scholarly journals Uptake of Childcare Arrangements—Grandparental Availability and Availability of Formal Childcare

2021 ◽  
Vol 10 (2) ◽  
pp. 50
Author(s):  
Naomi Biegel ◽  
Karel Neels ◽  
Layla Van den Berg
Keyword(s):  
Decision Making ◽  
Informal Care ◽  
Regression Models ◽  
Local Level ◽  
Formal Care ◽  
Multinomial Regression ◽  
Contextual Data ◽  
Care Arrangement ◽  
Combined Use ◽  
Formal Childcare

Grandparents constitute an important source of childcare to many parents. Focusing on the Belgian context, this paper improves our understanding of childcare decision-making by investigating how formal childcare availability and availability of grandparents affect childcare arrangements. By means of multinomial regression models we simultaneously model uptake of formal and informal childcare by parents. Combining linked microdata from the Belgian censuses with contextual data on childcare at the level of municipalities, we consider formal childcare availability at a local level, while including a wide array of characteristics which may affect grandparental availability. Results indicate that increasing formal care crowds-out informal care as the sole care arrangement, whereas combined use of formal and informal care becomes more prevalent. Characteristics indicating a lack of grandmaternal availability increase uptake of formal care and inhibit to a lesser extent the uptake of combined formal and informal care. While increasing formal care substitutes informal care use, the lack of availability of informal care by grandparents may be problematic, particularly for those families most prone to use informal care.

Widen NomoGram for multinomial logistic regression: an application to staging liver fibrosis in chronic hepatitis C patients

2014 ◽  
Vol 26 (2) ◽  
pp. 823-838 ◽  
Author(s):  
Ilaria Ardoino ◽  
Monica Lanzoni ◽  
Giuseppe Marano ◽  
Patrizia Boracchi ◽  
Elisabetta Sagrini ◽  
...  
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Hepatitis C ◽  
Liver Fibrosis ◽  
Regression Models ◽  
Multinomial Logistic Regression ◽  
Multinomial Regression ◽  
Graphical Tool ◽  
Decision Making Processes ◽  
User Friendly

The interpretation of regression models results can often benefit from the generation of nomograms, ‘user friendly’ graphical devices especially useful for assisting the decision-making processes. However, in the case of multinomial regression models, whenever categorical responses with more than two classes are involved, nomograms cannot be drawn in the conventional way. Such a difficulty in managing and interpreting the outcome could often result in a limitation of the use of multinomial regression in decision-making support. In the present paper, we illustrate the derivation of a non-conventional nomogram for multinomial regression models, intended to overcome this issue. Although it may appear less straightforward at first sight, the proposed methodology allows an easy interpretation of the results of multinomial regression models and makes them more accessible for clinicians and general practitioners too. Development of prediction model based on multinomial logistic regression and of the pertinent graphical tool is illustrated by means of an example involving the prediction of the extent of liver fibrosis in hepatitis C patients by routinely available markers.

The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

2019 ◽  
pp. 1-5
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Skin Necrosis ◽  
Regression Models ◽  
Multivariable Analysis ◽  
P Value ◽  
Flap Necrosis ◽  
Single Institution ◽  
Logistic Regression Models ◽  
The Impact

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

scholarly journals Correction to: MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Matthew D. Koslovsky ◽  
Marina Vannucci
Keyword(s):  
Variable Selection ◽  
Regression Models ◽  
R Package ◽  
Bayesian Variable Selection ◽  
Multinomial Regression

An amendment to this paper has been published and can be accessed via the original article.

Modified ridge and other regularization criteria: A brief review on meaningful regression models

2021 ◽  
Vol 16 (3) ◽  
pp. 225-227
Author(s):  
Stan Lipovetsky
Keyword(s):  
Decision Making ◽  
Regression Models ◽  
Latent Class ◽  
Marketing Research ◽  
Latent Class Models ◽  
Response Models ◽  
Modeling And Analysis ◽  
Regularization Parameters ◽  
Lp Metric ◽  
Class Models

The work describes a series of techniques designed to obtain regression models resistant to multicollinearity and having some other features needed for meaningful results. These models include enhanced ridge-regressions with several regularization parameters, regressions by data segments and by levels of the dependent variable, latent class models, unitary response, models, orthogonal and equidistant regressions, minimization in Lp-metric, and other criteria and models. All the approaches have been practically implemented in various projects and found useful for decision making in economics, management, marketing research, and other fields requiring data modeling and analysis.

Formal and informal long term care work: policy conflict in a liberal welfare state

2017 ◽  
Vol 37 (3/4) ◽  
pp. 134-147 ◽  
Author(s):  
Caroline Murphy ◽  
Thomas Turner
Keyword(s):  
Welfare State ◽  
Informal Care ◽  
Long Term Care ◽  
Care Work ◽  
Formal Care ◽  
Term Care ◽  
Content Type ◽  
Care Workers ◽  
Informal Carers

Purpose The undervaluing of care work, whether conducted informally or formally, has long been subject to debate. While much discussion, and indeed reform has centred on childcare, there is a growing need, particularly in countries with ageing populations, to examine how long-term care (LTC) work is valued. The purpose of this paper is to provide an overview of the way in which employment policies (female labour market participation, retirement age, and precarious work) and social policies (care entitlements and benefits/leave for carers) affect both informal carers and formal care workers in a liberal welfare state with a rapidly ageing population. Design/methodology/approach Drawing the adult worker model the authors use the existing literature on ageing care and employment to examine the approach of a liberal welfare state to care work focusing on both supports for informal carers and job quality in the formal care sector. Findings The research suggests that employment policies advocating increased labour participation, delaying retirement and treating informal care as a form of welfare are at odds with LTC strategies which encourage informal care. Furthermore, the latter policy acts to devalue formal care roles in an economic sense and potentially discourages workers from entering the formal care sector. Originality/value To date research investigating the interplay between employment and LTC policies has focused on either informal or formal care workers. In combining both aspects, we view informal and formal care workers as complementary, interdependent agents in the care process. This underlines the need to develop social policy regarding care and employment which encompasses the needs of each group concurrently.

scholarly journals The Association Between Patients' eHealth Literacy and Satisfaction With Shared Decision-making and Well-being: Multicenter Cross-sectional Study (Preprint)

2020 ◽  
Author(s):  
Richard Huan Xu ◽  
Ling-Ming Zhou ◽  
Eliza Lai-Yi Wong ◽  
Dong Wang
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Regression Models ◽  
Well Being ◽  
Shared Decision ◽  
Background Characteristics ◽  
Cross Sectional ◽  
Ehealth Literacy ◽  
High Level ◽  
The Relationship

BACKGROUND Although previous studies have shown that a high level of health literacy can improve patients’ ability to engage in health-related shared decision-making (SDM) and improve their quality of life, few studies have investigated the role of eHealth literacy in improving patient satisfaction with SDM (SSDM) and well-being. OBJECTIVE This study aims to assess the relationship between patients’ eHealth literacy and their socioeconomic determinants and to investigate the association between patients’ eHealth literacy and their SSDM and well-being. METHODS The data used in this study were obtained from a multicenter cross-sectional survey in China. The eHealth Literacy Scale (eHEALS) and Investigating Choice Experiments Capability Measure for Adults were used to measure patients’ eHealth literacy and capability well-being, respectively. The SSDM was assessed by using a self-administered questionnaire. The Kruskal-Wallis one-way analysis of variance and Wilcoxon signed-rank test were used to compare the differences in the eHEALS, SSDM, and Investigating Choice Experiments Capability Measure for Adults scores of patients with varying background characteristics. Ordinary least square regression models were used to assess the relationship among eHealth literacy, SSDM, and well-being adjusted by patients’ background characteristics. RESULTS A total of 569 patients completed the questionnaire. Patients who were male, were highly educated, were childless, were fully employed, were without chronic conditions, and indicated no depressive disorder reported a higher mean score on the eHEALS. Younger patients (SSDM<sub>≥61 years</sub>=88.6 vs SSDM<sub>16-30 years</sub>=84.2) tended to show higher SSDM. Patients who were rural residents and were well paid were more likely to report good capability well-being. Patients who had a higher SSDM and better capability well-being reported a significantly higher level of eHealth literacy than those who had lower SSDM and poorer capability well-being. The regression models showed a positive relationship between eHealth literacy and both SSDM (<i>β</i>=.22; <i>P</i>&lt;.001) and well-being (<i>β</i>=.26; <i>P</i>&lt;.001) after adjusting for patients’ demographic, socioeconomic status, lifestyle, and health status variables. CONCLUSIONS This study showed that patients with a high level of eHealth literacy are more likely to experience optimal SDM and improved capability well-being. However, patients’ depressive status may alter the relationship between eHealth literacy and SSDM. CLINICALTRIAL

scholarly journals Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248956
Author(s):  
Elizabeth R. Lusczek ◽  
Nicholas E. Ingraham ◽  
Basil S. Karam ◽  
Jennifer Proper ◽  
Lianne Siegel ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Regression Models ◽  
Principal Component ◽  
Hospitalized Patients ◽  
Future Research ◽  
Ensemble Clustering ◽  
Multinomial Regression ◽  
Tailored Therapy ◽  
Clinical Phenotypes ◽  
Multivariable Models

Purpose Heterogeneity has been observed in outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of clinical phenotypes may facilitate tailored therapy and improve outcomes. The purpose of this study is to identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. Methods This is a retrospective analysis of COVID-19 patients from March 7, 2020 to August 25, 2020 at 14 U.S. hospitals. Ensemble clustering was performed on 33 variables collected within 72 hours of admission. Principal component analysis was performed to visualize variable contributions to clustering. Multinomial regression models were fit to compare patient comorbidities across phenotypes. Multivariable models were fit to estimate associations between phenotype and in-hospital complications and clinical outcomes. Results The database included 1,022 hospitalized patients with COVID-19. Three clinical phenotypes were identified (I, II, III), with 236 [23.1%] patients in phenotype I, 613 [60%] patients in phenotype II, and 173 [16.9%] patients in phenotype III. Patients with respiratory comorbidities were most commonly phenotype III (p = 0.002), while patients with hematologic, renal, and cardiac (all p<0.001) comorbidities were most commonly phenotype I. Adjusted odds of respiratory, renal, hepatic, metabolic (all p<0.001), and hematological (p = 0.02) complications were highest for phenotype I. Phenotypes I and II were associated with 7.30-fold (HR:7.30, 95% CI:(3.11–17.17), p<0.001) and 2.57-fold (HR:2.57, 95% CI:(1.10–6.00), p = 0.03) increases in hazard of death relative to phenotype III. Conclusion We identified three clinical COVID-19 phenotypes, reflecting patient populations with different comorbidities, complications, and clinical outcomes. Future research is needed to determine the utility of these phenotypes in clinical practice and trial design.

scholarly journals Advancing Relevance, Credibility, Legitimacy, and Effectiveness as a Heuristic for Local-Parallel Scenarios

2021 ◽  
Vol 3 ◽  
Author(s):  
Nicholas A. Cradock-Henry ◽  
Bob Frame
Keyword(s):  
Decision Making ◽  
Local Level ◽  
Global Scale ◽  
Global Changes ◽  
Scenario Development ◽  
Personal Time ◽  
Trade Offs ◽  
Economic Trends ◽  
Decision Making Processes ◽  
Competing Priorities

The parallel scenario process provides a framework for developing plausible scenarios of future conditions. Combining greenhouse gas emissions, social and economic trends, and policy responses, it enables researchers and policy makers to consider global-scale interactions, impacts and implications of climate change. Increasingly, researchers are developing extended scenarios, based on this framework, and incorporating them into adaptation planning and decision-making processes at the local level. To enable the identification of possible impacts and assess vulnerability, these local-parallel scenarios must successfully accommodate diverse knowledge systems, multiple values, and competing priorities including both “top down” modeling and “bottom-up” participatory processes. They must link across scales, to account for the ways in which global changes affect and influence decision-making in local places. Due to the growing use of scenarios, there is value in assessing these developments using criteria or, more specifically, heuristics that may be implicitly acknowledged rather than formally monitored and evaluated. In this Perspective, we reflect on various contributions regarding the value of heuristics and propose the adoption of current definitions for Relevance, Credibility, and Legitimacy for guiding local scenario development as the most useful as well as using Effectiveness for evaluation purposes. We summarize the internal trade-offs (personal time, clarity-complexity, speed-quality, push-pull) and the external stressors (equity and the role of science in society) that influence the extent to which heuristics are used as “rules of thumb,” rather than formal assessment. These heuristics may help refine the process of extending the parallel scenario framework to the local and enable cross-case comparisons.

scholarly journals Housing associations diversifying into market renting: local contexts and (re)interpretation shaping strategic decision making

2020 ◽  
Vol 11 (1) ◽  
pp. 3-20
Author(s):  
Julie Clarke ◽  
Rachel Kirk
Keyword(s):  
Decision Making ◽  
Housing Association ◽  
Local Level ◽  
Third Sector ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Strategic Decisions ◽  
Housing Associations ◽  
Commercial Activity ◽  
Hybrid Organisations

Within the context of housing associations as fluid third sector hybrid organisations, this article examines the dynamics of strategic decision making in relation to diversification into the market rented sector. A convergence of factors shaped an agenda for associations to engage with such commercial activity, crystallising debates about opportunities versus tensions and the remit of organisations. Qualitative research with senior housing association professionals operating in northern England illustrates the significance of external local and internal organisational contexts in making and justifying decisions; this is highlighted within an emergent typology of organisational responses. Depending on interpretation, the interplay between social and financial justifications varied, including legitimising activity within a broader social purpose. The potential for (re)interpreting parameters illustrates the importance of understanding the variety and complexity of interacting dynamics that influence the strategic decisions of third sector hybrid organisations and what they deliver at the local level.

Citizen-Government Collaborative Environment Using Social Networks

2019 ◽  
pp. 152-165
Author(s):  
Hany Abdelghaffar ◽  
Lobna Hassan
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Social Network ◽  
Local Governments ◽  
Local Level ◽  
Quantitative Approach ◽  
Collaborative Environment ◽  
Electronic Democracy ◽  
Democratic Change ◽  
The World

Electronic democracy is a concept which is used in some countries around the world with mixed success. Social networks helped in facilitating democracy and democratic change in several countries suggesting that they could be utilized as an e-democracy tool. This research proposed a new model of how the decision-making process for local governments could be improved via social networks. Quantitative approach was used to investigate how the use of a social network amongst people living in the same suburb could improve decision making on the local level. Findings showed that awareness building, deliberation, and consultation factors could be used to affect the decision making for their local governments.

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