Matthew Vowels

University of Lausanne | UNIL

Causal reasoning is a crucial part of science and human intelligence. In order to discover causal relationships from data, we need structure discovery methods. We provide a review of background theory and a survey of methods for structure discovery. We primarily focus on modern, continuous optimization methods, and provide reference to further reso...

Causality is a fundamental part of the scientific endeavour to understand the world. Unfortunately, causality is still taboo in much of psychology and social science. Motivated by a growing number of recommendations for the importance of adopting causal approaches to research, we reformulate the typical approach to research in psychology to harmoni...

Causal inference is a crucial goal of science, enabling researchers to arrive at meaningful conclusions regarding the predictions of hypothetical interventions using observational data. Path models, Structural Equation Models (SEMs), and, more generally, Directed Acyclic Graphs (DAGs), provide a means to unambiguously specify assumptions regarding...

Artificial Neural Networks (ANNs), including fully-connected networks and transformers, are highly flexible and powerful function approximators, widely applied in fields like computer vision and natural language processing. However, their inability to inherently respect causal structures can limit their robustness, making them vulnerable to covaria...

Machine learning explainability techniques have been proposed as a means for psychologists to “explain” or interrogate a model in order to gain an understanding of a phenomenon of interest. Researchers concerned with imposing overly restrictive functional form (e.g., as would be the case in a linear regression) may be motivated to use machine learn...

In their study, Stavropoulos et al. (2023) capitalized on supervised machine learning and a longitudinal design and reported that the User-Avatar Bond could be accurately employed to detect Gaming Disorder (GD) risk in a community sample of gamers. The authors suggested that the User-Avatar Bond is a “digital phenotype” that could be used as a diag...

This randomized controlled trial evaluated the efficacy, feasibility, and technical outcomes of Amanda, a GPT-4-based chatbot, in delivering single-session relationship interventions. A total of 258 participants were randomly assigned to engage with either Amanda (n = 130) or a writing task (n = 128) focused on conflict reappraisal. Findings reveal...

Call for Special Section Submissions (Archives of Sexual Behavior) on Artificial Intelligence (AI) and Sexuality. Abstract submission: November 15, 2024. Full paper submission: June 1, 2025. Web: https://link.springer.com/journal/10508/updates/27497494

Sign Language Assessment (SLA) tools are useful to aid in language learning and are underdeveloped. Previous work has focused on isolated signs or comparison against a single reference video to assess Sign Languages (SL). This paper introduces a novel SLA tool designed to evaluate the comprehensibility of SL by modelling the natural distribution of...

It is well-documented that people living with obesity are at greater risk of poorer mental health outcomes. The aim of our study was twofold: First, to examine the longitudinal trajectories of depression and anxiety in people living with obesity over two years across eight waves of a UK national COVID-19 survey (March 2020-March 2022) using smoothi...

psifx is a plug-and-play multi-modal feature extraction toolkit, aiming to facilitate and democratize the use of state-of-the-art machine learning techniques for human sciences research. It is motivated by a need (a) to automate and standardize data annotation processes, otherwise involving expensive, lengthy, and inconsistent human labor, such as...

Introduction Human behaviour is one of the primary factors influencing the loss of biodiversity, and calls for increased conservation efforts are growing. Therefore, people's adherence to conservation measures is essential. However, affective reactions may hinder motivation to do the 'right thing'. For example, owls are beneficial to sustainable ag...

We examined human deepfake detection performance (DDP) in relation to face identity processing ability among Berlin Police officers, including Super-Recognizers (SRs). While we find no relationship, further research into human DDP using state-of-the-art static deepfakes is needed to establish the potential value of SR-deployment.

In their study, Stavropoulos et al. (2023) capitalized on supervised machine learning and a longitudinal design and reported that the User-Avatar Bond could be accurately employed to detect Gaming Disorder (GD) risk in a community sample of gamers. The authors suggested that the User-Avatar Bond is a “digital phenotype” that could be used as a diag...

The present study is the first empirical investigation of the relationshion between human deepfake detection performance (DDP) and individuals' face identity processing ability. Using videos from the Deepfake Detection Challenge, we investigated DDP in two unique observer groups: Super-Recognizers (SRs) and "normal" officers from within the 18K mem...

Normality, in the colloquial sense, has historically been considered an aspirational trait, synonymous with ideality. The arithmetic average and, by extension, statistics including linear regression coefficients, have often been used to characterize normality, and are often used as a way to summarize samples and identify outliers. We provide intuit...

Social interactions play a critical role in human coexistence. Several theories have been developed to explain how partners influence each other during an interaction in specific situations (e.g., mother-child, intimate partners, patient-therapist). However, new standards have been defined by meta-researchers for how to develop and test theories. T...

International law enforcement agencies are tasked with processing increasing amounts of security-relevant digital information, particularly images and videos showing physical persons' facial identity. The permissible use of technology is subject to certain legal conditions, which vary across legal systems. But even if automatic assistance is permis...

Contemporary emotion theories predict that how partners’ emotions are coupled together across an interaction can inform on how well the relationship functions. However, few studies have compared how individual (i.e., mean, variability) and dyadic aspects of emotions (i.e., coupling) during interactions predict future relationship separation. In thi...

Background: Recent research has shown that insecure attachment, especially attachment anxiety, is associated with poor mental health outcomes, especially during the COVID-19 pandemic. Other research suggests that insecure attachment may be linked to nonadherence to social distancing behaviours during the pandemic. Aims: The present study aims to...

Data collection and research methodology represents a critical part of the research pipeline. On the one hand, it is important that we collect data in a way that maximises the validity of what we are measuring, which may involve the use of long scales with many items. On the other hand, collecting a large number of items across multiple scales resu...

Normality, in the colloquial sense, has historically been considered an aspirational trait, synonymous with harmony and ideality. The arithmetic average has often been used to characterize normality, and is often used both productively and unproductively as a blunt way to characterize samples and outliers. A number of prior commentaries in the fiel...

Perceiving one’s partner as supportive is considered essential for relationships, but we know little about which factors are central to predicting perceived partner support. Traditional statistical techniques are ill-equipped to compare a large number of potential predictor variables and cannot answer this question. This research used machine learn...

Causal identification is at the core of the causal inference literature, where complete algorithms have been proposed to identify causal queries of interest. The validity of these algorithms hinges on the restrictive assumption of having access to a correctly specified causal structure. In this work, we study the setting where a probabilistic model...

Structural Equation Models (SEMs) represent a popular and powerful methodology for estimating causal effects in psychological research. However, the sample size required to estimate the parameters associated with an SEM quickly explodes with the complexity of the model. This means that any opportunities we have to simplify the model should be taken...

Machine Learning explainability techniques have been proposed as a means of `explaining' or interrogating a model in order to understand why a particular decision or prediction has been made. Such an ability is especially important at a time when machine learning is being used to automate decision processes which concern sensitive factors and legal...

Parameter estimation in the empirical fields is usually undertaken using parametric models, and such models are convenient because they readily facilitate statistical inference. Unfortunately, they are unlikely to have a sufficiently flexible functional form to be able to adequately model real-world phenomena, and their usage may therefore result i...

Sexual satisfaction has been robustly associated with relationship and individual well-being. Previous studies have found several individual (e.g., gender, self-esteem, and attachment) and relational (e.g., relationship satisfaction, relationship length, and sexual desire) factors that predict sexual satisfaction. The aim of the present study was t...

Communication is an important component of many healthy sexual and romantic relationships. Positive communication strategies including expressing fondness and affection, exchanging compliments, and disclosing information about oneself with a partner are associated with relationship and sexual satisfaction, but less is known about its association to...

Many processes in psychology are complex, such as dyadic interactions between two interacting partners (e.g., patient-therapist, intimate relationship partners). Nevertheless, many basic questions about interactions are difficult to investigate because dyadic processes can be within a person and between partners, they are based on multimodal aspect...

The replicability crisis has drawn attention to numerous weaknesses in psychology and social science research practice. In this work we focus on three issues that cannot be addressed with replication alone, and which deserve more attention: Functional misspecification, structural misspecification, and unreliable interpretation of results. We demons...

Infidelity can be a disruptive event in a romantic relationship with a devastating impact on both partners’ well-being. Thus, there are benefits to identifying factors that can explain or predict infidelity, but prior research has not utilized methods that would provide the relative importance of each predictor. We used a machine learning algorithm...

Attention is an important component of modern deep learning. However, less emphasis has been put on its inverse: ignoring distraction. Our daily lives require us to explicitly avoid giving attention to salient visual features that confound the task we are trying to accomplish. This visual prioritisation allows us to concentrate on important tasks w...

Social scientists have become increasingly interested in using intensive longitudinal methods to study social phenomena that change over time. Many of these phenomena are expected to exhibit cycling fluctuations (e.g., sleep, mood, sexual desire). However, researchers typically employ analytical methods which are unable to model such patterns. We p...

Many processes in psychology are complex, such as dyadic interactions between two interacting partners (e.g. patient-therapist, intimate relationship partners). Nevertheless, many basic questions about interactions are difficult to investigate because dyadic processes can be within a person and between partners, they are based on multimodal aspects...

Background: Low sexual desire is the most common sexual problem reported with 34% of women and 15% of men reporting lack of desire for at least 3 months in a 12-month period. Sexual desire has previously been associated with both relationship and individual well-being highlighting the importance of understanding factors that contribute to sexual d...

An important goal across most scientific fields is the discovery of causal structures underling a set of observations. Unfortunately, causal discovery methods which are based on correlation or mutual information can often fail to identify causal links in systems which exhibit dynamic relationships. Such dynamic systems (including the famous coupled...

Disentangled representations support a range of downstream tasks including causal reasoning, generative modeling, and fair machine learning. Unfortunately, disentanglement has been shown to be impossible without the incorporation of supervision or inductive bias. Given that supervision is often expensive or infeasible to acquire, we choose to incor...

Causal reasoning is a crucial part of science and human intelligence. In order to discover causal relationships from data, we need structure discovery methods. We provide a review of background theory and a survey of methods for structure discovery. We primarily focus on modern, continuous optimization methods, and provide reference to further reso...

The deleterious nature of U.S. economic recessions over the last several decades highlight a need to investigate the role of family economic strain on families. The current study explored the impact of family economic strain on marital quality and marital stability through dyadic associations of marital support and work–family conflict of 370 marri...

Two methods for undertaking subjective evaluation were compared: a pairwise dissimilarity task (PDT) and a projective mapping task (PMT). For a set of unambiguous, synthetic, auditory stimuli, the aim was to determine the following: whether the PMT limits the recovered dimensionality to two dimensions; how subjects respond using PMT’s two-dimension...

Undertaking causal inference with observational data is extremely useful across a wide range of domains including the development of medical treatments, advertisements and marketing, and policy making. There are two main challenges associated with undertaking causal inference using observational data: treatment assignment heterogeneity (i.e., diffe...

Infidelity is a common occurrence in relationships and can have a devastating impact on both partners’ well-being. A large body of literature have attempted to factors that can explain or predict infidelity but have been unable to estimate the relative importance of each predictor. We used a machine learning algorithm, random forest (a type of inte...

Previous studies have found a number of individual, relational, and societal factors that are associated with sexual desire. However, no studies to date have examined which of these variables are the most predictive of sexual desire. We used a machine learning algorithm, random forest (a type of interpretable highly non-linear decision tree), to pr...

Previous studies have found a number of different factors that are associated with sexual satisfaction but have been unable to estimate the relative importance of each predictor. We used a machine learning algorithm, random forest (a type of interpretable highly non-linear decision tree), to predict sexual satisfaction across two samples (total N =...

Social scientists have become increasingly interested in using intensive longitudinal methods to study social phenomena that change over time. Many of these phenomena are expected to exhibit cycling fluctuations (e.g., sleep, mood, sexual desire). However, researchers typically employ analytical methods which are unable to model such patterns. We p...

The replicability crisis has drawn attention to numerous weaknesses in psychology and social science research practice. In this work we focus on three issues that deserve more attention: The use of models with limited functional form, the use of misspecified causal models, and unreliable interpretation of results. We demonstrate a number of possibl...

A crucial component of successful counseling and psychotherapy is the dyadic emotion co-regulation process between patient and therapist which unfolds moment-to-moment during therapy sessions. The major reason for the disappointing progress in understanding this process is the lack of appropriate methods to assess subjectively experienced emotions...

Fair and unbiased machine learning is an important and active field of research, as decision processes are increasingly driven by models that learn from data. Unfortunately, any biases present in the data may be learned by the model, thereby inappropriately transferring that bias into the decision making process. We identify the connection between...

Variational AutoEncoders (VAEs) provide a means to generate representational latent embeddings. Previous research has highlighted the benefits of achieving representations that are disentangled, particularly for downstream tasks. However, there is some debate about how to encourage disentanglement with VAEs and evidence indicates that existing impl...

Over the past few decades, US families have been faced with several economic recessions. The regularity and severity of these economic crises lends to the importance of having an understanding of how these events affect families. The present study investigates the effects of family economic strain on marital quality and marital stability through in...

Sexual desire discrepancy is one of the most frequently reported sexual concerns for individuals and couples and has been shown to be negatively associated with sexual and relationship satisfaction. Sexual desire has increasingly been examined as a state-like construct that ebbs and flows, but little is known about whether there are patterns in the...

Sexual desire discrepancy and low sexual desire are two of the most frequently reported sexual concerns for individuals and couples and both have been shown to be negatively associated with sexual and relationship satisfaction. Sexual desire has increasingly been examined as a state like construct that ebbs and flows, but little is known about whet...