Patterns of SARS-CoV-2 testing preferences in a national cohort in the United States: Latent class analysis of a discrete choice experiment (Preprint)

ObjectiveDoctor absenteeism is widespread in Bangladesh, and the perspectives of the actors involved are insufficiently understood. This paper sought to elicit preferences of doctors over aspects of jobs in rural areas in Bangladesh that can help to inform the development of packages of policy interventions that may persuade them to stay at their posts.MethodsWe conducted a discrete choice experiment with 308 doctors across four hospitals in Dhaka, Bangladesh. Four attributes of rural postings were included based on a literature review, qualitative research and a consensus-building workshop with policymakers and key health-system stakeholders: relationship with the community, security measures, attendance-based policies and incentive payments. Respondents’ choices were analysed with mixed multinomial logistic and latent class models and were used to simulate the likely uptake of jobs under different policy packages.ResultsAll attributes significantly impacted doctor choices (p<0.01). Doctors strongly preferred jobs at rural facilities where there was a supportive relationship with the community (β=0.93), considered good attendance in education and training (0.77) or promotion decisions (0.67), with functional security (0.67) and higher incentive payments (0.5 per 10% increase of base salary). Jobs with disciplinary action for poor attendance were disliked by respondents (−0.63). Latent class analysis identified three groups of doctors who differed in their uptake of jobs. Scenario modelling identified intervention packages that differentially impacted doctor behaviour and combinations that could feasibly improve doctors’ attendance.ConclusionBangladeshi doctors have strong but varied preferences over interventions to overcome absenteeism. We generated evidence suggesting that interventions considering the perspective of the doctors themselves could result in substantial reductions in absenteeism. Designing policy packages that take account of the different situations facing doctors could begin to improve their ability and motivation to be present at their job and generate sustainable solutions to absenteeism in rural Bangladesh.

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Should I Stay or Should I Go Home? A Latent Class Analysis of a Discrete Choice Experiment on Hospital-At-Home

Value in Health ◽

10.1016/j.jval.2014.05.004 ◽

2014 ◽

Vol 17 (5) ◽

pp. 588-596 ◽

Cited By ~ 19

Author(s):

Lucas M.A. Goossens ◽

Cecile M.A. Utens ◽

Frank W.J.M. Smeenk ◽

Bas Donkers ◽

Onno C.P. van Schayck ◽

...

Keyword(s):

Latent Class Analysis ◽

Discrete Choice Experiment ◽

Discrete Choice ◽

Choice Experiment ◽

Latent Class ◽

Class Analysis ◽

Hospital At Home ◽

At Home

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Public preferences for pasture landscapes in Germany—A latent class analysis of a nationwide discrete choice experiment

Land Use Policy ◽

10.1016/j.landusepol.2019.104371 ◽

2020 ◽

Vol 91 ◽

pp. 104371 ◽

Cited By ~ 3

Author(s):

Henning Schaak ◽

Oliver Musshoff

Keyword(s):

Latent Class Analysis ◽

Discrete Choice Experiment ◽

Discrete Choice ◽

Choice Experiment ◽

Latent Class ◽

Class Analysis ◽

Public Preferences

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HIV Pre-exposure Prophylaxis, Condoms, or Both? Insights on Risk Compensation Through a Discrete Choice Experiment and Latent Class Analysis Among Men Who Have Sex With Men

Value in Health ◽

10.1016/j.jval.2020.11.023 ◽

2021 ◽

Author(s):

Rayner Kay Jin Tan ◽

Yi Wang ◽

Kiesha Prem ◽

Jack Harrison-Quintana ◽

Alvin Kuo Jing Teo ◽

...

Keyword(s):

Latent Class Analysis ◽

Discrete Choice Experiment ◽

Discrete Choice ◽

Choice Experiment ◽

Latent Class ◽

Risk Compensation ◽

Class Analysis ◽

Sex With Men ◽

Exposure Prophylaxis

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How to incentivise doctor attendance in Bangladesh: a latent class analysis of a discrete choice experiment

10.1101/2021.03.21.21254042 ◽

2021 ◽

Author(s):

Blake Angell ◽

Mushtaq Khan ◽

Mir Raihanul Islam ◽

Kate Mandeville ◽

Nahitun Naher ◽

...

Keyword(s):

Latent Class Analysis ◽

Discrete Choice Experiment ◽

Discrete Choice ◽

Choice Experiment ◽

Latent Class ◽

Latent Class Models ◽

Disciplinary Action ◽

Class Analysis ◽

Sustainable Solutions ◽

Incentive Payments

AbstractObjectiveTo elicit preferences of doctors over interventions to address doctor absenteeism in rural facilities in Bangladesh, a pervasive form of corruption across the country.MethodsWe conducted a discrete choice experiment with 308 doctors across four tertiary hospitals in Dhaka, Bangladesh. Four attributes of rural postings were included based on a literature review, qualitative research and a consensus-building workshop with policymakers and key health-system stakeholders: relationship with the community, security measures, attendance-based policies, and incentive payments. Respondents’ choices were analysed with mixed multinomial logistic and latent class models and were used to simulate the likely uptake of jobs under different policy packages.ResultsAll attributes significantly impacted doctor choices (p<0.01). Doctors strongly preferred jobs at rural facilities where there was a supportive relationship with the community (β=0.93), considered good attendance in education and training (0.77) or promotion decisions (0.67), with functional security (0.67) and higher incentive payments (0.5 per 10% increase of base salary). Jobs with disciplinary action for poor attendance were disliked by respondents (-.63). Latent class analysis identified three groups of doctors that differed in their uptake of jobs. Scenario modelling identified intervention packages that differentially impacted doctor behaciour and combinations that could feasibly improve doctors’ attendance.ConclusionBangladeshi doctors have strong but varied preferences over interventions to overcome absenteeism. Some were unresponsive to intervention but a substantial number appear amenable to change. Designing policy packages that consider these differences and target particular doctors could begin to generate sustainable solutions to doctor absenteeism in rural Bangladesh.

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A national study of the availability of law enforcement agency wellness programming for officers: A latent class analysis

International Journal of Police Science & Management ◽

10.1177/14613557211064050 ◽

2021 ◽

pp. 146135572110640

Author(s):

Bruce G Taylor ◽

Weiwei Liu ◽

Elizabeth A. Mumford

Keyword(s):

Mental Health ◽

United States ◽

Substance Use ◽

Law Enforcement ◽

Latent Class Analysis ◽

Latent Class ◽

Wellness Programs ◽

The United States ◽

Substance Use Treatment ◽

Class Analysis

The purpose of this study is to understand the availability of employee wellness programs within law enforcement agencies (LEAs) across the United States, including physical fitness, resilience/wellness, coping skills, nutrition, mental health treatment, and substance use treatment. The research team investigated whether patterns of LEA wellness programming are identifiable and, if so, what characteristics describe these patterns. We assess using latent class analysis whether there are distinct profiles of agencies with similar patterns offering different types of wellness programs and explore what characteristics distinguish agencies with certain profiles of wellness programming. Data were from a nationally representative sample of 1135 LEAs: 80.1% municipal, 18.6% county and 1.3% other agencies (state-level and Bureau of Indian Affairs LEAs). We found that many agencies (62%) offer no wellness programming. We also found that 23% have comprehensive wellness programming, and that another group of agencies specialize in specific wellness programming. About 14% of the agencies have a high probability of providing resilience coping skill education, mental health and/or substance use treatment services programming. About 1% of the agencies in the United States limit their programming to fitness and nutrition, indicating that fitness and nutrition programs are more likely to be offered in concert with other types of wellness programs. The analyses revealed that agencies offering broad program support are more likely to be large, municipal LEAs located in either the West, Midwest or Northeast (compared with the southern United States), and not experiencing a recent budget cut that impacted wellness programming.

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