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Book ; Online: Strategic Usage in a Multi-Learner Setting

Shekhtman, Eliot / Dean, Sarah

2024

Abstract: Real-world systems often involve some pool of users choosing between a set of services. With the increase in popularity of online learning algorithms, these services can now self-optimize, leveraging data collected on users to maximize some reward such ... ...

Abstract	Real-world systems often involve some pool of users choosing between a set of services. With the increase in popularity of online learning algorithms, these services can now self-optimize, leveraging data collected on users to maximize some reward such as service quality. On the flipside, users may strategically choose which services to use in order to pursue their own reward functions, in the process wielding power over which services can see and use their data. Extensive prior research has been conducted on the effects of strategic users in single-service settings, with strategic behavior manifesting in the manipulation of observable features to achieve a desired classification; however, this can often be costly or unattainable for users and fails to capture the full behavior of multi-service dynamic systems. As such, we analyze a setting in which strategic users choose among several available services in order to pursue positive classifications, while services seek to minimize loss functions on their observations. We focus our analysis on realizable settings, and show that naive retraining can still lead to oscillation even if all users are observed at different times; however, if this retraining uses memory of past observations, convergent behavior can be guaranteed for certain loss function classes. We provide results obtained from synthetic and real-world data to empirically validate our theoretical findings. Comment: 17 pages, 6 figures
Keywords	Computer Science - Machine Learning ; Computer Science - Computer Science and Game Theory ; 91A10
Subject code	000
Publishing date	2024-01-29
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Decision-aid or Controller? Steering Human Decision Makers with Algorithms

Xu, Ruqing / Dean, Sarah

2023

Abstract: Algorithms are used to aid human decision makers by making predictions and recommending decisions. Currently, these algorithms are trained to optimize prediction accuracy. What if they were optimized to control final decisions? In this paper, we study a ... ...

Abstract	Algorithms are used to aid human decision makers by making predictions and recommending decisions. Currently, these algorithms are trained to optimize prediction accuracy. What if they were optimized to control final decisions? In this paper, we study a decision-aid algorithm that learns about the human decision maker and provides ''personalized recommendations'' to influence final decisions. We first consider fixed human decision functions which map observable features and the algorithm's recommendations to final decisions. We characterize the conditions under which perfect control over final decisions is attainable. Under fairly general assumptions, the parameters of the human decision function can be identified from past interactions between the algorithm and the human decision maker, even when the algorithm was constrained to make truthful recommendations. We then consider a decision maker who is aware of the algorithm's manipulation and responds strategically. By posing the setting as a variation of the cheap talk game [Crawford and Sobel, 1982], we show that all equilibria are partition equilibria where only coarse information is shared: the algorithm recommends an interval containing the ideal decision. We discuss the potential applications of such algorithms and their social implications.
Keywords	Computer Science - Artificial Intelligence ; Computer Science - Computers and Society ; Computer Science - Human-Computer Interaction ; Computer Science - Machine Learning
Subject code	006
Publishing date	2023-03-23
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Understanding how therapeutic exercise prescription changes outcomes important to patients with persistent non-specific low back pain: a realist review protocol.

Wood, Lianne / Booth, Vicky / Dean, Sarah / Foster, Nadine E / Hayden, Jill A / Booth, Andrew

Systematic reviews

2024 Volume 13, Issue 1, Page(s) 63

Abstract: Introduction: Persistent low back pain (LBP) is the leading cause of disability worldwide, and therapeutic exercise is recommended as a first-line treatment in international guidelines. The effects of exercise on clinical outcomes of pain and physical ... ...

Abstract	Introduction: Persistent low back pain (LBP) is the leading cause of disability worldwide, and therapeutic exercise is recommended as a first-line treatment in international guidelines. The effects of exercise on clinical outcomes of pain and physical function are small to moderate, despite broader impacts on cardiovascular systems, biological health, mood, and emotional well-being. Therapeutic exercise prescription is defined as exercise that is prescribed by a clinician for a health-related treatment. It is unknown how therapeutic exercise prescription creates effects on outcomes of importance. Realist reviews explore how underlying mechanisms (M) may be active in the context (C) of certain situations, settings, or populations to create an intended or unintended outcome (O). Our objective is to explore and understand the mechanisms by which therapeutic exercise prescription changes outcomes for people with persistent LBP. Methods: We will develop initial programme theories based on preliminary data from a previous systematic review and consensus workshop. These theories will be modified with input from a steering group (experts), a stakeholder group (people with lived experience of exercise for persistent LBP and clinicians), and a scoping search of the published literature. An information specialist will design and undertake an iterative search strategy. These will be used to create CMO configurations, which will be refined and tested using the literature. The realist review will be reported following RAMESES guidance. Discussion: Realist reviews are uncommon in LBP research to date, yet those offer an opportunity to contrast with traditional methods of randomised controlled trials and systematic reviews and provide additional information regarding the contexts and mechanisms that may trigger certain outcomes. This can aid our understanding of the contextual features that may influence exercise prescription, such as for whom they are most effective, in what setting, how they are implemented and why. This realist synthesis will enhance our understanding of therapeutic exercise prescription to improve adherence and engagement and ultimately will provide clinically relevant recommendations regarding exercise prescription for those with persistent LBP. Systematic review registration: The review has been registered with PROSPERO (CRD42017072023).
MeSH term(s)	Humans ; Low Back Pain/therapy ; Exercise Therapy ; Exercise
Language	English
Publishing date	2024-02-08
Publishing country	England
Document type	Journal Article
ZDB-ID	2662257-9
ISSN	2046-4053 ; 2046-4053
ISSN (online)	2046-4053
ISSN	2046-4053
DOI	10.1186/s13643-024-02466-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Contexts, behavioural mechanisms and outcomes to optimise therapeutic exercise prescription for persistent low back pain: a realist review.

Wood, Lianne / Foster, Nadine E / Dean, Sarah Gerard / Booth, Vicky / Hayden, Jill A / Booth, Andrew

British journal of sports medicine

2024 Volume 58, Issue 4, Page(s) 222–230

Abstract: Objective: Therapeutic exercises are a core treatment for low back pain (LBP), but it is uncertain how rehabilitative exercise facilitates change in outcomes. Realist reviews explore how the context (C) of certain settings or populations and underlying ... ...

Abstract	Objective: Therapeutic exercises are a core treatment for low back pain (LBP), but it is uncertain how rehabilitative exercise facilitates change in outcomes. Realist reviews explore how the context (C) of certain settings or populations and underlying mechanisms (M) create intended or unintended outcomes (O). Our objective was to explore and understand the behavioural mechanisms by which therapeutic exercise creates change in outcomes of adherence, engagement and clinical outcomes for patients with LBP. Methods: This was a realist review reported following the Realist and Meta-narrative Evidence Syntheses: Evolving Standards guidance. We developed initial programme theories, modified with input from a steering group (experts, n=5), stakeholder group (patients and clinicians, n=10) and a scoping search of the published literature (n=37). Subsequently, an information specialist designed and undertook an iterative search strategy, and we refined and tested CMO configurations. Results: Of 522 initial papers identified, 75 papers were included to modify and test CMO configurations. We found that the patient-clinician therapeutic consultation builds a foundation of trust and was associated with improved adherence, engagement and clinical outcomes, and that individualised exercise prescription increases motivation to adhere to exercise and thus also impacts clinical outcomes. Provision of support such as timely follow-up and supervision can further facilitate motivation and confidence to improve adherence to therapeutic exercises for LBP. Conclusions: Engagement in and adherence to therapeutic exercises for LBP, as well as clinical outcomes, may be optimised using mechanisms of trust, motivation and confidence. These CMO configurations provide a deeper understanding of ways to optimise exercise prescription for patients with LBP.
MeSH term(s)	Humans ; Low Back Pain/therapy ; Exercise Therapy ; Exercise ; Motivation
Language	English
Publishing date	2024-02-09
Publishing country	England
Document type	Journal Article
ZDB-ID	600592-5
ISSN	1473-0480 ; 0306-3674
ISSN (online)	1473-0480
ISSN	0306-3674
DOI	10.1136/bjsports-2023-107598
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Article ; Online: Pelvic floor exercises and female stress urinary incontinence.

Sims, Laura / Hay-Smith, Jean / Dean, Sarah

The British journal of general practice : the journal of the Royal College of General Practitioners

2022 Volume 72, Issue 717, Page(s) 185–187

MeSH term(s)	Exercise Therapy ; Female ; Humans ; Pelvic Floor ; Urinary Incontinence, Stress/therapy
Language	English
Publishing date	2022-03-31
Publishing country	England
Document type	Journal Article
ZDB-ID	1043148-2
ISSN	1478-5242 ; 0035-8797 ; 0960-1643
ISSN (online)	1478-5242
ISSN	0035-8797 ; 0960-1643
DOI	10.3399/bjgp22X719033
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Zs.B 576: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG)
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Book ; Online: Cross-Dataset Propensity Estimation for Debiasing Recommender Systems

Li, Fengyu / Dean, Sarah

2022

Abstract: Datasets for training recommender systems are often subject to distribution shift induced by users' and recommenders' selection biases. In this paper, we study the impact of selection bias on datasets with different quantization. We then leverage two ... ...

Abstract	Datasets for training recommender systems are often subject to distribution shift induced by users' and recommenders' selection biases. In this paper, we study the impact of selection bias on datasets with different quantization. We then leverage two differently quantized datasets from different source distributions to mitigate distribution shift by applying the inverse probability scoring method from causal inference. Empirically, our approach gains significant performance improvement over single-dataset methods and alternative ways of combining two datasets. Comment: In Workshop on Distribution Shifts, 36th Conference on Neural Information Processing Systems (NeurIPS 2022)
Keywords	Computer Science - Information Retrieval ; Computer Science - Machine Learning ; Statistics - Methodology
Publishing date	2022-12-21
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Preference Dynamics Under Personalized Recommendations

Dean, Sarah / Morgenstern, Jamie

2022

Abstract: Many projects (both practical and academic) have designed algorithms to match users to content they will enjoy under the assumption that user's preferences and opinions do not change with the content they see. Evidence suggests that individuals' ... ...

Abstract	Many projects (both practical and academic) have designed algorithms to match users to content they will enjoy under the assumption that user's preferences and opinions do not change with the content they see. Evidence suggests that individuals' preferences are directly shaped by what content they see -- radicalization, rabbit holes, polarization, and boredom are all example phenomena of preferences affected by content. Polarization in particular can occur even in ecosystems with "mass media," where no personalization takes place, as recently explored in a natural model of preference dynamics by~\citet{hkazla2019geometric} and~\citet{gaitonde2021polarization}. If all users' preferences are drawn towards content they already like, or are repelled from content they already dislike, uniform consumption of media leads to a population of heterogeneous preferences converging towards only two poles. In this work, we explore whether some phenomenon akin to polarization occurs when users receive \emph{personalized} content recommendations. We use a similar model of preference dynamics, where an individual's preferences move towards content the consume and enjoy, and away from content they consume and dislike. We show that standard user reward maximization is an almost trivial goal in such an environment (a large class of simple algorithms will achieve only constant regret). A more interesting objective, then, is to understand under what conditions a recommendation algorithm can ensure stationarity of user's preferences. We show how to design a content recommendations which can achieve approximate stationarity, under mild conditions on the set of available content, when a user's preferences are known, and how one can learn enough about a user's preferences to implement such a strategy even when user preferences are initially unknown. Comment: EC 2022
Keywords	Computer Science - Machine Learning ; Computer Science - Computer Science and Game Theory ; Computer Science - Information Retrieval ; Computer Science - Social and Information Networks ; Electrical Engineering and Systems Science - Systems and Control ; Statistics - Machine Learning
Subject code	303
Publishing date	2022-05-25
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Ranking with Long-Term Constraints

Brantley, Kianté / Fang, Zhichong / Dean, Sarah / Joachims, Thorsten

2023

Abstract: The feedback that users provide through their choices (e.g., clicks, purchases) is one of the most common types of data readily available for training search and recommendation algorithms. However, myopically training systems based on choice data may ... ...

Abstract	The feedback that users provide through their choices (e.g., clicks, purchases) is one of the most common types of data readily available for training search and recommendation algorithms. However, myopically training systems based on choice data may only improve short-term engagement, but not the long-term sustainability of the platform and the long-term benefits to its users, content providers, and other stakeholders. In this paper, we thus develop a new framework in which decision makers (e.g., platform operators, regulators, users) can express long-term goals for the behavior of the platform (e.g., fairness, revenue distribution, legal requirements). These goals take the form of exposure or impact targets that go well beyond individual sessions, and we provide new control-based algorithms to achieve these goals. In particular, the controllers are designed to achieve the stated long-term goals with minimum impact on short-term engagement. Beyond the principled theoretical derivation of the controllers, we evaluate the algorithms on both synthetic and real-world data. While all controllers perform well, we find that they provide interesting trade-offs in efficiency, robustness, and the ability to plan ahead.
Keywords	Computer Science - Information Retrieval
Subject code	303
Publishing date	2023-07-10
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Adherence to physical rehabilitation delivered via tele-rehabilitation for people with multiple sclerosis: a scoping review protocol.

Goldsmith, Geraldine / Bollen, Jessica C / Salmon, Victoria E / Freeman, Jennifer A / Dean, Sarah G

BMJ open

2023 Volume 13, Issue 3, Page(s) e062548

Abstract: Introduction: Using tele-rehabilitation methods to deliver exercise, physical activity (PA) and behaviour change interventions for people with multiple sclerosis (pwMS) has increased in recent years, especially since the SARS-CoV-2 pandemic. This ... ...

Abstract	Introduction: Using tele-rehabilitation methods to deliver exercise, physical activity (PA) and behaviour change interventions for people with multiple sclerosis (pwMS) has increased in recent years, especially since the SARS-CoV-2 pandemic. This scoping review aims to provide an overview of the literature regarding adherence to therapeutic exercise and PA delivered via tele-rehabilitation for pwMS. Methods and analysis: Frameworks described by Arksey and O'Malley and Levac Ethics and dissemination: Ethical approval was not required for this protocol. Findings will be submitted to a peer-reviewed journal and presented at conferences. Consultation with pwMS and clinicians will help to identify other dissemination methods.
MeSH term(s)	Humans ; Telerehabilitation ; Multiple Sclerosis ; COVID-19 ; SARS-CoV-2 ; Systematic Reviews as Topic ; Research Design ; Review Literature as Topic
Language	English
Publishing date	2023-03-08
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2599832-8
ISSN	2044-6055 ; 2044-6055
ISSN (online)	2044-6055
ISSN	2044-6055
DOI	10.1136/bmjopen-2022-062548
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Article ; Online: "Kind of empowered": Perceptions of socio-emotional development in children driving ride-on cars.

Barchus, Rebecca / Barroero, Chelsea / Schnare, Wendy / Dean, Sarah M / Feldner, Heather A

Rehabilitation psychology

2023 Volume 68, Issue 2, Page(s) 155–163

Abstract: Purpose/objective: Early powered mobility (PM) experiences can be essential facilitators of self-initiated mobility, socialization, and exploration for young children with disabilities. Cerebral palsy (CP) and developmental delay are two of the most ... ...

Abstract	Purpose/objective: Early powered mobility (PM) experiences can be essential facilitators of self-initiated mobility, socialization, and exploration for young children with disabilities. Cerebral palsy (CP) and developmental delay are two of the most common diagnoses associated with motor disability in young children with 1 in 345 children diagnosed with CP and 1 in 6 with developmental delay in the US. The purpose of this study was to explore the longitudinal experiences and caregiver perceptions of socio-emotional development in particular, in young children with disabilities during modified ride-on car (ROC) use. Research method/design: A qualitative, grounded theory approach was used. Semi-structured interviews were conducted with 15 families (children ages 1-4 with CP or developmental delay) at baseline, 6 months (as able due to COVID), and 1 year following ROC introduction. Data were coded independently by three researchers using constant comparison until data saturation occurred and themes emerged. Results: Four themes emerged from the data: "Leveling the Playing Field," "Breaking Down Barriers," "Fun and Work: ROC as Toy and Therapy Device," and "Mobility is a Pathway to Autonomy." Conclusions/Implication: Children and caregivers viewed ROCs as both fun and therapeutic, consistently identifying perceived benefits for children's socio-emotional development. This qualitative study provides a better understanding of the complexities and impact of ROCs on children and their families in the socio-emotional domain and may help facilitate clinical decision-making when introducing PM to young children with disabilities as part of a multimodal approach to early intervention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
MeSH term(s)	Humans ; Child ; Child, Preschool ; Disabled Children/psychology ; Automobiles ; COVID-19 ; Motor Disorders ; Emotions ; Cerebral Palsy
Language	English
Publishing date	2023-04-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	224747-1
ISSN	1939-1544 ; 0090-5550
ISSN (online)	1939-1544
ISSN	0090-5550
DOI	10.1037/rep0000482
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