Evidence map›Paper›PMID 34025111›Full record

ArticleProfessional development (Philadelphia, Pa.)2020

Different Patient Group Responses To Community Treatment Orders Suggest Alternative Approaches.

Steven Segal

Open access · greenAbstract read
In one paragraph

Article in Professional development (Philadelphia, Pa.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 71% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

Steven SegalProfessor at University of Melbourne, and a Professor of the Graduate Division and Director of the Mental Health and Social Welfare Research Group at University of California, Berkeley.
University of California, Berkeley · US

Funding

TRAINING IN MENTAL HEALTH FINANCE &SERVICE DELIVERYT32MH018828 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI SEGAL, STEVEN P · 1987 to 2001
$596k
NIMH NIH HHS T32 MH018828
6 · The paper itself

Abstract

Community treatment orders (CTOs) help people with severe mental illness survive through potentially harmful crises posing imminent threats to health and safety by providing needed treatment when possible as a less restrictive alternative (LRA) to involuntary hospitalization. This review considers how differing patient subgroups have responded to differing CTO implementation approaches. Though recent trends have favored restricting psychiatric discretion, patients selected by psychiatrists as eligible for brief CTO assignment and assigned randomly to either brief or fixed-longer-term CTOs were no different in adverse outcomes other than in the duration of supervised time. Though emphasis has been on dangerousness to others, a study excluding such patients found lesser amounts of victimization among CTO-assigned vs. non-CTO patients. Though the trend has been focused on shortening CTO-duration, studies of extended six-month CTO assignment found that such patients experienced reduced inpatient days. Though emphasis has been on using CTOs with patients who have repeatedly failed in voluntary community care, studies of early intervention CTO use yielded positive results. Finally, CTO diversion has received limited use but when used had positive outcomes. Average evidence rankings for all subgroup study areas were 3.58 of 5 with 1 being the best rank. These studies, while low in evidence ranking, suggest alternative approaches may improve CTO-use outcomes for different patient subgroups.

Identifiers

PMID34025111
PMCPMC8136251
OpenAlexW3164769767

What OpenQuestion holds

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LicenceTDM
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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.