Utility of Gestural Cues in Indexing Semantic Miscommunication

Inoue, Masashi; Ogihara, Mitsunori; Hanada, Ryoko; Furuyama, Nobuhiro

doi:10.1109/futuretech.2010.5482653

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…Joining is a complex interactional behavior to assess; raters are trained to pay attention to verbal as well as nonverbal interactions. While nonverbal cues can be detected by computational means (Inoue, Ogihara, Hanada, & Furuyama, 2010), the current approach is limited to transcribed speech of the facilitator only, thus severely limiting the information available for the computational algorithm, but making the computational task sufficiently “simple” to attack even after taking account of the fact that a facilitator may speak in both Spanish and English, sometimes in the same sentence. To the best of our knowledge, this is the first work that uses speech analysis, knowledge engineering, and computational linguistics to measure a component of fidelity.…”

Section: Introductionmentioning

confidence: 99%

Blending Qualitative and Computational Linguistics Methods for Fidelity Assessment: Experience with the Familias Unidas Preventive Intervention

Gallo

Pantín

Villamar

et al. 2014

Adm Policy Ment Health

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Careful fidelity monitoring and feedback are critical to implementing effective interventions. A wide range of procedures exist to assess fidelity; most are derived from observational assessments (Schoenwald et al, 2013). However, these fidelity measures are resource intensive for research teams in efficacy/effectiveness trials, and are often unattainable or unmanageable for the host organization to rate when the program is implemented on a large scale. We present a first step towards automated processing of linguistic patterns in fidelity monitoring of a behavioral intervention using an innovative mixed methods approach to fidelity assessment that uses rule-based, computational linguistics to overcome major resource burdens. Data come from an effectiveness trial of the Familias Unidas intervention, an evidence-based, family-centered preventive intervention found to be efficacious in reducing conduct problems, substance use and HIV sexual risk behaviors among Hispanic youth. This computational approach focuses on “joining,” which measures the quality of the working alliance of the facilitator with the family. Quantitative assessments of reliability are provided. Kappa scores between a human rater and a machine rater for the new method for measuring joining reached .83. Early findings suggest that this approach can reduce the high cost of fidelity measurement and the time delay between fidelity assessment and feedback to facilitators; it also has the potential for improving the quality of intervention fidelity ratings.

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Section: Introductionmentioning

confidence: 99%

Blending Qualitative and Computational Linguistics Methods for Fidelity Assessment: Experience with the Familias Unidas Preventive Intervention

Gallo

Pantín

Villamar

et al. 2014

Adm Policy Ment Health

Self Cite

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“…Recent work on machine learning demonstrates the ability to improve mental health services (Bickman, 2020) and to predict program sustainability with high levels of accuracy relative to human coding (Gallo et al, 2021). Other examples of innovative, automated methods include the recognition of stages of implementation through text mining (Wang et al, 2016), recognition of verbal discordance through image processing of gestures (Inoue et al, 2010(Inoue et al, , 2012, measurement of therapeutic alliance through computational linguistics (Gallo, Pantin et al, 2015), and identification of motivational interviewing through topic modeling (Atkins et al, 2014). These computational methods will become even more essential as we move toward virtual delivery of programs due to the COVID-19 pandemic.…”

Section: Innovative Measurement Systems For Implementationmentioning

confidence: 99%

Implementation methodology from a social systems informatics and engineering perspective applied to a parenting training program.

Gallo¹,

Berkel²,

Mauricio³

et al. 2021

Families, Systems, & Health

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Objective: For implementation of an evidence-based program to be effective, efficient, and equitable across diverse populations, we propose that researchers adopt a systems approach that is often absent in efficacy studies. To this end, we describe how a computer-based monitoring system can support the delivery of the New Beginnings Program (NBP), a parent-focused evidence-based prevention program for divorcing parents. Method: We present NBP from a novel systems approach that incorporates social system informatics and engineering, both necessary when utilizing feedback loops, ubiquitous in implementation research and practice. Examples of two methodological challenges are presented: how to monitor implementation, and how to provide feedback by evaluating system-level changes due to implementation. Results: We introduce and relate systems concepts to these two methodologic issues that are at the center of implementation methods. We explore how these system-level feedback loops address effectiveness, efficiency, and equity principles. These key principles are provided for designing an automated, low-burden, low-intrusive measurement system to aid fidelity monitoring and feedback that can be used in practice. Discussion: As the COVID-19 pandemic now demands fewer face-to-face delivery systems, their replacement with more virtual systems for parent training interventions requires constructing new implementation measurement systems based on social system informatics approaches. These approaches include the automatic monitoring of quality and fidelity in parent training interventions. Finally, we present parallels of producing generalizable and local knowledge bridging systems science and engineering method. This comparison improves our understanding of system-level changes, facilitates a program's implementation, and produces knowledge for the field.

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Partnerships for the Design, Conduct, and Analysis of Effectiveness, and Implementation Research: Experiences of the Prevention Science and Methodology Group

Brown

Kellam

Kaupert

et al. 2011

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What progress prevention research has made comes through strategic partnerships with communities and institutions that host this research, as well as professional and practice networks that facilitate the diffusion of knowledge about prevention. We discuss partnership issues related to the design, analysis, and implementation of prevention research and especially how rigorous designs, including random assignment, get resolved through a partnership between community stakeholders, institutions, and researchers. These partnerships shape not only study design, but they determine the data that can be collected and how results and new methods are disseminated. We also examine a second type of partnership to improve the implementation of effective prevention programs into practice. We draw on social networks to studying partnership formation and function. The experience of the Prevention Science and Methodology Group, which itself is a networked partnership between scientists and methodologists, is highlighted.

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Utility of Gestural Cues in Indexing Semantic Miscommunication

Cited by 4 publications

References 8 publications

Blending Qualitative and Computational Linguistics Methods for Fidelity Assessment: Experience with the Familias Unidas Preventive Intervention

Blending Qualitative and Computational Linguistics Methods for Fidelity Assessment: Experience with the Familias Unidas Preventive Intervention

Implementation methodology from a social systems informatics and engineering perspective applied to a parenting training program.

Partnerships for the Design, Conduct, and Analysis of Effectiveness, and Implementation Research: Experiences of the Prevention Science and Methodology Group

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