Ilaria Lega

Genetic influences on alexithymia and their relationship with depressive symptoms.

OBJECTIVE The factors involved in the etiology of alexithymia are still unclear. While a few studies suggested substantial genetic influences on alexithymia, it remains to be determined if these influences are independent of genetic influences on other mental health variables correlated with alexithymia, such as depression. This study is aimed at confirming previous findings of a genetic contribution to alexithymia, examining whether there are genetic or environmental influences common to alexithymia facets, and investigating whether genetic influences on alexithymia are independent of genetic influences on depression. METHODS The 20-item Toronto Alexithymia Scale and a validated measure of depression were administered to a sample of 729 twins (45% males) aged 23-24 years drawn from the population-based Italian Twin Register. Genetic structural equation modeling was performed with the Mx program. RESULTS Genetic factors accounted for 42% of individual differences in alexithymia. Unshared environmental factors explained the remaining proportion of variance. There was a substantial (0.65) genetic correlation between alexithymia and depression. The inclusion of depression as a covariate in the genetic models reduced the heritability estimate for alexithymia to 33%. CONCLUSIONS Despite some limitations, this study corroborates the notion that genetic factors contribute substantially to individual differences in alexithymia, with unshared environmental factors also playing an important role. Also, it suggests a genetic link between alexithymia and depression.

Monitoring and evaluating the Italian mental health system: the "Progetto Residenze" study and beyond.

Abstract Filling an alarming gap in evidence-based data on the post-1978 reformed Italian psychiatric system, two turn-of-millennium nationwide projects, Progetto Residenze (PROGRES) and PROGRES-Acute, provided detailed qualitative-quantitative information about care facilities. In 2000, there were 2.9 residential beds per 10,000 inhabitants, hospital care being delivered through small (15-bed) psychiatric units. Private inpatient facilities had proliferated, private inpatient beds per 10,000 inhabitants outnumbering public beds. In 2002, there were 1.7 acute inpatient beds per 10,000 inhabitants, one of Europe’s lowest current ratios. The PROGRES and other subsequent projects showed marked nationwide variation in the provision of residential inpatient and outpatient care, grounds for concern about the quality of such care, and an uneven service use pattern. Although the Italian reform law produced a broad network of facilities to meet diverse mental health care needs, the present overview article confirms that further efforts are required to improve quality, balance public and private sectors, and coordinate resources and agencies.

The Italian SEME Surveillance System of Severe Mental Disorders Presenting to Community Mental Health Services

Mental health is recognized worldwide as a major public health priority for the twenty-first century. Different actions are needed, including developing or strengthening national mental health information systems, based on standardized indicators that allow national and international monitoring. In 2008, the national Centre for Disease prevention and Control of the Italian Ministry of Health and the Mental Health Unit of the Italian National Institute of Health (INIH) jointly launched a mental health information system named SEME (an Italian acronym meaning ‘mental health epidemiological surveillance’) based upon data collected from trained psychiatrists working in 22 selected sentinel community mental health centers distributed across Italy and covering a total population of 1,941,853 inhabitants, in order to collect and report site-level information on first-contact patients suffering from specific severe mental disorders (schizophrenia, schizophreniform disorder, schizoaffective disorder, delusional disorder, bipolar I disorder, anorexia nervosa, major depressive episode with psychotic symptoms or suicide attempt). Strengths of the system are the high reliability of diagnoses and the use of a web-based technique for data collection with data entry forms designed for ease of completion. During the first year of implementation of this system, a total of 343 first-contact patients met criteria for one of the severe mental disorders under surveillance. As the system includes standardized instruments to measure psychiatric symptoms and psychosocial functioning, it may facilitate health services research based on longitudinal measurements aimed at evaluating the continuity of psychiatric care and the effectiveness of innovative therapeutic and rehabilitative programs.

Development and preliminary validation of the PC‐SAD5, a screener‐derived short depression severity measure

Background  The prevalence of depressive disorders is high among patients with skin disease. The PC‐SAD is a 37‐item self‐administered depression screening questionnaire that has been validated in dermatological patients.

Diagnostic Accuracy of the Primary Care Screener for Affective Disorder (PC-SAD) in Primary Care

Background: Depression goes often unrecognised and untreated in non-psychiatric medical settings. Screening has recently gained acceptance as a first step towards improving depression recognition and management. The Primary Care Screener for Affective Disorders (PC-SAD) is a self-administered questionnaire to screen for Major Depressive Disorder (MDD) and Dysthymic Disorder (Dys) which has a sophisticated scoring algorithm that confers several advantages. This study tested its performance against a ‘gold standard’ diagnostic interview in primary care. Methods: A total of 416 adults attending 13 urban general internal medicine primary care practices completed the PC-SAD. Of 409 who returned a valid PC-SAD, all those scoring positive (N=151) and a random sample (N=106) of those scoring negative were selected for a 3-month telephone follow-up assessment including the administration of the Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID-I) by a psychiatrist who was masked to PC-SAD results. Results: Most selected patients (N=212) took part in the follow-up assessment. After adjustment for partial verification bias the sensitivity, specificity, positive and negative predictive value for MDD were 90%, 83%, 51%, and 98%. For Dys, the corresponding figures were 78%, 79%, 8%, and 88%. Conclusions: While some study limitations suggest caution in interpreting our results, this study corroborated the diagnostic validity of the PC-SAD, although the low PPV may limit its usefulness with regard to Dys. Given its good psychometric properties and the short average administration time, the PC-SAD might be the screening instrument of choice in settings where the technology for computer automated scoring is available.

Parental Burden and its Correlates in Families of Children with Autism Spectrum Disorder: A Multicentre Study with Two Comparison Groups

Background: The effects of having a child with Autism Spectrum Disorder (ASD) on parents are multifaceted and pervasive. While ample evidence has been provided that these families are under severe stress, there are still several knowledge gaps and unresolved questions. Objective: This study aimed at quantifying the subjective and objective burden of ASD in mothers and fathers, and at improving the understanding of the interplay between parental burden, child’s characteristics, and parents’ coping resources and strategies. Methods: The parents of 359 children/adolescents with ASD were compared to parents of age-matched patients with Down syndrome (N=145) and Type 1 diabetes mellitus (N=155). Child’s clinical characteristics and parents’ caregiving burden, psychological distress, coping resources and strategies were assessed. Results: The parents of children with ASD reported higher objective and subjective burden, more frequent psychological distress, lower social support. Mothers reported greater subjective burden than fathers. Structural equation modeling showed that the most consistent positive and negative predictors of objective and subjective burden were ASD symptom severity and social support, respectively. Other positive predictors were engagement, distraction and disengagement coping, intellectual disability, and adaptive functioning. Other negative predictors were spiritual wellbeing and hardiness. Some effects were indirect through social support and coping strategies. Conclusion: This study confirmed that parents of children with ASD carry a huge caregiving burden, and added to our understanding of the factors associated with burden. The findings may help inform the design of effective interventions aimed at reducing burden among the parents of children with ASD.