Literature Collection

BACKGROUND: To investigate the impact of patient selection in different health sectors on sensitivities and specificities of psychosomatic questionnaires and clinical signs and symptoms (CSS) for predicting daily life impairment (DLI) in individuals after SARS-CoV-2 infection. METHODS: Secondary data analysis of three independent cross-sectional surveys in general population (n = 2828), fourteen primary care practices (n = 204), and rehabilitation hospital (n = 161). DLI and symptoms were captured using questionnaires. PHQ-15 (Patient Health Questionnaire-15) and SSD-12 (Somatic Symptom Disorder-12), PHQ-2 (Patient Health Questionnaire-2), GAD-2 (Generalized Anxiety Disorder-2), and FAS (Fatigue Assessment Scale) were used to assess somatic symptom disorder (SSD), depression, anxiety and fatigue. Diagnostic indices were calculated to predict DLI. RESULTS: The sensitivities of questionnaires and CSS increased, and specificities decreased from general population to practices and hospital. SSD-12 had a higher diagnostic odds ratio (dOR; 95 % confidence interval) (17.4; 12.6-24.0) in population than in practices (8.4; 3.6-19.7) or hospital (8.1; 1.7-31.7). FAS > 22 had higher dOR (15.0; 11.8-19.1) in population than in practices (5.3; 2.8-9.8) or hospital (4.8; 1.4-16.3). The pattern (population / practice / hospital) was similar in depression (9.2; 7.0-12.0 / 8.0; 3.6-18.1 / 12.2; 1.5-96.2) and anxiety (8.0; 6.0-10.8 / 2.4; 1.0-5.6 / 3.0; 0.6-14.1). Areas under the curves of questionnaires were highest in population, followed by hospital, and consistently lower for practices. CONCLUSION: There is a large variation in sensitivities and specificities to predict DLI. The extent to which SSD or psychosomatic comorbidity contributes to DLI varied across the health sectors in which patients are diagnosed and treated.

BACKGROUND: Social functioning (SF), the ability to engage with life and fulfill roles may be a salient "patient important outcome" in addiction treatment. It is not known if medication-assisted treatment (MAT) impacts SF in opioid use disorder (OUD). There is a growing evidence to suggest that men and women are impacted differently by OUD. This study is the largest to date to study sex differences in OUD and explore associations between MAT and SF. METHODS: Data were collected from 2736 participants with OUD, enrolled in MAT for varying lengths of time, in outpatient clinics across Ontario. SF was defined according to the Maudsley Addiction Profile's domains of (1) employment, (2) criminal activity, and (3) interpersonal conflict. Using logistic regression analysis, we examined sociodemographic and clinical factors associated with domains of SF. RESULTS: There were 1544 men (56%) and 1192 women (44%) in this study, and ages varied from 17 to 76 years for men and 18 to 69 years for women. At study entry, participants had been on MAT for a median of 2 years. Compared to men, women reported more psychological (mean MAP score 14/40, SD = 9.55, versus 11/40, SD = 8.64; p < 0.001) and physical symptoms (mean MAP score 17/40, SD = 7.70 versus 14/40, SD = 7.74; p < 0.001). More women reported unemployment(74% versus 58%; p < 0.0001) and interpersonal conflict (46% versus 35%; p < 0.0001). Men were more likely than women to report criminal activity (11%, versus 8%; p = 0.001). Psychological symptoms increased the risk of worse SF, across domains, for men and for women. Every year on MAT was associated with a 7% increase in the odds of women engaging with criminal activity (OR = 1.07, 95% CI 1.02, 1.12, p = 0.006). CONCLUSIONS: Men and women had different SF profiles and psychological symptoms scores while on MAT. The length of time on MAT increased the risk of criminal activity in women, and overall, duration of MAT was not associated with improvement in SF. This may suggest that MAT alone may not support continual improvements in SF in OUD.

The social support network is a health protective factor involving physical, mental and psychological aspects, providing a better quality of life, favoring better adaptation to adverse conditions, promoting resilience and mobilizing resources for a more effective coping with negative life events that can lead to illness. We aimed to analyze the association between physical diseases, common mental disorders and the social support network of patients serviced at primary care facilities in the cities of Rio de Janeiro and Sao Paulo through a cross-sectional study with 1,466 patients in the 18-65 years age group. We used the Social Network Index (SNI) to assess the support network through the categories of isolation and integration. The doctor/nurse completed the questionnaire to evaluate the physical disease diagnosis, while the Hospital Anxiety and Depression Scale was used to detect mental disorders. We found that the pattern of social support was different depending on the presence of physical diseases or mental disorders. Negative associations were found between diabetes and isolation; integration and anxiety; integration and depression. Positive associations were identified between isolation and anxiety and isolation and depression.