Aging is a demographic global trend and a challenge for public mental health; however, gaps persist for a comprehensive definition of mental health, risk, protective factors, and processes involved, which represent a greater problem in middle-income countries, where evidence is scarce.

To identify combined mental health profiles in older adults, based on self-report of anxiety symptoms, depressive symptoms, and perception of well-being, and to identify risk and protective variables for each of the groups, based on a sample of older adults attending primary health care (PHC) centers in the Province of Concepción, Chile.

A convenience sample of 573 adults of both sexes, over 65 years, autonomous, attending PHC centers in the Province of Concepción, Chile, answered a set of instruments assessing anxiety symptoms (SCL-90), depressive symptoms (PHQ-9) and perception of well-being (Pemberton Happiness Index) and eventually associated variables that included sociodemographic and living arrangements, social participation, threatening life events (LTE), loneliness (ULS-3), and social support (MSPSS). Latent profile mixture analysis was used to identify groups of adults with similar mental health, and pertinence in each group was explained using random forests. The relationship between predictors and latent profiles were analyzed with multinomial regression.

A solution of 4 groups with distinctive mental health profiles was determined: Group 1 (28%) with high depressive symptoms, high anxiety, and low well-being; Group 2 (32%) with moderate depressive symptoms, high anxiety and moderate well-being; Group 3 (24%) with moderate depressive symptoms, low anxiety and moderate well-being and; Group 4 (15%) characterized by individuals with low anxious or depressive symptoms, high well-being, and absence of mental disorder.

Using random forests, this model predicts 63% variance between groups. A large number of variables were found to significantly predict membership in one of the 4 groups. Specifically: gender, satisfaction with living arrangement, economic crisis, own disease, and death or illness of friend, perception of general health, intimate, relational and collective loneliness, social support from family and significant others, and social support from friends.

The 4-group classification is a parsimonious solution where group 1 characterize people with poor mental health; groups 2 and 3 languishing with high and low anxiety respectively; and group 4 healthy and flourishing. Overall, these groups highlight the role of close interpersonal relationships or primary ties, both in terms of intimacy versus loneliness/isolation and in satisfaction with living arrangements for the elderly. The importance of these psychosocial predictors on combined mental health in the elderly further the need to understand their role and mechanisms to design promotion and prevention strategies.

None Declared

Patients with bipolar disorder (BD) have an increased risk for cardiovascular morbimortality. Clinical risk factors, specifically for arrhythmias and sudden cardiac death remain understudied.

This study was conducted to assess differences in cardiac conduction among BD patients.

We included patients with BD in a cross-sectional design, confirmed by structured interview, age 18 through 80. Clinical characteristics were obtained using a structured questionnaire or medical records review. ECG intervals duration and morphology were manually assessed by cardiologists and compared among clinical subgroups using Chi-square, Mann-Whitney, and Kruskall-Wallis tests. Exploratory multivariable linear and logistic regression models were fitted to adjust for potential confounders.

We included 117 patients (60.7% women, 76.9% bipolar I, 50% history of psychosis, 22.6% suicide attempts). We found a significantly longer QTc interval in BD patients with hypertension (difference: 9.5 ms, p=0.006), obesity (difference: 25 ms, p=0.001), and metabolic syndrome (difference: 13 ms, p=0.007). Hypertension remained a significant predictor of longer QTc after adjusting for age, gender, and antipsychotic use (estimate 17.718, p=0.018). We observed a significantly shorter PR interval in women (difference: 6 ms, p=0.029), early age of onset (difference 6 ms, p=0.025), non-users of lithium (difference 4 ms, p=0.002), and early trauma (difference 4 ms, p=0.038). Finally, we identified significant correlations between symptom severity, blood glucose and PR interval (r=0.298, p=0.001; r=0.278, p=0.003; respectively).

Patients with BD and hypertension may have an increased risk for QTc prolongation. Careful cardiovascular monitoring may be warranted.

No significant relationships.

Researching from a symptom approach avoids possible spurious associations, given the co-occurrence of symptoms in a disorder (Costello, 1992). Here, we deepen the evidenced relationships among anxiety, delusions and hallucinations.

We intended to assess differences in Anxiety Sensitivity dimensions between patients with psychosis depending on presence/absence of hallucinations and/or delusions.

49 patients with DSM psychosis diagnosis (42 men and 7 women; mean age: 40), who attended a Mental Health Rehabilitation Service in 2008, of whom 7 only deluded, 6 only hallucinated, 11 deluded-hallucinated and the remaining 25 neither hallucinated nor deluded.

A Cross-sectional design (one measurement) for a co-relational method of comparison between groups.

We used the Spanish validated Anxiety Sensitivity lndex-3 -ASI 3- (Sandín et al., 2007), a 18-item Likert self-report that assesses fears of anxious symptoms. It presents a hierarchical structure (a general factor and three subscales -Physical, Cognitive and Social Concerns-). It's also used the first and third items (delusions and hallucinatory behaviour) of The Positive and Negative Syndrome Scale -PANSS- (Kay, Opler and Lindenmayer, 1988) to detect positive symptoms.

All analysis were accepted at p < .05. Patients only hallucinators showed a higher anxiety sensitivity in Social Subscale than non-hallucinative/non-delusional patients; the former presented lower punctuations in ASI-total and ASI-cognitive than patients with hallucinations and delusions. The latter showed a higher anxiety sensitivity in Cognitive Subscale than patients who only deluded.

It's hypothetized that both delusional and hallucinative activity is necessary for emergence of cognitive anxiety sensitivity.

An important corpus of scientist evidence is linking psychotic activity and anxiety-related processes (Freeman and Garety, 2003).

We intended to assess differences in Anxiety Sensitivity dimensions between patients diagnosed by psychosis with and without positive symptoms.

Participants: 49 patients with DSM psychosis diagnosis (42 men and 7 women; mean age: 40), who attended a Mental Health Rehabilitation Service in 2008, of whom 24 patients had positive symptomatology.

Design, materials and procedure: A Cross-sectional design (one measurement) for a co-relational method of comparison between groups.

We used the Spanish validated Anxiety Sensitivity lndex-3 -ASI 3- (Sandîn et al, 2007), a 18-item Likert self-report that assesses fears of anxious symptoms. It presents a hierarchical structure (a general factor and three subscales -Physical, Cognitive and Social Concerns-). It's also used the first and third items (delusions and hallucinatory behaviour) of The Positive and Negative Syndrome Scale -PANSS- (Kay, Opler and Lindenmayer, 1988) to detect positive symptoms.

Patients with positive symptoms showed a higher sensitivity to cognitive (z = -3.22, p < 0.01) and social anxiety (z = -2.66, p < 0.01), as well as higher punctuations in ASI-total (z = -2.91, p < 0.01), than patients without positive symptoms.

Patients with positive symptoms show significant fears of symptoms of different anxious domains (ASI-total) with regard to patients without this kind of symptomatology. Specially, they are worried about the possibility that concentration difficulties and restlessness lead to mental incapacitation (ASI-cognitive) and about social reactions before their own publicly observable anxiety manifestations (ASI-social).

There is increasing empirical evidence that links the classical separated psychopathological spectrums neurosis and psychosis. In this sense, anxiety is a factor for delusional/hallucinative development and maintenance (Freeman and Garety, 2003).

We intended to assess differences in Anxiety Sensitivity dimensions between patients with psychosis and a non-clinical sample.

Participants: 49 patients with DSM psychosis diagnosis (42 men and 7 women; mean age: 40), who attended a Mental Health Rehabilitation Service in 2008, were compared with a non-clinical sample (n = 582) from another study (Sandín, Valiente, Chorot and Santed, 2007).

A Cross-sectional design (one measurement) for a co-relational method of comparison between groups.

We used the Spanish validated Anxiety Sensitivity Index-3 -ASI 3- (Sandín et al., 2007), a 18-item Likert self-report that assesses fears of anxious symptoms. It presents a hierarchical structure (a general factor and three subscales -Physical, Cognitive and Social Concerns-). It's also used the first and third items (delusions and hallucinatory behaviour) of The Positive and Negative Syndrome Scale -PANSS- (Kay, Opler and Lindenmayer, 1988) to detect positive symptoms.

Patients present a higher anxiety sensitivity in the General Factor (t = 2.06, p < 0.05) and Cognitive Subscale (t = 3.91, p < 0.001) than nonpatient sample.

Patients with psychosis show significant fears of symptoms of different anxious domains (ASI-total) regarding a non-clinical sample. Particularly, they are worried about the possibility that concentration difficulties and restlessness lead to mental incapacitation (ASI-cognitive).

Albert Ellis’ Rational Therapy, founded in 1955, evolved into Rational-Emotive Therapy (RET) in 1959; and finally as Rational-Emotive Behavior Therapy (REBT) in 1992. This evolution has showed, much more, its resemblance to Acceptance and Commitment Therapy (ACT) (Ellis, 2005). REBT highlights treatment of secondary disturbances (berating oneself for having symptoms), beyond primary ones (nosographical symptoms), because these are ways of control and experiential avoidance which foster suffering.

To treat primary anxiety in a patient reducing his secondary disturbance through TREC.

Participants: A 40-year-old man diagnosed with Panic Disorder who attended a Public Mental Health Service. He was being treated with Alprazolam y Lorazepam, which he has taken before psychotherapy.

Design, materials and procedure: It's implemented a single-subject AB design during 4 months (7 therapeutic sessions). It's applied a weekly self-report to record panic attack frequency and variations in anxiolytics-taken. C Young (p < 0.01) was used for statistical analysis of data and the method of least squares to obtain trend line. 16 measures were registered at a weekly interval.

Significant declining trends are observed in panic attack frequency (C = .750, Zo = 3.201, Zt = 2.240), and collaterally in anxiolytics-taking (Alprazolam: C = .811, Zo = 3.462, Zt = 2.240; Lorazepam: C = .801, Zo = 3.420, Zt = 2.240) from beginning of therapy.

Techniques targeting symptoms-extirpation induced intolerance and self condemnation feelings when patient didn’t achieve the wanted control (as way of destructive experiential avoidance -Luciano and Hayes, 2001). Treating these feelings (secondary disturbance), based on symptomatology acceptance (Ellis, 2005), decreased distress related to panic attacks and paroxysmal crisis frequency itself.

The oculomotor system is closely linked to the neural circuits of attention. Recent evidence shows a novel role for eye vergence in orienting visual attention.

Identify patterns of attention disruption through eye vergence.

We investigated whether modulation in attention related eye vergence is disrupted in ADHD.

We measured eye vergence in children previously diagnosed with ADHD while performing a cue/no-cue task and compared the results to agematched controls.

We observed a strong modulation in the angle of vergence in the control group but not in the ADHD group. In addition, in the control group the modulation in eye vergence was different between the cue and no-cue condition. This difference was absent in the ADHD group.

Our study supports the observation of deficient binocular vision in ADHD children. We argue that the observed disruption in eye vergence modulation in ADHD children is proof of a deficient cognitive processing of sensory information. Our work may provide new insights into attention disorders, like ADHD.