Philippe J Giabbanelli
Biographic Data
| ID | 1753587 |
|---|---|
| NAME | Philippe J Giabbanelli |
| GIVEN NAMES | Philippe J |
| FAMILY NAME | Giabbanelli |
| SIGNATURE | GIABBANELLI P J |
| AFFILIATIONS | Miami University |
| ORCID | 0000-0001-6816-355X |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 12 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Big data meets storytelling
Fanfictions are a popular literature genre in which writers reuse a universe, for example to transform heteronormative relationships with queer characters or to bring romance into shows focused on horror and adventure. Fanfictions have been the subject of numerous studies in text mining and network analysis, which used Natural Language Processing (NLP) techniques to compare fanfictions with the original scripts or to make various predictions. In …
Guiding prevention initiatives by applying network analysis to systems maps of adverse childhood experiences and adolescent suicide
Suicide is a leading cause of death in the United States, particularly among adolescents. In recent years, suicidal ideation, attempts, and fatalities have increased. Systems maps can effectively represent complex issues such as suicide, thus providing decision-support tools for policymakers to identify and evaluate interventions. While network science has served to examine systems maps in fields such as obesity, there is limited research at the …
A systems science approach to identifying data gaps in national data sources on adolescent suicidal ideation and suicide attempt in the United States
Examining gaps in suicide research can help focus future data collection efforts in suicide prevention. Our analysis precisely identified where data is missing and also revealed that missing data affects some aspects of suicide research (e.g., distal factors at the community and societal level) more than others (e.g., proximal factors about individual characteristics). In sum, our analysis highlights limitations in current suicide-related data av…
How to use machine learning and fuzzy cognitive maps to test hypothetical scenarios in health behavior change interventions
Machine learning together with fuzzy cognitive maps can assist in building health behavior interventions with complex logic models. The testing of hypothetical scenarios may help interventionists finetune the intervention components thus increasing their potential effectiveness
Hybrid Agent-Based Simulation of Adoption Behavior and Social Interactions
Agent-based modeling and simulation (ABMS) is a powerful analysis tool that has led to significant contributions in the field of innovation diffusion. In this article, we examine the potential and pitfalls of extending adoption models used in agent-based diffusion via machine learning (ML) and soft computing (SC) techniques. More specifically, we 1) classify features related to agents’ decision-making and social interactions that are generally no…
Pathways to suicide or collections of vicious cycles? Understanding the complexity of suicide through causal mapping
Evaluating the Impact of Improving Access on Consumption of Fruits and Vegetables in a Rural Community in Texas
Purpose: Most residents in rural regions of the United States consume fewer amounts of fruits and vegetables (FVs) compared with their urban counterparts. Difficulties in access to FVs often contribute to different consumption patterns in rural regions, aside from a lack of education or motivation for eating healthy foods. This article uses simulation methods to estimate the relationship between increasing food access and FV consumption levels in…
Tools and methods in participatory modeling
Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provid…
Identifying small groups of foods that can predict achievement of key dietary recommendations
Objective Many dietary assessment methods attempt to estimate total food and nutrient intake. If the intention is simply to determine whether participants achieve dietary recommendations, this leads to much redundant data. We used data mining techniques to explore the number of foods that intake information was required on to accurately predict achievement, or not, of key dietary recommendations. Design We built decision trees for achievement of …
Identifying binge drinkers based on parenting dimensions and alcohol-specific parenting practices
Of the parenting dimensions and practices, rules are particularly informative in understanding drinking behaviour. Adolescents' perceptions and parents' reports are complementary as they can help identifying binge drinkers and non-binge drinkers respectively, indicating that surveying specific aspects of adolescent-parent dynamics can improve our understanding of complex addictive behaviours
Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population
Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model…
An Agent-Based Social Network Model of Binge Drinking Among Dutch Adults
Binge drinking is a complex social problem linked to an array of detrimental health effects. While binge drinking in youth has been analyzed extensively using traditional methods (e.g., regressions analyses), the adult population has received less attention, and recent work has exemplified the potential for simulations to help scholars and practitioners better understand the problem. In this paper, we used agent-based social network models to tes…
Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population
Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model…
An Agent-Based Social Network Model of Binge Drinking Among Dutch Adults
Binge drinking is a complex social problem linked to an array of detrimental health effects. While binge drinking in youth has been analyzed extensively using traditional methods (e.g., regressions analyses), the adult population has received less attention, and recent work has exemplified the potential for simulations to help scholars and practitioners better understand the problem. In this paper, we used agent-based social network models to tes…
Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population
Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model…
Identifying binge drinkers based on parenting dimensions and alcohol-specific parenting practices
Of the parenting dimensions and practices, rules are particularly informative in understanding drinking behaviour. Adolescents' perceptions and parents' reports are complementary as they can help identifying binge drinkers and non-binge drinkers respectively, indicating that surveying specific aspects of adolescent-parent dynamics can improve our understanding of complex addictive behaviours
Identifying small groups of foods that can predict achievement of key dietary recommendations
Objective Many dietary assessment methods attempt to estimate total food and nutrient intake. If the intention is simply to determine whether participants achieve dietary recommendations, this leads to much redundant data. We used data mining techniques to explore the number of foods that intake information was required on to accurately predict achievement, or not, of key dietary recommendations. Design We built decision trees for achievement of …
Tools and methods in participatory modeling
Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provid…
Evaluating the Impact of Improving Access on Consumption of Fruits and Vegetables in a Rural Community in Texas
Purpose: Most residents in rural regions of the United States consume fewer amounts of fruits and vegetables (FVs) compared with their urban counterparts. Difficulties in access to FVs often contribute to different consumption patterns in rural regions, aside from a lack of education or motivation for eating healthy foods. This article uses simulation methods to estimate the relationship between increasing food access and FV consumption levels in…
Hybrid Agent-Based Simulation of Adoption Behavior and Social Interactions
Agent-based modeling and simulation (ABMS) is a powerful analysis tool that has led to significant contributions in the field of innovation diffusion. In this article, we examine the potential and pitfalls of extending adoption models used in agent-based diffusion via machine learning (ML) and soft computing (SC) techniques. More specifically, we 1) classify features related to agents’ decision-making and social interactions that are generally no…
Pathways to suicide or collections of vicious cycles? Understanding the complexity of suicide through causal mapping
A systems science approach to identifying data gaps in national data sources on adolescent suicidal ideation and suicide attempt in the United States
Examining gaps in suicide research can help focus future data collection efforts in suicide prevention. Our analysis precisely identified where data is missing and also revealed that missing data affects some aspects of suicide research (e.g., distal factors at the community and societal level) more than others (e.g., proximal factors about individual characteristics). In sum, our analysis highlights limitations in current suicide-related data av…
How to use machine learning and fuzzy cognitive maps to test hypothetical scenarios in health behavior change interventions
Machine learning together with fuzzy cognitive maps can assist in building health behavior interventions with complex logic models. The testing of hypothetical scenarios may help interventionists finetune the intervention components thus increasing their potential effectiveness
Big data meets storytelling
Fanfictions are a popular literature genre in which writers reuse a universe, for example to transform heteronormative relationships with queer characters or to bring romance into shows focused on horror and adventure. Fanfictions have been the subject of numerous studies in text mining and network analysis, which used Natural Language Processing (NLP) techniques to compare fanfictions with the original scripts or to make various predictions. In …
Guiding prevention initiatives by applying network analysis to systems maps of adverse childhood experiences and adolescent suicide
Suicide is a leading cause of death in the United States, particularly among adolescents. In recent years, suicidal ideation, attempts, and fatalities have increased. Systems maps can effectively represent complex issues such as suicide, thus providing decision-support tools for policymakers to identify and evaluate interventions. While network science has served to examine systems maps in fields such as obesity, there is limited research at the …
Medicine (9 works) · Computer Science (8 works) · Psychology (7 works) · Environmental health (6 works) · Poison control (5 works) · Artificial Intelligence (4 works) · Child and Adolescent Psychosocial and Emotional Development (4 works) · Suicide prevention (4 works) · Agent-based model (3 works) · Biostatistics (3 works)