ABSTRACT
Background and Aims
Wet cupping, or Hijama, is commonly used by athletes for recovery, yet evidence regarding its relationship with sleep quality remains limited. This study examined cupping use, perceived benefits, adverse effects, and factors associated with self‐reported sleep quality among Palestinian athletes.
Methods
A cross‐sectional survey was conducted among Palestinian athletes. Of 754 athletes screened at nine sports clubs and training centers across the West Bank, 470 (62.3%) reported previous wet‐cupping use; 468 had sufficient primary‐outcome data and were analyzed. Data were collected using a structured paper‐based questionnaire incorporating the Pittsburgh Sleep Quality Index. Analyses included descriptive statistics, exact and chi‐square tests, Spearman correlations, multiple linear regression, and path analysis.
Results
Improved mobility (30.8%), reduced muscle cramps (25.6%), enhanced immunity (16.2%), and increased endurance (9.0%) were the most frequently reported intended benefits. Cupping was commonly reported for chronic or recurrent conditions (99.6%), muscle strain (41.5%), and headaches (41.2%). Higher BMI and greater cupping‐session frequency were associated with greater perceived cupping benefit (p = 0.010 and p < 0.001, respectively). Reported inflammation was associated with BMI category, gender, and competition level, while mild pain was associated with BMI category and competition level. Lower PSQI scores were associated with higher BMI, greater cupping‐session frequency, and greater perceived cupping benefit. In the multivariable model, higher BMI, vitamin use, greater cupping‐session frequency, greater perceived benefit, and manual rather than automated suction were independently associated with lower PSQI scores. The model explained 35.2% of the variance in sleep quality.
Conclusion
Cupping‐related practices and participant characteristics were associated with sleep quality. More frequent sessions, vitamin use, manual suction, higher BMI, and greater perceived benefit were associated with better sleep quality. These findings do not establish causality. Prospective studies are needed before cupping can be recommended to improve sleep or recovery.
Keywords: athletes, cupping; Hijama; physical activity; sleep; sport; traditional medicine
1. Introduction
Cupping therapy is an ancient alternative medicine practice that creates negative pressure on the skin using suction or heat [1]. With roots in ancient Egyptian medicine, it has been prevalent in various healing systems, including Chinese, Korean, Unani, and Arabic traditions. Notable Muslim physicians such as Al‐Zahrawi, Bakr Al‐Razi, and Ibn Sina endorsed this practice [2, 3].
Cupping is primarily classified into two types: dry and wet cupping. Dry cupping involves placing cups on the skin to create suction, enhancing circulation and activating the lymphatic system [4]. Wet cupping, on the other hand, includes minor skin incisions before applying suction to extract blood and extracellular fluid [4]. A typical wet cupping session lasts about 20 min and includes steps such as sanitizing the area, applying cups, making incisions, and disinfecting afterward [5]. Hijama, a variant of wet cupping, involves an additional round of cupping post‐scarification [5].
Several studies have reported potential effects of cupping therapy. For instance, Furhad et al. (2024) found that cupping improves blood circulation by increasing capillary filtration, which facilitates healing. It has also shown effectiveness in treating non‐specific pain in areas such as the neck, back, and shoulders [6]. Another study indicated that cupping's analgesic effects are comparable to acetaminophen, effectively reducing pain and swelling [7]. Al‐ Aleyeidi et al. (2015) noted that cupping could lower high blood pressure for weeks without significant side effects [8]. Furthermore, cupping has been reported to alleviate respiratory symptoms, improve skin conditions, and modulate immune responses [6].
Wet cupping may also enhance sleep quality by alleviating pain through the redistribution of inflammatory mediators [9]. This therapy has resulted in improved quality of life and reduced fatigue in patients with fibromyalgia syndrome. Wang et al. (2023) highlighted its potential in managing chronic pain conditions, which may indirectly benefit sleep quality, although evidence quality varies [10].
Despite these benefits, adverse events associated with cupping have been reported, including anemia and skin infections [11, 12, 13]. Cupping therapy must be administered by licensed professionals adhering to safety protocols. Future clinical trials should focus on documenting adverse events to better assess potential risks [11]. However, there is a lack of studies addressing the side effects of cupping therapy globally [14].
Athletes, who prioritize performance and recovery, increasingly use cupping therapy as a complementary recovery approach [4, 7]. Sleep quality is particularly vital for athletes, as it significantly impacts physical and cognitive functions essential for performance [15, 16]. Despite awareness, athletes often face sleep deprivation during intense training, which can adversely affect their health and performance [17]. Therefore, investigating alternative therapies like cupping is essential for athletes' comprehensive care.
A search in PubMed using the terms (“athlete”[Title/Abstract] OR “sport”[Title/Abstract]) AND (“cupping”[Title/Abstract] OR “Hijama”[Title/Abstract]) identified a limited body of literature examining cupping therapy in athletic populations [7, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]. Only one study conducted in Palestine focused on pain‐relief practices among student‐athletes and reported cupping use but did not examine athletes' cupping experiences in relation to sleep quality [21].
To address these gaps, this study aimed to characterize wet cupping/Hijama‐related experiences and identify demographic, health‐related, training, and cupping‐related factors associated with self‐reported sleep quality among Palestinian athletes.
The conceptual model summarizes hypothesized associations between sleep quality and health, demographic, training, and cupping‐related variables. Higher BMI, cupping‐session frequency, vitamin use, age, and perceived cupping benefit were specified as variables that might be associated with sleep quality or perceived benefit; the model was not intended to imply causal effects. See Figure 1.
Figure 1.
Conceptual model of factors hypothesized to be associated with sleep quality among Palestinian athletes.
2. Methods
2.1. Study Design
This cross‐sectional survey incorporated retrospective assessment of wet‐cupping/Hijama exposure during the preceding 3 years aiming to investigate the relationship between cupping‐therapy variables, sociodemographic factors, health indicators, training variables, and sleep quality among Palestinian athletes. The study followed the STROBE checklist [32] to support transparent reporting of the design, participants, variables, statistical methods, results, and limitations.
2.2. Sampling, Participants, and Setting
Using Stephen Thompson's formula [33], the minimum required sample size was calculated as 375 participants. The calculation assumed a 95% confidence level, a 5% margin of error, and an expected proportion of 50% to provide the most conservative sample size estimate. The Palestinian population size was used as the reference population in the calculation. A total of 754 Palestinian athletes were screened through convenience sampling at nine sports clubs and training centers across the West Bank. Of these, 470 athletes (62.3%) reported having undergone wet cupping, or Hijama, within the preceding 3 years. Two questionnaires were excluded because primary outcome data were insufficient, resulting in a final analytical sample of 468 participants. The achieved sample exceeded the calculated minimum of 375. Eligible participants were Palestinian athletes aged 18 years or older, engaged in any type of sport regardless of competition level, and who had received wet cupping/Hijama within the preceding 3 years. Data were collected between January and August 2024.
2.3. Data Collection Instrument and Variables
Data on cupping therapy were collected using a structured questionnaire informed by previous studies [7, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31] to assess participants' sociodemographic characteristics, health‐related factors, athletic training characteristics, and experiences with cupping therapy. To establish face and content validity, the study‐specific items were reviewed by an advisory panel comprising a complementary medicine specialist, a pharmacist, and a sports expert.
The independent variables included demographic characteristics (age, gender, height, place of residence, and monthly income), health‐related factors (chronic diseases, vitamin use, and smoking status), athletic training characteristics (training frequency and competition level), and cupping‐related characteristics, including previous use, session frequency, type of cup and suction, session duration, perceived benefits, and reported adverse effects. Perceived cupping benefit was assessed using a study‐specific single item rated on a five‐point Likert scale from 1 (not beneficial) to 5 (extremely beneficial). The item was reviewed by the expert panel and evaluated for clarity during pilot testing.
Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), originally developed by Buysse et al. and subsequently translated and validated in Arabic [34, 35]. The PSQI evaluates subjective sleep quality over the preceding month using 19 self‐rated items combined into seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. Each component is scored from 0 to 3, producing a global score from 0 to 21, with lower scores indicating better sleep quality. A global score greater than 5 was classified as poor sleep quality; psychometric evidence for use of the PSQI in student populations has also been reported [36].
The questionnaire was subsequently pilot‐tested among 20 athletes before the main data collection to assess clarity, relevance, comprehensibility, and feasibility. No modifications were considered necessary following the pilot. The PSQI section demonstrated good internal consistency, with a Cronbach's alpha of 0.801.
2.4. Procedure
Athletes were recruited from nine sports clubs and training centers across the West Bank. Prior to participation, informed consent was obtained from each athlete. A structured paper‐based questionnaire containing the validated Arabic PSQI and study‐specific items reviewed for face and content validity was administered in person. No publicly distributed electronic questionnaire was used.
2.5. Data Analysis
Data were analyzed using IBM SPSS Statistics version 21.0, with path analysis performed in IBM AMOS version 23.0. Descriptive statistics summarized participant characteristics and cupping‐related experiences. Categorical associations were assessed using Pearson's Chi‐square test or the Fisher–Freeman–Halton exact test when expected cell counts were small. Spearman rank correlation was used to examine associations between continuous or ordinal variables, perceived cupping benefit, and global PSQI scores. Rank‐based methods were used for bivariate PSQI analyses because the marginal PSQI distribution was non‐normal. Marginal non‐normality of the raw outcome did not by itself preclude multiple linear regression because regression assumptions concern the conditional model and its residuals rather than requiring a normally distributed raw outcome.
Variables for multivariable analysis were selected a priori based on the conceptual framework and clinical relevance rather than bivariate statistical significance alone. Multiple linear regression and path analysis were conducted using complete cases (N = 421); 47 participants with missing data for one or more model variables were excluded. The global PSQI score was the primary sleep outcome, while perceived benefit and individual adverse effects were examined as exploratory outcomes. The path analysis was exploratory and used observed variables. All candidate variables represented in the conceptual framework were entered into the initial AMOS model. The model was then iteratively refined by removing noncontributing variables or paths while reviewing AMOS modification indices, standardized path estimates, theoretical plausibility, and overall model‐fit statistics. This process continued until the parsimonious final model was obtained. Because model specification was refined using the same cross‐sectional dataset, the final path model was treated as data‐informed and exploratory rather than prespecified or confirmatory, and its coefficients were interpreted as associations rather than causal effects. The final model retained direct paths from cupping‐session frequency, vitamin use, perceived cupping benefit, and suction type to the global PSQI score.
Categorical analyses were reported using χ 2 or exact p values with corresponding effect sizes. Spearman correlations were presented as ρ with 95% confidence intervals. Regression estimates were reported as unstandardized coefficients (B), standardized coefficients (β), 95% confidence intervals, t statistics, and p values, with model performance summarized by R2, adjusted R2, and the overall F test. Path‐model fit was evaluated using the Chi‐square/degrees‐of‐freedom ratio (CMIN/DF), comparative fit index (CFI), Tucker–Lewis index (TLI), standardized root mean square residual (SRMR), and root mean square error of approximation (RMSEA). Given the exploratory nature of the model, fit indices were interpreted collectively rather than using a single index as the sole criterion of model adequacy. A complete set of residual and multicollinearity diagnostic statistics was not available in the retained analysis output used for this revision; therefore, these diagnostics are not reported, and the adjusted findings are interpreted cautiously. Statistical reporting followed the SAMPL guidance and the recommendations of Assel et al. [37, 38]. All tests were two‐sided, with statistical significance set at p < 0.05.
Two questionnaires were excluded due to missing primary outcome data, resulting in a descriptive analytical sample of 468 participants. Of these, 421 participants had complete data across all multivariable predictor variables and were included in the multiple linear regression and path analyses. Bivariate analyses and descriptive statistics utilized all available pairwise data for each variable (N = 468).
2.6. Ethical Considerations
This study received approval from the Institutional Review Board (IRB) of An‐Najah National University (Serial No.: Ph.T Jan.2023.7). Gatekeeper permissions were obtained from sports club officials and training centers. Athletes were contacted through these officials to ensure proper access to participants. Club officials facilitated access to eligible athletes. Participants received study information and provided informed consent before completing the questionnaire in compliance with the Declaration of Helsinki.
3. Results
3.1. Preliminary Analysis
A total of 754 athletes were screened. Of these, 470 (62.3%) reported previous wet‐cupping/Hijama use, and 468 had sufficient primary‐outcome data and were included in the analyses. The global PSQI score ranged from 0 to 21, with higher scores indicating poorer sleep quality. The mean global PSQI score was 9.05 ± 3.63, with a median of 9.0 (IQR: 6.0–12.0). The distribution of PSQI scores deviated significantly from normality (Shapiro–Wilk test, p < 0.001); therefore, non‐parametric methods were used for bivariate analyses.
3.2. Descriptive Statistics
Among the 468 athletes, 64.5% were student athletes and 35.5% were professional athletes, while 80.3% were male. Normal BMI was reported for 58.3% of the total sample, followed by overweight in 29.9%, obesity in 3.8%, and underweight in 0.6%; BMI data were missing for 7.3% of participants. Football was the most frequently reported sport (63.9%). Stimulant use was reported by 10.3% of participants, vitamin use by 36.1%, smoking by 20.9%, and chronic disease by 6.6%. See Table 1.
Table 1.
Sociodemographic, athletic‐training, and health characteristics of participants (N = 468).
| Variable | Category | N | % |
|---|---|---|---|
| BMI category | Underweight | 3 | 0.6 |
| Normal | 273 | 58.3 | |
| Overweight | 140 | 29.9 | |
| Obese | 18 | 3.8 | |
| Missing | 34 | 7.3 | |
| Gender | Female | 92 | 19.7 |
| Male | 376 | 80.3 | |
| Level of competition | Student | 302 | 64.5 |
| Professional | 166 | 35.5 | |
| Type of sportm | Gymnastics | 3 | 0.6 |
| Track and field | 8 | 1.7 | |
| Combat sports | 8 | 1.7 | |
| Tennis | 59 | 12.6 | |
| Team sports – Volleyball | 26 | 5.6 | |
| Team sports – Handball | 10 | 2.1 | |
| Team sports – Basketball | 40 | 8.5 | |
| Team sports – Football | 299 | 63.9 | |
| Water sports | 35 | 7.5 | |
| Stimulant use | Yes | 48 | 10.3 |
| Vitamin use | Yes | 169 | 36.1 |
| Smoking | Yes | 98 | 20.9 |
| Chronic disease | Yes | 31 | 6.6 |
Note: m, Multiple‐response variable. Percentages were calculated using the total study sample as the denominator.
Among the 468 included cupping users, the most frequently reported intended benefits were improved mobility (30.8%), reduced muscle cramps (25.6%), enhanced immunity (16.2%), and increased endurance (9.0%). Cupping was commonly reported for chronic or recurrent conditions (99.6%), muscle strain (41.5%), and headaches (41.2%). Glass cups were the most commonly used type (54.5%), and automated suction pumps were reported more frequently than manual pumps (67.7% vs 28.8%). Most sessions lasted less than 5 min (74.8%). The most commonly reported adverse effects were skin inflammation or related skin changes (70.3%) and mild pain (68.4%). Most reported side‐effect outcomes resolved rapidly and naturally (72.6%), while 0.9% required medical intervention. See Table 2.
Table 2.
Wet cupping/Hijama therapy characteristics and reported outcomes (N = 468).
| Variable | Category | N (%) |
|---|---|---|
| Why cupping rather than medication? a | Cupping is safer | 174 (37.2) |
| Disbelief in medications | 102 (21.8) | |
| Sufficient experience and knowledge of cupping | 50 (10.7) | |
| Other reasons | 21 (4.5) | |
| Intended outcomesa | Reduces cramps | 120 (25.6) |
| Improves mobility | 144 (30.8) | |
| Increases endurance | 42 (9.0) | |
| Boosts immunity | 76 (16.2) | |
| Other benefits | 36 (7.7) | |
| Type of conditiona | Acute sports injuries | 85 (18.2) |
| Semi‐acute sports injuries | 91 (19.4) | |
| Headaches | 193 (41.2) | |
| Muscle strain | 194 (41.5) | |
| Chronic or recurrent conditions | 466 (99.6) | |
| Side effectsa | Skin inflammation, erythema, discoloration, edema, or bruising | 329 (70.3) |
| Burning | 12 (2.6) | |
| Mild pain | 320 (68.4) | |
| Moderate pain | 55 (11.8) | |
| Severe pain | 4 (0.9) | |
| Headache | 106 (22.6) | |
| Nausea | 106 (22.6) | |
| Dizziness | 1 (0.2) | |
| Fatigue | 3 (0.6) | |
| Itching | 68 (14.5) | |
| Fainting | 5 (1.1) | |
| Insomnia | 7 (1.5) | |
| Sweating | 22 (4.7) | |
| Skin infection | 8 (1.7) | |
| Side‐effect outcome | Resolved rapidly and naturally | 340 (72.6) |
| Required medical intervention | 4 (0.9) | |
| Cup type | Plastic | 162 (34.6) |
| Glass | 255 (54.5) | |
| Metal | 39 (8.3) | |
| Missing | 12 (2.6) | |
| Suction type | Manual pump | 135 (28.8) |
| Automated suction pump | 317 (67.7) | |
| Missing | 16 (3.4) | |
| Session duration | < 5 min | 350 (74.8) |
| 5–10 min | 94 (20.1) | |
| > 10 min | 11 (2.4) | |
| Missing | 13 (2.8) | |
| Cupping‐session frequency | 1 | 191 (40.8) |
| 2 | 136 (29.1) | |
| 3 | 69 (14.7) | |
| 4 | 17 (3.6) | |
| 5 | 38 (8.1) | |
| 6 | 7 (1.5) | |
| Missing | 10 (2.1) |
Multiple‐response variable. Percentages were calculated using the total study sample as the denominator.
3.3. Associations Between Participant Characteristics and Selected Adverse Effects
BMI category was significantly associated with both reported inflammation (Fisher–Freeman–Halton exact p < 0.001, Cramér's V = 0.204) and mild pain (exact p = 0.001, Cramér's V = 0.186). Inflammation was reported more frequently among male than female athletes (72.9% vs 59.8%, χ2(1) = 6.066, p = 0.014, φ = 0.114) and among professional compared with student athletes (83.7% vs 62.9%, χ2(1) = 22.241, p < 0.001, φ = 0.218). Stimulant use and chronic disease were not significantly associated with inflammation. Mild pain was reported more frequently among professional than student athletes (78.9% vs 62.6%, χ2(1) = 13.215, p< 0.001, φ = 0.168). No significant associations were observed between mild pain and gender, stimulant use, or chronic disease. See Table 3.
Table 3.
Associations of inflammation and mild pain with sociodemographic and health characteristics.
| Outcome | Predictor | Category | Yes, n (%) | No, n (%) | Test statistic | Effect size | p |
|---|---|---|---|---|---|---|---|
| Inflammation | BMI category | Underweight | 1 (33.3) | 2 (66.7) | Fisher–Freeman–Halton exact | V = 0.204 | < 0.001 |
| Normal | 180 (65.9) | 93 (34.1) | |||||
| Overweight | 116 (82.9) | 24 (17.1) | |||||
| Obese | 16 (88.9) | 2 (11.1) | |||||
| Missing† | 16 (47.1) | 18 (52.9) | Excluded from BMI test | ||||
| Gender | Female | 55 (59.8) | 37 (40.2) | χ2(1) = 6.066 | φ = 0.114 | 0.014 | |
| Male | 274 (72.9) | 102 (27.1) | |||||
| Stimulant use | Yes | 35 (72.9) | 13 (27.1) | χ2(1) = 0.176 | φ = 0.019 | 0.675 | |
| No | 294 (70.0) | 126 (30.0) | |||||
| Competition level | Student | 190 (62.9) | 112 (37.1) | χ2(1) = 22.241 | φ = 0.218 | < 0.001 | |
| Professional | 139 (83.7) | 27 (16.3) | |||||
| Chronic disease | Yes | 20 (64.5) | 11 (35.5) | χ2(1) = 0.532 | φ = 0.034 | 0.466 | |
| No | 309 (70.7) | 128 (29.3) | |||||
| Mild pain | BMI category | Underweight | 1 (33.3) | 2 (66.7) | Fisher–Freeman–Halton exact | V = 0.186 | 0.001 |
| Normal | 174 (63.7) | 99 (36.3) | |||||
| Overweight | 112 (80.0) | 28 (20.0) | |||||
| Obese | 15 (83.3) | 3 (16.7) | |||||
| Missing† | 18 (52.9) | 16 (47.1) | Excluded from BMI test | ||||
| Gender | Female | 62 (67.4) | 30 (32.6) | χ2(1) = 0.051 | φ = 0.010 | 0.821 | |
| Male | 258 (68.6) | 118 (31.4) | |||||
| Stimulant use | Yes | 32 (66.7) | 16 (33.3) | χ2(1) = 0.072 | φ = 0.012 | 0.788 | |
| No | 288 (68.6) | 132 (31.4) | |||||
| Competition level | Student | 189 (62.6) | 113 (37.4) | χ2(1) = 13.215 | φ = 0.168 | < 0.001 | |
| Professional | 131 (78.9) | 35 (21.1) | |||||
| Chronic disease | Yes | 20 (64.5) | 11 (35.5) | χ2(1) = 0.229 | φ = 0.022 | 0.632 | |
| No | 300 (68.6) | 137 (31.4) |
Note: Percentages are row percentages: φ, phi coefficient; V, Cramér's V.
3.4. Correlates of Sleep Quality and Perceived Cupping Benefit
Higher BMI and greater cupping‐session frequency were significantly associated with greater perceived cupping benefit (ρ = 0.119, p = 0.010 and ρ = 0.280, p < 0.001, respectively). Lower PSQI scores, indicating better sleep quality, were significantly associated with higher BMI (ρ = −0.140, p = 0.002), higher personal income (ρ = −0.100, p = 0.031), greater sporting experience (ρ = −0.110, p = 0.017), greater cupping‐session frequency (ρ = −0.220, p < 0.001), and greater perceived cupping benefit (ρ = −0.250, p < 0.001). See Table 4.
Table 4.
Spearman correlations with overall sleep quality and perceived cupping benefit.
| Variable | Relationship with PSQI score (ρ) | 95% CI | p‐value | Relationship with perceived cupping benefit (ρ) | 95% CI | p‐value |
|---|---|---|---|---|---|---|
| Age | −0.080 | −0.169 to 0.011 | 0.084 | 0.020 | −0.071 to 0.110 | 0.666 |
| BMI | −0.140 | −0.228 to −0.050 | 0.002 | 0.119 | 0.029 to 0.207 | 0.010 |
| Monthly personal income | −0.100 | −0.189 to −0.009 | 0.031 | 0.080 | −0.011 to 0.169 | 0.084 |
| Years of sporting experience | −0.110 | −0.199 to −0.020 | 0.017 | 0.100 | 0.009 to 0.189 | 0.031 |
| Training frequency per week | −0.080 | −0.169 to 0.011 | 0.084 | 0.090 | −0.001 to 0.179 | 0.052 |
| Cupping‐session frequency | −0.220 | −0.305 to −0.132 | < 0.001 | 0.280 | 0.194 to 0.361 | < 0.001 |
| Perceived cupping benefit | −0.250 | −0.333 to −0.163 | < 0.001 | — | — | — |
Note: ρ, Spearman's rank correlation coefficient; CI, confidence interval. Confidence intervals were estimated using Fisher's z transformation.
3.5. Multivariable Predictors of Sleep Quality
The regression model was statistically significant, F(13,407) = 17.007, p < 0.001, and explained 35.2% of the variance in global PSQI score (R2 = 0.352; adjusted R2 = 0.331). Higher BMI (β = −0.150, p = 0.010), vitamin use (β = −0.300, p < 0.001), greater cupping‐session frequency (β = −0.280, p < 0.001), and greater perceived cupping benefit (β = −0.180, p = 0.001) were independently associated with lower PSQI scores. Automated rather than manual suction was associated with higher PSQI scores (β = 0.190, p = 0.002), indicating poorer sleep quality. Age, stimulant use, smoking, training frequency, cup type, session duration, and number of adverse effects were not independently associated with PSQI score. See Table 5.
Table 5.
Multiple linear regression predictors of global PSQI score.
| Predictor | B | Standardized β | 95% CI for B | t | p |
|---|---|---|---|---|---|
| Age | −0.012 | −0.080 | −0.028 to 0.004 | −1.470 | 0.142 |
| BMI | −0.050 | −0.150 | −0.088 to −0.012 | −2.579 | 0.010 |
| Stimulant use | 0.220 | 0.050 | −0.330 to 0.770 | 0.784 | 0.433 |
| Vitamin use | −0.627 | −0.300 | −0.900 to −0.354 | −4.502 | < 0.001 |
| Smoking | 0.140 | 0.060 | −0.190 to 0.470 | 0.832 | 0.406 |
| Training frequency/week | −0.050 | −0.060 | −0.140 to 0.040 | −1.089 | 0.277 |
| Cupping‐session frequency | −0.145 | −0.280 | −0.202 to −0.088 | −4.986 | < 0.001 |
| Perceived cupping benefit | −0.235 | −0.180 | −0.374 to −0.096 | −3.314 | 0.001 |
| Plastic vs glass cup | 0.044 | 0.020 | −0.310 to 0.398 | 0.244 | 0.808 |
| Metal vs glass cup | 0.025 | 0.010 | −0.365 to 0.415 | 0.126 | 0.900 |
| Automated vs manual suction | 0.410 | 0.190 | 0.153 to 0.667 | 3.127 | 0.002 |
| Session time 5–10 vs < 5 min | 0.121 | 0.060 | −0.164 to 0.406 | 0.832 | 0.406 |
| Number of adverse effects | −0.030 | −0.030 | −0.170 to 0.110 | −0.420 | 0.675 |
Note: Complete‐case analysis was based on N = 421 participants. The overall regression model was statistically significant, F (13, 407) = 17.007, p < 0.001, with R2 = 0.352 and adjusted R2 = 0.331. B, unstandardized regression coefficient; β, standardized regression coefficient; CI, confidence interval. Reference categories were glass cup for cup type, manual suction for suction type, and session duration < 5 min for session time.
3.6. Path Analysis
Path analysis indicated that greater cupping‐session frequency (β = −0.14), vitamin use (β = −0.41), and greater perceived cupping benefit (β = −0.20) were associated with lower PSQI scores, indicating better self‐reported sleep quality. In contrast, automated rather than manual suction was associated with higher PSQI scores (β = 0.20), indicating poorer sleep quality. The final exploratory path model showed overall adequate fit to the data, with CMIN/DF = 3.076, CFI = 0.92, TLI = 0.90, SRMR = 0.07, and RMSEA = 0.066. The model explained 35.2% of the variance in global PSQI score. See Figure 2.
Figure 2.
Path analysis model for global PSQI score (complete‐case N = 421).
4. Discussion
4.1. Interpretation of the Main Results
The findings characterize cupping use among Palestinian athletes and identify factors associated with perceived benefit, adverse effects, and sleep quality. Improved mobility and reduced muscle cramps were the most frequently reported intended benefits, while chronic or recurrent conditions, muscle strain, and headaches were common reasons for use. Higher BMI and greater cupping‐session frequency were associated with greater perceived benefit. Reported inflammation was associated with BMI category, gender, and competition level, while mild pain was associated with BMI category and competition level. Most reported side effects resolved without medical intervention.
Higher BMI, vitamin use, greater cupping‐session frequency, greater perceived benefit, and manual rather than automated suction remained associated with better self‐reported sleep quality. In athletes, higher BMI may reflect greater skeletal muscle and lean body mass rather than greater adiposity because BMI does not distinguish fat mass from fat‐free mass. The association with vitamin use may also reflect broader health behaviors rather than a direct effect of supplementation. Likewise, the relationship between cupping frequency and better sleep does not establish a dose‐response effect, since athletes who perceive greater benefit may be more likely to repeat cupping sessions.
4.2. Comparison with Existing Literature
Research examining cupping among athletes remains limited. A systematic review of cupping therapy among amateur and professional athletes reported growing use of the intervention but concluded that evidence regarding its effectiveness and safety remained insufficient [27]. The present study extends this literature by examining reasons for cupping use, perceived benefit, reported adverse effects, and factors associated with self‐reported sleep quality.
Chiu et al. (2020) investigated dry cupping among athletes with myofascial pain syndrome and reported improvements in soft‐tissue compliance and function [24]. Although these outcomes differ from sleep quality, the findings indicate that cupping‐related practices may be associated with aspects of physical recovery.
Ekrami et al. (2021) reported anti‐inflammatory effects of wet cupping following vigorous exercise among martial arts athletes [23]. Such findings provide a possible physiological context for studying cupping in relation to recovery‐related outcomes. However, the present study cannot determine whether inflammatory changes explain the observed sleep associations because inflammatory biomarkers were not measured.
Hou et al. (2021) found no significant immediate effect of cupping therapy on neuromuscular fatigue, although delayed effects were reported [22]. This finding reinforces the need for caution when interpreting perceived benefits as evidence of treatment effectiveness. In the present study, greater cupping‐session frequency was associated with both greater perceived benefit and lower PSQI scores, but these observational associations may reflect athlete characteristics, health behaviors, treatment preferences, or unmeasured factors. Similarly, the association between greater perceived cupping benefit and lower PSQI scores in the present study should not be interpreted as proof that cupping directly improves sleep.
4.3. Strengths and Limitations
This study addresses a gap in the literature by examining wet cupping experiences, adverse effects, and sleep quality among Palestinian athletes. The inclusion of sociodemographic, health‐related, athletic‐training, and cupping‐related variables allowed several potential correlates of sleep quality to be assessed. The use of the PSQI also provided a standardized measure of self‐reported sleep quality.
Several limitations should be considered. First, the cross‐sectional design does not establish temporal or causal relationships. Cupping‐related experiences and adverse effects were self‐reported and may therefore be affected by recall and reporting bias. Exact time since the most recent cupping session was not recorded. This concern is particularly relevant because participants were eligible if they had received Hijama during the preceding 3 years, whereas the PSQI assesses sleep during the preceding month. Consequently, temporal correspondence between cupping exposure and measured sleep quality could not be established. Recall or reporting errors may also have misclassified cupping exposure or adverse effects and could either attenuate or exaggerate the observed associations.
Second, convenience sampling may limit the generalizability of the findings. The sample was predominantly male, and some categories contained small numbers of participants, particularly within BMI groups. Associations involving these categories should therefore be interpreted cautiously. Missing data were also present for several cupping‐related variables.
Third, residual confounding remains possible. Sport type was described but was not included in the final multivariable model, and detailed training intensity or load, psychological factors, sleep hygiene, underlying sleep disorders, medication use, pain severity, and the exact timing of the most recent cupping session were not fully measured or controlled. Duration of repeated cupping use and contraindications to prolonged use were not assessed. A complete set of regression residual and multicollinearity diagnostics was unavailable in the retained analysis output. In addition, the path model was iteratively refined using the same dataset in which its fit was evaluated. This data‐informed model‐trimming process may introduce model‐selection optimism and limits the confirmatory value of the fit indices. These limitations reduce the certainty of the adjusted and path‐model findings, which should be interpreted as exploratory and validated in an independent sample.
4.4. Future Implications
The findings identify demographic, health‐related, and cupping‐related characteristics that may be relevant when investigating sleep quality among athletes who use wet cupping. They do not provide evidence that cupping should be incorporated into athlete recovery protocols because the study design cannot establish whether cupping preceded or caused differences in sleep quality.
Future studies should use prospective designs that document the timing, frequency, duration, and characteristics of individual cupping sessions and assess sleep before and after exposure. Objective sleep measures could be used alongside validated self‐report instruments to strengthen outcome assessment. Larger samples would also allow more reliable comparisons by sex, BMI category, competition level, and cupping practice. Prospective safety reporting should also document adverse events and contraindications.
Interventional studies are needed to determine whether particular cupping practices produce measurable changes in sleep quality, recovery, pain, or athletic performance. Such studies should also examine possible mechanisms, including pain reduction and inflammatory responses, because previous research has suggested effects of cupping in these areas [23, 24]. Until such evidence is available, the present findings should be regarded as hypothesis‐generating rather than evidence of therapeutic benefit.
5. Conclusion
Cupping‐related practices and selected participant characteristics were associated with self‐reported sleep quality among Palestinian athletes. More frequent cupping sessions, vitamin use, manual rather than automated suction, higher BMI, and greater perceived cupping benefit were associated with lower PSQI scores. The final model explained 35.2% of the variance in sleep quality. These findings do not establish that cupping improves sleep or recovery. Prospective and interventional studies are required before cupping can be recommended as a strategy to improve sleep quality in athletes.
Author Contributions
Faten Amer: conceptualization, Investigation, writing – original draft, writing – review and editing, visualization, validation, project administration, supervision, data curation, formal analysis. Mahmoud Alatrash: data curation, methodology. Deema Salahat: writing – review and editing, writing – original draft, data curation, validation. Amir Kafrin: writing – original draft, writing – review and editing, data curation, validation. Nidal Jaradat: project administration, methodology, conceptualization, writing – review and editing, supervision.
Funding
The authors have nothing to report.
Ethics Statement
This study was approved by the Institutional Review Board (IRB) of the Faculty of Medicine and Health Sciences at An‐Najah National University in January 2023 (Serial No.: Ph.T Jan.2023.7). All participants provided informed consent in accordance with the Declaration of Helsinki.
Conflicts of Interest
The authors declare no conflicts of interest.
Author Declarations
All authors have read and approved the final version of the manuscript. Faten Amer had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis.
Transparency Statement
The lead author Faten Amer affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained. Faten Amer is the guarantor of this manuscript.
Data Availability Statement
The data supporting the findings of this study are available from the corresponding author upon reasonable request, subject to applicable ethical and institutional requirements.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data supporting the findings of this study are available from the corresponding author upon reasonable request, subject to applicable ethical and institutional requirements.