Effectiveness of a needs-tailored nurse-led recovery program for community-dwelling people with schizophrenia: a cluster-randomized controlled trial.

BACKGROUND: Meeting people's needs is positively correlated with their recovery. However, recovery services rarely include nurse-led programs tailored to the needs of these people. This study aimed to evaluate the effectiveness of a new needs-tailored recovery program by using a cluster-randomized controlled trial design. METHODS: We conducted a parallel randomized controlled trial in two community psychiatric departments, employing nurse-level clustering for intervention delivery and selecting participants through convenience sampling. The participants were people diagnosed with schizophrenia that were receiving homecare services. The experimental group (n = 82) received needs-tailored recovery program for six months. The control group (n = 82) received traditional homecare. Data were collected at baseline, post-intervention, and the three-month follow-up (the study ran from February to December 2021). The outcomes were recovery, needs, hope, empowerment, psychotic symptoms, and medication adherence. We used repeated measures ANOVA tests to examine the effect of the group × time interaction. RESULTS: The participants in the experimental group demonstrated statistically significant improvements in recovery, hope, and medication adherence compared to the control group, both immediately post-intervention and at the three-month follow-up. Moreover, they exhibited statistically significant reductions in needs compared to the control group at the three-month follow-up (p < .05). While the interaction effect for psychotic symptoms was not significant, the time effect was significant (p < .05). No significant interaction or time effect was observed for empowerment. CONCLUSION: The findings increase our understanding of recovery-oriented care that prioritizes therapeutic alliance, integrated needs assessment, individual goals, hope, and empowerment. TRIAL REGISTRATION: The Clinicaltrials.gov identifier NCT05304780 retrospectively registered on 03/31/2022.

The mediators for the link between autism and real-world executive functions in adolescence and young adulthood.

LAY ABSTRACT: Childhood factors that predict real-world executive function in autism spectrum disorder during the transition into adulthood are largely unknown. This study aimed to identify the predictors for the behavioral and cognitive aspects of real-world executive function in late adolescent and young adult autistic populations. We followed up 289 autistic youth (mean age 11.6 years) and 203 non-autistic controls (10.7 years) to their ages of 16.9 and 15.8, respectively. The Behavior Rating Inventory of Executive Function scale was used to measure the real-world executive function at late adolescence and young adulthood at follow-up. Potential predictors such as autistic symptoms, inattention or hyperactivity symptoms, peer relationship, emotional symptoms, and parenting styles were assessed in childhood at first enrollment. The results showed that childhood inattention, withdrawn behaviors, social communication difficulties, and child-reported emotion and inattention/hyperactivity may predict real-world lower executive function in late adolescence and young adults with autism. When separating executive function into behavioral and cognitive aspects, we found that oppositional behaviors and peer problems were specific predictors for behavioral regulation and cognitive function, respectively. Our findings suggested that treating common predictors in childhood, such as inattention, may potentially improve real-world executive function in autism during the transition into adulthood.

Diabetes self-care behaviours among people diagnosed with serious mental illness: A cross-sectional correlational study.

WHAT IS KNOWN ON THE SUBJECT?: People diagnosed with serious mental illness have a high risk of diabetes and are more likely to develop type 2 diabetes at ages below 60 years. Effective diabetes self-care behaviours among people diagnosed with serious mental illness can improve glycaemic control and reduce vascular complications. Few studies have investigated diabetes self-care behaviours and their associations with health literacy and self-efficacy in people diagnosed with serious mental illness. WHAT THE PAPER ADDS TO EXISTING KNOWLEDGE?: Diabetes self-care behaviours in people diagnosed with serious mental illness were suboptimal; the least frequently performed self-care activities were self-monitoring of blood glucose. Factors associated with diabetes self-care behaviours are gender, age, communicative and critical health literacy and self-efficacy. Self-efficacy is the strongest predictor of self-care behaviours among people diagnosed with comorbid serious mental illness and type 2 diabetes. WHAT ARE THE IMPLICATIONS OF PRACTICE?: Mental health nurses should assess diabetes-specific health literacy of people diagnosed with serious mental illness to ensure that they possess the knowledge and skills related to diabetes self-care. When treating young people and those with newly diagnosed type 2 diabetes, nurses should incorporate strategies to minimise their perceptions of diabetes-related distress and increase their confidence in managing comorbid diabetes. ABSTRACT: Introduction People diagnosed with serious mental illness (SMI) experience greater challenges in managing their type 2 diabetes mellitus (T2DM) than do those diagnosed with T2DM alone. Aim This study investigated diabetes self-care activities and the factors associated with these activities in people diagnosed with SMI in a hospital setting. Methods A cross-sectional correlational study was conducted among 126 people diagnosed with comorbid SMI and T2DM in Taipei, Taiwan, between October 2020 and April 2021. Data were collected using self-report questionnaires and a chart review. Three-step hierarchical multiple regression analysis was used to identify factors associated with diabetes self-care behaviours. Results Diabetes self-care behaviours in people diagnosed with SMI were suboptimal overall. Hierarchical multiple regression analyses revealed that age (ß = 0.18, p = .037) and self-efficacy (ß = 0.27, p = .004) significantly associated with diabetes self-care behaviours. Discussion Self-efficacy is the strongest predictor of self-care behaviours among people diagnosed with comorbid SMI and T2DM. Implications for Practice Mental health professionals should focus on enhancing confidence in managing comorbid diabetes in people diagnosed with comorbid SMI, especially young people and those with newly diagnosed T2DM.

Autistic Traits and Cyberbullying Involvement Mediated by Psychopathologies and School Functions in a Nationally Representative Child Sample.

Cyberbullying has become an international concern among youth with autistic traits in the digital age. It draws the attention of professionals in mental health and education due to its potentially severe psychosocial and academic impacts. However, there is limited knowledge about the mediators for these associations. This study investigated whether school dysfunction and comorbid psychopathologies mediated the link between autistic traits and cyberbullying. We used a nationally representative sample of 9,483 students (9-14 years of age). The instruments included the Social Responsiveness Scale for autistic traits; the Cyberbullying Experiences Questionnaire for cyberbullying victimization and perpetration; the Swanson, Nolan, and Pelham, version IV for inattention, hyperactivity/impulsivity, and oppositional behaviors; the Child Behavior Checklist for anxiety/depression; and the Social Adjustment Inventory for Children and Adolescents for impaired school functions. Multiple mediation models were used for statistical analyses. The results showed that the 1-year prevalence rates of pure victims, pure perpetrators, and bully-victims of cyberbullying were 7.9 percent, 2.4 percent, and 5.7 percent, respectively. Cyberbullying victimization and perpetration were positively associated with autistic traits, school dysfunction, and comorbid psychopathologies. The associations between autistic traits and cyberbullying victims and bully-victims were significantly mediated by school dysfunction and hyperactivity/impulsivity (only for bully-victims), independent of sex and age. Our results suggest that early identification and intervention of these difficulties may mitigate the risks of cyberbullying. ClinicalTrials.gov ID: NCT02707848.

Genetic Variants Associated With Subjective Cognitive Decline in Patients With Migraine.

The genetic association between subjective cognitive decline (SCD) and migraine comorbidity remains unclear. Furthermore, single nucleotide polymorphisms (SNP) associated with SCD have not been identified previously. Migraineurs were genotyped using an Affymetrix array. The correlation between different SNP variants in migraineurs with or without SCD and non-migraine controls was investigated. Migraineurs with or without SCD were further divided for the analysis of relevant SNP variants linked to migraine with aura (MA), migraine without aura (MoA), episodic migraine (EM), and chronic migraine (CM). Significant connectivity between SNPs and clinical indices in migraineurs and non-migraine controls with SCD were assessed using multivariate regression analysis. The rs144191744 SNP was found in migraineurs (p = 3.19E-08), EM (p = 1.34E-07), and MoA(p = 7.69E-07) with and without SCD. The T allele frequency for rs144191744 in TGFBR3 was 0.0054 and 0.0445 in migraineurs with and without SCD (odds ratio, 0.12), respectively. rs2352564, rs6089473 in CDH4, rs112400385 in ST18, rs4488224 and rs17111203 in ARHGAP29 SNPs were found, respectively, in non-migraineurs (p = 4.85E-06, p = 8.28E-06), MoA (p = 3.13E-07), and CM subgroups (p = 1.05E-07, 6.24E-07) with and without SCD. Rs144191744 closely relates to SCD with the all-migraine group and the EM and MoA subgroups. In conclusion, rs144191744 in TGFBR3 was significantly associated with SCD in migraineurs, especially in the EM, MoA, and female patient subgroups. Furthermore, three SNPs (rs112400385, rs4488224, and rs17111203) were associated with SCD in migraineurs but not in non-migraine controls.

Psychopathologies mediate the link between autism spectrum disorder and bullying involvement: A follow-up study.

BACKGROUND/PURPOSE: Youths with autism spectrum disorder (ASD) are at a high risk of involvement in school bully. The study investigated whether comorbid psychopathologies mediated the link between ASD and bullying involvement. METHODS: We assessed 353 youths (mean age, 11.8 ± 3.1 years), including 121 youths with ASD and 232 typically developing (TD) controls, using semi-structured diagnostic interviews on ASD and other psychiatric conditions. Follow-up assessments took place 2-5 years (37.6 ± 15 months) later. Meanwhile, their parents reported on the Social Adjustment Inventory for Children and Adolescents about bullying involvement statuses. We identified significant mediators by simple mediation models, followed by multiple mediation models to scrutinize the mediation effects of selected mediators. RESULTS: The results showed a sevenfold increased risk of bullying involvement among youths with ASD compared with TD controls at follow-up. In general, psychopathologies mediated the link between ASD and bullying involvement, even independent of age and sex. Specifically, we found mediating effects of social problems on victimization-only and aggressive behaviors on victimization-perpetration. CONCLUSION: Our findings strongly suggest the link between ASD and later bullying involvement is mediated by pre-existing comorbid psychiatric conditions, besides the direct effect of ASD on bullying victimization. Hence, early identification and intervention of these psychopathologies are highly suggested.

Mental health correlates and potential childhood predictors for the wish to be of the opposite sex in young autistic adults.

LAY ABSTRACT: Autistic people/people with autism spectrum disorder are more likely to experience gender dysphoria. However, the possible longitudinal predictors and underlying mechanisms of this co-occurrence are unclear. To fill this knowledge gap, we assessed 88 people with autism spectrum disorder and 42 typically developing individuals at their average ages of 13.0 (baseline, childhood/adolescence) and 20.2 years old (follow-up, adulthood). At follow-up, their endorsement on the item "I wish I was the opposite sex" was used to evaluate gender dysphoric symptoms. We compared mental health symptoms between adults with and without this item endorsement at the follow-up assessment. We explored parent-reported family and autism characteristics-related predictors in childhood/adolescence to this item endorsement in adulthood. We found that more autistic adults reported the wish to be of the opposite sex than did typically developing individuals. Autistic adults who endorsed this item experienced more mental health challenges, more school bullying and cyberbullying, more suicidal ideation, and worse quality of life. Moreover, parent-reported lower family support and more stereotyped/repetitive behaviors during childhood/adolescence predicted the self-reported wish to be of the opposite sex in adulthood in autistic individuals. More attention and support should be provided to autistic people regarding gender development and related mental health and quality of life impact, especially during the transition period to young adulthood.

Machine Learning Based Suicide Ideation Prediction for Military Personnel.

Military personnel have greater psychological stress and are at higher suicide attempt risk compared with the general population. High mental stress may cause suicide ideations which are crucially driving suicide attempts. However, traditional statistical methods could only find a moderate degree of correlation between psychological stress and suicide ideation in non-psychiatric individuals. This article utilizes machine learning techniques including logistic regression, decision tree, random forest, gradient boosting regression tree, support vector machine and multilayer perceptron to predict the presence of suicide ideation by six important psychological stress domains of the military males and females. The accuracies of all the six machine learning methods are over 98%. Among them, the multilayer perceptron and support vector machine provide the best predictions of suicide ideation approximately to 100%. As compared with the BSRS-5 score ≥7, a conventional criterion, for the presence of suicide ideation ≥1, the proposed algorithms can improve the performances of accuracy, sensitivity, specificity, precision, the AUC of ROC curve and the AUC of PR curve up to 5.7%, 35.9%, 4.6%, 65.2%, 4.3% and 53.2%, respectively; and for the presence of more severely intense suicide ideation ≥2, the improvements are 6.1%, 26.2%, 5.8%, 83.5%, 2.8% and 64.7%, respectively.

Gender differences in metabolic syndrome risk factors among patients with serious mental illness.

The prevalence of metabolic syndrome and its components continue to increase among patients with serious mental illness. This cross-sectional study investigated whether metabolic syndrome prevalence and risk factors differ between male and female patients with serious mental illness. In total, 260 eligible patients were recruited from two hospitals. The data on demographic characteristics, lifestyle behaviour factors, biochemistry, and anthropometry were collected. Analyses were performed using multivariate logistic regression. Metabolic syndrome prevalence was 40.8% (35.1% in men and 46.8% in women). Among patients aged 40-49 years, metabolic syndrome prevalence was higher in men; however, the trend was reversed among patients aged 50 years or older. Notably, gender-specific metabolic syndrome risk factors were observed. In men, they included low education level, high body mass index (BMI), prolonged illness, comorbid physical illness, and diagnosis of bipolar disorder, whereas they included being married, old age, and high BMI in women. Our findings suggest that mental health professionals should consider the gender- and age-based metabolic syndrome prevalence trend in patients with serious mental illness when designing interventions for the study population to minimize metabolic syndrome prevalence.