Literature DB >> 27015158

A randomised controlled trial of the effectiveness of a program for early detection and treatment of depression in primary care.

A Picardi1, I Lega2, L Tarsitani3, M Caredda3, G Matteucci3, M P Zerella3, R Miglio4, A Gigantesco2, M Cerbo5, A Gaddini6, F Spandonaro7, M Biondi3.   

Abstract

OBJECTIVE: There is considerable uncertainty about whether depression screening programs in primary care may improve outcomes and what specific features of such programs may contribute to success. We tested the effectiveness of a program involving substantial commitment from local mental health services.
METHODS: Prospective, randomised, patient- and evaluator-masked, parallel-group, controlled study. Participants were recruited in several urban primary care practices where they completed the PC-SAD screener and WHOQOL-Bref. Those who screened positive and did not report suicidal ideation (N=115) were randomised to an intervention group (communication of the result and offer of psychiatric evaluation and treatment free of charge; N=56) or a control group (no feedback on test result for 3 months; N=59). After 3 months, 100 patients agreed to a follow-up telephone interview including the administration of the PC-SAD5 and WHOQOL-Bref.
RESULTS: Depression severity and quality of life improved significantly in both groups. Intent-to-treat analysis showed no effect of the intervention. As only 37% of patients randomised to the intervention group actually contacted the study outpatient clinic, we performed a per-protocol analysis to determine whether the intervention, if delivered as planned, had been effective. This analysis revealed a significant positive effect of the intervention on severity of depressive symptoms, and on response and remission rate. Complier average causal effect analysis yielded similar results.
CONCLUSION: Due to the relatively small sample size, our findings should be regarded as preliminary and have limited generalizability. They suggest that there are considerable barriers on the part of many patients to the implementation of depression screening programs in primary care. While such programs can be effective, they should be designed based on the understanding of patients' perspectives.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Depression; Mental health services; Primary care; Screening

Mesh:

Year:  2016        PMID: 27015158     DOI: 10.1016/j.jad.2016.03.025

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  6 in total

Review 1.  Routine provision of feedback from patient-reported outcome measurements to healthcare providers and patients in clinical practice.

Authors:  Chris Gibbons; Ian Porter; Daniela C Gonçalves-Bradley; Stanimir Stoilov; Ignacio Ricci-Cabello; Elena Tsangaris; Jaheeda Gangannagaripalli; Antoinette Davey; Elizabeth J Gibbons; Anna Kotzeva; Jonathan Evans; Philip J van der Wees; Evangelos Kontopantelis; Joanne Greenhalgh; Peter Bower; Jordi Alonso; Jose M Valderas
Journal:  Cochrane Database Syst Rev       Date:  2021-10-12

2.  What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts?

Authors:  Jingfang Liu; Mengshi Shi
Journal:  Int J Environ Res Public Health       Date:  2022-05-18       Impact factor: 4.614

3.  An Elevated FIB-4 Score Is Associated with an Increased Incidence of Depression among Outpatients in Germany.

Authors:  David Schöler; Karel Kostev; Münevver Demir; Mark Luedde; Marcel Konrad; Tom Luedde; Christoph Roderburg; Sven H Loosen
Journal:  J Clin Med       Date:  2022-04-15       Impact factor: 4.964

4.  Case vignette-based evaluation of psychiatric blended training program of primary care doctors.

Authors:  Kabir Garg; N Manjunatha; Channaveerachaari Naveen Kumar; Prabhat K Chand; Suresh Bada Math
Journal:  Indian J Psychiatry       Date:  2019 Mar-Apr       Impact factor: 1.759

5.  Early Detection of Depression: Social Network Analysis and Random Forest Techniques.

Authors:  Diego Fernandez; Fidel Cacheda; Francisco J Novoa; Victor Carneiro
Journal:  J Med Internet Res       Date:  2019-06-10       Impact factor: 5.428

6.  Depression Risk Prediction for Chinese Microblogs via Deep-Learning Methods: Content Analysis.

Authors:  Xiaofeng Wang; Shuai Chen; Tao Li; Wanting Li; Yejie Zhou; Jie Zheng; Qingcai Chen; Jun Yan; Buzhou Tang
Journal:  JMIR Med Inform       Date:  2020-07-29
  6 in total

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