Melola Discovery

← Melola Discovery

Open access Journal

Identification of antipsychotic side effects in Schizophrenia patients using Naranjo algorithm at Jambi Psychiatric Hospital

Proceedings Academic Universitas Jambi · Vol. 1 No. 2 (2025) · pp. 632–640

DOI
10.22437/proca.v1i2.50325
Published
2025-11-29
Publisher
LPPM Universitas Jambi
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

Background: Schizophrenia is a chronic mental disorder that requires long-term antipsychotic therapy. However, the use of antipsychotics may lead to adverse drug reactions (ADRs) that can affect patients’ quality of life. Objective: This study aimed to identify the types and likelihood of antipsychotic-related side effects among patients with schizophrenia using the Naranjo Algorithm. Methods: A descriptive observational study was conducted in September 2025. Data were collected through structured patient interviews and verified using medical records. The probability of ADRs was assessed using the Naranjo Algorithm, and the data were analyzed descriptively. Results: Among 119 patients with schizophrenia, 12 met the inclusion criteria. These 12 patients experienced a total of 23 ADR events. Based on the Naranjo Algorithm, 4 patients (33.33%) were categorized as probable and 8 (66.67%) as possible. The most common adverse effects were severe sedation (6 cases, 29.09%) and weakness (6 cases, 29.09%), followed by acute dystonia, mouth stiffness, and hypotension (each 8.70%). Less frequent events included hyperglycemia, hypertension, leukocytosis, slurred speech, and hypersalivation (each 4.35%). Conclusion: Most adverse effects showed a possible to probable causal relationship with antipsychotic use. The Naranjo Algorithm proved useful for identifying ADRs and supporting pharmacovigilance activities in psychiatric settings. Enhanced clinical monitoring and patient education are recommended to minimize serious adverse effects.

Keywords

Collaboration network of the authors

40 authors · 135 co-authorship links · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
FitrianingsihAffiliation unknown8
Mirna Marhami IskandarAffiliation unknown5
Wahyu Indah Dewi AuroraAffiliation unknown5
SyamsurizalAffiliation unknown4
Andika SulistiawanAffiliation unknown4
Tia Wida EkaputriAffiliation unknown3
Indri MahariniAffiliation unknown3
MaimumAffiliation unknown3
Lipinwati LipinwatiAffiliation unknown3
Elisma .Affiliation unknown3
Fathnur Sani KasmadiAffiliation unknown3
Huntari HarahapAffiliation unknown2
Hasna DewiAffiliation unknown2
Puspa Dwi PratiwiAffiliation unknown2
FitriyantiAffiliation unknown2
Niken Irfa NastitiAffiliation unknown2
Fitriyanti FitriyantiAffiliation unknown2
Tengku Arief Buana PerkasaAffiliation unknown2
TasariAffiliation unknown1
Septiana WijayantiAffiliation unknown1
L. AgusuAffiliation unknown1
SukriAffiliation unknown1
Indang DewataAffiliation unknown1
Aloysius Hari KristiantoAffiliation unknown1
Eddy SuratmanAffiliation unknown1
Akhmad YaniAffiliation unknown1
Indra Lasmana TariganAffiliation unknown1
Diah Riski GustiAffiliation unknown1
Intan LestariAffiliation unknown1
Minarni MinarniAffiliation unknown1
Ade AdriadiAffiliation unknown1
M. DamrisAffiliation unknown1
Rina Nofri EnisAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://online-journal.unja.ac.id/index.php/PROCA/oai, first harvested 6 Nov 2026, last seen 6 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Identification of antipsychotic side effects in Schizophrenia patients using Naranjo algorithm at Jambi Psychiatric Hospital</dc:title>
	<dc:creator xml:lang="en">Yuliawati</dc:creator>
	<dc:creator xml:lang="en">Istarini, Attiya</dc:creator>
	<dc:creator xml:lang="en">Kamariyah</dc:creator>
	<dc:creator xml:lang="en">Yuliana</dc:creator>
	<dc:creator xml:lang="en">Lestari, Uce</dc:creator>
	<dc:creator xml:lang="en">Sofyan, Indah Sri Wulan</dc:creator>
	<dc:creator xml:lang="en">Apriyanti, Sofia Elisa</dc:creator>
	<dc:subject xml:lang="en">Antipsychotic; Inpatient; Naranjo Algorithm; Schizophrenia; Adverse Drug Reaction.</dc:subject>
	<dc:description xml:lang="en">Background: Schizophrenia is a chronic mental disorder that requires long-term antipsychotic therapy. However, the use of antipsychotics may lead to adverse drug reactions (ADRs) that can affect patients’ quality of life. Objective: This study aimed to identify the types and likelihood of antipsychotic-related side effects among patients with schizophrenia using the Naranjo Algorithm. Methods: A descriptive observational study was conducted in September 2025. Data were collected through structured patient interviews and verified using medical records. The probability of ADRs was assessed using the Naranjo Algorithm, and the data were analyzed descriptively. Results: Among 119 patients with schizophrenia, 12 met the inclusion criteria. These 12 patients experienced a total of 23 ADR events. Based on the Naranjo Algorithm, 4 patients (33.33%) were categorized as probable and 8 (66.67%) as possible. The most common adverse effects were severe sedation (6 cases, 29.09%) and weakness (6 cases, 29.09%), followed by acute dystonia, mouth stiffness, and hypotension (each 8.70%). Less frequent events included hyperglycemia, hypertension, leukocytosis, slurred speech, and hypersalivation (each 4.35%). Conclusion: Most adverse effects showed a possible to probable causal relationship with antipsychotic use. The Naranjo Algorithm proved useful for identifying ADRs and supporting pharmacovigilance activities in psychiatric settings. Enhanced clinical monitoring and patient education are recommended to minimize serious adverse effects.</dc:description>
	<dc:publisher xml:lang="en">LPPM Universitas Jambi</dc:publisher>
	<dc:date>2025-11-29</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://online-journal.unja.ac.id/PROCA/article/view/50325</dc:identifier>
	<dc:identifier>10.22437/proca.v1i2.50325</dc:identifier>
	<dc:source xml:lang="en">Proceedings Academic Universitas Jambi; Vol. 1 No. 2 (2025): The 6th Jambi Medicine and Health Science International Conference (JAMHESIC); 632-640</dc:source>
	<dc:source>10.22437/proca.v1i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://online-journal.unja.ac.id/PROCA/article/view/50325/22651</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Yuliawati, Attiya Istarini, Kamariyah, Yuliana, Uce Lestari, Indah Sri Wulan Sofyan, Sofia Elisa Apriyanti</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>