Evidence map›Paper›PMID 31308672›Full record

ArticleNeuropsychiatric disease and treatment2019

Patients' experiences of long-acting injectable antipsychotics: a qualitative study.

Lin-Ling Chiu, Chun-Hao Liu, Chun-Lin Chu, Huang-Li Lin, Shu-Chung Lii

Abstract read
In one paragraph

Article in Neuropsychiatric disease and treatment, 2019. 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
–field-weighted citation impact
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.

  1. Article
  2. Review
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.

Lin-Ling Chiu *School of Medicine, Collage of Medicine, Chang Gung University, Taoyuan, Taiwan.
Chun-Hao Liu *Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
Chun-Lin ChuDepartment of Psychiatry, Chang Gung Memorial Hospital at Taoyuan, Taoyuan, Taiwan.
Huang-Li LinDepartment of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
Shu-Chung Lii *Humanistic & Social Medicine Division, College of Medicine, Chang Gung University, Taoyuan, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn this study, we applied a qualitative approach to explore patients' subjective experiences of long-acting injectable antipsychotics (LAIs).

methodsPatients undergoing psychiatric treatment from the chronic ward or outpatient department of a medical center in northern Taiwan who had experience with LAI treatment were enrolled. Information was obtained through semi-structured in-depth interviews. The interviews were audio-recorded and then translated verbatim, and the data were collected and analyzed concurrently to develop major themes and categories.

resultIn total, 14 participants (8 female) were interviewed. In a bio-psycho-social model, the participants used LAIs as a method to become "normal," in order to achieve a balance between the "effects" and "side effects" that may influence their daily lives. Their past experiences constructed their concepts about and expectations regarding LAIs, and their relationships with their family members and co-workers also modeled their experiences.

conclusionIn our study, we sought to understand the experience of LAI in the daily life context of the patients. We attempted to use a bio-psycho-social model to evaluate the subjective experience of the patients; an improved understanding can help mental health specialists gain a closer insight into patient experience.

Indexed as

antipsychoticsexperienceLAIlong-acting injectablequalitative research

Identifiers

PMID31308672
PMCPMC6613361

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.