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Mobile phones are playing an increasingly important role in supporting mental health, by providing confidential, accessible and scalable support for individuals who may not seek or have means of accessing professional help. There are concerns, however, that many apps claiming to support mental health do not meet professional, ethical or evidence-based standards. App store search algorithms favour popularity (reviews and downloads) and commercial factors (in-app purchases), with what appears to be low prioritisation of safety or effectiveness features. In this paper, the most visible 100 apps for "depression", "anxiety" and/or "mood" on the Google Play and Apple App stores were selected for assessment using the American Psychiatric Association App Evaluation model. This model systematically assesses apps across five broad steps: accessibility, integrity, clinical and research evidence base, user engagement and interoperability. Assessment is hierarchical, with the most fundamental requirements of apps assessed first, with apps excluded at each step if they do not meet the criteria. The relationship between app quality and app store visibility was first analysed. App quality was also compared across four different app function types: mental health promotion or psychoeducation; monitoring or tracking; assessment or prevention; and intervention or treatment. Of the 92 apps assessed (after eight failed to meet inclusion criteria), half failed to meet the first criterion step of accessibility, and a further 20% of the remaining apps failed to meet the second criterion step of security and privacy. Only three of the 10 apps most visible on app stores met the criteria for research/clinical base and engagement/ease of use, and only one app fulfilled all five criterion steps of the evaluation model. Quality did not differ significantly across app function type. There was no significant correlation between app quality and app store visibility, which presents a potential risk t

Aims: The aim of this study was to develop, validate, and illustrate an updated prediction model (SCORE2) to estimate 10-year fatal and non-fatal cardiovascular disease (CVD) risk in individuals without previous CVD or diabetes aged 40-69 years in Europe. Methods and results : We derived risk prediction models using individual-participant data from 45 cohorts in 13 countries (677 684 individuals, 30 121 CVD events). We used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol. We defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions. Region-specific incidence was estimated using CVD mortality and incidence data on 10 776 466 individuals. For external validation, we analysed data from 25 additional cohorts in 15 European countries (1 133 181 individuals, 43 492 CVD events). After applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65-0.68) to 0.81 (0.76-0.86). Predicted CVD risk varied several-fold across European regions. For example, the estimated 10-year CVD risk for a 50-year-old smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low-risk countries to 14.0% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries. Conclusion : SCORE2-a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations-enhances the identification of individuals at higher risk of developing CVD across Europe.

Background Many individuals with mental health problems have comorbid physical conditions, or may present with substance/alcohol misuse or abuse issues. This results in complex treatment challenges that may not be adequately addressed by a model of care that is solely delivered by an individual clinician using a sole intervention. Mainstream pharmacotherapeutic treatment of mental health problems often have limited effectiveness in completely resolving symptoms, and may cause adverse side effects. Adjunctive treatment approaches, including nutraceuticals, lifestyle and behaviour change interventions, are widely used to assist with treatment of mental health problems. However, whilst these can be generally safer with fewer side effects, they have varying levels of evidentiary support. These circumstances warrant reframing the current treatment approach towards a more evidence-based integrative model which may better address the real-world challenges of psychiatric disorders and comorbid physical conditions. In essence, this means developing an integrative model of care which embodies an evidence-informed, personalized stepwise approach using both conventional pharmacological treatments alongside novel adjunctive treatments (where applicable) via the application of a collaborative care approach. Discussion In order to inform this position, a brief review of findings on common patterns of comorbidity in mental illness is presented, followed by identification of limitations of conventional treatments, and potential applications of integrative medicine interventions. Advantages and challenges of integrative mental health care, collaborative models of care, review of research highlights of select integrative approaches, and comment on potential cost advantages are then discussed. Summary We propose that a collaborative care model incorporating evidence-based integrative medicine interventions may more adequately address mental health problems with comorbid medical conditi

Background: Schema Therapy mode formulations have recently been extended to a range of chronic, treatment-resistant psychological disorders. Aim: The aim of this study was to examine whether two forms of repetitive negative thinking (rumination and worry) can be conceptualised as a maladaptive coping mode, we term the “over-analysing” mode, consistent with Young's schema mode model, which serves to distance individuals from distressing emotional states. Methodology: Two online survey studies were conducted in community populations: study one (n = 109) investigated the relationship between schema modes, worry, and experiential avoidance. Study two (n = 129) extended the findings to include, in addition to schema modes and experiential avoidance, rumination and repetitive negative thinking. Results: Correlational analyses supported all hypothesised relationships across both studies. Mediation analyses across both studies identified a model in which the relationship between angry and vulnerable child modes, and worry, rumination, and repetitive negative thinking, respectively, was mediated by experiential avoidance. Conclusion: These findings conceptually support the addition of a new “over-analysing” coping mode, which serves an avoidant function through repetitive negative thinking (a central component of mood and anxiety disorders) to the schema mode model. Generalisability of results is limited through the use of a cross-sectional design and a heterogeneous, nonclinical sample. Further examination of the “over-analysing” mode may enhance Schema Therapy conceptualisations, particularly in the treatment of mood and anxiety disorders. Moreover, emotion-focused techniques found to be successful in Schema Therapy for personality disorders (e.g., imagery rescripting, chair-techniques) may be relevant to modifying maladaptive schemas thoughts to underlie repetitive negative thinking processes such as worry and rumination.