Evidence map›Paper›PMID 38026721›Full record

ArticleAddiction & health2023

Classifying the Factors Affecting Information Therapy to Support Clinical Decisions on Addiction.

Sedigheh Mohammadesmaeil, Shiba Kianmehr

Open access · diamondAbstract read
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Article in Addiction & health, 2023. 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 74% 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

2 authors at 2 institutions in 1 country.

Sedigheh MohammadesmaeilDepartment of Knowledge and Information Science, Islamic Azad University, Science and Research Branch, Tehran, Iran.ORCID https://orcid.org/0000-0002-4972-9789
Shiba KianmehrStudent of Medical Library and Information Science, Tehran University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0002-1161-5989
Islamic Azad University, Science and Research Branch · IRTehran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The present study aimed to identify the dimensions and components of developing an information therapy approach for clinical decisions on addiction in addiction treatment centers based on the opinions of thematic specialists in Iran using the fuzzy Delphi technique. Methods: This study was a qualitative one conducted using Delphi method on 20 researchers of addiction treatment in the areas of psychiatry, psychology, medicine, etc. Findings: The analysis of the data revealed 92 indicators in two dimensions, namely information dimension (health literacy) and treatment dimension (health services), each containing 6 components. The information dimension included acquiring information, identifying information, sharing information, raising awareness, information needs, and health knowledge, and the treatment dimension included patient satisfaction, information-seeking behaviors and skills, treatment methods and costs, participatory care and use of information, educational interventions, and disease prevention. Conclusion: Developing an information therapy approach in addiction treatment, as a cost-effective and low-cost method, is one of the cognitive strategies that can be used by officials to pave the way for health in this regard. This technique aims to improve the quality of medical services and care for addicts and is a suitable solution to meet their needs.

Indexed as

Clinical therapy for addictionFuzzy Delphi techniqueHealth literacyHealth servicesInformation therapy

Identifiers

PMID38026721
PMCPMC10658106
OpenAlexW4387644831

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.