Canadian Journal of Psychiatry-Revue Canadienne De Psychiatrie最新文献

Objective: Responsible media reporting is an accepted strategy for preventing suicide. In 2015, suicide prevention experts launched a media engagement initiative aimed at improving suicide-related reporting in Canada; its impact on media reporting quality and suicide deaths is unknown.

Method: This pre-post observational study examined changes in reporting characteristics in a random sample of suicide-related articles from major publications in the Greater Toronto Area (GTA) media market. Articles (n = 900) included 450 from the 6-year periods prior to and after the initiative began. We also examined changes in suicide counts in the GTA between these epochs. We used chi-square tests to analyse changes in reporting characteristics and time-series analyses to identify changes in suicide counts. Secondary outcomes focused on guidelines developed by media professionals in Canada and how they may have influenced media reporting quality as well as on the overarching narrative of media articles during the most recent years of available data.

Results: Across-the-board improvement was observed in suicide-related reporting with substantial reductions in many elements of putatively harmful content and substantial increases in all aspects of putatively protective content. However, overarching article narratives remained potentially harmful with 55.2% of articles telling the story of someone's death and 20.8% presenting an other negative message. Only 3.6% of articles told a story of survival. After controlling for potential confounders, a nonsignificant numeric decrease in suicide counts was identified after initiative implementation (ω = -5.41, SE  =  3.43, t  =  1.58, p  =  0.12).

Conclusions: We found evidence that a strategy to engage media in Canada changed the content of reporting, but there was only a nonsignificant trend towards fewer suicides. A more fundamental change in media narratives to focus on survival rather than death appears warranted.

Objective: To estimate prevalence and incidence rates over time in children and youth with attention deficit/hyperactivity disorder from the validation of population-based administrative data algorithms using family physicians' electronic medical records as a reference standard.

Methods: A retrospective cohort study was conducted in Ontario, Canada to identify attention deficit/hyperactivity disorder among children and youth aged 1-24 years in health administrative data derived from case-finding algorithms using family physicians' electronic medical records. Multiple administrative data algorithms identifying attention deficit/hyperactivity disorder cases were developed and tested from physician-diagnosis of attention deficit/hyperactivity disorder in the electronic medical record to determine their diagnostic accuracy. We calculated algorithm performance using sensitivity, specificity, and predictive values. The most optimal algorithm was used to estimate prevalence and incidence rates of attention deficit/hyperactivity disorder from 2014 to 2021 in Ontario.

Results: The optimal performing algorithm was "2 physician visits for attention deficit/hyperactivity disorder in 1 year or 1 attention deficit/hyperactivity disorder-specific prescription" with sensitivity: 83.2% (95% confidence interval [CI], 81.8% to 84.5%), specificity: 98.6% (95% CI, 98.5% to 98.7%), positive predictive value: 78.6% (95% CI, 77.1% to 80.0%) and negative predictive value: 98.9% (95% CI, 98.8% to 99.0%). From 2014, prevalence rates for attention deficit/hyperactivity disorder increased from 5.29 to 7.48 per 100 population in 2021 (N = 281,785). Males had higher prevalence rates (7.49 to 9.59 per 100 population, 1.3-fold increase) than females (2.96-5.26 per 100 population, 1.8-fold increase) from 2014 to 2021. Incidence rates increased from 2014 (0.53 per 100 population) until 2018, decreased in 2020 then rose steeply in 2021 (0.89 per 100 population, N = 34,013). Males also had higher incidence rates than females from 2014 to 2020 with females surpassing males in 2021 (0.70-0.81 per 100 male population,1.2-fold increase versus 0.36-0.97 per 100 female population, 2.7-fold increase).

Conclusions: Attention deficit/hyperactivity disorder is increasing in prevalence. We developed an administrative data algorithm that can reliably identify children and youth with attention deficit/hyperactivity disorder with good diagnostic accuracy.

Objectives: Emergency departments (EDs) are a vital part of healthcare systems, at times acting as a gateway to community-based mental health (MH) services. This may be particularly true for veterans of the Royal Canadian Mounted Police who were released prior to 2013 and the Canadian Armed Forces, as these individuals transition from federal to provincial healthcare coverage on release and may use EDs because of delays in obtaining a primary care provider. We aimed to estimate the hazard ratio (HR) of MH-related ED visits between veterans and non-veterans residing in Ontario, Canada: (1) overall; and by (2) sex; and (3) length of service.

Methods: This retrospective cohort study used administrative healthcare data from 18,837 veterans and 75,348 age-, sex-, geography-, and income-matched non-veterans residing in Ontario, Canada between April 1, 2002, and March 31, 2020. Anderson-Gill regression models were used to estimate the HR of recurrent MH-related ED visits during the period of follow-up. Sex and length of service were used as stratification variables in the models.

Results: Veterans had a higher adjusted HR (aHR) of MH-related ED visits than non-veterans (aHR, 1.97, 95% CI, 1.70 to 2.29). A stronger effect was observed among females (aHR, 3.29; 95% CI, 1.96 to 5.53) than males (aHR, 1.78; 95% CI, 1.57 to 2.01). Veterans who served for 5-9 years had a higher rate of use than non-veterans (aHR, 3.76; 95% CI, 2.34 to 6.02) while veterans who served for 30+ years had a lower rate compared to non-veterans (aHR, 0.60; 95% CI, 0.42 à 0.84).

Conclusions: Rates of MH-related ED visits are higher among veterans overall compared to members of the Ontario general population, but usage is influenced by sex and length of service. These findings indicate that certain subpopulations of veterans, including females and those with fewer years of service, may have greater acute mental healthcare needs and/or reduced access to primary mental healthcare.

Objectives: There is limited evidence on how opioid agonist treatment (OAT) may affect psychoactive non-opioid substance use in prescription-type opioid use disorder (POUD) and whether this effect might explain OAT outcomes. We aimed to assess the effect of methadone on non-opioid substance use compared to buprenorphine/naloxone (BUP/NX), to explore whether non-opioid substance use is associated with opioid use and retention in treatment, and to test non-opioid use as a moderator of associations between methadone with retention in OAT and opioid use compared to BUP/NX.

Methods: This is a secondary analysis of data from the OPTIMA trial, an open-label, pragmatic, parallel, two-arm, pan-Canadian, multicentre, randomized-controlled trial to compare standard methadone model of care and flexible take-home dosing BUP/NX for POUD treatment. We studied the effect of methadone and BUP/NX on non-opioid substance use evaluated by urine drug screen (UDS) and by classes of non-opioid substances (i.e., tetrahydrocannabinol [THC], benzodiazepines, stimulants) (weeks 2-24) using adjusted generalized estimation equation (GEE). We studied the association between non-opioid substance-positive UDS and opioid-positive UDS and retention in treatment, using adjusted GEE and logistic regressions.

Results: Overall, methadone was not associated with non-opioid substance-positive UDS compared to BUP/NX (OR: 0.78; 95%CI, 0.41 to 1.48). When non-opioid substances were studied separately, methadone was associated with lower odds of benzodiazepine-positive UDS (OR: 0.63; 95% CI: 0.40 to 0.98) and THC-positive UDS (OR: 0.47; 95% CI: 0.28 to 0.77), but not with different odds of stimulant-positive UDS (OR: 1.29; 95% CI: 0.78 to 2.16) compared to BUP/NX. Substance-positive UDS, overall and separate classes, were not associated with opioid-positive UDS or retention in treatment.

Conclusion: Methadone did not show a significant effect on overall non-opioid substance use in POUD compared to BUP/NX treatment but was associated with lower odds of benzodiazepine and THC use in particular. Non-opioid substance use did not predict OAT outcomes. Further research is needed to ascertain whether specific patterns of polysubstance use (quantity and frequency) may affect treatment outcomes.

Objective: This study established a machine learning model based on the multidimensional data of resting-state functional activity of the brain and P11 gene DNA methylation to predict the early efficacy of antidepressant treatment in patients with major depressive disorder (MDD).

Methods: A total of 98 Han Chinese MDD were analysed in this study. Patients were divided into 51 responders and 47 nonresponders according to whether the Hamilton Depression Rating Scale-17 items (HAMD-17) reduction rate was ≥50% after 2 weeks of antidepressant treatment. At baseline, the Illumina HiSeq Platform was used to detect the methylation of 74 CpG sites of the P11 gene in peripheral blood samples. Resting-state functional magnetic resonance imaging (rs-fMRI) scan detected the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) in 116 brain regions. The least absolute shrinkage and selection operator analysis method was used to perform feature reduction and feature selection. Four typical machine learning methods were used to establish support vector machine (SVM), random forest (RF), Naïve Bayes (NB), and logistic regression (LR) prediction models based on different combinations of functional activity of the brain, P11 gene DNA methylation and clinical/demographic features after screening.

Results: The SVM model based on ALFF, ReHo, FC, P11 methylation, and clinical/demographic features showed the best performance, with 95.92% predictive accuracy and 0.9967 area under the receiver operating characteristic curve, which was better than RF, NB, and LR models.

Conclusion: The multidimensional data features combining rs-fMRI, DNA methylation, and clinical/demographic features can predict the early antidepressant efficacy in MDD.

Objectives: Many people who are diagnosed with bipolar disorder also have comorbid personality disorder. Few studies have explored how personality disorder may influence pharmacological treatment outcomes. The aim of this study was to conduct a secondary analysis of data from a clinical trial of adjunctive nutraceutical treatments for bipolar depression, to determine whether maladaptive personality traits influence treatment outcomes.

Methods: Scores on the Standardised Assessment of Personality - Abbreviated Scale screener were used to classify participants as having bipolar disorder with (n = 119) and without (n = 29) above threshold personality disorder symptoms (personality disorder). Outcome measures included: The Montgomery Åsberg Depression Rating Scale, Clinical Global Impressions and Improvement Severity Scales, Patient Global Impressions-Improvement scale, Bipolar Depression Rating Scale, Range of Impaired Functioning Tool, Social and Occupational Functioning Assessment Scale and Quality of Life and Enjoyment Scale (Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form). Generalised estimated equations examined the two-way interactions of personality disorder by time or treatment and investigated personality disorder as a non-specified predictor of outcomes.

Results: Over time, the Patient Global Impressions-Improvement scores were significantly higher in those in the personality disorder group. No other significant differences in the two-way interactions of personality disorder by treatment group or personality disorder by time were found. Personality disorder was a significant but non-specific predictor of poorer outcomes on the Bipolar Depression Rating Scale, Range of Impaired Functioning Tool, and Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form, regardless of time or treatment group.

Conclusions: This study highlights the potential impact of maladaptive personality traits on treatment outcomes and suggests that the presence of comorbid personality disorder may confer additional burden and compromise treatment outcomes. This warrants further investigation as does the corroboration of these exploratory findings. This is important because understanding the impact of comorbid personality disorder on bipolar disorder may enable the development of effective psychological and pharmacotherapeutic options for personalised treatments.

Objective: Electroconvulsive therapy (ECT) is used to treat several mental illnesses. Seizure duration is used to determine if the administered stimulus was adequate. Duration is estimated by electroencephalogram (EEG) interpretation and/or observed motor response (OMR). Neither method is considered the gold standard. This study investigated the relationship between the 2 methods. The hypothesis was that both EEG and OMR would be significantly positively correlated. Previous researchers have suggested that the 2 methods resulted in different estimates.

Methods: A case series was conducted using recorded estimates obtained prospectively from 102 ECTs on adult psychiatric inpatients.

Results: A strong positive association was not observed in this study, correlation coefficient 0.510 (p < 0.001).

Conclusions: This study suggests that the 2 methods differ, and further research is needed to determine the best indicator of adequate treatment.