Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Nouboukpo, A.; Allili, M. S.
Semi-supervised flow-augmented Gaussian mixture VAEs with weighted contrastive learning for out-of-distribution detection Journal Article
In: Knowledge-Based Systems, vol. 347, 2026, ISSN: 09507051 (ISSN).
Abstract | Links | BibTeX | Tags: Auto encoders, Benchmarking, Classification (of information), Clusterings, Contrastive Learning, Flow based, Flow-based GMM clustering, Gaussian distribution, Gaussian-mixtures, Learning algorithms, Learning systems, Out-of-distribution detection, Semantics, Semi-supervised, Semi-supervised learning, uncertainty, Variational autoencoder, Variational autoencoders (VAEs)
@article{nouboukpoSemisupervisedFlowaugmentedGaussian2026,
title = {Semi-supervised flow-augmented Gaussian mixture VAEs with weighted contrastive learning for out-of-distribution detection},
author = {A. Nouboukpo and M. S. Allili},
url = {https://www.scopus.com/pages/publications/105040505017?origin=resultslist},
doi = {10.1016/j.knosys.2026.116312},
issn = {09507051 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Knowledge-Based Systems},
volume = {347},
publisher = {Elsevier B.V.},
abstract = {Out-of-distribution (OOD) detection is essential for the safe deployment of machine learning systems, particularly in high-stakes domains where identifying inputs that deviate from the in-distribution (ID) is critical. However, in real-world scenarios, true OOD data are typically unavailable at training time, and only auxiliary datasets acting as imperfect proxies can be used. This makes fully supervised approaches impractical and potentially biased toward specific anomaly types. To address this limitation, we propose FLoW-ssGMVAE, a semi-supervised generative–discriminative framework that leverages limited proxy anomaly supervision together with abundant unlabeled data for robust OOD detection. Our model integrates a flow-augmented Gaussian Mixture VAE, enabling flexible latent modeling that captures nonlinear and multimodal intra-class distributions. Unlike standard VAEs with unimodal Gaussian priors, it uses class-conditional normalizing flows to better represent complex ID and OOD variability. To further refine the latent space and strengthen ID/OOD separation, our model integrates a weighted contrastive learning objective guided by sample-wise attention scores derived from likelihood uncertainty. This mechanism emphasizes ambiguous or hard-to-classify instances, reinforcing semantic boundaries and reducing false detections. By combining expressive generative modeling with uncertainty-aware discriminative training, our method constructs a structured and interpretable latent space that reliably identifies OOD samples under limited supervision. Experiments on standard benchmarks validate the effectiveness and scalability of our approach, demonstrating state-of-the-art performance with reasonable computational cost. Our implementation will be available at: FLoW-ssGMVAE. © 2026},
keywords = {Auto encoders, Benchmarking, Classification (of information), Clusterings, Contrastive Learning, Flow based, Flow-based GMM clustering, Gaussian distribution, Gaussian-mixtures, Learning algorithms, Learning systems, Out-of-distribution detection, Semantics, Semi-supervised, Semi-supervised learning, uncertainty, Variational autoencoder, Variational autoencoders (VAEs)},
pubstate = {published},
tppubtype = {article}
}
Out-of-distribution (OOD) detection is essential for the safe deployment of machine learning systems, particularly in high-stakes domains where identifying inputs that deviate from the in-distribution (ID) is critical. However, in real-world scenarios, true OOD data are typically unavailable at training time, and only auxiliary datasets acting as imperfect proxies can be used. This makes fully supervised approaches impractical and potentially biased toward specific anomaly types. To address this limitation, we propose FLoW-ssGMVAE, a semi-supervised generative–discriminative framework that leverages limited proxy anomaly supervision together with abundant unlabeled data for robust OOD detection. Our model integrates a flow-augmented Gaussian Mixture VAE, enabling flexible latent modeling that captures nonlinear and multimodal intra-class distributions. Unlike standard VAEs with unimodal Gaussian priors, it uses class-conditional normalizing flows to better represent complex ID and OOD variability. To further refine the latent space and strengthen ID/OOD separation, our model integrates a weighted contrastive learning objective guided by sample-wise attention scores derived from likelihood uncertainty. This mechanism emphasizes ambiguous or hard-to-classify instances, reinforcing semantic boundaries and reducing false detections. By combining expressive generative modeling with uncertainty-aware discriminative training, our method constructs a structured and interpretable latent space that reliably identifies OOD samples under limited supervision. Experiments on standard benchmarks validate the effectiveness and scalability of our approach, demonstrating state-of-the-art performance with reasonable computational cost. Our implementation will be available at: FLoW-ssGMVAE. © 2026
2.
Zhang, H.; Xu, Y.; Tian, Y.; Li, Y.; Falk, T. H.; Wang, F. -Y.
Selective Shift: Towards Personalized Domain Adaptation in Multi-Agent Collaborative Perception Proceedings Article
In: MM - Proc. ACM Int. Conf. Multimedia, Co-Located with MM, pp. 886–895, Association for Computing Machinery, Inc, 2025, ISBN: 979-840072035-2 (ISBN), (Journal Abbreviation: MM - Proc. ACM Int. Conf. Multimedia, Co-Located with MM).
Abstract | Links | BibTeX | Tags: 3D object, 3D object detection, Adaptation methods, Adaptive alignment, Collaborative perception, Domain adaptation, Entropy, Intelligent agents, Multi agent, Multi agent systems, Object detection, Object recognition, Objects detection, Relational semantics, Semantics, uncertainty
@inproceedings{zhangSelectiveShiftPersonalized2025,
title = {Selective Shift: Towards Personalized Domain Adaptation in Multi-Agent Collaborative Perception},
author = {H. Zhang and Y. Xu and Y. Tian and Y. Li and T. H. Falk and F. -Y. Wang},
url = {https://www.scopus.com/pages/publications/105024076483?origin=resultslist},
doi = {10.1145/3746027.3754723},
isbn = {979-840072035-2 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {MM - Proc. ACM Int. Conf. Multimedia, Co-Located with MM},
pages = {886–895},
publisher = {Association for Computing Machinery, Inc},
abstract = {Given the scarcity of real data and the time-intensive nature of labeling, current multi-agent perception models often rely on simulated sensor data for training and validation. However, perception performance deteriorates significantly due to domain gap between simulated and real data. Existing adaptation methods focus on domain-generalized feature extraction while neglecting multi-agent shift uncertainty and relational semantic loss. To address this issue, we propose a Selective Shift Domain Adaptation method in multi-agent collaborative perception, called SSDA. SSDA incorporates two essential components: the frequency-decoupled feature shift adjustment (FSA) and the entropy-driven staged adaptive alignment (SAA). To mitigate the relational semantic loss, the FSA is proposed to simplify the representation of correlation features and remove redundant information from the source domain, thereby mitigating interference for domain adversarial scenarios. To tackle the shift uncertainty, the SAA is designed to achieve adaptive alignment from global to local guided by information entropy, which dynamically adjusts weights for samples according to their level of uncertainty. The results demonstrate that the SSDA is significantly superior to the SOTA, achieving up to 7.35% improvements on AP@0.7. © 2025 ACM.},
note = {Journal Abbreviation: MM - Proc. ACM Int. Conf. Multimedia, Co-Located with MM},
keywords = {3D object, 3D object detection, Adaptation methods, Adaptive alignment, Collaborative perception, Domain adaptation, Entropy, Intelligent agents, Multi agent, Multi agent systems, Object detection, Object recognition, Objects detection, Relational semantics, Semantics, uncertainty},
pubstate = {published},
tppubtype = {inproceedings}
}
Given the scarcity of real data and the time-intensive nature of labeling, current multi-agent perception models often rely on simulated sensor data for training and validation. However, perception performance deteriorates significantly due to domain gap between simulated and real data. Existing adaptation methods focus on domain-generalized feature extraction while neglecting multi-agent shift uncertainty and relational semantic loss. To address this issue, we propose a Selective Shift Domain Adaptation method in multi-agent collaborative perception, called SSDA. SSDA incorporates two essential components: the frequency-decoupled feature shift adjustment (FSA) and the entropy-driven staged adaptive alignment (SAA). To mitigate the relational semantic loss, the FSA is proposed to simplify the representation of correlation features and remove redundant information from the source domain, thereby mitigating interference for domain adversarial scenarios. To tackle the shift uncertainty, the SAA is designed to achieve adaptive alignment from global to local guided by information entropy, which dynamically adjusts weights for samples according to their level of uncertainty. The results demonstrate that the SSDA is significantly superior to the SOTA, achieving up to 7.35% improvements on AP@0.7. © 2025 ACM.
3.
Dugas, M. J.; Marchal, K. Giguère; Cormier, S.; Bouchard, S.; Gouin, J. -P.; Shafran, R.
Pain catastrophizing and worry about health in generalized anxiety disorder Journal Article
In: Clinical Psychology and Psychotherapy, vol. 30, no. 4, pp. 852–861, 2023, ISSN: 10633995, (Publisher: John Wiley and Sons Ltd).
Abstract | Links | BibTeX | Tags: adult, Anxiety, Anxiety disorder, Anxiety Disorders, Catastrophization, catastrophizing, human, Humans, Pain, psychology, uncertainty
@article{dugas_pain_2023,
title = {Pain catastrophizing and worry about health in generalized anxiety disorder},
author = {M. J. Dugas and K. Giguère Marchal and S. Cormier and S. Bouchard and J. -P. Gouin and R. Shafran},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150514206&doi=10.1002%2fcpp.2843&partnerID=40&md5=2676de0f5a42bcdaea5f10aa5e8e3f55},
doi = {10.1002/cpp.2843},
issn = {10633995},
year = {2023},
date = {2023-01-01},
journal = {Clinical Psychology and Psychotherapy},
volume = {30},
number = {4},
pages = {852–861},
publisher = {John Wiley and Sons Ltd},
abstract = {Because the diagnostic criteria of generalized anxiety disorder (GAD) are not tied to specific worry domains (worry is ‘generalized’), research on the content of worry in GAD is lacking. To our knowledge, no study has addressed vulnerability for specific worry topics in GAD. The goal of the current study, a secondary analysis of data from a clinical trial, is to explore the relationship between pain catastrophizing and worry about health in a sample of 60 adults with primary GAD. All data for this study were collected at pretest, prior to randomization to experimental condition in the larger trial. The hypotheses were that (1) pain catastrophizing would be positively related to the severity of GAD, (2) the relationship between pain catastrophizing and the severity of GAD would not be explained by intolerance of uncertainty and psychological rigidity, and (3) pain catastrophizing would be greater in participants reporting worry about health compared to those not reporting worry about health. All hypotheses were confirmed, suggesting that pain catastrophizing may be a threat-specific vulnerability for health-related worry in GAD. The implications of the current findings include a better understanding of the ideographic content of worry, which could help focus treatment interventions for individuals with GAD. © 2023 The Authors. Clinical Psychology & Psychotherapy published by John Wiley & Sons Ltd.},
note = {Publisher: John Wiley and Sons Ltd},
keywords = {adult, Anxiety, Anxiety disorder, Anxiety Disorders, Catastrophization, catastrophizing, human, Humans, Pain, psychology, uncertainty},
pubstate = {published},
tppubtype = {article}
}
Because the diagnostic criteria of generalized anxiety disorder (GAD) are not tied to specific worry domains (worry is ‘generalized’), research on the content of worry in GAD is lacking. To our knowledge, no study has addressed vulnerability for specific worry topics in GAD. The goal of the current study, a secondary analysis of data from a clinical trial, is to explore the relationship between pain catastrophizing and worry about health in a sample of 60 adults with primary GAD. All data for this study were collected at pretest, prior to randomization to experimental condition in the larger trial. The hypotheses were that (1) pain catastrophizing would be positively related to the severity of GAD, (2) the relationship between pain catastrophizing and the severity of GAD would not be explained by intolerance of uncertainty and psychological rigidity, and (3) pain catastrophizing would be greater in participants reporting worry about health compared to those not reporting worry about health. All hypotheses were confirmed, suggesting that pain catastrophizing may be a threat-specific vulnerability for health-related worry in GAD. The implications of the current findings include a better understanding of the ideographic content of worry, which could help focus treatment interventions for individuals with GAD. © 2023 The Authors. Clinical Psychology & Psychotherapy published by John Wiley & Sons Ltd.
4.
Dugas, M. J.; Sexton, K. A.; Hebert, E. A.; Bouchard, S.; Gouin, J. -P.; Shafran, R.
Behavioral Experiments for Intolerance of Uncertainty: A Randomized Clinical Trial for Adults With Generalized Anxiety Disorder Journal Article
In: Behavior Therapy, vol. 53, no. 6, pp. 1147–1160, 2022, ISSN: 00057894 (ISSN), (Publisher: Elsevier Inc.).
Abstract | Links | BibTeX | Tags: adult, aged, antidepressant agent, Anxiety, Anxiety disorder, Anxiety Disorders, anxiolytic agent, article, behavior assessment, behavioral experiments, benzodiazepine, cognitive behavioral therapy, cognitive vulnerability, Cognitive-behavioral treatment, confusion (uncertainty), controlled study, dependent variable, Depression, disease severity, female, follow up, generalized anxiety disorder, growth curve, human, Humans, intolerance of uncertainty, major clinical study, male, mental disease, outcome assessment, patient worry, procedures, psychology, randomized controlled trial, uncertainty
@article{dugas_behavioral_2022,
title = {Behavioral Experiments for Intolerance of Uncertainty: A Randomized Clinical Trial for Adults With Generalized Anxiety Disorder},
author = {M. J. Dugas and K. A. Sexton and E. A. Hebert and S. Bouchard and J. -P. Gouin and R. Shafran},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133178888&doi=10.1016%2fj.beth.2022.05.003&partnerID=40&md5=4dd15547cbef29c5f1adc84169176c53},
doi = {10.1016/j.beth.2022.05.003},
issn = {00057894 (ISSN)},
year = {2022},
date = {2022-01-01},
journal = {Behavior Therapy},
volume = {53},
number = {6},
pages = {1147–1160},
publisher = {Elsevier Inc.},
abstract = {Sophisticated multicomponent treatments for adults with generalized anxiety disorder (GAD) have been developed over the past three decades. Although these comprehensive treatments have produced encouraging results, they appear to be less efficacious than treatments for other anxiety disorders. The goal of this randomized controlled trial is to test a newly developed, highly focused treatment for adults with GAD: Behavioral Experiments for Intolerance of Uncertainty. Sixty (60) participants (51 women, 9 men), with a mean age of 34.60 years (range: 19 to 67 years), were randomized to either treatment (n = 30) or wait-list control (n = 30). Treatment consisted of 12 weekly 1-hour sessions in which participants learned to use behavioral experiments to test their catastrophic beliefs about uncertainty. Assessments were conducted at pre-, mid- and postcondition, and at 6- and 12-month follow-up. The primary outcome was the severity of GAD, and secondary outcomes were worry, depression, somatic anxiety, and intolerance of uncertainty. Using growth curve modeling, we found that (1) the treatment group was superior to the wait-list group in terms of change from pre- to posttest on all outcomes; (2) the combined sample (once wait-listed participants received treatment) evidenced large and significant decreases on all outcomes; and (3) treatment gains were either maintained or increased over the 12-month follow-up period of the study. The new treatment is a promising treatment option for adults with GAD considering that it may be as efficacious as more comprehensive evidence-based psychological treatments for GAD. © 2022},
note = {Publisher: Elsevier Inc.},
keywords = {adult, aged, antidepressant agent, Anxiety, Anxiety disorder, Anxiety Disorders, anxiolytic agent, article, behavior assessment, behavioral experiments, benzodiazepine, cognitive behavioral therapy, cognitive vulnerability, Cognitive-behavioral treatment, confusion (uncertainty), controlled study, dependent variable, Depression, disease severity, female, follow up, generalized anxiety disorder, growth curve, human, Humans, intolerance of uncertainty, major clinical study, male, mental disease, outcome assessment, patient worry, procedures, psychology, randomized controlled trial, uncertainty},
pubstate = {published},
tppubtype = {article}
}
Sophisticated multicomponent treatments for adults with generalized anxiety disorder (GAD) have been developed over the past three decades. Although these comprehensive treatments have produced encouraging results, they appear to be less efficacious than treatments for other anxiety disorders. The goal of this randomized controlled trial is to test a newly developed, highly focused treatment for adults with GAD: Behavioral Experiments for Intolerance of Uncertainty. Sixty (60) participants (51 women, 9 men), with a mean age of 34.60 years (range: 19 to 67 years), were randomized to either treatment (n = 30) or wait-list control (n = 30). Treatment consisted of 12 weekly 1-hour sessions in which participants learned to use behavioral experiments to test their catastrophic beliefs about uncertainty. Assessments were conducted at pre-, mid- and postcondition, and at 6- and 12-month follow-up. The primary outcome was the severity of GAD, and secondary outcomes were worry, depression, somatic anxiety, and intolerance of uncertainty. Using growth curve modeling, we found that (1) the treatment group was superior to the wait-list group in terms of change from pre- to posttest on all outcomes; (2) the combined sample (once wait-listed participants received treatment) evidenced large and significant decreases on all outcomes; and (3) treatment gains were either maintained or increased over the 12-month follow-up period of the study. The new treatment is a promising treatment option for adults with GAD considering that it may be as efficacious as more comprehensive evidence-based psychological treatments for GAD. © 2022
5.
Dugas, M. J.; Sexton, K. A.; Hebert, E. A.; Bouchard, S.; Gouin, J. -P.; Shafran, R.
Behavioral Experiments for Intolerance of Uncertainty: A Randomized Clinical Trial for Adults With Generalized Anxiety Disorder Journal Article
In: Behavior Therapy, vol. 53, no. 6, pp. 1147–1160, 2022, ISSN: 00057894 (ISSN).
Abstract | Links | BibTeX | Tags: adult, aged, antidepressant agent, Anxiety, Anxiety disorder, Anxiety Disorders, anxiolytic agent, article, behavior assessment, behavioral experiments, benzodiazepine, cognitive behavioral therapy, cognitive vulnerability, Cognitive-behavioral treatment, confusion (uncertainty), controlled study, dependent variable, Depression, disease severity, female, follow up, generalized anxiety disorder, growth curve, human, Humans, intolerance of uncertainty, major clinical study, male, mental disease, outcome assessment, patient worry, procedures, psychology, randomized controlled trial, uncertainty
@article{dugasBehavioralExperimentsIntolerance2022,
title = {Behavioral Experiments for Intolerance of Uncertainty: A Randomized Clinical Trial for Adults With Generalized Anxiety Disorder},
author = {M. J. Dugas and K. A. Sexton and E. A. Hebert and S. Bouchard and J. -P. Gouin and R. Shafran},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133178888&doi=10.1016%2fj.beth.2022.05.003&partnerID=40&md5=4dd15547cbef29c5f1adc84169176c53},
doi = {10.1016/j.beth.2022.05.003},
issn = {00057894 (ISSN)},
year = {2022},
date = {2022-01-01},
journal = {Behavior Therapy},
volume = {53},
number = {6},
pages = {1147–1160},
publisher = {Elsevier Inc.},
abstract = {Sophisticated multicomponent treatments for adults with generalized anxiety disorder (GAD) have been developed over the past three decades. Although these comprehensive treatments have produced encouraging results, they appear to be less efficacious than treatments for other anxiety disorders. The goal of this randomized controlled trial is to test a newly developed, highly focused treatment for adults with GAD: Behavioral Experiments for Intolerance of Uncertainty. Sixty (60) participants (51 women, 9 men), with a mean age of 34.60 years (range: 19 to 67 years), were randomized to either treatment (n = 30) or wait-list control (n = 30). Treatment consisted of 12 weekly 1-hour sessions in which participants learned to use behavioral experiments to test their catastrophic beliefs about uncertainty. Assessments were conducted at pre-, mid- and postcondition, and at 6- and 12-month follow-up. The primary outcome was the severity of GAD, and secondary outcomes were worry, depression, somatic anxiety, and intolerance of uncertainty. Using growth curve modeling, we found that (1) the treatment group was superior to the wait-list group in terms of change from pre- to posttest on all outcomes; (2) the combined sample (once wait-listed participants received treatment) evidenced large and significant decreases on all outcomes; and (3) treatment gains were either maintained or increased over the 12-month follow-up period of the study. The new treatment is a promising treatment option for adults with GAD considering that it may be as efficacious as more comprehensive evidence-based psychological treatments for GAD. © 2022},
keywords = {adult, aged, antidepressant agent, Anxiety, Anxiety disorder, Anxiety Disorders, anxiolytic agent, article, behavior assessment, behavioral experiments, benzodiazepine, cognitive behavioral therapy, cognitive vulnerability, Cognitive-behavioral treatment, confusion (uncertainty), controlled study, dependent variable, Depression, disease severity, female, follow up, generalized anxiety disorder, growth curve, human, Humans, intolerance of uncertainty, major clinical study, male, mental disease, outcome assessment, patient worry, procedures, psychology, randomized controlled trial, uncertainty},
pubstate = {published},
tppubtype = {article}
}
Sophisticated multicomponent treatments for adults with generalized anxiety disorder (GAD) have been developed over the past three decades. Although these comprehensive treatments have produced encouraging results, they appear to be less efficacious than treatments for other anxiety disorders. The goal of this randomized controlled trial is to test a newly developed, highly focused treatment for adults with GAD: Behavioral Experiments for Intolerance of Uncertainty. Sixty (60) participants (51 women, 9 men), with a mean age of 34.60 years (range: 19 to 67 years), were randomized to either treatment (n = 30) or wait-list control (n = 30). Treatment consisted of 12 weekly 1-hour sessions in which participants learned to use behavioral experiments to test their catastrophic beliefs about uncertainty. Assessments were conducted at pre-, mid- and postcondition, and at 6- and 12-month follow-up. The primary outcome was the severity of GAD, and secondary outcomes were worry, depression, somatic anxiety, and intolerance of uncertainty. Using growth curve modeling, we found that (1) the treatment group was superior to the wait-list group in terms of change from pre- to posttest on all outcomes; (2) the combined sample (once wait-listed participants received treatment) evidenced large and significant decreases on all outcomes; and (3) treatment gains were either maintained or increased over the 12-month follow-up period of the study. The new treatment is a promising treatment option for adults with GAD considering that it may be as efficacious as more comprehensive evidence-based psychological treatments for GAD. © 2022
6.
Marcotte-Beaumier, G.; Bouchard, S.; Gosselin, P.; Langlois, F.; Belleville, G.; Marchand, A.; Dugas, M. J.
In: JMIR Mental Health, vol. 8, no. 3, 2021, ISSN: 23687959, (Publisher: JMIR Publications Inc.).
Abstract | Links | BibTeX | Tags: adult, article, clinical article, cognitive behavioral therapy, consensus, controlled study, female, follow up, generalized anxiety disorder, human, male, mediation analysis, outcome assessment, randomized controlled trial, telehealth, therapeutic alliance, treatment outcome, uncertainty, videoconferencing
@article{marcotte-beaumier_role_2021,
title = {The role of intolerance of uncertainty and working alliance in the outcome of cognitive behavioral therapy for generalized anxiety disorder delivered by videoconference: Mediation analysis},
author = {G. Marcotte-Beaumier and S. Bouchard and P. Gosselin and F. Langlois and G. Belleville and A. Marchand and M. J. Dugas},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103169307&doi=10.2196%2f24541&partnerID=40&md5=6d4abe613d27257552970428c3a84bb4},
doi = {10.2196/24541},
issn = {23687959},
year = {2021},
date = {2021-01-01},
journal = {JMIR Mental Health},
volume = {8},
number = {3},
publisher = {JMIR Publications Inc.},
abstract = {Background: Previous meta-analyses have shown a significant relationship between working alliance and treatment outcome in general. Some studies have examined the relationship between working alliance and treatment outcome during telepsychotherapy, but to the best of our knowledge, no study has examined the mediating role of individual components of the working alliance. Objective: As part of a clinical trial of cognitive behavioral therapy (CBT) for generalized anxiety disorder (GAD) delivered by videoconference (VC), the aim of this study is to examine the mediating role of intolerance of uncertainty on the relationship between the components of the working alliance and treatment outcome. Methods: A sample of 46 adults with primary GAD received 15 sessions of CBT for GAD delivered over VC. Participants completed the measure of working alliance immediately after the fifth therapy session. The degree of change in intolerance of uncertainty (a key psychological process) was assessed from pre- to posttreatment. Treatment outcome was assessed via changes in GAD symptoms from pretreatment to the 6-month follow-up. Results: The results revealed that the therapeutic bond did not predict treatment outcome (r=-0.23; P=.12). However, agreement on therapeutic goals and tasks did predict treatment outcome (r=-0.42; P=.004 and r=-0.37; P=.01, respectively). In addition, the relationship between consensus on therapeutic tasks and treatment outcome was completely mediated by changes in intolerance of uncertainty (unstandardized β=-0.03; r2=0.12), whereas consensus relative to treatment goals had a direct impact on treatment outcome. Conclusions: These results provide a better understanding of the differential role of the components of the working alliance in telepsychotherapy as a facilitative factor for changes in key cognitive processes, leading to therapeutic change. © 2021 JMIR Publications Inc. All Rights Reserved.},
note = {Publisher: JMIR Publications Inc.},
keywords = {adult, article, clinical article, cognitive behavioral therapy, consensus, controlled study, female, follow up, generalized anxiety disorder, human, male, mediation analysis, outcome assessment, randomized controlled trial, telehealth, therapeutic alliance, treatment outcome, uncertainty, videoconferencing},
pubstate = {published},
tppubtype = {article}
}
Background: Previous meta-analyses have shown a significant relationship between working alliance and treatment outcome in general. Some studies have examined the relationship between working alliance and treatment outcome during telepsychotherapy, but to the best of our knowledge, no study has examined the mediating role of individual components of the working alliance. Objective: As part of a clinical trial of cognitive behavioral therapy (CBT) for generalized anxiety disorder (GAD) delivered by videoconference (VC), the aim of this study is to examine the mediating role of intolerance of uncertainty on the relationship between the components of the working alliance and treatment outcome. Methods: A sample of 46 adults with primary GAD received 15 sessions of CBT for GAD delivered over VC. Participants completed the measure of working alliance immediately after the fifth therapy session. The degree of change in intolerance of uncertainty (a key psychological process) was assessed from pre- to posttreatment. Treatment outcome was assessed via changes in GAD symptoms from pretreatment to the 6-month follow-up. Results: The results revealed that the therapeutic bond did not predict treatment outcome (r=-0.23; P=.12). However, agreement on therapeutic goals and tasks did predict treatment outcome (r=-0.42; P=.004 and r=-0.37; P=.01, respectively). In addition, the relationship between consensus on therapeutic tasks and treatment outcome was completely mediated by changes in intolerance of uncertainty (unstandardized β=-0.03; r2=0.12), whereas consensus relative to treatment goals had a direct impact on treatment outcome. Conclusions: These results provide a better understanding of the differential role of the components of the working alliance in telepsychotherapy as a facilitative factor for changes in key cognitive processes, leading to therapeutic change. © 2021 JMIR Publications Inc. All Rights Reserved.