Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
António, H.; Albuquerque, S.; de Castro, M. Vieira; Bouchard, S.; Gamito, P.; Pinto, R. J.
In: Psychiatry International, vol. 7, no. 4, 2026, ISSN: 26735318 (ISSN).
Abstract | Links | BibTeX | Tags: adult, Anxiety, article, cross-sectional study, decision making, Depression, DSM-5, female, Global Severity Index, hostility, human, human experiment, Latent Class Analysis, LEC-5, major clinical study, male, paranoia, phobia, police, Positive symptom distress index, Positive symptom total, posttraumatic stress disorder, posttraumatic stress disorder checklist, Proximal Traumatic Exposure, psychological distress, psychosis, PTSD, questionnaire, receiver operating characteristic, Security, security professionals, self report, sociodemographics, trauma exposure
@article{antonioLatentClassesProximal2026,
title = {Latent Classes of Proximal Traumatic Exposure Among Portuguese Police and Security Professionals: Associations with PTSD Symptoms and Psychological Distress},
author = {H. António and S. Albuquerque and M. Vieira de Castro and S. Bouchard and P. Gamito and R. J. Pinto},
url = {https://www.scopus.com/pages/publications/105048524559?origin=resultslist},
doi = {10.3390/psychiatryint7040173},
issn = {26735318 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Psychiatry International},
volume = {7},
number = {4},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
abstract = {Background: Police and security professionals are routinely exposed to potentially traumatic events as part of occupational duties, placing them at increased risk for post-traumatic stress and broader psychological difficulties. This study aimed to identify latent classes of proximal traumatic exposure among Portuguese police/security professionals and examine their associations with PTSD symptoms and general psychological distress. Methods: A cross-sectional online survey was conducted with Portuguese police/security professionals (N = 644). Latent class analysis (LCA) was applied to 17 indicators of potentially traumatic events coded as directly experienced or witnessed, derived from the Life Events Checklist for DSM-5. PTSD symptoms were assessed using the PTSD Checklist for DSM-5, and general psychological distress was assessed using the Brief Symptom Inventory. Exploratory receiver operating characteristic (ROC) analyses examined whether counts of proximal traumatic events could approximate the LCA-derived classes. Results: A three-class solution was identified, comprising low proximal exposure (37.3%), moderate proximal exposure (40.7%), and high proximal/cumulative exposure (22.0%) classes. The classes reflected a graded cumulative pattern of exposure across traumatic event categories, rather than clearly distinct qualitative configurations defined by specific event types. Higher exposure classes were associated with progressively higher PTSD symptoms and psychological distress, and these associations remained significant after adjustment for sociodemographic and occupational variables. Exploratory receiver operating characteristic (ROC) analyses showed that a simple count of proximal traumatic event categories closely approximated the empirically derived class structure within the present sample. However, the resulting thresholds are sample-specific, exploratory, and should not be interpreted as validated screening cutoffs. Conclusions: Proximal traumatic exposure among police/security professionals appears to follow a graded cumulative structure associated with increased PTSD symptoms and psychological distress. The person-centered analysis provided an empirical test of whether exposure was organized according to qualitatively distinct event configurations or primarily along a cumulative gradient. In this sample, cumulative exposure burden emerged as the dominant organizing dimension. The count-based approximation requires external validation before any screening or decision-making application can be considered. © 2026 by the authors.},
keywords = {adult, Anxiety, article, cross-sectional study, decision making, Depression, DSM-5, female, Global Severity Index, hostility, human, human experiment, Latent Class Analysis, LEC-5, major clinical study, male, paranoia, phobia, police, Positive symptom distress index, Positive symptom total, posttraumatic stress disorder, posttraumatic stress disorder checklist, Proximal Traumatic Exposure, psychological distress, psychosis, PTSD, questionnaire, receiver operating characteristic, Security, security professionals, self report, sociodemographics, trauma exposure},
pubstate = {published},
tppubtype = {article}
}
Background: Police and security professionals are routinely exposed to potentially traumatic events as part of occupational duties, placing them at increased risk for post-traumatic stress and broader psychological difficulties. This study aimed to identify latent classes of proximal traumatic exposure among Portuguese police/security professionals and examine their associations with PTSD symptoms and general psychological distress. Methods: A cross-sectional online survey was conducted with Portuguese police/security professionals (N = 644). Latent class analysis (LCA) was applied to 17 indicators of potentially traumatic events coded as directly experienced or witnessed, derived from the Life Events Checklist for DSM-5. PTSD symptoms were assessed using the PTSD Checklist for DSM-5, and general psychological distress was assessed using the Brief Symptom Inventory. Exploratory receiver operating characteristic (ROC) analyses examined whether counts of proximal traumatic events could approximate the LCA-derived classes. Results: A three-class solution was identified, comprising low proximal exposure (37.3%), moderate proximal exposure (40.7%), and high proximal/cumulative exposure (22.0%) classes. The classes reflected a graded cumulative pattern of exposure across traumatic event categories, rather than clearly distinct qualitative configurations defined by specific event types. Higher exposure classes were associated with progressively higher PTSD symptoms and psychological distress, and these associations remained significant after adjustment for sociodemographic and occupational variables. Exploratory receiver operating characteristic (ROC) analyses showed that a simple count of proximal traumatic event categories closely approximated the empirically derived class structure within the present sample. However, the resulting thresholds are sample-specific, exploratory, and should not be interpreted as validated screening cutoffs. Conclusions: Proximal traumatic exposure among police/security professionals appears to follow a graded cumulative structure associated with increased PTSD symptoms and psychological distress. The person-centered analysis provided an empirical test of whether exposure was organized according to qualitatively distinct event configurations or primarily along a cumulative gradient. In this sample, cumulative exposure burden emerged as the dominant organizing dimension. The count-based approximation requires external validation before any screening or decision-making application can be considered. © 2026 by the authors.
2.
Zhu, Y.; Falk, T.
WavRx: A Disease-Agnostic, Generalizable, and Privacy-Preserving Speech Health Diagnostic Model Journal Article
In: IEEE Journal of Biomedical and Health Informatics, vol. 29, no. 9, pp. 6353–6365, 2025, ISSN: 21682194 (ISSN).
Abstract | Links | BibTeX | Tags: Agnostic, area under the curve, article, artificial neural network, asthma, autoencoder, Benchmarking, breathing, chronic obstructive lung disease, Computer-Assisted, controlled study, convolutional neural network, coronavirus disease 2019, Cross-domain, Databases, Diagnosis, Diagnostic, Diagnostic model, diagnostic test accuracy study, diagnostics, Differential privacy, Dynamics, dysarthria, Electronic health record, embedding, Embeddings, Factual, factual database, Generalizability, Health embedding, Health embeddings, Health monitoring, human, Humans, Machine learning, malignant neoplasm, model, Pathological speech, pathophysiology, physiology, pneumonia, Privacy, Privacy preserving, privacy preserving speech health diagnostic model, privacy-preserving, Privacy-preserving techniques, receiver operating characteristic, short time Fourier transform, Signal processing, speech, speech articulation, speech disorder, Speech Disorders, State of the art, temporal representation encoder, training, waveform
@article{zhuWavRxDiseaseAgnosticGeneralizable2025,
title = {WavRx: A Disease-Agnostic, Generalizable, and Privacy-Preserving Speech Health Diagnostic Model},
author = {Y. Zhu and T. Falk},
url = {https://www.scopus.com/pages/publications/85203439930?origin=resultslist},
doi = {10.1109/JBHI.2024.3454550},
issn = {21682194 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {IEEE Journal of Biomedical and Health Informatics},
volume = {29},
number = {9},
pages = {6353–6365},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Speech is known to carry health-related attributes, which has emerged as a novel venue for remote and long-term health monitoring. However, existing models are usually tailored for a specific type of disease, and have been shown to lack generalizability across datasets. Furthermore, concerns have been raised recently towards the leakage of speaker identity from health embeddings. To mitigate these limitations, we propose WavRx, a speech health diagnostics model that captures the respiration and articulation related dynamics from a universal speech representation. Our in-domain and cross-domain experiments on six pathological speech datasets demonstrate WavRx as a new state-of-the-art health diagnostic model. Furthermore, we show that the amount of speaker identity entailed in the WavRx health embeddings is significantly reduced without extra guidance during training. An in-depth analysis of the model was performed, thus providing physiological interpretation of its improved generalizability and privacy-preserving ability. © 2013 IEEE.},
keywords = {Agnostic, area under the curve, article, artificial neural network, asthma, autoencoder, Benchmarking, breathing, chronic obstructive lung disease, Computer-Assisted, controlled study, convolutional neural network, coronavirus disease 2019, Cross-domain, Databases, Diagnosis, Diagnostic, Diagnostic model, diagnostic test accuracy study, diagnostics, Differential privacy, Dynamics, dysarthria, Electronic health record, embedding, Embeddings, Factual, factual database, Generalizability, Health embedding, Health embeddings, Health monitoring, human, Humans, Machine learning, malignant neoplasm, model, Pathological speech, pathophysiology, physiology, pneumonia, Privacy, Privacy preserving, privacy preserving speech health diagnostic model, privacy-preserving, Privacy-preserving techniques, receiver operating characteristic, short time Fourier transform, Signal processing, speech, speech articulation, speech disorder, Speech Disorders, State of the art, temporal representation encoder, training, waveform},
pubstate = {published},
tppubtype = {article}
}
Speech is known to carry health-related attributes, which has emerged as a novel venue for remote and long-term health monitoring. However, existing models are usually tailored for a specific type of disease, and have been shown to lack generalizability across datasets. Furthermore, concerns have been raised recently towards the leakage of speaker identity from health embeddings. To mitigate these limitations, we propose WavRx, a speech health diagnostics model that captures the respiration and articulation related dynamics from a universal speech representation. Our in-domain and cross-domain experiments on six pathological speech datasets demonstrate WavRx as a new state-of-the-art health diagnostic model. Furthermore, we show that the amount of speaker identity entailed in the WavRx health embeddings is significantly reduced without extra guidance during training. An in-depth analysis of the model was performed, thus providing physiological interpretation of its improved generalizability and privacy-preserving ability. © 2013 IEEE.
3.
Marschall-Lévesque, S.; Rouleau, J. -L.; Renaud, P.
In: Archives of Sexual Behavior, vol. 47, no. 2, pp. 417–428, 2018, ISSN: 00040002, (Publisher: Springer New York LLC).
Abstract | Links | BibTeX | Tags: Acoustic Stimulation, Adolescent, adult, auditory stimulation, Child, clinical article, controlled study, crime victim, Crime Victims, Diagnosis, DSM-5, Feedback, female, human, Humans, male, Pedophilia, Penis, Photic Stimulation, photostimulation, physiology, Plethysmography, procedures, psychology, receiver operating characteristic, Sensory, sensory feedback, sex determination, Sex Offenses, sexual crime, stimulus, victim, Young Adult
@article{marschall-levesque_increasing_2018,
title = {Increasing Valid Profiles in Phallometric Assessment of Sex Offenders with Child Victims: Combining the Strengths of Audio Stimuli and Synthetic Characters},
author = {S. Marschall-Lévesque and J. -L. Rouleau and P. Renaud},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033397289&doi=10.1007%2fs10508-017-1053-y&partnerID=40&md5=bbb82341dfebd50938aa29358f8e0e69},
doi = {10.1007/s10508-017-1053-y},
issn = {00040002},
year = {2018},
date = {2018-01-01},
journal = {Archives of Sexual Behavior},
volume = {47},
number = {2},
pages = {417–428},
publisher = {Springer New York LLC},
abstract = {Penile plethysmography (PPG) is a measure of sexual interests that relies heavily on the stimuli it uses to generate valid results. Ethical considerations surrounding the use of real images in PPG have further limited the content admissible for these stimuli. To palliate this limitation, the current study aimed to combine audio and visual stimuli by incorporating computer-generated characters to create new stimuli capable of accurately classifying sex offenders with child victims, while also increasing the number of valid profiles. Three modalities (audio, visual, and audiovisual) were compared using two groups (15 sex offenders with child victims and 15 non-offenders). Both the new visual and audiovisual stimuli resulted in a 13% increase in the number of valid profiles at 2.5 mm, when compared to the standard audio stimuli. Furthermore, the new audiovisual stimuli generated a 34% increase in penile responses. All three modalities were able to discriminate between the two groups by their responses to the adult and child stimuli. Lastly, sexual interest indices for all three modalities could accurately classify participants in their appropriate groups, as demonstrated by ROC curve analysis (i.e., audio AUC = .81, 95% CI [.60, 1.00]; visual AUC = .84, 95% CI [.66, 1.00], and audiovisual AUC = .83, 95% CI [.63, 1.00]). Results suggest that computer-generated characters allow accurate discrimination of sex offenders with child victims and can be added to already validated stimuli to increase the number of valid profiles. The implications of audiovisual stimuli using computer-generated characters and their possible use in PPG evaluations are also discussed. © 2017, Springer Science+Business Media, LLC.},
note = {Publisher: Springer New York LLC},
keywords = {Acoustic Stimulation, Adolescent, adult, auditory stimulation, Child, clinical article, controlled study, crime victim, Crime Victims, Diagnosis, DSM-5, Feedback, female, human, Humans, male, Pedophilia, Penis, Photic Stimulation, photostimulation, physiology, Plethysmography, procedures, psychology, receiver operating characteristic, Sensory, sensory feedback, sex determination, Sex Offenses, sexual crime, stimulus, victim, Young Adult},
pubstate = {published},
tppubtype = {article}
}
Penile plethysmography (PPG) is a measure of sexual interests that relies heavily on the stimuli it uses to generate valid results. Ethical considerations surrounding the use of real images in PPG have further limited the content admissible for these stimuli. To palliate this limitation, the current study aimed to combine audio and visual stimuli by incorporating computer-generated characters to create new stimuli capable of accurately classifying sex offenders with child victims, while also increasing the number of valid profiles. Three modalities (audio, visual, and audiovisual) were compared using two groups (15 sex offenders with child victims and 15 non-offenders). Both the new visual and audiovisual stimuli resulted in a 13% increase in the number of valid profiles at 2.5 mm, when compared to the standard audio stimuli. Furthermore, the new audiovisual stimuli generated a 34% increase in penile responses. All three modalities were able to discriminate between the two groups by their responses to the adult and child stimuli. Lastly, sexual interest indices for all three modalities could accurately classify participants in their appropriate groups, as demonstrated by ROC curve analysis (i.e., audio AUC = .81, 95% CI [.60, 1.00]; visual AUC = .84, 95% CI [.66, 1.00], and audiovisual AUC = .83, 95% CI [.63, 1.00]). Results suggest that computer-generated characters allow accurate discrimination of sex offenders with child victims and can be added to already validated stimuli to increase the number of valid profiles. The implications of audiovisual stimuli using computer-generated characters and their possible use in PPG evaluations are also discussed. © 2017, Springer Science+Business Media, LLC.
4.
Marschall-Lévesque, S.; Rouleau, J. -L.; Renaud, P.
In: Archives of Sexual Behavior, vol. 47, no. 2, pp. 417–428, 2018, ISSN: 00040002.
Abstract | Links | BibTeX | Tags: Acoustic Stimulation, Adolescent, adult, auditory stimulation, Child, clinical article, controlled study, crime victim, Crime Victims, Diagnosis, DSM-5, Feedback, female, human, Humans, male, Pedophilia, Penis, Photic Stimulation, photostimulation, physiology, Plethysmography, procedures, psychology, receiver operating characteristic, Sensory, sensory feedback, sex determination, Sex Offenses, sexual crime, stimulus, victim, Young Adult
@article{marschall-levesqueIncreasingValidProfiles2018,
title = {Increasing Valid Profiles in Phallometric Assessment of Sex Offenders with Child Victims: Combining the Strengths of Audio Stimuli and Synthetic Characters},
author = {S. Marschall-Lévesque and J. -L. Rouleau and P. Renaud},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033397289&doi=10.1007%2fs10508-017-1053-y&partnerID=40&md5=bbb82341dfebd50938aa29358f8e0e69},
doi = {10.1007/s10508-017-1053-y},
issn = {00040002},
year = {2018},
date = {2018-01-01},
journal = {Archives of Sexual Behavior},
volume = {47},
number = {2},
pages = {417–428},
publisher = {Springer New York LLC},
abstract = {Penile plethysmography (PPG) is a measure of sexual interests that relies heavily on the stimuli it uses to generate valid results. Ethical considerations surrounding the use of real images in PPG have further limited the content admissible for these stimuli. To palliate this limitation, the current study aimed to combine audio and visual stimuli by incorporating computer-generated characters to create new stimuli capable of accurately classifying sex offenders with child victims, while also increasing the number of valid profiles. Three modalities (audio, visual, and audiovisual) were compared using two groups (15 sex offenders with child victims and 15 non-offenders). Both the new visual and audiovisual stimuli resulted in a 13% increase in the number of valid profiles at 2.5 mm, when compared to the standard audio stimuli. Furthermore, the new audiovisual stimuli generated a 34% increase in penile responses. All three modalities were able to discriminate between the two groups by their responses to the adult and child stimuli. Lastly, sexual interest indices for all three modalities could accurately classify participants in their appropriate groups, as demonstrated by ROC curve analysis (i.e., audio AUC = .81, 95% CI [.60, 1.00]; visual AUC = .84, 95% CI [.66, 1.00], and audiovisual AUC = .83, 95% CI [.63, 1.00]). Results suggest that computer-generated characters allow accurate discrimination of sex offenders with child victims and can be added to already validated stimuli to increase the number of valid profiles. The implications of audiovisual stimuli using computer-generated characters and their possible use in PPG evaluations are also discussed. © 2017, Springer Science+Business Media, LLC.},
keywords = {Acoustic Stimulation, Adolescent, adult, auditory stimulation, Child, clinical article, controlled study, crime victim, Crime Victims, Diagnosis, DSM-5, Feedback, female, human, Humans, male, Pedophilia, Penis, Photic Stimulation, photostimulation, physiology, Plethysmography, procedures, psychology, receiver operating characteristic, Sensory, sensory feedback, sex determination, Sex Offenses, sexual crime, stimulus, victim, Young Adult},
pubstate = {published},
tppubtype = {article}
}
Penile plethysmography (PPG) is a measure of sexual interests that relies heavily on the stimuli it uses to generate valid results. Ethical considerations surrounding the use of real images in PPG have further limited the content admissible for these stimuli. To palliate this limitation, the current study aimed to combine audio and visual stimuli by incorporating computer-generated characters to create new stimuli capable of accurately classifying sex offenders with child victims, while also increasing the number of valid profiles. Three modalities (audio, visual, and audiovisual) were compared using two groups (15 sex offenders with child victims and 15 non-offenders). Both the new visual and audiovisual stimuli resulted in a 13% increase in the number of valid profiles at 2.5 mm, when compared to the standard audio stimuli. Furthermore, the new audiovisual stimuli generated a 34% increase in penile responses. All three modalities were able to discriminate between the two groups by their responses to the adult and child stimuli. Lastly, sexual interest indices for all three modalities could accurately classify participants in their appropriate groups, as demonstrated by ROC curve analysis (i.e., audio AUC = .81, 95% CI [.60, 1.00]; visual AUC = .84, 95% CI [.66, 1.00], and audiovisual AUC = .83, 95% CI [.63, 1.00]). Results suggest that computer-generated characters allow accurate discrimination of sex offenders with child victims and can be added to already validated stimuli to increase the number of valid profiles. The implications of audiovisual stimuli using computer-generated characters and their possible use in PPG evaluations are also discussed. © 2017, Springer Science+Business Media, LLC.