The Effectiveness of Music Therapy on Fatigue and Laboratory Values in Acute Leukemia Patients Undergoing Chemotherapy
Phase: NA
Conditions: Acute Myeloid Leukemia, Fatigue
Sponsor: Chang Gung University

The Effectiveness of Music Therapy on Fatigue  
and Laboratory Values in Acute Myeloid Leukemia Patients 
 undergoing Chemotherapy 
 
 
 
 
 
 
 
 
 
 
 
 
NCT Number : NCT06286332    
 
 
November 14, 2025 
 

Background 
Statistics from the American Cancer Society (ACS) (2020) indicate that the 
global 5-year survival rate for all types of leukemia ranges from approximately 25% 
to 85%. For adult Acute Lymphoblastic Leukemia (ALL), the 5-year survival rate is 
40%–50%, whereas for Chronic Lymphocytic Leukemia (CLL), it is as high as 85%. 
Fatigue is the most prevalent symptom reported by leukemia patients (AlFayyad et al., 
2020; Schumacher et al., 2002; Wang et al., 2002). Given that leukemia treatment 
primarily involves chemotherapy and radiation therapy, side effects such as fatigue, 
nausea, and vomiting are typical (Schumacher et al., 2002). Approximately 60% to 
90% of patients experience cancer-related fatigue (CRF) during chemotherapy (Chen 
& Tang, 2020; Rutkowski et al., 2021). Factors contributing to CRF include cancer 
stage, treatment-related side effects (e.g., pancytopenia, malnutrition, and poor sleep 
quality secondary to chemotherapy or radiotherapy), and psychological distress (e.g., 
tension, anxiety, and fear stemming from uncertainty and stress regarding diagnosis 
and treatment) (Rau et al., 2020). With advancements in medical resources, cancer 
patient survival rates are gradually increasing (Miller et al., 2019). Therefore, early 
detection and timely intervention for fatigue by healthcare professionals are crucial 
for enhancing patients' quality of life. 
As per the 2023 National Comprehensive Cancer Network (NCCN) guidelines, 
non-pharmacological interventions are the recommended first-line approach for 
managing CRF. These are broadly categorized into six types: physical activity 
(Hilfiker et al., 2018; Wu et al., 2019), psychosocial interventions (Wu et al., 2021; 
Lai, 2015; Lai et al., 2017; Mustian et al., 2017; Poort et al., 2017), energy 
conservation techniques (Rau et al., 2023; Chou & Tang, 2008; Barsevick et al., 2002), 
complementary and alternative medicine (CAM) (Chen & Tang, 2020; Rau et al., 
2023; Zick et al., 2021), nutritional management (Inglis et al., 2019; Thong et al., 
2020), and light therapy (Monteleone et al., 2011; Starreveld et al., 2021; Van Maanen 
et al., 2016). 
Interventions such as acupressure, massage, and art or music therapy fall under the 
CAM category (Chen & Tang, 2020; Rau et al., 2023; Zick et al., 2021). Considering 
the specific characteristics of leukemia and the need for practical clinical application, 
music therapy presents as a non-invasive, safe, comfortable, and easily administered 
nursing intervention. It can be conveniently implemented by healthcare providers, 
patients themselves, or family members. Research indicates that music therapy can 
reduce depression, anxiety, and pain in cancer patients (Köhler et al., 2020; Li et al., 
2020; Sezgı̇N & Bektas, 2022). Unfortunately, the application of music therapy for 
managing CRF in leukemia patients remains limited. Therefore, this study aims to 
investigate the effects of music therapy on fatigue and clinical laboratory values (e.g., 

White Blood Cell [WBC] count, Hemoglobin [Hb], Albumin) in patients with acute 
leukemia, to provide a reference for clinical practice. 
Section 1: Research Purpose 
To investigate the effects of music therapy on fatigue and clinical laboratory values 
(White Blood Cell count, Hemoglobin, and Albumin) in patients with acute leukemia. 
Section 2: Research Hypotheses 
1. Patients with acute leukemia who receive music therapy will experience lower 
levels of fatigue during chemotherapy compared to those receiving standard 
care. 
2. Patients with acute leukemia who receive music therapy will demonstrate 
improved clinical laboratory values (White Blood Cell count, Hemoglobin, 
and Albumin) during chemotherapy compared to those receiving standard 
care. 
 
Literature Review 
I. Leukemia and Its Classification 
According to the Global Cancer Observatory (GLOBOCAN) (2020), the global 
incidence of leukemia was 5.4 per 100,000 population, with a mortality rate of 3.3 per 
100,000 population (Sung et al., 2021). In Taiwan, statistics from the Ministry of 
Health and Welfare (2022) indicate that malignant neoplasms have remained the 
leading cause of death for the past four decades. Leukemia ranked 13th among cancer 
deaths, with an incidence rate of 2.9 per 100,000 and a mortality rate of 5.0 per 
100,000. 
Among leukemia cases, Acute Myeloid Leukemia (AML) was the most prevalent, 
accounting for 32.21% of cases. This was followed by Acute Lymphocytic Leukemia 
(ALL) at 11.21%, Chronic Myelogenous Leukemia (CML) at 10.30%, and Chronic 
Lymphocytic Leukemia (CLL) at 8.77%. The median age at diagnosis was 63 years 
for both sexes. The crude incidence rates for males and females were 13.27 and 10.09 
per 100,000 population, respectively, indicating a higher incidence in males (Ministry 
of Health and Welfare, 2022; Chang, 2021). 
Under normal conditions, hematopoietic stem cells in the bone marrow differentiate 
and mature into two major lineages: the myeloid lineage and the lymphoid lineage. 
The pathogenesis of leukemia involves the uncontrolled proliferation of abnormal 
blood cells during hematopoiesis, which may result from genetic abnormalities such 
as translocation, deletion, point mutation, or epigenetic alterations. The precise 
etiology remains unclear, but potential risk factors include: advanced age, male sex, 
exposure to radiation, prior radiotherapy or chemotherapy, exposure to chemical 
agents (e.g., formaldehyde, building material coatings, industrial disinfectants), 

lifestyle factors (e.g., smoking, alcohol consumption), viral infections such as 
Epstein-Barr virus (EBV) and human immunodeficiency virus (HIV), heredity, and 
genetic mutations (Chang, 2021; Bispo et al., 2020; Vogado et al., 2018; Dohner et al., 
2015). 
Leukemia is classified based on cell origin and morphological features into 
lymphoblastic leukemia and myeloid leukemia. It is further categorized by cancer cell 
maturity and the clinical speed of progression into acute (excess immature blast cells) 
and chronic (excess mature blood cells). This results in the four main types: AML, 
CML, ALL, and CLL (Bispo et al., 2020; Dohner et al., 2015). 
II. Diagnostic Methods for Leukemia 
Diagnostic methods include blood tests, peripheral blood smears, and bone marrow 
aspiration and biopsy to observe the infiltration of leukemia cells in the blood and 
marrow. Imaging studies, such as computed tomography (CT) or magnetic resonance 
imaging (MRI), are used to assess for lymphadenopathy (swollen lymph nodes) or 
hepatosplenomegaly (enlarged liver and spleen). Genetic testing is also employed for 
disease classification (Wang et al., 2020). 
III. Treatment Modalities for Leukemia 
Currently, there are four primary treatment modalities for leukemia: chemotherapy, 
radiation therapy, hematopoietic stem cell transplantation (HSCT), and supportive 
therapy (Wang et al., 2020; Bispo et al., 2020). 
1. Chemotherapy: This is the primary treatment for leukemia, typically divided 
into three phases: 1) Induction: Short-term, intensive, high-dose therapy, 
usually lasting 1–2 months; 2) Consolidation/Intensification: High-dose 
therapy continued for several months; and 3) Maintenance/Post-consolidation: 
Low-dose therapy, typically continued for about two years. Common side 
effects include alopecia (hair loss), oral mucositis (mouth sores), anorexia 
(loss of appetite), nausea, vomiting, diarrhea or constipation, and pancytopenia 
(Wang et al., 2020; Turcotte et al., 2022). 
2. Radiation Therapy: This modality utilizes high-energy radiation to eliminate 
abnormal cells. It may be used for leukemia that has infiltrated the central 
nervous system (CNS) or to reduce tumor size. Side effects include fatigue, 
pancytopenia, skin reactions in the treatment area (ranging from mild redness 
or burning to desquamation [peeling]), and hair loss in the treated area. 
Depending on the irradiated zone, side effects such as nausea and vomiting (if 
the head or abdomen is treated) or diarrhea (if the abdomen or pelvis is treated) 
may occur (Wang et al., 2020; Turcotte et al., 2022). 
3. Hematopoietic Stem Cell Transplantation (HSCT): This is divided into 
allogeneic hematopoietic stem cell transplantation (allo-HSCT) and peripheral 

blood stem cell transplantation (PBSCT). PBSCT is commonly used today. 
Because hematopoietic stem cells are scarce in peripheral blood, 
granulocyte-colony stimulating factor (G-CSF) is administered for 3–5 days to 
accelerate stem cell growth and mobilize them into the peripheral blood. These 
cells are then collected, separated, cryopreserved, and stored for 
transplantation (Wang et al., 2020). 
4. Supportive Therapy: This involves symptomatic treatment, such as 
administering antibiotics for fever or providing blood transfusions for low 
hemoglobin or platelet counts (Wang et al., 2020). 
 
II Overview of Cancer-Related Fatigue 
Fatigue is the most prevalent symptom reported by leukemia patients (AlFayyad et al., 
2020; BIKMAZ & ÜNSAR, 2021; Schumacher et al., 2002; Wang et al., 2002). As 
leukemia treatment primarily involves chemotherapy and radiation therapy, side 
effects such as fatigue, nausea, and vomiting are typical (BIKMAZ & ÜNSAR, 2021; 
Großek et al., 2023; Schumacher et al., 2002). Approximately 80% of patients 
receiving chemotherapy and 90% receiving radiation therapy experience 
cancer-related fatigue (CRF) post-treatment. For some patients, this fatigue may 
persist for years after completing cancer therapy. Compared to other side effects like 
nausea and vomiting, fatigue is one of the most common and distressing issues. 
Factors contributing to CRF include cancer stage, treatment-related side effects (e.g., 
pancytopenia, malnutrition, and poor sleep quality secondary to chemotherapy or 
radiotherapy), and psychological distress, such as fatigue caused by tension, anxiety, 
and fear stemming from uncertainty and stress regarding the diagnosis and treatment 
(Rau et al., 2020). 
1. Definition of Cancer-Related Fatigue 
According to the National Comprehensive Cancer Network (NCCN) (2023), CRF is 
defined as a distressing, persistent, subjective sense of physical, emotional, and/or 
cognitive tiredness or exhaustion related to cancer or cancer treatment that interferes 
with daily functioning (Son, 2019; Piper, 1989; Aistars, 1987). Aistars (1987) defined 
fatigue as a subjective feeling of tiredness, weakness, exhaustion, and lack of energy 
resulting from long-term stress, which directly or indirectly impacts the disease 
process. Even with adequate sleep, the individual experiences an overwhelming sense 
of exhaustion, accompanied by reduced physical and mental capacity. Aaronson et al. 
(1999) defined fatigue as an imbalanced state in the availability, utilization, and 
restoration of an individual's resources, leading to a perceived reduction in physical or 
psychological capacity. 

Domestic scholar Liu (2001) described fatigue as: an individual's subjective 
perception, an unpleasant experience, and an overwhelming, persistent sense of 
exhaustion. Li and Lin (2002) proposed fatigue as: persistent physical and 
psychological weakness, reduced capacity for physical or mental activity, and an 
imbalanced state of energy preventing the attainment of comfort. 
Synthesizing the definitions from domestic and international scholars, fatigue is a 
subjective experience (Li & Lin, 2002; Liu, 2001; Aistars, 1987; NCCN, 2023). Its 
assessment dimensions should encompass physical, psychological, activity, and 
cognitive aspects (Li & Lin, 2002; Liu, 2001; Aistars, 1987; Aaronson et al., 1999; 
Charalambous & Kouta, 2016; Bennett et al., 2016; NCCN, 2023). Therefore, to 
comprehensively measure a patient's fatigue, multidimensional assessment tools are 
necessary. 
2. Theoretical Basis of CRF: The Proinflammatory Cytokine Dysregulation 
Hypothesis 
The pathogenic mechanism of CRF is not yet fully understood. However, many 
scholars suggest that CRF results from the interaction of multiple factors. The most 
widely accepted theory is the proinflammatory cytokine dysregulation hypothesis 
(Bower, 2014; Chao et al., 2011). When the body's immune response is affected by 
cancer cells or related treatments (e.g., chemotherapy, radiotherapy), it triggers the 
abnormal secretion of proinflammatory cytokines. This increases the inflammatory 
response, which in turn interferes with the central nervous system (CNS), leading to 
symptoms such as fever, sleep disturbances, headaches, reduced activity, and fatigue. 
This process can also impact the hypothalamic–pituitary–adrenal (HPA) axis, causing 
abnormal secretion of cortisol, hematopoietic cells, and serotonin, thereby disrupting 
circadian rhythms and resulting in physical and psychological fatigue (Taiwanese 
Society of Cancer Palliative Medicine, 2017; Bower, 2014; Hart & Reviews, 1988; 
Rau et al., 2023; Thong et al., 2020). 
3. Clinical Laboratory Values Associated with CRF 
The occurrence of CRF may be associated with clinical laboratory values. Common 
indicators are discussed in three parts below: 
1. White Blood Cell (WBC) Count (Leukocyte) An elevated WBC count is a key 
indicator of systemic inflammation. Influenced by the leukemia disease process and 
treatment side effects like chemotherapy, pancytopenia is a common adverse event. 
When patients develop pancytopenia and their WBC count drops, they become 
susceptible to infection (Oun et al., 2018; Tenold et al., 2021; Wei & Li, 2018). 
In a 2007 study of 65 leukemia patients, Alibhai et al. found a negative correlation 
between WBC count and fatigue severity (r = –0.34, p < 0.01) (Alibhai et al., 2007). 
Conversely, a domestic study by Tsai (2007) on 42 terminal cancer patients found a 

moderate positive correlation between WBC count and fatigue (r = 0.63, p < 0.05). 
However, other studies, including those on post-operative colorectal cancer patients 
and leukemia patients, reported no significant correlation between fatigue severity and 
WBC count (β = -0.037, p = 0.588; β = 0.16, p = 0.29, respectively) (Addisia et al., 
2022; Wei & Li, 2018). 
The possible reasons for these discrepant findings may relate to cancer type and stage. 
Different cancer types and stages necessitate different treatment dosages, leading to 
varying degrees of myelosuppression (Anand et al., 2023; Kuter, 2015). Furthermore, 
the timing of fatigue assessment is relevant. If assessed during chemotherapy, patients 
are likely experiencing side effects, including leukopenia. If survivors are assessed, 
the decrease in WBCs may be less pronounced. The week following chemotherapy is 
the period of peak side effects (Chen & Tang, 2020). Therefore, research designs 
should collect blood laboratory values concurrently with fatigue assessments during 
the patient's chemotherapy process to accurately monitor the fatigue problem. Study 
designs must reflect the clinical reality, synchronizing the collection of laboratory data 
and fatigue assessments to effectively capture the correlation between fatigue and 
WBC count. 
2. Hemoglobin (Hb) According to the World Health Organization (WHO) and the 
American Association of Blood Banks (AABB), anemia is defined as Hb < 12 g/dl for 
females and < 13 g/dl for males (Lotterman & Sharma, 2022; Safiri et al., 2021). 
Anemia (Hb < 12 g/dl) can result from the cancer itself, treatments 
(chemo/radiotherapy), malnutrition, bone marrow infiltration, or hemorrhage 
(Madeddu et al., 2018; Wang et al., 2002). Chemotherapy side effects cause 
myelosuppression, inhibiting erythropoiesis (red blood cell production) (Jhamb et al., 
2008; Thong et al., 2020). This leads to insufficient hemoglobin, which impairs 
systemic oxygen delivery and subsequently causes fatigue (Thong et al., 2020; Wang, 
2008). While 0% to 67% of chemotherapy patients may develop anemia, some studies 
note that fatigue can occur even in non-anemic cancer patients (Gaston‐Johansson et 
al., 1999). 
Oswald et al. (2021) found that low hemoglobin and low platelets were strongly 
associated with fatigue in leukemia patients (β = 0.56, 95% CI = 0.12 to 0.99, p = 
0.013; β = 0.18, 95% CI = 0.08 to 0.28, p = 0.001, respectively). Shafqat et al. (2005) 
and Blair et al. (2008), in studies of 228 leukemia patients and 40 breast cancer 
patients, respectively, found a low-to-moderate negative correlation between 
hemoglobin and fatigue (r = 0.332, p < 0.001; r = 0.71, p = 0.002, respectively) (Blair 
et al., 2008; Shafqat et al., 2005). 
In contrast, Dimeo et al. (2004), studying 71 leukemia survivors who were 
relapse-free and had not received treatment (chemo, radiotherapy, or 

immunomodulators) for at least 3 months, found fatigue was unrelated to the degree 
of anemia (r < 0.20, p = 0.79). This may be because data collection did not occur 
during active chemo/radiotherapy; the patients' anemia was not pronounced (mean Hb 
= 12 ± 1.0 g/dl) and did not meet the criteria for anemia treatment (transfusion or 
erythropoietin-stimulating agents) (Dimeo et al., 2004). 
The literature suggests a negative correlation between Hb and fatigue. As CRF peaks 
within one week post-chemotherapy (Chen & Tang, 2020), fatigue-related studies 
must ensure appropriate data collection timing to accurately monitor the CRF-Hb 
relationship. Considering the clinical situation, a single-item scale (e.g., Numerical 
Rating Scale) can simplify the burden of questionnaire completion, thereby enhancing 
internal validity and reducing attrition. Synchronizing the collection of laboratory data 
and fatigue assessments is essential to truly reflect the correlation between fatigue and 
hemoglobin. 
3. Albumin In the human body, albumin is not only a key nutritional marker but also 
reflects the body's inflammatory response. Studies indicate that as C-reactive protein 
(CRP) levels increase, albumin levels tend to decrease (McGovern et al., 2022; 
McMillan & Care, 2009; Schvartsman et al., 2017). Beyond the cancer process itself, 
treatment side effects (chemo/radiotherapy), such as nausea and vomiting leading to 
malnutrition, can also indirectly cause fatigue (McGovern et al., 2022; Schvartsman et 
al., 2017). 
Wang et al. (2002) and Shafqat et al. (2005), in studies of 174 mixed-cancer patients 
(lung, breast, leukemia, renal, etc.) and 228 leukemia patients, respectively, found a 
low-to-moderate negative correlation between albumin and fatigue (r = -0.22, P = 
0.004; r = -0.396, p < 0.001, respectively) (Shafqat et al., 2005; Wang et al., 2002). 
However, Schvartsman et al. (2017) (222 cancer patients) and Dimeo et al. (2004) (71 
leukemia survivors >3 months post-treatment) found no significant correlation 
between albumin and fatigue (p = 0.171; p = 0.99, respectively). Dimeo et al. noted 
that treatment side effects are a primary cause of fatigue; because their study enrolled 
patients who had not received recent cancer-related treatment, the associated side 
effects were absent, preventing the detection of a correlation between albumin and 
fatigue (Dimeo et al., 2004; Schvartsman et al., 2017). 
The literature thus suggests a negative correlation between albumin and fatigue, and 
indicates that data collection and fatigue measurement should be conducted while the 
patient is undergoing chemotherapy to accurately monitor the fatigue problem. 
 
III Overview of Music Therapy 
Section 1. Definition of Music Therapy (MT) 
The American Music Therapy Association (AMTA) defined music therapy in 2005 as 

a clinical and evidence-based intervention implemented by a qualified and certified 
music therapist. This therapeutic interaction utilizes the rich diversity of music to 
achieve individualized treatment goals for the client (AMTA, 2005). In the United 
States, certification for music therapists requires completion of a music therapy 
bachelor's degree, including an internship, passing the national certification board 
examination, and engaging in continuing education. In addition to the US, regions 
such as Canada, the UK, Australia, Germany, Japan, and Korea also have the 
professional designation of music therapist (Liu, 2021; AMTA, 2005). 
However, music therapy is still in its developmental stage in Taiwan; therefore, its 
definition is broader. It encompasses measures conducted by a music therapist, or 
music-related therapeutic activities conducted by healthcare personnel certified by the 
domestic Ministry of Health and Welfare (MOHW). These activities are implemented 
within their professional scope, following a systematic assessment of the patient's 
physical, psychological, and spiritual state, and are applicable for promoting or 
maintaining the patient's holistic health (Wu & Huang, 2006; Shih, 2006; Lin et al., 
2011). Music therapy utilizes musical elements to design activities appropriate for the 
client, thereby enhancing and maintaining their physiological, psychological, and 
spiritual balance and health. Healthcare professionals trained in music therapy can 
apply these techniques systematically and skillfully in clinical practice to help patients 
improve their physical, mental, and spiritual well-being (Lin et al., 2011; Hung & 
Wang, 1999). 
2. Mechanisms of Music Therapy 
After music enters the brain via the ear and auditory nerve, it can activate the limbic 
system and reduce the activity of the neuroendocrine and sympathetic nervous 
systems. It is then transmitted via the hypothalamus, reducing the secretion of 
adrenocorticotropic hormone (ACTH), which in turn decreases cortisol secretion. This 
alleviates the release of the body's stress-related chemical substances and promotes 
muscle relaxation (Lin et al., 2011; Beck, 1991; Cook, 1986; Suda et al., 2008). 
Music can also activate the ventral tegmental area (VTA) in the midbrain, promoting 
dopamine secretion, which induces feelings of pleasure and positivity (Tsai & Chou, 
2015; Gerdner, 2000; Menon & Levitin, 2005). Scholars note that song selection for 
MT must align with the client's background and personal preferences. Through 
appropriate assessment and selection of music that corresponds to the client's current 
emotional state, the therapeutic effects of music can be achieved (Tsai & Chou, 2015; 
Browning, 2000; Gerdner, 2000). 
Section II: Research on Music Therapy for Cancer-Related Fatigue 
Music therapy is currently widely used in populations such as older adults with 
dementia (Gassner et al., 2022; Lam et al., 2020; McDermott et al., 2013; 

Moreno-Morales et al., 2020), psychiatric patients (Carr et al., 2013; Gassner et al., 
2022; Gold et al., 2009; Köhler et al., 2020; Marquez-Garcia et al., 2021), and 
children with autism (Mayer-Benarous et al., 2021). Research by Sezgin et al. (2022) 
indicates that interventions—including the use of instruments, classical, modern, or 
personalized music therapy—typically last between 20–45 minutes, are conducted 
1–2 times per week, and continue for 1–2 months (Burns et al., 2008; Sezgin & 
Bektas, 2022). 
Although many studies have found that music therapy can reduce depression, anxiety, 
and pain in cancer patients, its application for managing fatigue is less common. This 
review identified six clinical trials that utilized music therapy as an intervention for 
fatigue in leukemia patients. The frequency, duration, intervention methods, and 
outcomes of these studies are summarized below (see Table 2-4). 
All six studies involved leukemia patients aged 18 or older undergoing chemotherapy. 
Four of these clinical trials reported significant differences (Burns et al., 2008; 
Cassileth et al., 2003; Reimnitz et al., 2020; Miladinia et al., 2021), finding small to 
large effect sizes (ES, d = 0.12–1.95). 
• 
Burns et al. (2008) randomized 49 patients into a music therapy (MT) group 
(N=25) and a standard care group (N=24). The MT group received 20-minute 
sessions twice weekly for one month (eight sessions total). Using The 
Functional Assessment of Chronic Illness Therapy - Fatigue (FACIT-F) scale, 
they found a significant difference in fatigue between the groups, showing a 
small effect (Cohen's d = 0.12, p < 0.001). 
• 
Cassileth et al. (2003) randomized 62 patients undergoing autologous stem 
cell transplantation (ASCT) into an MT group (N=34) and a standard care 
group (N=28). The MT group received 20-minute sessions of individualized 
live music (vocal and instrumental, based on patient preference) for 3–7 weeks. 
Fatigue, measured by the POMS-Fatigue subscale, decreased significantly in 
the MT group (Cohen's d = 0.21, p = 0.03). 
• 
Reimnitz et al. (2020) randomized 35 leukemia patients to an MT group 
(N=18) or a standard care group (N=17). The MT group received two 
30-minute individual sessions of live music. The Visual Analogue Scale - 
Fatigue (VAS-F) showed a significant difference between groups, 
demonstrating a moderate effect (Cohen's d = 0.78, p = 0.004). 
• 
Miladinia et al. (2021) randomized 104 acute leukemia patients (with pain 
and fatigue scores ≥3) into three groups: light massage (N=34), MT (N=33), 
and standard care (N=37). Interventions were 15 minutes, 3 times/week for 4 
weeks. The MT group listened to self-selected instrumental music via 
headphones. Results showed significant inter-group differences in fatigue for 

both the MT group (vs. standard care) (Cohen's d = 1.95, p = 0.001, large 
effect) and the massage group (vs. standard care) (Cohen's d = 2.42, p = 0.001, 
large effect). Fatigue in both intervention groups decreased progressively, with 
no significant difference between them (p = 0.148). 
Conversely, two studies showed no significant benefit of music therapy on fatigue 
(Bates et al., 2017; Rosenow & Silverman, 2014). 
• 
Rosenow and Silverman (2014) assigned 18 acute leukemia patients to an 
MT group (N=8) or standard care (N=10). The MT group received only one 
30–45 minute session. The Brief Fatigue Inventory (BFI) showed no 
significant difference (p = 0.173). 
• 
Bates et al. (2017) randomized 82 patients (multiple myeloma or lymphoma) 
undergoing ASCT to an MT group (N=37) or standard care (N=45). The MT 
group received two 30-minute sessions (chemo day 1 and day 5). The POMS, 
measured at baseline and day 5, showed no significant difference (p = 0.173). 
According to the literature, the peak of chemotherapy side effects often occurs 
one week after its completion (Chen & Tang, 2020). Therefore, conducting 
assessments on day 1 and day 5 may have occurred before patients reached 
their peak fatigue levels. 
Synthesizing these articles, the dosage (frequency and duration) of the MT 
intervention is a critical consideration. The two studies with non-significant results 
(Bates et al., 2017; Rosenow & Silverman, 2014) had methodological limitations. The 
Rosenow et al. (2014) RCT had a small sample size (N=18) and a low intervention 
dosage (one session), which was likely insufficient. Furthermore, Bates et al. (2017) 
did not set an inclusion criterion for moderate-to-severe baseline fatigue (e.g., ≥4 
points); thus, the enrolled patients may not have had significant fatigue issues at the 
outset. 
 
Literature Summary 
Based on the literature review, CRF is a significant and distressing problem for 
leukemia patients. Due to the disease itself, considerations for hemoglobin, platelets, 
and patient activity safety severely limit the available intervention options for fatigue. 
Music therapy is a non-invasive, safe, comfortable, and easily administered nursing 
intervention. Following appropriate assessment and selection of resonant music based 
on client preferences, it can be implemented by healthcare providers or by the 
patients' families. 
Discrepancies exist between domestic (Taiwanese) and international music therapy 
practices, primarily in education systems, professional certification, legal regulations, 
and cultural factors. Currently, Taiwan lacks a formal certification system for music 

therapists, unlike many other countries. Compounded by financial constraints that 
often preclude hiring therapists with foreign qualifications, the implementation of 
standardized MT is challenging. 
Therefore, this study aims to recruit patients newly diagnosed with leukemia who are 
undergoing conventional chemotherapy. It will utilize music therapy as an 
intervention to investigate its effects on fatigue and clinical laboratory values. 
 
Research Methods 
This chapter is divided into nine sections, detailing the methods and procedures of this 
study. It includes: (1) research framework, (2) research design, (3) research setting 
and participants, (4) sample size, (5) the music therapy protocol, (6) research 
instruments and reliability/validity, (7) research procedures, (8) ethical considerations, 
and (9) data processing and analysis. 
 
Research Framework 
Based on the aforementioned literature review, the research framework for this study 
was developed as illustrated in Figure 3-1. 
The primary purpose of this study is to investigate the effects of music therapy on 
fatigue and clinical laboratory values (e.g., White Blood Cell [WBC] count, 
Hemoglobin [Hb], Albumin) in patients with acute leukemia undergoing 
chemotherapy. The study is designed to provide music therapy to this patient 
population, utilizing fatigue severity and clinical laboratory values as the primary 
outcome variables. This framework will be used to compare the differences in these 
key outcome variables between the music therapy group and the standard care group. 
 
 
Research Design 
This study employs an experimental research design utilizing randomized 
assignment and repeated measures. Participants who consent to the study will be 
allocated to either the experimental group (Group A) or the control group (Group B). 
Group A participants will listen to self-selected music in addition to receiving 
standard care. Group B participants will receive standard care only. The objective is to 
evaluate the effectiveness of music therapy in alleviating fatigue. A total of 44 patients 
with leukemia undergoing their initial chemotherapy will be recruited, with 22 
participants allocated to each group. 
The measurement process will be conducted in two parts: 
1. Primary Data Collection: Data will be collected at two main time points: 
upon admission for initial chemotherapy (Baseline, T0) and on Day 21 of the 

chemotherapy cycle (T1). On Day 21, the researcher will visit the ward to 
collect the required data, including the Tang's Fatigue Scale, the Fatigue 
Numerical Rating Scale (NRS), and clinical laboratory data. If a participant 
has been discharged, data will be collected via telephone interview or an 
online questionnaire. 
2. Symptom Diary: Participants will record their fatigue levels using the Fatigue 
NRS immediately following each music therapy session. 
Baseline demographic data will be collected only at T0. The measurement time points 
and the application of corresponding instruments are detailed in Table 3-2. 
Table 1: Schedule of Research Measurements 
Time 
Before Chemo 
(T0) 
Chemo 
Day 7 
Chemo Day 
14 
Chemo Day 21 
(T1) 
Tang's Fatigue Scale 
○ 
 
 
○ 
Numerical Rating Scale 
(NRS) 
○ 
○ 
○ 
○ 
WBC 
○ 
 
 
○ 
Hemoglobin 
○ 
 
 
○ 
Albumin 
○ 
 
 
○ 
Demographic Data 
○ 
 
 
 
Note: ○ = Data to be collected 
 
 Research Setting and Participants 
This study will be conducted in the hematology-oncology ward of a medical center 
located in Northern Taiwan. Participants must meet the following inclusion criteria: 
1. Clinically diagnosed with Acute Myeloid Leukemia (AML) by a specialist 
physician. 
2. Scheduled to receive initial (first-time) chemotherapy. 
3. Aged 20 years or older. 
4. Able to communicate in Mandarin or Taiwanese. 
5. Possess normal hearing ability. 
6. No history of psychiatric illness and clear consciousness. 
7. No prior participation in any fatigue management intervention study. 
8. Understands the research purpose, voluntarily agrees to participate, and has 
signed the informed consent form. 
9. Willing to cooperate with all study procedures during the research period. 
Participants will be excluded from the study if they meet the following criteria: 
1. Severe hearing impairment. 

2. Unstable vital signs or unclear consciousness. 
 
 III: Sample Size Calculation 
The sample size was estimated based on the Generalized Estimating Equations 
(GEE) approach for repeated measures. The analysis will control for baseline 
demographic and disease characteristics as covariates (e.g., age, sex, education level, 
occupation, perceived economic status, marital status, religious beliefs, and 
metastasis). The dependent variables are fatigue, White Blood Cell (WBC) count, 
hemoglobin, and albumin. 
The calculation was performed using G*Power software (version 3.1.9.7). Parameters 
were set as follows: a significance level (α) of 0.05, statistical power (1-β) of 0.80, a 
95% confidence interval, and an anticipated effect size of 0.21. This calculation 
yielded a required sample size of 34 participants (as shown in Figure 3-2). To account 
for a potential attrition rate of 30%, the study aims to recruit a total of 44 participants 
(n=22 for Group A, n=22 for Group B). 
 
Music Therapy Protocol 
1. Music Selection, Dosage, and Headphone Use 
According to the literature, a music therapy duration of 15–30 minutes is effective for 
fatigue alleviation (Burns et al., 2008; Cassileth et al., 2003; Miladinia et al., 2021; 
Reimnitz et al., 2020; Sezgı̇n & Bektas, 2022). Music selection will be based on 
individual preferences and cultural background (Tsai & Chou, 2015; Browning, 2000; 
Gerdner, 2000). 
To ensure data integrity while considering the patient's length of stay, physical burden 
during chemotherapy, and protocol adherence, the music therapy intervention in this 
study will be administered once daily for 21 consecutive days. The 30-minute 
intervention will commence at the start of the chemotherapy infusion. During the 
study, participants will be provided with a chemotherapy symptom tracking diary to 
confirm adherence to the music therapy protocol in the experimental group. 
For reasons of personal hygiene, preference, and potential patient discharge, 
participants will be asked to use their own headphones. If a participant does not have 
headphones, a set will be provided by the researcher. 
 
Research Instruments and Psychometric Properties 
1. Participant Demographic Data Sheet Data will be collected using Google Forms 
or paper questionnaires, as appropriate. This sheet includes demographic information 
such as age, sex, education level, occupation, perceived economic status, marital 
status, and religious beliefs, to be completed by the participant. The questionnaire also 

includes items regarding the participant's prior musical training, frequency of daily 
music listening, motivations for listening, typical timing and methods of listening, and 
preferred activities during rest. 
2. Leukemia-Related Treatment Data Sheet This data will be extracted from the 
patient's medical records by the researcher. It includes information on chemotherapy 
drugs and dosages, as well as laboratory values—specifically Absolute Neutrophil 
Count (ANC), Hemoglobin (Hb), and Albumin—from before chemotherapy (T0) and 
on Day 21 (T1). 
3. Tang Fatigue Rating Scale (TFRS) While many reliable and valid fatigue scales 
exist globally, many have limitations. Considering that fatigue assessment should 
encompass physical, psychological, and activity dimensions, the TFRS was selected 
as the primary outcome measure for this study. 
The TFRS contains 37 items across three subscales: Physical (15 items), Psychosocial 
(12 items), and Daily-Living (10 items). It uses a 10-point rating scale, where higher 
scores indicate greater fatigue severity. The TFRS underwent content validity testing 
by three PhD-level experts in fatigue theory and psychometrics. It was validated in a 
sample of 107 patients with chronic heart failure. The internal consistency 
(Cronbach's α) was 0.96 for the total scale, and 0.83 (Physical), 0.92 (Psychosocial), 
and 0.97 (Daily-Living) for the subscales. The TFRS demonstrated excellent validity: 
convergent validity with the Visual Analogue Scale for Fatigue (VAS-F) was 0.87, 
and construct validity with The Beck Depression Inventory-Second Edition (BDI-II) 
was 0.77 (Tang et al., 2010). 
In the study by Tang et al. (2010), the TFRS also showed a significant positive 
correlation with the New York Heart Association (NYHA) functional class (r = 0.75, p 
< 0.01) and significant negative correlations with Ejection Fraction (EF) (r = -0.46, p 
< 0.01) and Hemoglobin (Hb) (r = -0.27, p < 0.01) (Tang et al., 2010). 
4. G-8 Geriatric Screening Tool (G-8) The G-8 consists of 8 items, including three 
related to nutritional status (Item A: food intake, Item B: weight loss, Item F: Body 
Mass Index), motor skills (Item C), psychological status (Item E), number of 
medications (Item H), and self-perception of health (Item P). 
Bellera et al. (2012), in a study of 364 cancer patients aged >70 receiving 
chemotherapy, found that a G-8 cut-off value of 14 had good sensitivity (85%) and 
specificity (65%) for vulnerability. In 2022, Chen et al. studied 755 newly diagnosed 
cancer patients in Taiwan (aged >20) and found a cut-off value of ≤13 was more 
suitable for screening vulnerability in both elderly and non-elderly Taiwanese cancer 
patients (Sensitivity=68.4%, Negative Predictive Value=76.8%). They recommended 
stratifying patients by age (<65 and ≥65) to differentiate the effect of age on 
vulnerability (Chen et al., 2022). 

5. Numeric Rating Scale (NRS) for Fatigue This is an 11-point Likert-type scale 
(0–10) that serves as a simple and convenient single-item tool for assessing subjective 
fatigue (Gladman et al., 2020; Nordin et al., 2016; Whitehead, 2009). A score of 0 
indicates "no fatigue at all," and 10 indicates "the worst fatigue imaginable," with 
higher scores representing greater fatigue severity. Numerous studies have 
demonstrated that the fatigue NRS possesses good construct validity when correlated 
with other internationally recognized psychological and fatigue assessment tools, such 
as the Profile of Mood States (POMS), Visual Analogue Scale - Fatigue (VAS-F), 
Medical Outcomes Study Short Form-20 (MOS SF-20), and Functional Assessment of 
Cancer Therapy–Anemia (FACT-An) (Aaronson et al., 1999; de Boer et al., 2004; 
Gladman et al., 2020; Kirsh et al., 2001; Lee et al., 1991; Van Hooff et al., 2007; 
Youngblut & Casper, 1993). 
 
Research Procedures 
Prior to study commencement, approval will be obtained from the Institutional 
Review Board (IRB). Following IRB approval, and after explaining the study to and 
receiving consent from the attending physicians and ward nursing staff, the researcher 
will conduct participant recruitment in the inpatient wards and outpatient clinics. 
Individuals who meet the inclusion criteria will be identified as potential participants. 
The researcher will explain the study's purpose and methodology to these individuals. 
After obtaining informed consent and a signed consent form, the researcher will 
administer the pre-test (T0) questionnaires. This packet includes the Demographic 
Data Sheet, the Tang Fatigue Rating Scale (TFRS), the G-8 screening tool, and the 
symptom diary. This self-administration process is expected to take approximately 10 
minutes. If a participant is unable or unwilling to self-report (e.g., due to advanced 
age or fatigue), the researcher will conduct a structured interview to complete the 
questionnaires, which is estimated to take 30–40 minutes. Concurrently, all 
participants will be invited to join the study's official LINE group for communication. 
Following the collection of baseline questionnaires, a computer-generated 
randomization sequence will be implemented by personnel not directly involved in 
the study (i.e., someone other than the principal investigator) to allocate participants 
to either the experimental group (Group A) or the control group (Group B). 
Participants in Group A, after confirming their chemotherapy infusion line is properly 
connected, will begin listening to 30 minutes of self-selected music while 
concurrently receiving standard care. Participants in Group B will receive standard 
care only. A total of 60 participants with Acute Myeloid Leukemia (AML) 
undergoing chemotherapy are expected to be recruited (n=30 per group). 
Both groups will be required to complete the symptom diary throughout the 21-day 

study period (est. 1 minute per entry). Group A will complete the Fatigue Numerical 
Rating Scale (NRS) immediately following each music therapy session. Group B will 
complete the Fatigue NRS 30 minutes after the commencement of their chemotherapy 
infusion. 
On Day 21 (T1), the researcher will collect the post-test data (TFRS, NRS, and G-8) 
in the ward. If a participant has been discharged, data will be collected via telephone 
interview or an online questionnaire. 
The laboratory data required for this study (WBC, Hb, Albumin) will be obtained by 
the researcher through a medical record review. Data from blood samples drawn as 
part of standard clinical care, taken before chemotherapy (T0) and on Day 21 (±3 
days) (T1), will be utilized. No additional blood draws will be required for this 
study. 
Throughout the study period, participants may ask questions at any time via the 
official LINE group, and the researcher will provide responses. 
 
Ethical Considerations 
This study will be initiated only after obtaining approval from the Institutional 
Review Board (IRB) and securing consent from the nursing administrators and 
attending physicians of the recruitment site. Prior to formal enrollment, the researcher 
will personally explain the study's purpose, procedures, and methodology to each 
potential participant. 
The researcher will address all participant inquiries. Participants will be explicitly 
informed that their participation is voluntary, that they may withdraw from the study 
at any time without penalty, and that their decision will not affect the quality of their 
medical treatment or nursing care in any way. 
All research data collected from participants will be processed using anonymous 
coding. The data will be securely stored by the researcher and used exclusively for 
academic purposes. Confidentiality will be strictly maintained, and data will not be 
publicly disclosed or used for other purposes, ensuring the protection of participant 
privacy. 
 
Data Processing and Statistical Analysis 
1. Data Management The researcher will review all questionnaires for completeness. 
All collected data will be coded and entered into the Statistical Packages for the 
Social Sciences (SPSS) version 26.0 for data processing and management. 
2. Statistical Analysis In accordance with the study's objectives, data analysis will be 
divided into descriptive and inferential statistics, as outlined in Table 3-3. 
• 
a. Descriptive Statistics: Based on the characteristics of the variables, data 

will be categorized into four measurement scales: nominal, ordinal, interval, 
and ratio (Kaur et al., 2018). Nominal and ordinal scale data are considered 
categorical variables (e.g., sex, education level, occupation, perceived 
economic status, marital status, religious beliefs, and chemotherapy drug 
names) and will be presented as frequencies (n) and percentages (%). Interval 
and ratio scale data are considered continuous variables (e.g., age, fatigue 
severity, Absolute Neutrophil Count [ANC], hemoglobin, and albumin) and 
will be presented using means, standard deviations (SD), and ranges 
(minimum and maximum) (Kaur et al., 2018). 
• 
b. Inferential Statistics: This study utilizes an experimental design with 
longitudinal follow-up and repeated measures, analyzed on an 
intention-to-treat (ITT) basis. It will compare the differences in fatigue 
severity and clinical laboratory values between the music therapy and control 
groups. During the study, data attrition may occur due to factors such as 
disease progression or a participant's personal decision to withdraw, leading to 
unequal sample sizes at different measurement points. Therefore, this study 
will employ Generalized Estimating Equations (GEE) to analyze the 
relationship between the independent and dependent variables. GEE will be 
used to compare pre- and post-test values (fatigue severity, Absolute 
Neutrophil Count [ANC], hemoglobin, and albumin) between the 
experimental and control groups. A p-value of < 0.05 will be considered the 
standard for statistical significance (Ziegler & Vens, 2010).