to professional attributes of facilities management stakeholders in Nigeria.

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Anatomy in the metaverse: Exploring student technology acceptance through the UTAUT2 model

Kalınkara,

Özdemir

2023

Anatomical Sciences Ed

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The impact of technology on educational domains has been a subject of research for many years. Therefore, understanding how students perceive and utilize technologies for educational purposes is crucial. Especially in a critical subject like anatomy education, it is essential to employ various models to determine students' technology acceptance and usage levels. One of these models is the unified theory of acceptance and use of technology‐2 (UTAUT2). In this study, the acceptance and usage levels of metaverse technology by students in the context of anatomy education in the metaverse environment have been investigated within the framework of the UTAUT2 model. The study was conducted with students from the Department of Midwifery at the Faculty of Health Sciences during the fall semester of the 2022–2023 academic year. After 6 weeks of anatomy education in the metaverse environment, the student's acceptance and usage levels of metaverse technology were assessed using the UTAUT2 scale. The collected data were analyzed using the partial least squares structural equation modeling method. The research has revealed the technology acceptance and usage levels of students who utilized metaverse technology in anatomy education. According to the obtained results, it has been observed that social influence affects behavioral intention, facilitating conditions influence behavioral intention, and habit variable affects behavioral intention, while habit, in turn, influences usage. Other variables explain behavioral intention with a proportion of 75.30%, whereas other variables explain usage behavior with 54.90%. Upon analyzing the responses to the UTAUT2 scale, it has been concluded that there is the highest level of participation in hedonic motivation. In contrast, the habit variable has the lowest participation level. The findings of this study have enabled the identification of the impacts of metaverse technologies on anatomy and health education. These results will likely contribute to improving the utilization of metaverse technologies in anatomy and health education.

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Manipulating the data

Cited by 195 publications

References 0 publications

Type of cancer and complementary and alternative medicine are determinant factors for the patient delay experienced by children with cancer: A study in West Java, Indonesia

Type of cancer and complementary and alternative medicine are determinant factors for the patient delay experienced by children with cancer: A study in West Java, Indonesia

Barriers to BIM for facilities management adoption in Nigeria: a multivariate analysis

Anatomy in the metaverse: Exploring student technology acceptance through the UTAUT2 model

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