Digital Storytelling Interventions for Cardiovascular Disease Risk Factor Modification: A Scoping Review

Akinosun, Adewale Samuel; Grant, Noreen; Polson, Rob; Coyle, David; Leslie, Stephen J; Grindle, Mark

doi:10.18848/2156-8960/cgp/v11i01/209-224

Cited by 3 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…22 Rurality and obesity: This study deviates from previous research ndings on intervention design subsidy that compare rural to urban areas. 13 The results show that the chances of exposure (Co-eff=20, P=.99) to obesity in the study population are high and equal for both rural and urban groups. This suggests that rural dwellers may not be regionally deprived when compared with their urban counterparts within a geographically remote population as also re ected in the study done by Teckle et al 28 However, this nding could not a rm socio-economic status for the study population as SIMD ranking does not indicate a signi cant level of association with all the CVD risk factor determinants except in cholesterol concentration determinant and the smoking groups.…”

Section: Discussionmentioning

confidence: 80%

“…Common examples include, health training and coaching sessions, health promotion and campaigns, and community-based participatory research. 13 Storytelling, which is also referred to as a narrative, has historically been used as a means of in uencing public opinion and regulating human behaviour. More recently on a digital platform, it has been used for marketing and politics.…”

Section: Introduction Backgroundmentioning

confidence: 99%

See 1 more Smart Citation

Cardiovascular Disease Behavioural Risk Factors in Rural Interventions: Cross-Sectional Study.

Akinosun

Kamya

Watt

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Aims:This study aims to 1) assess the prevalence of cardiovascular disease (CVD) behavioural risk factors in patients who have undergone percutaneous coronary intervention (PCI) 2) identify target risk factor(s) for behaviour modification intervention, and 3) develop an analytical model to define cluster(s) of risk factors which could help make any generic intervention more targeted to the local patient population.Subject and Methods:Study patients with at least one CVD behavioural risk factors living in a rural region. The study used STROBE methodology for cross-sectional studies. Demographic and clinical data of patients (n=2025) were collected at the point of admission for PCI between 04.01.2016 to 31.12.2019. Collected data distributions were analysed by CVD behavioural risk factors for prevalence, associations, and direction of associations. Cluster definition was measured by assignment of a unit score each for overall level of prevalence and significance of associations, and general logistics modelling for direction and significance of risk.Results:The mean (SD) age was 69.47(±10.93) years [95% CI (68.99 - 69.94)]. The key risk factors were hyperlipidaemia, hypertension, and elevated body mass index (BMI). Approximately 40% of the population have multiple risk factor counts of two. Analytical measures revealed a population risk factor cluster with elevated BMI [77.5% (1570/2025)] that is mostly either hyperlipidaemic [9.43%, co-eff. (17), P=.007] or hypertensive [22.72%, co-eff. (17), P=.99] as key risk factor clusters.Conclusion:Carefully modelled analyses revealed clustered behavioural risk associated with elevated BMI. This information would support a strategy for applying targeted clusters in novel interventions to improve implementation efficiency.Conclusion: Risk factors, cardiovascular disease, obesity, and percutaneous coronary intervention.

show abstract

Section: Discussionmentioning

confidence: 80%

Section: Introduction Backgroundmentioning

confidence: 99%

Cardiovascular Disease Behavioural Risk Factors in Rural Interventions: Cross-Sectional Study.

Akinosun

Kamya

Watt

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Objective [1], [13], [52], [55] Story screening [3], [5], [13], [15], [17], [19], [20], [21], [22], [24], [25], [26], [27], [28], [30], [32], [34], [35], [37], [38], [51], [53] Content analysis [17], [22], [24], [33], [34], [37], [43], [52], [53] Health information story [1], [2], [3], [26], [27], [28], [30], [32], [33], [34], [35], [39], [40], [42], [43],…”

Section: Story Informationmentioning

confidence: 99%

“…How to tell a story [1], [5], [18], [24], [27], [34], [37], [41], [44], [46], [51], [52], [53], [55] Narrator/ listener/actor [1], [5], [13], [19], [20], [22], [24], [25], [27], [28], [32], [37], [39], [41], [44], [46], [49], [50] Narration [2], [3], [13], [17], [22], [29], [37], [39], [50], [52], [53], [55] Creative text [1], [2], [3], [13], [26], [28],…”

Section: Characteristics Of the Speaker/listenermentioning

confidence: 99%

See 1 more Smart Citation

A Systematic Review of the Intelligent Digital Storytelling Process in Disseminating Health Information

Eumbunnapong

Nilsook²,

Wannapiroon³

2023

Int. J. Onl. Eng.

View full text Add to dashboard Cite

Digital storytelling is a new concept in education that involves creating meaning. It is a tool with great potential, but in Thailand, it is currently not very popular in terms of sharing stories about disease. This review analyzes the components and processes of intelligent digital storytelling to aid the development of an intelligent digital storytelling platform for disseminating health information. Based on the synthesis of relevant documents, the research process involves 9 main steps: 1) identifying the review objectives, 2) reviewing research questions, 3) determining inclusion criteria, 4) finding relevant studies, 5) selecting documents, 6) data extraction, 7) arriving at a conclusion, 8) document synthesis and 9) discussion of the results. A study of articles from the PRISMA Checklist published between 2017 and 2022 revealed that ultimately only 47 articles met the inclusion criteria. From the analysis of the data, it was found that there are four main elements and 16 sub-components of intelligent digital storytelling. There are 12 steps in the process of intelligent digital storytelling with regard to health information dissemination. The optimal length of an intelligent digital narrative video clip relating to health information dissemination is approximately 2-5 minutes when it comes to achieving the best knowledge of health information.

show abstract

Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study

Akinosun,

Kamya,

Watt

et al. 2023

Sci Rep

View full text Add to dashboard Cite

This study aims to (1) assess the distribution of variables within the population and the prevalence of cardiovascular disease (CVD) behavioural risk factors in patients, (2) identify target risk factor(s) for behaviour modification intervention, and (3) develop an analytical model to define cluster(s) of risk factors which could help make any generic intervention more targeted to the local patient population. Study patients with at least one CVD behavioural risk factor living in a rural region of the Scottish Highlands. The study used the STROBE methodology for cross-sectional studies. Demographic and clinical data of patients (n = 2025) in NHS Highlands hospital were collected at the point of admission for PCI between 04.01.2016 and 31.12.2019. Collected data distributions were analysed by CVD behavioural risk factors for prevalence, associations, and direction of associations. Cluster definition was measured by assignment of a unit score each for the overall level of prevalence and significance of associations, and general logistics modelling for direction and significance of the risk. The mean (SD) age was 69.47(± 10.93) years [95% CI (68.99–69.94)]. The key risk factors were hyperlipidaemia, hypertension, and elevated body mass index (BMI). Approximately 40% of the population have multiple risk factor counts of two. Analytical measures revealed a population risk factor cluster with elevated BMI [77.5% (1570/2025)] that is mostly either hyperlipidaemic [9.43%, co-eff. (17), P = 0.007] or hypertensive [22.72%, co-eff. (17), P = 0.99] as key risk factor clusters. Carefully modelled analyses revealed clustered risk associated with elevated BMI. This information would support a strategy for targeting risk factor clusters in novel interventions to improve implementation efficiency. Exposure to and outcome of an elevated BMI is linked more to the population’s socio-economic outcomes rather than to regional rurality or urbanity.

show abstract

Digital Storytelling Interventions for Cardiovascular Disease Risk Factor Modification: A Scoping Review

Cited by 3 publications

References 0 publications

Cardiovascular Disease Behavioural Risk Factors in Rural Interventions: Cross-Sectional Study.

Cardiovascular Disease Behavioural Risk Factors in Rural Interventions: Cross-Sectional Study.

A Systematic Review of the Intelligent Digital Storytelling Process in Disseminating Health Information

Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study

Contact Info

Product

Resources

About