Using economic evidence to support policy decisions to fund interventions for non-communicable diseases

Bertram, Melanie; Banatvala, Nick; Kulikov, Alexey; Belausteguigoitia, Itziar; Sandoval, Rosa Carolina; Hennis, Anselm; Webb, Douglas; Tarlton, Dudley

doi:10.1136/bmj.l1648

Cited by 23 publications

(16 citation statements)

References 7 publications

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“…Nearly 80% of American adults do not meet the guidelines for both aerobic and muscle-strengthening activities [ 5 ], and the prevalence of overweight or obesity reached 71.6% in 2016 [ 6 ]. Therefore, developing cost-effective and feasible lifestyle interventions is urgently needed to reduce the prevalence [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Zhang¹,

Oh²,

Lange³

et al. 2020

J Med Internet Res

214

116

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Background Chatbots empowered by artificial intelligence (AI) can increasingly engage in natural conversations and build relationships with users. Applying AI chatbots to lifestyle modification programs is one of the promising areas to develop cost-effective and feasible behavior interventions to promote physical activity and a healthy diet. Objective The purposes of this perspective paper are to present a brief literature review of chatbot use in promoting physical activity and a healthy diet, describe the AI chatbot behavior change model our research team developed based on extensive interdisciplinary research, and discuss ethical principles and considerations. Methods We conducted a preliminary search of studies reporting chatbots for improving physical activity and/or diet in four databases in July 2020. We summarized the characteristics of the chatbot studies and reviewed recent developments in human-AI communication research and innovations in natural language processing. Based on the identified gaps and opportunities, as well as our own clinical and research experience and findings, we propose an AI chatbot behavior change model. Results Our review found a lack of understanding around theoretical guidance and practical recommendations on designing AI chatbots for lifestyle modification programs. The proposed AI chatbot behavior change model consists of the following four components to provide such guidance: (1) designing chatbot characteristics and understanding user background; (2) building relational capacity; (3) building persuasive conversational capacity; and (4) evaluating mechanisms and outcomes. The rationale and evidence supporting the design and evaluation choices for this model are presented in this paper. Conclusions As AI chatbots become increasingly integrated into various digital communications, our proposed theoretical framework is the first step to conceptualize the scope of utilization in health behavior change domains and to synthesize all possible dimensions of chatbot features to inform intervention design and evaluation. There is a need for more interdisciplinary work to continue developing AI techniques to improve a chatbot’s relational and persuasive capacities to change physical activity and diet behaviors with strong ethical principles.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Zhang¹,

Oh²,

Lange³

et al. 2020

J Med Internet Res

214

116

View full text Add to dashboard Cite

show abstract

“…A recent World Health Organization-led study estimated that depression and anxiety disorders cost the global economy US $1 trillion each year in lost productivity [4]. The implementation of cost-effective and feasible interventions could therefore have a significant impact on the individual, organization, and economy [5].…”

Section: Introductionmentioning

confidence: 99%

Chatbot-Based Assessment of Employees’ Mental Health: Design Process and Pilot Implementation

Hungerbuehler¹,

Daley²,

Cavanagh³

et al. 2021

JMIR Form Res

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Background Stress, burnout, and mental health problems such as depression and anxiety are common, and can significantly impact workplaces through absenteeism and reduced productivity. To address this issue, organizations must first understand the extent of the difficulties by mapping the mental health of their workforce. Online surveys are a cost-effective and scalable approach to achieve this but typically have low response rates, in part due to a lack of interactivity. Chatbots offer one potential solution, enhancing engagement through simulated natural human conversation and use of interactive features. Objective The aim of this study was to explore if a text-based chatbot is a feasible approach to engage and motivate employees to complete a workplace mental health assessment. This paper describes the design process and results of a pilot implementation. Methods A fully automated chatbot (“Viki”) was developed to evaluate employee risks of suffering from depression, anxiety, stress, insomnia, burnout, and work-related stress. Viki uses a conversation style and gamification features to enhance engagement. A cross-sectional analysis was performed to gain first insights of a pilot implementation within a small to medium–sized enterprise (120 employees). Results The response rate was 64.2% (77/120). In total, 98 employees started the assessment, 77 of whom (79%) completed it. The majority of participants scored in the mild range for anxiety (20/40, 50%) and depression (16/28, 57%), in the moderate range for stress (10/22, 46%), and at the subthreshold level for insomnia (14/20, 70%) as defined by their questionnaire scores. Conclusions A chatbot-based workplace mental health assessment seems to be a highly engaging and effective way to collect anonymized mental health data among employees with response rates comparable to those of face-to-face interviews.

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“…If not tackled, these diseases will continue to have severe consequences for healthcare systems and economic development. Poorer individuals will generally bear the greatest burden of associated morbidity and mortality [ 10 , 11 ]. In recognition of these challenges, there is growing global momentum to use pricing policies, such as sweetened beverage taxes, as a key intervention to help address the global NCD pandemic, make progress towards achieving the Sustainable Development Goals [ 12 ] and reduce inequities [ 10 , 13 – 16 ].…”

Section: Introductionmentioning

confidence: 99%

How should we evaluate sweetened beverage tax policies? A review of worldwide experience

Colchero

White

2021

BMC Public Health

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Over 45 jurisdictions globally have implemented sweetened beverage taxes. Researchers and policymakers need to assess whether and how these taxes change beverage demand and supply, their intended and unanticipated health, economic and equity impacts. Lessons from such evaluations can maximise the policies’ success and impact on non-communicable disease prevention globally. We discuss key theoretical, design and methodological considerations to help policymakers, funders and researchers commission and conduct rigorous evaluations of these policies and related disease prevention efforts. We encourage involving the perspectives of various stakeholders on what evaluations are needed given the specific context, what data and methods are appropriate, readily available or can be collected within time and budget constraints. A logic model /conceptual system map of anticipated implications across sectors and scales should help identify optimal study design, analytical techniques and measures. These models should be updated when synthesising findings across diverse methods and integrating findings across subpopulations using similar methods.

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Using economic evidence to support policy decisions to fund interventions for non-communicable diseases

Abstract: Economic analysis of interventions to reduce non-communicable diseases can encourage countries to increase investment, say Melanie Bertram and colleagues

Cited by 23 publications

References 7 publications

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Chatbot-Based Assessment of Employees’ Mental Health: Design Process and Pilot Implementation

How should we evaluate sweetened beverage tax policies? A review of worldwide experience

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