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The COVID-19 outbreak could be considered as an uncontrollable stressful life event. Lockdown measures have provoked a disruption of daily life with a great impact over older adults’ health and well-being. Nevertheless, eudaimonic well‐being plays a protective role in confronting adverse circumstances, such as the COVID-19 situation. This study aims to assess the association between age and psychological well-being (personal growth and purpose in life). Young–old (60–70 years) and old–old (71–80 years) community-dwelling Spaniards (N = 878) completed a survey and reported on their sociodemographic characteristics and their levels of health, COVID-19 stress-related, appraisal, and personal resources. Old–old did not evidence poorer psychological well-being than young–old. Age has only a negative impact on personal growth. The results also suggest that the nature of the COVID-19 impact (except for the loss of a loved one) may not be as relevant for the older adults’ well-being as their appraisals and personal resources for managing COVID-related problems. In addition, these results suggest that some sociodemographic and health-related variables have an impact on older adults’ well-being. Thus, perceived-health, family functioning, resilience, gratitude, and acceptance had significant associations with both personal growth and purpose in life. Efforts to address older adults’ psychological well-being focusing on older adults’ personal resources should be considered.
Describe Attention Deficit Hyperactive Disorder's (ADHD) prevalence in Bipolar Disorders (BD) and relatives.
78 admissions for Bipolar Disorder (DSM-IV) in Impatient Psychiatric Unit, in Hospital Clínico Universitario of Valladolid (Spain). Only 36/78 patients participate in study. Demographic, social and clinical information were registered. ADHD symptomatology was evaluated from patient and descendant (Conners short version).
ADHD symptomatology suggestive in childhood/adolescence were detected in 13,9% (5/36). Conners score were negative (below 15) in all case.
ADHD symptomatology suggestive in their children were detected in 6,25% (n=3). Conner score were positive in 2,1%. Family psychiatry history in 72,2% (n=26), affective disorder in 60,52% (n=23). No family history with ADHD diagnosis. Only one case (2,8%) with symptomatology suggestive of ADHD in relatives.
The ADHD prevalence in our sample of BD and relatives weren’t higher than general population.
- Frontiers Between Attention Deficit Hyperactivity Disorder and Bipolar Disorder. Cathryn A. Galanter, MDa, Ellen Leibenluft, MD. Child Adolesc Psychiatric Clin N Am 17 (2008) 325-346.
- Co-occurrence of bipolar and attention-deficit hyperactivity disorders in children.
UPD is a regional referral hospital psychiatric care unit, endowed with multidisciplinary equipment. It provides care to people with light/moderate/severe intellectual incapacity coexisting with mental disease and/or severe behavioral disorders. It offers attention to patients who need a protected therapeutical environment for correcting behavior disorders. It was opened in September 2008.
Description of:therapeutic goals, inclusion/exclusion criteria, admission protocol and psychotherapeutic/pharmacological interventions.
Analysis of inpatients's sociodemographic/clinical characteristics and preliminary assessment of therapy goals.
Retrospective study(13-month) of patients admitted to UPD of Leon Hospital from its inception to date. Data are collected from medical histories.
47 referrals have been received,5 of them have been rejected not to fulfill criteria. We’ve 16 patients on waiting list.32 incomes have been realized and 22 discharges have occurred.
19 of the incomes correspond to Mild,6 to Moderate,6 to Severe and 1 to Profound mental Retardation.
Regarding co-morbidity:22 patients presented serious behavioral disorder. From this group, 2 met criteria for autistic disorder, 5 had schizophrenia or unspecific psychotic disorders, 5 presented Personality Disorder and one ADHD.
10 patients did’nt present any important behavioral disturbance. From this group 2 were diagnosed with OCD,3 presented problems due to Alcohol and Substance-related Disorders,3 had Psychotic Disorders, one met criteria for Impulse Control Disorder and one presented Mood Disorder.
Before admission, 12 patients resided in specific handicappeds center, 5 intermittently at selected centers and in family, and 15 lived with family.
Psychotherapeutic intervention and treatment were useful in most cases. It was particularly helpful in treatment of behavioral disturbances. Now we must determine effectiveness in maintenance of improvement when they return to their community.
Different neuropsychological studies have consistently found an attention, memory and executive function deficit in schizophrenic patients. The Positive and Negative Syndrome Scale (PANSS) evaluates different clinical aspects of schizophrenia. Factor analyses of this scale suggest the existence of a “cognitive factor”, constituted by several items pertaining to the different subscales. In order to have an acceptable concurrent validity, this “cognitive factor” should correlate with the execution of neuropsychological tasks. Our objective was to study the correlation between the PANSS “cognitive factor” and the execution of neuropsychological tasks evaluating attention, memory and executive functions.
Thirty-five schizophrenic patients were evaluated using the Continuous Performance Test (CPT), the Rey-Osterrieth Complex Figure Test (Rey CFT) and the Wisconsin Card Sorting Test (WCST). Bivariate partial correlation between the neuropsychological variables and the PANSS “cognitive factor” was examined. In order to obtain this cognitive component, and based on previous studies, items P2, N5, PG10 and PG11 were used.
The PANSS “cognitive factor” was significantly correlated to CPT omission errors (r=0.45; p=0.006), Rey CFT recall after 5 minutes (r=-0.34; p=0.049), Rey CFT recall after 30 minutes (r=-0.40; p=0.020), WCST perseverative responses (r=0.36; p=0.035), and WCST perseverative errors (r=0.35; p=0.041).
The existence of significant correlations between the PANSS “cognitive factor” and performance on neuropsychological tasks evaluating attention (CPT), memory (Rey CFT) and executive functions (WCST) supports the concurrent validity of this factor.
The Positive and Negative Syndrome Scale (PANSS) evaluates different psychopathological aspects of schizophrenic patients. Scores on the negative subscale of the PANSS have been associated with clinical and neuropsychological differences in these patients. Our aim was to study the relationship between PANSS negative scores and different clinical and neuropsychological variables in a sample of schizophrenic patients.
Our sample of 174 schizophrenic patients was split into two groups according to scores on the negative subscale of the PANSS: a group of 85 patients (55 male and 30 female; mean age 38.0 years, SD 9.3) with scores below the median (“low negative PANSS” group), and a group of 89 patients (58 male and 31 female; mean age 37.3, SD 8.4) with scores above the median (“high negative PANSS” group). The neuropsychological task used was the Wisconsin Card Sorting Test.
Significant clinical differences were found between both groups. In the “high negative PANSS” group a lower age of illness onset was found (p=0.030), as well as a lower age at first psychiatric admission (p=0.002) compared to the “low negative PANSS” group, without there being significant differences in current age (p=0.570). Regarding cognitive functions, “high negative PANSS” patients achieved fewer categories (p=0.005) and made more perseverative errors (p=0.031) than “low negative PANSS” patients.
Schizophrenic patients with higher scores on the negative subscale of the PANSS had an earlier age of onset of their illness and exhibited poorer cognitive functioning than patients with lower scores.
The Wender-Utah Rating Scale (WURS) was developed for the retrospective diagnosis of childhood attention-deficit/hyperactivity disorder (ADHD). It consists of a list of childhood behaviours and symptoms suggestive of ADHD. Our objective was to study correlations of WURS scores with different impulsivity, personality, anxiety and depression psychometric scales.
A group of 110 healthy university students were evaluated using the WURS. Four subjects scored higher than the cut-off value of 37 (compatible with childhood ADHD) and were excluded. The Barratt Impulsivity Scale (BIS-11), the Big Five Questionarie (BFQ), the State-Trait Anxiety Inventory (STAI) and the Beck Depression Inventory (BDI) were administered. Partial bivariate correlation analyses were performed.
WURS scores were correlated with total scores on the BIS-11 (r=0.430; p<0.001), as well as with the motor (r=0.410; p<0.001), attentional (r=0.328; p=0.001), and improvisation subscales (r=0.289; p=0.003). Regarding the BFQ, a correlation was found between WURS scores and the “emotional stability” factor (r=-0.379; p<0.001) as well as with the subfactors “emotion control” (r=-0.310; p=0.001) and “impulse control” (r=-0.354; p<0.001). Finally, significant correlations were also found between WURS scores and scores on the STAI-trait (r=0.366; p<0.001), STAI-state (r=0.200; p=0.039), and the BDI (r=0.350; p<0.001).
Correlations between the WURS and other impulsivity-related psychometric scales such as the BIS-11, or the “emotional stability” factor and the “emotion control” and “impulse control” subfactors of the BFQ, provides evidence for the concurrent validity of the WURS. The correlation of this instrument with anxiety and depression scales points to possible clinical implications.
Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.
To characterise clusters of individuals based on adherence to dietary recommendations and to determine whether changes in Healthy Eating Index (HEI) scores in response to a personalised nutrition (PN) intervention varied between clusters.
Food4Me study participants were clustered according to whether their baseline dietary intakes met European dietary recommendations. Changes in HEI scores between baseline and month 6 were compared between clusters and stratified by whether individuals received generalised or PN advice.
Individuals in cluster 1 (C1) met all recommended intakes except for red meat, those in cluster 2 (C2) met two recommendations, and those in cluster 3 (C3) and cluster 4 (C4) met one recommendation each. C1 had higher intakes of white fish, beans and lentils and low-fat dairy products and lower percentage energy intake from SFA (P<0·05). C2 consumed less chips and pizza and fried foods than C3 and C4 (P<0·05). C1 were lighter, had lower BMI and waist circumference than C3 and were more physically active than C4 (P<0·05). More individuals in C4 were smokers and wanted to lose weight than in C1 (P<0·05). Individuals who received PN advice in C4 reported greater improvements in HEI compared with C3 and C1 (P<0·05).
The cluster where the fewest recommendations were met (C4) reported greater improvements in HEI following a 6-month trial of PN whereas there was no difference between clusters for those randomised to the Control, non-personalised dietary intervention.
To characterise participants who dropped out of the Food4Me Proof-of-Principle study.
The Food4Me study was an Internet-based, 6-month, four-arm, randomised controlled trial. The control group received generalised dietary and lifestyle recommendations, whereas participants randomised to three different levels of personalised nutrition (PN) received advice based on dietary, phenotypic and/or genotypic data, respectively (with either more or less frequent feedback).
Seven recruitment sites: UK, Ireland, The Netherlands, Germany, Spain, Poland and Greece.
Adults aged 18–79 years (n 1607).
A total of 337 (21 %) participants dropped out during the intervention. At baseline, dropouts had higher BMI (0·5 kg/m2; P<0·001). Attrition did not differ significantly between individuals receiving generalised dietary guidelines (Control) and those randomised to PN. Participants were more likely to drop out (OR; 95 % CI) if they received more frequent feedback (1·81; 1·36, 2·41; P<0·001), were female (1·38; 1·06, 1·78; P=0·015), less than 45 years old (2·57; 1·95, 3·39; P<0·001) and obese (2·25; 1·47, 3·43; P<0·001). Attrition was more likely in participants who reported an interest in losing weight (1·53; 1·19, 1·97; P<0·001) or skipping meals (1·75; 1·16, 2·65; P=0·008), and less likely if participants claimed to eat healthily frequently (0·62; 0·45, 0·86; P=0·003).
Attrition did not differ between participants receiving generalised or PN advice but more frequent feedback was related to attrition for those randomised to PN interventions. Better strategies are required to minimise dropouts among younger and obese individuals participating in PN interventions and more frequent feedback may be an unnecessary burden.
The interplay between the fat mass- and obesity-associated (FTO) gene variants and diet has been implicated in the development of obesity. The aim of the present analysis was to investigate associations between FTO genotype, dietary intakes and anthropometrics among European adults. Participants in the Food4Me randomised controlled trial were genotyped for FTO genotype (rs9939609) and their dietary intakes, and diet quality scores (Healthy Eating Index and PREDIMED-based Mediterranean diet score) were estimated from FFQ. Relationships between FTO genotype, diet and anthropometrics (weight, waist circumference (WC) and BMI) were evaluated at baseline. European adults with the FTO risk genotype had greater WC (AAv. TT: +1·4 cm; P=0·003) and BMI (+0·9 kg/m2; P=0·001) than individuals with no risk alleles. Subjects with the lowest fried food consumption and two copies of the FTO risk variant had on average 1·4 kg/m2 greater BMI (Ptrend=0·028) and 3·1 cm greater WC (Ptrend=0·045) compared with individuals with no copies of the risk allele and with the lowest fried food consumption. However, there was no evidence of interactions between FTO genotype and dietary intakes on BMI and WC, and thus further research is required to confirm or refute these findings.
An efficient and robust method to measure vitamin D (25-hydroxy vitamin D3 (25(OH)D3) and 25-hydroxy vitamin D2 in dried blood spots (DBS) has been developed and applied in the pan-European multi-centre, internet-based, personalised nutrition intervention study Food4Me. The method includes calibration with blood containing endogenous 25(OH)D3, spotted as DBS and corrected for haematocrit content. The methodology was validated following international standards. The performance characteristics did not reach those of the current gold standard liquid chromatography-MS/MS in plasma for all parameters, but were found to be very suitable for status-level determination under field conditions. DBS sample quality was very high, and 3778 measurements of 25(OH)D3 were obtained from 1465 participants. The study centre and the season within the study centre were very good predictors of 25(OH)D3 levels (P<0·001 for each case). Seasonal effects were modelled by fitting a sine function with a minimum 25(OH)D3 level on 20 January and a maximum on 21 July. The seasonal amplitude varied from centre to centre. The largest difference between winter and summer levels was found in Germany and the smallest in Poland. The model was cross-validated to determine the consistency of the predictions and the performance of the DBS method. The Pearson’s correlation between the measured values and the predicted values was r 0·65, and the sd of their differences was 21·2 nmol/l. This includes the analytical variation and the biological variation within subjects. Overall, DBS obtained by unsupervised sampling of the participants at home was a viable methodology for obtaining vitamin D status information in a large nutritional study.