Evidence map›Paper›PMID 33487810›Full record

ArticleIndian journal of psychological medicine2020

Methodology for Development of a Community Level Intervention Module for Physical Illness in Persons with Mental Illness (CLIPMI).

Ramanujam Govindan, Thara Rangaswamy, Sujit John, Sunitha Kandasamy

Open access · diamondAbstract read
In one paragraph

Article in Indian journal of psychological medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 2 institutions in 1 country.

Ramanujam GovindanTirunelveli Medical College, Tirunelveli, Tamil Nadu, India.
Thara RangaswamySchizophrenia Research Foundation, Chennai, Tamil Nadu, India.
Sujit JohnSchizophrenia Research Foundation, Chennai, Tamil Nadu, India.
Sunitha KandasamyTirunelveli Medical College, Tirunelveli, Tamil Nadu, India.
Schizophrenia Research Foundation · INTirunelveli Medical College · IN

Funding

Psychiatric research infrastructure for intervention and implementation in India – TEAMSD43TW009114 · FIC · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Smita N Deshpande, Mary Elizabeth Hawk · 2014 to 2026
$3.2M
FIC NIH HHS D43 TW009114
6 · The paper itself

Abstract

BACKGROUND AND

objectivesMedical illnesses seen in persons with psychiatric disorders are important but often ignored causes of increased morbidity and mortality. Hence, a community level intervention program addressing the issue is proposed. MATERIALS AND

methodsPatients with severe mental illnesses will be identified by a door-to-door survey and assessed for comorbid physical illnesses like anemia, hypertension, diabetes, and so on. They will then be randomized into two groups. The treatment as usual (TAU) group will not receive intervention from the trained community level workers, while the Intervention group will receive it.

resultsThe two groups will be compared for the prevalence and severity of comorbid physical illnesses. The expected outcome is compared to the TAU group, the intervention group will have a greater reduction in the morbidity due to physical illnesses and improved mental health.

conclusionIf successful, the module can be incorporated into the community level mental health delivery system of the District Mental Health Program (DMHP).

Indexed as

Community engagementcommunity mental healthcommunity psychiatrysocial intervention

Identifiers

PMID33487810
PMCPMC7802035
OpenAlexW3117883194

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.