Identifying the most critical side effects of antidepressant drugs: a new model proposal with quantum spherical fuzzy M-SWARA and DEMATEL techniques

Abstract

Identifying and managing the most critical side effects encourages patients to take medications regularly and adhere to the course of treatment. Therefore, priority should be given to the more important ones, among these side effects. However, the number of studies that make a priority examination is limited. There is a need for a new study that determines which of these effects are more priority to increase the quality of the treatment. Accordingly, this study aims to define the most important side effects of antidepressant drugs with a novel model. Quantum Spherical fuzzy M-SWARA technique is considered to compute the importance weights of the items. The main contribution of this study is that the most critical side effects can be understood for antidepressant drugs by establishing a novel decision-making model. The findings demonstrate that psychological side effects are defined as the most critical side effects of antidepressant drugs. Furthermore, physical side effects also play a key role in this condition. Side effects in antidepressant treatment have a great impact on the effectiveness of treatment and patient compliance.

Full text

Silahtaroğluetal.
BMC Medical Informatics and Decision Making (2024) 24:276
https://doi.org/10.1186/s12911-024-02692-z
RESEARCH
Identifying themost critical side eects
ofantidepressant drugs: anew model proposal
withquantum spherical fuzzy M-SWARA
andDEMATEL techniques
Gökhan Silahtaroğlu1, Hasan Dinçer1, Serhat Yüksel1, Abdurrahman Keskin2*, Nevin Yılmaztürk2 and
Alperen Kılıç3
Abstract
Identifying and managing the most critical side effects encourages patients to take medications regularly and adhere
to the course of treatment. Therefore, priority should be given to the more important ones, among these side
effects. However, the number of studies that make a priority examination is limited. There is a need for a new study
that determines which of these effects are more priority to increase the quality of the treatment. Accordingly, this
study aims to define the most important side effects of antidepressant drugs with a novel model. Quantum Spheri-
cal fuzzy M-SWARA technique is considered to compute the importance weights of the items. The main contribution
of this study is that the most critical side effects can be understood for antidepressant drugs by establishing a novel
decision-making model. The findings demonstrate that psychological side effects are defined as the most critical side
effects of antidepressant drugs. Furthermore, physical side effects also play a key role in this condition. Side effects
in antidepressant treatment have a great impact on the effectiveness of treatment and patient compliance.
Keywords Antidepressant drugs, Correct drug use, Side effect, Fuzzy logic, Multi-criteria decision making
Introduction
Doctors should determine the appropriate drugs for their
patients. e main reason is that choosing the right med-
ication can have a critical impact on improving patients’
health or relieving symptoms. Each disease has different
treatment methods and drugs. Doctors can determine the
most effective treatment based on the patient’s specific
conditions and diagnosis [1]. Incorrect drug selection can
lead to delays or failures in disease control or recovery.
On the other hand, it is also critical that drugs must be
safe as well as effective. Each patient has a different medi-
cal history, allergies, or tolerance levels to other medica-
tions [2]. By considering patients’ current conditions and
characteristics, physicians can determine the options
that minimize potential side effects. With the help of this
issue, these drugs can be the safest for patients. It is very
important to identify and reduce the side effects of drugs
in this process. Side effects can affect patients’ daily lives
and may adversely affect the functionality and general
quality of life of patients. Identifying and reducing side
effects can help patients feel more comfortable during
the treatment process and continue their normal lives [3].
Using a drug with adverse side effects may cause patients
Open Access
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BMC Medical Informatics and
Decision Making
*Correspondence:
Abdurrahman Keskin
abdurrahman.keskin@pusulayazilim.com.tr
1 The School of Business, İstanbul Medipol University, İstanbul, Turkey
2 Research and Development Centre, Pusula Enterprise Business
Solutions, İstanbul, Turkey
3 Department of Psychiatry, Istanbul University-Cerrahpasa Faculty
of Medicine, İstanbul, Turkey
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Silahtaroğluetal. BMC Medical Informatics and Decision Making (2024) 24:276
to hesitate to take the drug or not complete the treat-
ment. erefore, reducing side effects may encourage
patients to be more compliant with medication. Moreo-
ver, side effects can sometimes lead to serious health
problems [4].
Psychiatric medications can also have some side effects.
e side effects of these drugs can vary depending on the
type of drug, dose, and individual factors. For example,
some antidepressants can have side effects, such as nau-
sea and diarrhea. Similarly, some of these drugs can also
cause sexual dysfunction. Furthermore, it is seen that
some people who use psychiatric drugs have an excessive
need for sleep [5]. On the other hand, the side effects of
psychiatric drugs can sometimes lead to serious health
problems [6], such as metabolic syndrome, diabetes, and
heart problems. Physicians need to take appropriate pre-
cautions to manage or minimize these side effects. It is
vital to determine the side effects of psychiatric drugs
and to take the necessary precautions [7]. is is neces-
sary for the treatment process of patients to be safe and
effective. Most of the scholars in the literature examine
the possible side effects of psychiatric drugs [8]. However,
there are limited studies on which side effects are more
important. On the other hand, it is critical to determine
the most critical side effects of psychiatric drugs [9].
Long-term treatments are common, especially with psy-
chological side effects. us, identifying and managing
the most critical side effects encourages patients to take
medications regularly and adhere to the course of treat-
ment. is situation increases treatment compliance and
may positively affect treatment outcomes [10]. erefore,
priority should be given to the more important ones,
among these side effects. Nevertheless, the number of
studies that make a priority examination is limited. is
situation can be accepted as an essential gap in this lit-
erature. As a result, there is a need for a new study that
determines which of these effects are more priority to
increase the quality of the treatment [11].
Accordingly, this study, aims to determine the most
important side effects of antidepressant drugs. e
research question of the study is which side effects should
doctors primarily consider when administering antide-
pressant medications to their patients. In this context,
a comprehensive literature review has been carried out
and basically, six different side effects of these drug types
are determined. After that, a novel model is suggested
to determine which side effects are more important. In
this model, the quantum spherical fuzzy M-SWARA
technique is taken into consideration to calculate the
importance weights of the criteria. On the other hand,
a comparative analysis is carried out with the quantum
spherical fuzzy DEMATEL method to test the consist-
ency of the results obtained. e main motivation of this
study is the necessity to make a comprehensive evalua-
tion with respect to the side effects of antidepressant
drugs. In this framework, decision-making models can
be taken into consideration. However, there are lots of
criticisms of the existing models. One of the most critical
criticisms is related to the failure to successfully manage
uncertainty. is condition should be considered while
generating a model.
e main contribution of this study is that the most
critical side effects can be understood for antidepressant
drugs by establishing a novel decision-making model.
us, it can be possible to mention both theoretical and
methodological contributions to the literature. Accord-
ing to the methodological contribution, one of the most
important features of the study is the priority analysis
to determine the most important side effects of antide-
pressant drugs. Detecting critical side effects of psychi-
atric drugs allows for optimizing the treatment plan.
Each patient has a different side effect tolerance and risk
profile. Detection of side effects helps physicians select
medications and adjust dosages based on patients’ indi-
vidual characteristics, medical history, and sensitivity to
side effects [12]. us, it is ensured that patients have the
most appropriate treatment plan and achieve the best
results by minimizing side effects. On the other side,
regarding the methodological contribution, the main
superiorities of this proposed model compared with the
previously generated ones are demonstrated as follows.
(i) e main methodological novelty of this study is the
generation of a new decision-making technique named
M-SWARA. Although the classical SWARA approach
provides many benefits, the causal relationship between
the items cannot be considered [13]. However, the side
effects of psychiatric drugs may have a strong influence
on each other. For instance, psychological side effects can
also increase the problems related to the stomach. e
causal directions between the indicators cannot be iden-
tified by other weighting models in the literature, such as
the analytical hierarchy process and analytical network
process. Owing to this situation, some improvements are
made to the classical SWARA technique, and M-SWARA
methodology is proposed. is newly developed tech-
nique helps to consider the cause-and-effect relationship
between the criteria [14]. (ii) e use of the DEMATEL
technique in the evaluation of the criteria provides some
advantages. e side effects of psychiatric drugs can be
effective on each other. For example, stomach side effects
can have an effect on physical side effects. Many differ-
ent decision-making techniques are used in literature.
e most important advantage of the DEMATEL method
over the others is that it also examines the cause-effect
relationship between the criteria [15, 16]. erefore, it is
seen that the DEMATEL technique is the most optimal
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Silahtaroğluetal. BMC Medical Informatics and Decision Making (2024) 24:276
method in the analysis to be made to determine the most
significant side effect. In addition to this situation, the
DEMATEL methodology is also used in this proposed
model to check the reliability of the findings. In other
words, in this study, two different methods are taken
into consideration for weighting the criteria. us, it
becomes possible to make a comparative analysis. is
helps to test the accuracy, consistency, and reliability of
the results obtained. In this way, more effective strategies
can be developed. (iii) Integrating quantum theory and
spherical fuzzy numbers also provides some advantages.
Quantum theory allows to consider different possibilities
[17]. is theory is very successful in making accurate
estimations. Due to this benefit, quantum theory is used
with fuzzy decision-making methodology. Hence, uncer-
tainties in the analysis process can be handled more suc-
cessfully. On the other hand, Spherical fuzzy sets use a
three-dimensional membership function, namely degree
of membership, degree of non-membership, and degree
of hesitation. erefore, these numbers also help to work
with a larger data set [18]. Moreover, in spherical fuzzy
sets, the degree of hesitation is considered when deciding
on the membership of an element. anks to this, deci-
sion-makers can make a more comprehensive evaluation.
is situation can be accepted as the main superiority
of these sets over Pythagorean and intuitionistic fuzzy
numbers. is issue also contributes to minimizing the
uncertainty in the process and achieving more accurate
results [19].
A literature review is presented in the second part. e
methodology is explained in the new part. e results
and conclusions are given in the following sections.
Literature review
Selective serotonin reuptake inhibitors (SSRIs) are the
first-line drugs for the treatment of depression [20]. In
this drug group, fluoxetine, escitalopram, citalopram,
paroxetine, and sertraline are among the most preferred
drugs [21]. e most common side effects of antidepres-
sant drugs are sleep, eating, pain, and sexual problems
[22]. A study of SSRI drugs focused on the digestive side
effects they cause in patients [23]. It has been shown to
have side effects such as stomach upset, burning sensa-
tion, nausea, vomiting, abdominal pain, diarrhea, and
constipation [24].
It is anticipated that the use of SSRIs may worsen
depression and sleep-related respiratory disorders,
particularly during NREM sleep [25]. In a retrospec-
tive study on individuals with depressive disorders and
sleep complaints, norepinephrine-dopamine reup-
take inhibitors in NREM sleep were found to have a
lower oxygen saturation subpoint and a higher oxygen
desaturation index than the drug-free group [26]. As a
result, it is predicted that there may be a relationship
between irregular breathing problems and nighttime
oxygen saturation in patients with depressive disorders
and sleep complaints [27]. Psychological symptoms,
irritability, anxiety, low mood, sleep disturbance, sui-
cidal thoughts, and hallucinations are observed [28].
The daily side effects in the sample group receiving
antidepressant medication were reported as gastro-
intestinal side effects (17%), indigestion (22%), nau-
sea (18%), diarrhea (9%), and constipation (11%). The
side effect reports of the sample group as somatic side
effects are fatigue (45%), dizziness (24%), hypotension
(15%), headache (34%) and blurred vision (22%). Other
reported somatic side effects reports due to hormonal
imbalance are as follows: sweating at 34%, sudden heat
stroke at 22%, swelling at 8%, and dryness in the mouth
at 25% [29, 30]. It is seen that the senses of smell func-
tion at a lower level in people treated for depressive
disorder compared to control groups [31]. As a result
of a systematic literature review that reported sexual
disorder, weight changes, and insomnia side effects;
In antidepressant drugs such as trazodone, venlafax-
ine, escitalopram and vortioxetine, sexual dysfunction
was observed to be moderate, and anxiety and weight
change were among the side effects seen in a high
course [32]. Weight gain is among the common side
effects of many antidepressant groups [33]. Bupropion
is highly relevant for weight loss [34, 35]. On the con-
trary, weight loss is observed in the drug Topiramate
[36].
Psychological side effects account for approxi-
mately 22.8% of the global disease burden [37]. e
leading cause of this disability is depression, which
has increased significantly in the last 30 years due to
population growth and aging (WHO, 2008) [38]. is
trend poses a significant challenge for health systems
in developed and developing countries in treating
patients, optimizing resources, and improving men-
tal health services [39, 40]. It has been observed that
there are patients who have different responses to the
same treatment during drug treatment [41]. It is known
that this situation is caused by clinically significant sub-
group diseases and personal conditions of individuals
[42]. ree drugs were compared in the field study of
monotherapy antidepressants [43]. 90.79% of the par-
ticipants reported an improvement in their psychologi-
cal distress levels [44]. e results of the drug’s efficacy
were found to be statistically insignificant, as it was
shown to be effective in adult patients suffering from
major depressive disorders without accompanying dis-
orders [45]. e future of psychiatry is expected to use
big data approach techniques integrating electronic
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health records, sensor records, and feedback of the
patient informed by clinical evaluation [46, 47].
It is possible to underline some critical issues as a
result of the literature evaluation. Most of the schol-
ars in the literature examine the possible side effects of
psychiatric drugs. However, there are limited studies
on which side effects are more important. On the other
hand, it is critical to determine the most critical side
effects of psychiatric drugs. erefore, priority should
be given to the more important ones, among these side
effects. However, the number of studies that make a
priority examination is limited. is condition can be
accepted as an essential gap in this literature. In other
words, there is a need for a new study that determines
which of these effects are more priority to increase the
quality of the treatment. To satisfy this gap in the lit-
erature, a new decision-making model has been estab-
lished in this study to make a priority analysis of the
side effects of the antidepressant drugs.
Methodology
A novel model is suggested to find the most critical side
effects of antidepressant drugs. For this purpose, both
Quantum Spherical fuzzy M-SWARA and DEMATEL
methods are taken into consideration. In this section,
these models are explained. e details of the proposed
model are illustrated in Fig.1.
Spherical fuzzy sets
Multi-criteria decision-making models can be used
with fuzzy numbers to increase their effectiveness. It
is possible to discuss the importance of using fuzzy
numbers in these models. Uncertainty is increasing in
real-world problems [48]. Using fuzzy numbers with
these techniques also allows this uncertainty to be
minimized. In this way, it is possible to model com-
plex relationships more successfully [49]. Spherical
fuzzy sets are obtained by expanding Pythagorean and
intuitionistic fuzzy numbers. In these sets, a three-
dimensional membership function is used, including
membership degree, non-membership degree, and
hesitation degree. This situation provides more infor-
mation than classical fuzzy sets. In spherical fuzzy
sets, the hesitation degree is considered when deciding
on the membership of an element [50]. Thanks to this
situation, decision-makers can make a more compre-
hensive evaluation. Furthermore, the sets work with
a more comprehensive data set. This situation allows
uncertainty to be managed more successfully. This
situation increases the accuracy and reliability of the
decision-making process.
The extended approach toM‑SWARA
SWARA method is used to compute the weights of the
items. e main drawback of this technique is that cau-
sality evaluation is not identified [51]. To satisfy this situ-
ation, some improvements are adopted to SWARA, and a
new method (M-SWARA) is generated [52, 53]. With the
help of this new approach, an impact relation map of the
factors can be created [54]. Firstly, evaluations are taken
from the decision-makers. Next, Eq.(1) is used to define
the relation matrix.
Fig. 1 Flowchart of the proposed model
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In the following process, aggregated values are com-
puted by Eq.(2).
Next, the values are defuzzified with Eq.(3).
After that,
sj
(importance rate),
kj
(coefficient),
qj
(recal-
culated weight), and
wj
(weight) values are calculated by
Eqs.(4)-(6).
In the final step, weights are calculated while transpos-
ing and limiting the matrix to the power of 2t + 1.
(1)
ς
k=
0ς12 ··· ··· ς1n
ς21 0··· ··· ς2n
.
.
.
.
.
....··· ···
.
.
.
.
.
.
.
.
.....
.
.
ς
n1
ς
n2
··· ··· 0
(2)
ς
=





1−k
i=11−ςµi
21
k
1
2
e
2π.1−k
i=11−αi
2π21
k
1
2
,k
i=1ςvi
1
ke2π.k
i=1γi
2π1
k,
k
i=11−ςµi
21
k
−k
i=11−ςµi
2−ςhi
21
k
1
2
e
2π.
k
i=11−αi
2π21
k
−k
i=11−αi
2π2
−βi
2π21
k

1
2











(3)
Def
ςi=ςµi+ςµi
ςµi+ςhi+ςvi+

αi
2π

+


αi
2π

αi
2π

+

γi
2π

+

βi
2π


(4)
k
j=

1j=1
sj+1j>
1
(5)
q
j=

1j=1
qj−1
kjj>
1
If sj
−1=
sj,qj
−1=
qj
;
If sj
=
0, kj
−1=
kj
(6)
w
j=
q
j

n
k=1
q
k
The extended approach toDEMATEL
DEMATEL technique is considered to compute the sig-
nificance weight of the items. Hence, this approach helps
to find solutions for difficult and complex problems [55].
Additionally, the causal relationship between the factors
is also used with the help of this technique [56]. is situ-
ation is accepted as the main superiority of DEMATEL
[57]. DEMATEL is used with Quantum Spherical fuzzy
sets. After obtaining the evaluations from the expert
team, the relation matrix is identified with Eq.(7).
Equation(8) includes the calculation of the aggregated
values.
Defuzzified values are calculated with Eq.(9).
Normalization process is applied by Eqs. (10) and
(11).
(7)
ς
k=








0
ς12 ··· ··· ς1n
ς21 0··· ··· ς2n
.
.
.
.
.
....··· ···
.
.
.
.
.
.
.
.
.....
.
.
ς
n1
ς
n2
··· ··· 0








(8)
ς
=





1−k
i=11−ςµi
21
k
1
2
e
2π.1−k
i=11−αi
2π21
k
1
2
,k
i=1ςvi
1
ke2π.k
i=1γi
2π1
k,
k
i=11−ςµi
21
k
−k
i=11−ςµi
2−ςhi
21
k
1
2
e
2π.
k
i=11−αi
2π21
k
−k
i=11−αi
2π2
−βi
2π21
k

1
2











(9)
Def
ςi=ςµi+ςhiςµi
ςµi+ςvi+

αi
2π

+

γi
2π


αi
2π

αi
2π

+

βi
2π


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Equation(12) is used to create relation matrix.
e sum of rows and columns of this matrix are iden-
tified as in Eqs.(13) and (14).
Finally, causal directions are determined with the
threshold value defined in Eq.(15).
An evaluation withfuzzy decision‑making models
In this section, the details of the evaluation with Quan-
tum Spherical fuzzy M-SWARA and DEMATEL are
presented.
(10)
B
=
ς
max1≤i≤n

n
j=
1ς
ij
(11)
0
≤
bij
≤
1
(12)
C
=lim
k→∞
B+B2+... +Bk

=B(I−B)
−
1
(13)
D
=

n
j=1eij
nx1
(14)
E
=

n
i=1eij
1xn
(15)
α
=
n
i=1
n
j=1

eij

N
Denition oftheproblem andidentication ofcriteria set
is study aims to define the most significant side effects
of antidepressant drugs. Within this scope, a detailed lit-
erature evaluation has been conducted and 6 different
side effects of these drug types are selected. e details
of the selected side effects of these drugs are denoted in
Table1.
Antidepressant drugs can also cause ear, nose, and
throat disorders such as tinnitus and dizziness. ese dis-
orders can negatively affect patients’ activities of daily liv-
ing and reduce their general well-being. Some side effects
of psychiatric medications can cause physical discom-
fort. ese side effects can manifest as various physical
symptoms or disturbances in the body, such as fatigue
and headaches. Some side effects of psychiatric drugs
can cause movement and balance disorders. ese side
effects can lead to changes in muscle movements, trem-
ors, or balance problems.
Weighting thefactors withquantum spherical fuzzy
M‑SWARA
Evaluations are obtained from 5 decision makers. ese
people consider the scales detailed in Table2.
e details of the evaluations are indicated in Table3.
In the following step, average values are calculated and
given in Table4.
Relation matrix is constructed with these values as
given in Table8.
Finally, weighting priorities are shown in Table9.
It is concluded that psychological side effects are
defined as the most critical side effects of antidepressant
drugs. Similarly, physical ailments also play a key role in
this situation. On the other hand, stomach ailments and
ENT disorders are in the last ranks.
Making acomparative evaluation withquantum spherical
fuzzy DEMATEL
In this section, another evaluation has also been per-
formed by using Quantum Spherical fuzzy DEMATEL
methodology. is situation helps to test the quality of
Table 1 Side effects
Side Eects Supported
Literature
Stomach Ailments (STLM) [2]
Respiratory Ailments (RRLM) [4]
Psychological side effects (PYDD) [7]
ENT side effects (ENTD) [10]
Physical Ailments (PYLM) [58]
Movement and Support Disorders (MVSD) [12]
Table 2 Scales
Scales Possibility Degrees Numerical Scales QSFNs
No (n) 0.40 1

√0.16ej2π0.4,√0.10ej2π0.25 ,√0.74ej2π0.35

some (s) 0.45 2

√0.20ej2π0.45,√0.13ej2π0.28 ,√0.67ej2π0.27

medium (m) 0.50 3

√0.25ej2π0.50,√0.15ej2π0.31 ,√0.60ej2π0.19

high (h) 0.55 4

√0.30ej2π0.55,√0.19ej2π0.34 ,√0.51ej2π0.11

very high (vh) 0.60 5

√0.36ej2π0.6,√0.22ej2π0.37 ,√0.42ej2π0.03

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Silahtaroğluetal. BMC Medical Informatics and Decision Making (2024) 24:276
the analysis results. e total relation matrix and weight-
ing priorities are denoted in Table10.
e comparative weighting priorities computed by
both M-SWARA and DEMATEL are illustrated in Fig.2.
Figure 1 demonstrates that both techniques explain
similar issues. is situation gives information that this
model provides reliable findings.
Conclusions anddiscussions
is study aims to define the most essential side effects
of antidepressant drugs. For this purpose, a detailed lit-
erature review has been carried out and 6 different side
effects of these drug types are identified. In the next pro-
cess, a novel model is suggested to determine which side
effects are more important. In this model, the Quantum
Spherical fuzzy M-SWARA technique is taken into con-
sideration to calculate the significance weights of the cri-
teria. Additionally, a comparative analysis is carried out
with the Quantum Spherical fuzzy DEMATEL method
to test the reliability of the results. It is concluded that
psychological side effects are defined as the most criti-
cal side effects of antidepressant drugs. Similarly, physi-
cal ailments also play a key role in this situation. On the
other hand, stomach ailments and ENT disorders are
Table 3 Evaluations
STLM RRLM PYDD ENTD PYLM MVSD
Decision Maker 1
STLM M M S S S
RRLM S H M H H
PYDD H H H H M
ENTD M M H S H
PYLM S S H S M
MVSD M M VH N H
Decision Maker 2
STLM H H M M M
RRLM S H H H H
PYDD VH VH H H H
ENTD S H H M M
PYLM M M VH S H
MVSD M M VH M H
Decision Maker 3
STLM S S M S N
RRLM S M S H H
PYDD VH H H H H
ENTD S M M S M
PYLM S M H S VH
MVSD M H H S VH
Decision Maker 4
STLM M H S H M
RRLM S M H M M
PYDD H M H H M
ENTD S M M S S
PYLM M M H S H
MVSD S H H M H
Decision Maker 5
STLM S H S M M
RRLM S M S H H
PYDD H M M M M
ENTD S S S M M
PYLM S M H S H
MVSD S S H S H
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Silahtaroğluetal. BMC Medical Informatics and Decision Making (2024) 24:276
on the last ranks. Similarly, the core symptoms of psychi-
atric disorders are psychological and physical, which are
an important part of them. For this reason, this modeling
may provide some solution to the dilemma of whether
these are the symptoms of psychiatric disorders or the
side effects of antidepressant drugs, which are perhaps
the most difficult things for physicians in the drug treat-
ment process.
Antidepressant drugs have become very widely pre-
scribed. Along with the high level of effectiveness of
drugs, their side effects are also quite common. is
often leads to discontinuation of treatment [59]. Side
Table 4 Average values
STLM RRLM PYDD ENTD PYLM MVSD
STLM


√
.24e
j2
π
..48
,
√.14ej2π..30,
√.62
e
j2π..22




√
.28e
j2
π
..52
,
√.16ej2π..32,
√.58
e
j2π..19




√
.22e
j2
π
..47
,
√.14ej2π..29,
√.64
e
j2π..24




√
.24e
j2
π
..48
,
√.14ej2π..30,
√.62
e
j2π..22




√
.23e
j2
π
..48
,
√.14ej2π..30,
√.63
e
j2π..23


RRLM


√
.20e
j2
π
..45
,
√.13ej2π..28,
√.67ej2π..27




√
.27e
j2
π
..51
,
√.15ej2π..31,
√.60ej2π..22




√
.26e
j2
π
..50
,
√.14ej2π..30,
√.62ej2π..23




√
.29e
j2
π
..54
,
√.18ej2π..33,
√.54ej2π..15




√
.29e
j2
π
..54
,
√.18ej2π..33,
√.54ej2π..15


PYDD


√
.33e
j2
π
..57
,
√.20ej2π..35,
√.49
e
j2π..11




√
.30e
j2
π
..55
,
√.19ej2π..34,
√.51
e
j2π..11




√
.29e
j2
π
..54
,
√.18ej2π..33,
√.54
e
j2π..15




√
.29e
j2
π
..54
,
√.18ej2π..33,
√.54
e
j2π..15




√
.27e
j2
π
..51
,
√.15ej2π..31,
√.60
e
j2π..22


ENTD


√
.21e
j2
π
..46
,
√.13ej2π..28,
√.66
e
j2π..26




√
.25e
j2
π
..50
,
√.15ej2π..31,
√.60
e
j2π..19




√
.26e
j2
π
..50
,
√.14ej2π..30,
√.62
e
j2π..23




√
.22e
j2
π
..47
,
√.14ej2π..29,
√.64
e
j2π..24




√
.25e
j2
π
..50
,
√.15ej2π..31,
√.60
e
j2π..19


PYLM


√
.22e
j2
π
..47
,
√.14ej2π..29,
√.64ej2π..24




√
.24e
j2
π
..48
,
√.14ej2π..30,
√.62ej2π..22




√
.32e
j2
π
..57
,
√.20ej2π..35,
√.48ej2π..09




√
.20e
j2
π
..45
,
√.13ej2π..28,
√.67ej2π..27




√
.31e
j2
π
..55
,
√.19ej2π..34,
√.51ej2π..13


MVSD


√
.23e
j2
π
..48
,
√.14ej2π..30,
√.63
e
j2π..23




√
.26e
j2
π
..50
,
√.14ej2π..30,
√.62
e
j2π..23




√
.33e
j2
π
..57
,
√.20ej2π..35,
√.49
e
j2π..11




√
.22e
j2
π
..47
,
√.14ej2π..29,
√.64
e
j2π..24




√
.32e
j2
π
..57
,
√.20ej2π..35,
√.48
e
j2π..09


Table 8 Relation matrix
STLM RRLM PYDD ENTD PYLM MVSD
STLM 0.211 0.253 0.149 0.211 0.177
RRLM 0.144 0.202 0.169 0.243 0.243
PYDD 0.238 0.198 0.198 0.198 0.167
ENTD 0.149 0.210 0.254 0.177 0.210
PYLM 0.162 0.192 0.280 0.138 0.228
MVSD 0.162 0.191 0.280 0.138 0.229
Table 9 Stable matrix and weighting priorities
STLM RRLM PYDD ENTD PYLM MVSD Weighting
priorities
STLM 0.149 0.149 0.149 0.149 0.149 0.149 5
RRLM 0.166 0.166 0.166 0.166 0.166 0.166 4
PYDD 0.203 0.202 0.203 0.203 0.203 0.203 1
ENTD 0.138 0.138 0.138 0.138 0.138 0.138 6
PYLM 0.175 0.175 0.175 0.175 0.175 0.175 2
MVSD 0.169 0.169 0.169 0.169 0.169 0.169 3
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effects in antidepressant treatment have a great impact
on the effectiveness of treatment and patient compli-
ance. e treatment is started by choosing among the
drugs that are thought to be effective in the decision-
making phase of the treatment by the physician. Due to
the individual situation and adverse effects, it is possible
to change the medication during the treatment period.
e side effects may prevent the person from losing faith
in treatment and trying a new drug. e clinical decision
support system, which takes into consideration the per-
sonal differences of the patients, recommends the drugs
that are expected to have the least side effects at this
stage. e system should be designed as supportive for
the physician to give the right treatment at the right time.
Otherwise, the treatment process of the patients can be
significantly prolonged. is situation causes a signifi-
cant deterioration in the quality of life of patients. One of
the most important contributions of the study is making
a priority analysis to determine the most important side
effects of antidepressant drugs. Detection of side effects
helps physicians select medications and adjust dosages
based on patients’ individual characteristics, medical
history, and sensitivity to side effects. is situation
helps patients have the most appropriate treatment plan
and achieve the best results by minimizing side effects.
Side effect studies are generally performed in single drug
use and homogeneous patient groups. In the study, the
patients in the sample group whose side effect reports
were collected include a sample group suitable for real-
life use, who also use drugs other than antidepressants
due to different types of diseases. In this respect, it
stands out differently from similar studies that include a
single drug and a homogeneous sample population.
e main contribution of this study is that the most
critical side effects can be understood for antidepressant
drugs by establishing a novel decision-making model.
Additionally, the generation of a new decision-making
technique named M-SWARA is also accepted as the main
methodological originality of this study. is newly devel-
oped technique helps to consider the cause-and-effect
relationship between the criteria. Integrating quantum
theory and spherical fuzzy numbers also provides some
advantages. Quantum theory allows us to consider differ-
ent possibilities. is theory is very successful in making
Table 10 Total relation matrix and weighting results
STLM RRLM PYDD ENTD PYLM MVSD D E D + E D‑E Weighting
results Weighting
priorities
STLM 1.641 1.864 1.988 1.774 1.919 1.896 11.08 11.03 22.11 0.049 0.159 5
RRLM 1.858 1.800 2.079 1.866 2.024 2.007 11.63 11.53 23.17 0.103 0.167 4
PYDD 2.014 2.087 2.048 1.994 2.148 2.123 12.41 12.29 24.71 0.119 0.178 1
ENTD 1.778 1.865 1.982 1.630 1.910 1.904 11.07 10.97 22.04 0.095 0.159 6
PYLM 1.846 1.929 2.071 1.829 1.838 1.990 11.50 11.90 23.40 − 0.394 0.168 3
MVSD 1.896 1.985 2.127 1.880 2.061 1.871 11.82 11.79 23.61 0.028 0.170 2
Fig. 2 Comparative Weighting Results
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Silahtaroğluetal. BMC Medical Informatics and Decision Making (2024) 24:276
accurate estimations. Due to this benefit, quantum theory
is used with fuzzy decision-making methodology. Hence,
uncertainties in the analysis process can be handled more
successfully. is study has many limitations, both theo-
retically and methodologically. In terms of methodologi-
cal limitations, only antidepressant drugs are included in
the scope of the study. However, side effects are also very
important for other types of drugs. In this context, other
types such as stomach drugs can be examined in future
studies. On the other hand, there are some limitations in
the model developed in this study. In this model, 3 differ-
ent experts are asked to evaluate the criteria. e aver-
age of the evaluations obtained in this process is taken. In
other words, the importance and weight of each expert is
accepted as equal. However, this situation is also criticized
by many researchers. e reason for this is that each of
the experts has different educational backgrounds and
work experiences. In this direction, a model can be estab-
lished in future studies in which the importance weights
of the experts are determined. Techniques such as artifi-
cial intelligence and machine learning can contribute sig-
nificantly to achieving this goal.
Authors’ contributions
All authors contributed equally to the work. G.S, H.D, S.Y, A.K, N.Y, A.K, jointly
carried out the design, methodology, data analysis and interpretation of the
results of the study. All authors reviewed and approved the manuscript.
Funding
This research did not receive any specific grant from funding agencies in the
public, commercial, or not-for-profit sectors.
Availability of data and materials
Data Availability Statement: “This study did not involve the use of datasets that
require a Data Availability Statement. “Additional Explanation: “Although the
‘Yes’ option was selected in the system, this study does not involve any data-
sets that require a data availability statement. The statement provided above
reflects the accurate status regarding data availability.”
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Received: 12 June 2024 Accepted: 19 September 2024
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