Jean-Francois Pelletier, PhD
Assistant Clinical ProfessorAbout
Titles
Assistant Clinical Professor
Departments & Organizations
Education & Training
- PhD
- University of Quebec (2002)
Research
Publications
2024
The black box of the relationship between breast cancer patients and accompanying patients: the accompanied patients’ point of view
Pomey M, Iliescu Nelea M, Vialaron C, Normandin L, Côté M, Desforges M, Pomey-Carpentier P, Adjtoutah N, Fortin I, Ganache I, Régis C, Rosberger Z, Charpentier D, Bélanger L, Dorval M, Ghadiri D, Lavoie-Tremblay M, Boivin A, Pelletier J, Fernandez N, Danino A, de Guise M. The black box of the relationship between breast cancer patients and accompanying patients: the accompanied patients’ point of view. BMC Cancer 2024, 24: 822. PMID: 38987731, PMCID: PMC11234724, DOI: 10.1186/s12885-024-12585-z.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsSemi-structured interviewsCare trajectoryClinical teamBreast cancer patientsCare trajectory of peopleMethodsA qualitative studyEmotional well-beingQuality of lifeEnhance overall qualityCancer patientsResultsThree themesHealth professionalsPatient experienceHealthcare professionalsProvince of QuebecPatient communicationPatients' perceptionsEmotional reassuranceThematic analysisHealthcare systemUniversity Medical CenterQualitative studyPatient's pointTrajectories of peopleReduce anxietyPredicting the Population Risk of Suicide Using Routinely Collected Health Administrative Data in Quebec, Canada: Model-Based Synthetic Estimation Study
Wang J, Kharrat F, Gariépy G, Gagné C, Pelletier J, Massamba V, Lévesque P, Mohammed M, Lesage A. Predicting the Population Risk of Suicide Using Routinely Collected Health Administrative Data in Quebec, Canada: Model-Based Synthetic Estimation Study. JMIR Public Health And Surveillance 2024, 10: e52773. PMID: 38941610, PMCID: PMC11245657, DOI: 10.2196/52773.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsHealth administrative dataCommunity-level predictorsRisk prediction modelHealth care systemPopulation riskAdministrative dataHigh-risk regionsHealth systemCare systemIndividual's risk of suicideApplication of risk prediction modelsPopulation health planningHealth administrative databasesSignificant public health issueCase-control study designCommunity-level variablesRisk prediction toolsPublic health issueRisk of suicideSex-specific modelsProportion of suicidesIndividual-level predictorsAdministrative databasesHealth plansSuicide preventionExplainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec
Kharrat F, Gagne C, Lesage A, Gariépy G, Pelletier J, Brousseau-Paradis C, Rochette L, Pelletier E, Lévesque P, Mohammed M, Wang J. Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec. PLOS ONE 2024, 19: e0301117. PMID: 38568987, PMCID: PMC10990247, DOI: 10.1371/journal.pone.0301117.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsQuebec Integrated Chronic Disease Surveillance SystemLogistic regressionChronic Disease Surveillance SystemPredicting risk of suicideMental health service planningPrimary care programsHealth administrative dataHealth service planningCommunity level variablesCase-control study designPositive predictive valueManaged care systemRisk of suicideDisease surveillance systemsCare programProvince of QuebecSubstance use disordersCare systemMental healthSuicide preventionCommunity factorsService planningAdministrative dataPopulation riskExperience of suicidal behaviorsIntegrating accompanying patients into clinical oncology teams: limiting and facilitating factors
Pomey M, Paquette J, Nelea M, Vialaron C, Mourad R, Bouchard K, Normandin L, Côté M, Desforges M, Pomey-Carpentier P, Fortin I, Ganache I, Régis C, Rosberger Z, Charpentier D, Vachon M, Bélanger L, Dorval M, Ghadiri D, Lavoie-Tremblay M, Boivin A, Pelletier J, Fernandez N, Danino A, de Guise M. Integrating accompanying patients into clinical oncology teams: limiting and facilitating factors. BMC Health Services Research 2024, 24: 150. PMID: 38291443, PMCID: PMC10826234, DOI: 10.1186/s12913-024-10624-w.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsClinical oncology teamClinical teamTeam membersImproving cancer patients' experiencesOncology teamIdentification of patient needsCancer patients' experiencesClinical team membersMethodsA qualitative studyImprove patient servicesTeaching team membersSemi-structured interviewsExperiential knowledgePatient advisorsHealthcare teamPatient experienceHealthcare professionalsPatient needsPatient servicesFocus groupsStatus factorsAP-integralHealth establishmentsQualitative studyCommunication challengesThe Signature Biobank: A longitudinal biopsychosocial repository of psychiatric emergency patients
Kerr P, Le Page C, Giguère C, Marin M, Trudel-Fitzgerald C, Romain A, Taschereau-Dumouchel V, Ouellet-Morin I, Lecomte T, Potvin S, Geoffrion S, Sasseville M, Caihol L, Lipp O, Pelletier J, Dumais A, Lesage A, Labelle R, Lavoie M, Godbout R, Vincent P, Boissonneault J, Findlay H, Lupien S, Guay S, Juster R, Consortium S. The Signature Biobank: A longitudinal biopsychosocial repository of psychiatric emergency patients. Psychiatry Research 2024, 332: 115718. PMID: 38198857, DOI: 10.1016/j.psychres.2024.115718.Peer-Reviewed Original ResearchCitationsAltmetricConceptsPsychiatric emergency patientsPsychiatric disordersEmergency patientsOutpatient clinic appointmentsCommon psychiatric disordersSubsample of patientsPsychiatric emergency unitHospital dischargeClinic appointmentsPsychiatric comorbidityEmergency unitPatientsSystematic reviewSanté mentalePsychosocial functioningComparison groupDisordersField of psychiatryResearch protocolBiobankDiagnostic dataInstitut universitaireQuestionnaire dataLarge proportionBiological profile