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Purpose

This paper describes the design of a theory-informed pragmatic intervention for adolescent perinatal depression in primary care in Nigeria.

Methods

We conducted Focus Group Discussions (FGDs) among 17 adolescent mothers and 25 maternal health care providers with experience in the receipt and provision of care for perinatal depression. The Consolidated Framework for Implementation Research (CFIR) was used to systematically examine the barriers and facilitators affecting adolescent mothers' use of an existing intervention package for depression. The Theoretical Domain Framework (TDF) and the Capability, Opportunity, Motivation, Behaviour (COM-B) model were used to analyze the results of the data across the five CFIR domains.

Results

FGD analysis revealed that care providers lacked knowledge on approaches to engage young mothers in treatment. Young mothers had poor treatment engagement, low social support, and little interest in parenting. A main characteristic of the newly designed intervention is the inclusion of age-appropriate psychoeducation supported with weekly mobile phone calls, to address treatment engagement and parenting behaviours of young mothers. Also in the outer setting, low social support from relatives was addressed with education, “as need arises” phone calls, and the involvement of "neighborhood mothers”. In the inner settings, care providers’ behaviour is addressed with training to increase their capacity to engage young mothers in treatment.

Conclusion

A theory-based approach helped develop an age-appropriate intervention package targeting depression and parenting skills deficit among perinatal adolescents in primary maternal care and in which a pragmatic use of mobile phone was key.

  相似文献   
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Major depressive disorder and other neuropsychiatric disorders are often managed with long-term use of antidepressant medication. Fluoxetine, an SSRI antidepressant, is widely used as a first-line treatment for neuropsychiatric disorders. However, fluoxetine has also been shown to increase the risk of metabolic diseases such as non-alcoholic fatty liver disease. Fluoxetine has been shown to increase hepatic lipid accumulation in vivo and in vitro. In addition, fluoxetine has been shown to alter the production of prostaglandins which have also been implicated in the development of non-alcoholic fatty liver disease. The goal of this study was to assess the effect of fluoxetine exposure on the prostaglandin biosynthetic pathway and lipid accumulation in a hepatic cell line (H4-II-E-C3 cells). Fluoxetine treatment increased mRNA expression of prostaglandin biosynthetic enzymes (Ptgs1, Ptgs2, and Ptgds), PPAR gamma (Pparg), and PPAR gamma downstream targets involved in fatty acid uptake (Cd36, Fatp2, and Fatp5) as well as production of 15-deoxy-Δ12,14PGJ2 a PPAR gamma ligand. The effects of fluoxetine to induce lipid accumulation were attenuated with a PTGS1 specific inhibitor (SC-560), whereas inhibition of PTGS2 had no effect. Moreover, SC-560 attenuated 15-deoxy-Δ12,14PGJ2 production and expression of PPAR gamma downstream target genes. Taken together these results suggest that fluoxetine-induced lipid abnormalities appear to be mediated via PTGS1 and its downstream product 15d-PGJ2 and suggest a novel therapeutic target to prevent some of the adverse effects of fluoxetine treatment.  相似文献   
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Cognitive Therapy and Research - Despite interest in psychological inflexibility as a marker of suicide risk, no measure of psychological inflexibility specific to SI exists. The present study...  相似文献   
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Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.  相似文献   
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