Evidence map›Paper›PMID 18601741›Full record

ArticleInternational journal of mental health systems2008

Does community care work? A model to evaluate the effectiveness of mental health services.

Emiliano Monzani, Arcadio Erlicher, Antonio Lora, Piergiorgio Lovaglio, Giorgio Vittadini

Open access · goldAbstract read
In one paragraph

Article in International journal of mental health systems, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Validation aspects of the health of the nation outcome scales.International journal of mental health systems · 2011
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

Emiliano MonzaniDipartimento di Salute Mentale dell'Azienda Ospedaliera "G, Salvini", Garbagnate Milanese, Italy. emiliano.monzani@fastwebnet.it
Arcadio Erlicher
Antonio Lora
Piergiorgio Lovaglio
Giorgio Vittadini
Azienda Ospedaliera di Desio e Vimercate · ITAzienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda · ITUniversity of Milan · ITUniversity of Milano-Bicocca · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this paper is to evaluate the effectiveness of community Mental Health Departments in Lombardy (Italy), and analyse the eventual differences in outcome produced by different packages of care. The survey was conducted in 2000 on 4,712 patients treated in ten Mental Health Departments. Patients were assessed at least twice in a year with HoNOS (Health of the Nation Outcome Scales). Data on treatment packages were drawn from the regional mental health information system, which includes all outpatient and day-care contacts, as well as general hospital and inpatient admissions provided by Mental Health Departments. Multilevel growth models were used for outcomes statistical analysis, expressed in terms of change of the total HoNOS score. On the whole, Mental Health Departments were effective in reducing HoNOS scores. The main predictor of improvement was treatment, while length of care, gender and diagnosis were weaker predictors. After severity adjustment, some packages of care proved more effective than others. Appropriate statistical methods, comprehensive treatment descriptions and routine outcome assessment tools are needed to evaluate the effectiveness of community mental health services in clinical settings.

Identifiers

PMID18601741
PMCPMC2488329
OpenAlexW2020055883

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.