scholarly journals The social determinants of health and health seeking behaviour in populations affected by armed conflict: a qualitative systematic review

2021 ◽  
pp. 1-26
Author(s):  
Elsa Munezero ◽  
Sarkis Manoukian
Keyword(s):  
Systematic Review ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Armed Conflict ◽  
Determinants Of Health ◽  
Health Seeking Behaviour ◽  
Health Seeking ◽  
Qualitative Systematic Review ◽  
The Social

scholarly journals Are COVID-19 models blind to the social determinants of health? A systematic review protocol

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e048995
Author(s):  
Ava John-Baptiste ◽  
Marc S Moulin ◽  
Shehzad Ali
Keyword(s):  
Infectious Disease ◽  
Systematic Review ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Social Factors ◽  
Determinants Of Health ◽  
Disease Models ◽  
The Social ◽  
Modelling Studies ◽  
Infectious Disease Models

IntroductionInfectious disease models are important tools to inform public health policy decisions. These models are primarily based on an average population approach and often ignore the role of social determinants in predicting the course of a pandemic and the impact of policy interventions. Ignoring social determinants in models may cause or exacerbate inequalities. This limitation has not been previously explored in the context of the current pandemic, where COVID-19 has been found to disproportionately affect marginalised racial, ethnic and socioeconomic groups. Therefore, our primary goal is to identify the extent to which COVID-19 models incorporate the social determinants of health in predicting outcomes of the pandemic.Methods and analysisWe will search MEDLINE, EMBASE, Cochrane Library and Web of Science databases from December 2019 to August 2020. We will assess all infectious disease modelling studies for inclusion of social factors that meet the following criteria: (a) focused on human spread of SARS-CoV-2; (b) modelling studies; (c) interventional or non-interventional studies; and (d) focused on one of the following outcomes: COVID-19-related outcomes (eg, cases, deaths), non-COVID-19-related outcomes (ie, impacts of the pandemic or control policies on other health conditions or health services), or impact of the pandemic or control policies on economic outcomes. Data will only be extracted from models incorporating social factors. We will report the percentage of models that considered social factors, indicate which social factors were considered, and describe how social factors were incorporated into the conceptualisation and implementation of the infectious disease models. The extracted data will also be used to create a narrative synthesis of the results.Ethics and disseminationEthics approval is not required as only secondary data will be collected. The results of this systematic review will be disseminated through peer-reviewed publication and conference proceedings.PROSPERO registration numberCRD42020207706.

Mobile Health Interventions to Support Caregivers of Older Adults: An Equity-Focused Systematic Review (Preprint)

2021 ◽  
Author(s):  
Anna Garnett ◽  
Melissa Northwood ◽  
Justine Ting ◽  
Ruheena Sangrar
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Social Determinants Of Health ◽  
Mobile Health ◽  
Social Determinants ◽  
Determinants Of Health ◽  
Health Technologies ◽  
Health And Wellbeing ◽  
The Social ◽  
The Impact

BACKGROUND Caregivers provide crucial support to older adults so they can remain safely in their homes as they age. Over time, caregivers’ own health can be negatively impacted by their caregiving role. The social determinants of health, such as gender and socioeconomic status, can influence assuming a caregiving role as well as the impacts of caregiving on the caregiver. While programs exist to support caregivers, uptake of these services does not match the need for services expressed by caregivers. Research suggests that supportive interventions offered via mobile health technologies have the potential to increase caregiver accessibility of supportive services. However, a knowledge gap exists regarding the extent to which the social determinants of health are considered in the design, implementation, and evaluation of mobile health (mHealth) interventions intended to support caregivers of older adults. Furthermore, a comprehensive review of the impact of mHealth interventions in this population does not exist. OBJECTIVE To conduct a systematic review to: (1) determine how health inequities are considered in the design, implementation, and evaluation of mHealth interventions for caregivers of older adults using Cochrane-Equity's PROGRESS-Plus framework; and (2) synthesize evidence of the impacts of caregiver-focused mHealth interventions. METHODS A systematic review was conducted in five databases and articles published between January 2010 and June 2021 were included if they evaluated or explored the impacts of mHealth interventions on the health and wellbeing of informal caregivers of older adults. mHealth interventions were defined as those that caregivers of older adults accessed via mobile or wireless devices. RESULTS A total of 28 articles met the inclusion criteria and were included in the systematic review. The interventions evaluated by the included studies sought to help caregivers make connections with services, facilitate the caregiving process, and promote the caregivers’ health and wellbeing. The PROGRESS-Plus framework factors were mainly considered in the results, discussion, and limitations sections of included studies. Some PROGRESS-Plus factors such as sexual orientation, religion and occupation, received little to no consideration in all phases of intervention design, implementation, or evaluation. Overall, findings of this review suggest that mHealth interventions were positively received by users. Such interventions may have the potential to reduce caregiver burden and positively impact caregivers’ physical and mental health while supporting them in their caregiving role. Study findings highlight the importance of available supports to help facilitate caregivers’ use of mHealth interventions particularly early on as well as the use of appropriate language and text. CONCLUSIONS Successful uptake and spread of mHealth interventions to support caregivers of older adults will depend on creating opportunities for inclusive involvement of a broad range of stakeholders at all stages of design, implementation, and assessment. CLINICALTRIAL PROSPERO CRD42021239584; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=239584

scholarly journals Examining the relation between the subjective and objective social status with health reported needs and health-seeking behaviour in Dande, Angola

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Edite Vila Nova Rosário ◽  
Milton Severo ◽  
Diogo Francisco ◽  
Miguel Brito ◽  
Diogo Costa
Keyword(s):  
Social Status ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Subjective Perception ◽  
Socioeconomic Indicators ◽  
Health Seeking Behaviour ◽  
Health Seeking ◽  
The Social ◽  
Reported Health ◽  
Macarthur Scale

Abstract Background Assessing subjective social status (SSS) may be easily accommodated in the context of a Health and Demographic Surveillance System (HDSS). To our knowledge, no prior studies have examined the association of SSS and health in Angola. Subjective socioeconomic measures may provide a rapid assessment of a relevant social status construct, important for studying health inequalities. In this study, we addressed social determinants of health by examining the relationship between the subjective and objective social status, reported health and healthcare-seeking behaviour. Methods This research results from a cross-sectional study performed during 2015 in the Dande HDSS, in Angola. We tested the application of the MacArthur scale as a measure of SSS in a developing setting, in a sample of 12,246 households. First, we investigated its relation to objective socioeconomic indicators, and then we explored how subjective and objective social status associate with health reported needs and health-seeking behaviour of the surveyed population. Chi-square, ANOVA tests, and Receiver Operating Characteristics (ROC) Curves analysis were computed for testing relationships between subjective status ladder quartiles, sociodemographic and household characteristics. Logistic regression was used to examine the influence of subjective perception of status in self-reported health and health-seeking behaviour. Results Our findings suggest that the SSS follows a gradient distribution obtained with more objective socioeconomic indicators. Additionally, we found that subjective perception of status influence health needs reporting and health-seeking behaviour and its significant effect remained after controlling for the objective socioeconomic markers. Individuals standing in the second quartile of the social ladder have more odds of reporting illness and those in the highest quartiles of the ladder were twice more likely (OR = 2.23, 95% CI = 1.52–3.26) to seek help from formal health services than those at the bottom of the ladder. Conclusions The MacArthur Scale is a valuable tool to measure SSS in the Dande HDSS, relevant for studying socioeconomic disparities and health inequalities. It is also an easier alternative to traditional measures such as income, usually difficult to measure in developing settings. The social perception of status should be considered as a complement with objective indicators when exploring social determinants of health.

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