The relationship between smartphone usage position, pain, smartphone addiction, and hand function

Abstract

BACKGROUND:

The hand is the most frequently used part of the body during daily life activities. Any musculoskeletal problem that may occur in the hand can lead to loss of function.

OBJECTIVE:

This study examined the relationship between the wrist and elbow position adapted during smartphone use, pain and discomfort, smartphone addiction, and hand function.

METHODS:

Pain and discomfort were evaluated with the visual analog scale, wrist and elbow angle during phone use were evaluated with a universal goniometer, smartphone addiction was evaluated with the Smartphone Addiction Scale-Short Version, and functional status of the hand was evaluated with the Michigan Hand Outcomes Questionnaire.

RESULTS:

A total of 120 university students (female: $n=$ 60), with an average age of 22.71 $\pm$ 2.7 years, were included in this cross-sectional study. A relationship was found between the angle of the wrist and elbow during smartphone use and pain/discomfort ($r=$ 0.692, $p=$ 0.001), smartphone addiction ($r=$ 0.575, $p=$ 0.001), and hand function parameters ($r=$ 0.20–0.55, $p⩽$ 0.05).

CONCLUSION:

Due to the increased use of smartphones in today’s environment, a preventive program should be developed in which texting for extended periods is avoided, along with frequent breaks to rest the hands, and stretching exercises for the upper extremities during rest.

1. Introduction

Smartphones are powerful communication devices introduced by Motorola in 1973 and have been used commercially since 1984. In recent years, smartphones have become an integral part of our lives, with more than seven billion users worldwide. For students, smartphones have become an essential part of addiction. Symptoms of smartphone addiction include constantly looking at the phone for no reason, feeling anxious or restless without the phone, waking up in the middle of the night to check smartphones, delaying professional performance after long-term phone use, and being distracted by smartphone applications [1].

Since smartphones are used not only for communication but also for entertainment purposes such as messaging, music, media, internet access, photos, and games, it can adapt to a small screen for a long time and trigger the formation of repetitive bad posture [2]. Besides the benefits of smartphones in daily life, excessive usage was found to cause muscle fatigue and deterioration of hand function after repeated upper extremity movements [3]. Repeated movement refers to the malalignment of the elbow, wrist, and hand. The prevalence of musculoskeletal pain, predominantly in the hand and wrist, was found to be high (67.7%) in individuals with smartphone addiction [2]. In a review study, it was found that the body parts most associated with smartphone use were 19%–53% for thumbs, 13%–32% for hands and wrists, 14.1%–15% for elbows, 37.8%–71.6% for shoulders, 55.8%–89.9% for neck and upper back [4]. It has also been determined that there is a correlation between hand pain and excessive use of smartphones and that excessive use of such devices may cause subclinical effects on the human hand [5].

The screen size of the smartphone or choosing a phone unsuitable for the person’s anthropometer may cause discomfort and fatigue in the hand and wrist area after a while [6]. Constant repetitive movements of the thumb and fingers with smartphone use can lead to functional problems in the hand, such as tendinosis, which can cause burning, numbness, and tingling in the thenar region of the hand, as well as pain symptoms in the thumb, wrist, and forearm [2, 7, 8].

Lack of forearm support or single-handed use of smartphones may increase musculoskeletal symptoms. In addition, texting with one finger or high-speed movements of the thumb causes high muscle activation in the extensor muscles in the forearm. It is aimed at preventing symptoms with ergonomic interventions [9]. Therefore, assessing the relationship between elbow and wrist position during smartphone use will guide future ergonomic approach recommendations.

Humans use their hands for many tasks during daily life. Hand grasping and manipulating ability is achieved thanks to the musculoskeletal system, and a problem in this system can cause deterioration of hand function. Little is known about the effects of smartphone holding position on the elbow and hand to date. Although the position of the thumb during smartphone use has been examined in the literature [7], studies investigating wrist and elbow posture are insufficient. Accordingly, this study examined the relationship between the wrist and elbow position adapted during smartphone use, pain and discomfort, smartphone addiction, and hand function.

2. Materials and methods

This study was planned and carried out as a cross-sectional study. This study was approved by the Eastern Mediterranean University Research and Publication Ethics Board (decision number ETK00-2023-0183). All individuals obtained informed consent before participation. The study was conducted following the ethical principles of the Declaration of Helsinki.

2.1. Participants

2.1.1. Inclusion criteria

• •University students
• •Aged between 18–25
• •Body Mass Index 30.0 kg/cm²
• •Using the same smartphone for at least one year
• •Using the smartphone with the right single-hand-held

2.1.2. Exclusion criteria

• •Who have received physiotherapy and rehabilitation for musculoskeletal symptoms in the hand/ wrist and elbow in the last six months
• •Who have had any previous surgery on their upper extremities

The age, gender, and body mass index (BMI) of the participants, the weight (grams) and screen size (inches) of the smartphone, how many hours a day the smartphone was used and with which hand was it mainly used, the average time spent using the computer and keyboard and sitting time per day were recorded. After half an hour of smartphone use, perceived pain and discomfort, as well as elbow and wrist angle while using the smartphone, were evaluated.

2.2. Assessment of pain and discomfort

Perceived discomfort and pain in the hand/wrist and elbow after using the smartphone for 20 minutes were evaluated with the visual analog scale (VAS). VAS is a pain rating scale first used by Hayes and Patterson in 1921. The individuals marked their perceived pain and discomfort along a 10 cm line representing the continuum between the two ends of the scale. The left end of the VAS, which will be used to evaluate pain intensity, indicates “no pain” (0 cm), and the right end indicates “the most severe pain” (10 cm). In contrast, the left end of the VAS, which will be used to evaluate the level of discomfort, indicates “no discomfort” (0 cm), and the right end was defined as “the most severe discomfort” (10 cm) [11]. This scale showed excellent test-retest and inter-rater reliability (ICC: $>$ 0.90) [12].

2.3. Assessment of wrist and elbow position during smartphone usage

Wrist and elbow angles during smartphone use in the seated position were measured with a universal goniometer (UG) (Jamar Stainless-Steel Goniometers; Lafayette Instrument, IN, USA) that has a plastic 360^∘ goniometer face and 10-inch movable arms. In wrist angle measurements, the pivot point of the UG was placed at the 3rd carpometacarpal joint. For wrist ulnar deviation measurement, the stationary arm was fixed at the midpoint of the radius and ulna, and the movable arm followed the third metacarpal bone [13]. For wrist extension measurement, the stationary arm placement paralleled the longitudinal midline of the radial forearm, and the movable arm parallelled the longitudinal axis of the second metacarpal [14]. In elbow position measurement, the UG was centered on the lateral epicondyle, the stationary arm was pointing at the tip of the acromion process, and the movable arm of the UG was oriented to the ulnar styloid process [15]. All position measurements were recorded in degrees (^∘) (Fig. 1). The accuracy and intra-rater reliability of wrist deviations UG measurement were high compared to the gold standard of fluoroscopic measurement (ICC: 0.80) [16]. The technique’s intra- and inter-rater reliability for measuring wrist extension was above the 0.80 ICC [14]. The Goniometer’s intra- and inter-rater reliability compared with the gold standard radiographic measurement of the elbow flexion range of motion was excellent (ICC: 0.945–0.980) [15].

Figure 1.

Assessment of wrist and elbow position. A) Wrist extension B) Wrist deviation C) Elbow flexion.

2.4. Assessment of smartphone addiction

The smartphone addiction of the participants was evaluated with the Smartphone Addiction Scale-Short Version (SAS-SV). This scale was developed by Kwon et al. [17] to measure the risk of smartphone addiction in adolescents and consists of 10 items. Items in the scale are scored using a six-point Likert scale from 1 to 6. The total score varies between 10–60, and as the score increases, the addiction increases. The validity and reliability study of the scale in Turkish was conducted by Noyan et al. [18] on university students, and Cronbach’s alpha coefficient of the internal consistency and concurrent validity of the scale is 0.91.

2.5. Assessment of hand function

Participants’s perception of symptoms and functional status of their hands was assessed with the Michigan Hand Outcomes Questionnaire (MHQ). It is a hand-specific outcomes questionnaire with 57 items in 6 domains: overall hand function, activities of daily living (ADLs), pain, work performance, aesthetics, and patient satisfaction. Except for pain and work performance, each MHQ category is separated into questions specific to the right hand and left hand. A set of questions on both hand task performance is included in the activities of daily living. Each item is scored using a scale of 1 to 5. While 0 represents the worst score and 100 represents the best score in every domain except pain, a higher score indicates more pain [19, 20]. Oksuz et al. [21] performed a cultural adaptation, validation, and reliability study of the Turkish version of MHQ. The ICC of the test-retest reliability ranged from 0.79 to 0.96, and the internal consistency of the MHQ ranged from 0.85 to 0.96 for the 6 subscales.

2.6. Sample size

The G* Power 3.0 program determined the study’s sample size. Since reference data from comparable research were unavailable, Cohen’s d was used to assess the effect size. In the study by Cohen, the effect size specified in the correlation studies was determined as 0.30 (moderate), and the total sample size was determined to be 115 by using the Type I and Type II error rate of 5%, assuming $\alpha =$ 0.05 and 95% power [10].

2.7. Statistical analysis

The Statistical Package for Social Science (SPSS) version 26.0 statistical data analysis package software was used to analyze the data. Scale data such as age, smartphone, and computer usage time were given as arithmetic mean and standard deviation (X $\pm$ SD), and categorical data such as gender were given as percentages (%). The data distribution was visually examined with histograms and plots and analytical methods using the Kolmogorov-Smirmnov test for normality. The Spearman Correlation test was used in the correlation analysis of the clinical findings of the participants. The significance level for all statistical analyses was set at 0.05. The correlation coefficient was interpreted as a 0.00–0.29: weak or low; 0.30–0.49: moderate; 0.50–1.0: high or strong relationship [22].

3. Results

A total of 120 participants (female: 60, male: 60) were included in the study, with an average age and body mass index of 22.71 $\pm$ 2.7 years and 23.12 $\pm$ 3.55 kg/cm², respectively. The average smartphone weight was 204.46 $\pm$ 31.3 grams, and the size was 5.85 $\pm$ 0.54 inches. While 84.2% of the participants used the smartphone with their right hand, the average daily usage time was 6.99 $\pm$ 2.93 hours. The average wrist deviation, extension, and elbow flexion angle during smartphone use were 20.33 $\pm$ 8.8^∘, 28.55 $\pm$ 3.54, and 100.48 $\pm$ 15.90^∘, respectively. While the mean participants’ perceived discomfort was 23.3%, 34.2% experienced pain during smartphone usage; the mean values were 4.47 $\pm$ 1.40 cm and 4.26 $\pm$ 1.42 cm, respectively. The smartphone addiction rate of the participants was found to be 55.8%, and the average score was 34.91 $\pm$ 9.81 (Table 1).

Table 1.

Participants’ demographic and smartphone usage-related information

		N (%)	X $\pm$ SD
Age (year)			22.71 $\pm$ 2.7
Gender	Female	60 (50)
	Male	60 (50)
BMI (kg/m2)			23.12 $\pm$ 3.55
Smartphone usage year			8.02 $\pm$ 2.77
Smartphone weight (gram)			206.23 $\pm$ 31.52
Smartphone size (inch)			6.07 $\pm$ 0.71
Smartphone daily usage (hour)			6.99 $\pm$ 2.93
Smartphone screen usage (hour)			5.89 $\pm$ 2.65
Daily computer and keyboard usage (hours)	Yes	78 (65)	1.57 $\pm$ 1.52
	No	42 (35)
Daily sitting time (hours)			5.36 $\pm$ 1.56
Wrist deviation angle			20.33 $\pm$ 8.8
Wrist extension angle			28.55 $\pm$ 3.54
Elbow flexion angle			100.48 $\pm$ 15.90
The feeling of discomfort in the elbow, wrist, and hand when using the smartphone (cm)	No	92 (76.7)	4.47 $\pm$ 1.40a
	Elbow	3 (2.5)
	Wrist and hand	25 (20.8)
The feeling of pain in the elbow, wrist, and hand when using the smartphone (cm)	No	79 (65.8)	4.26 $\pm$ 1.42a
	Elbow	48 (3.3)
	Wrist and hand	37 (30.8)
Smartphone addiction	Yes	67 (55.8)	34.91 $\pm$ 9.81
	No	53 (44.2)

^aCalculated based on existing pain and discomfort.

A moderate positive correlation was found between wrist deviation and flexion angle during smartphone use, smartphone usage years ($r=$ 0.476, $p=$ 0.00; $r=$ 0.363, $p=$ 0.001), and screen usage time ($r=$ 0.472, $p=$ 0.001; $r=$ 0.402, $p=$ 0.001) respectively. While wrist deviation angle had a high positive correlation with daily smartphone usage time ($r=$ 0.505, $p=$ 0.001), pain/discomfort ($r=$ 0.692, $p=$ 0.001), and smartphone addiction ($r=$ 0.575, $p=$ 0.001), wrist flexion angle had a moderate positive relationship with them ($r=$ 0.363, $p=$ 0.001; $r=$ 0.419, $p=$ 0.001; $r=$ 0.303, $p=$ 0.001 respectively). A moderate positive relationship was found between elbow angle and years of smartphone usage ($r=$ 0.445, $p=$ 0.001), daily smartphone usage time ($r=$ 0.380, $p=$ 0.001), and screen time ($r=$ 0.360, $p=$ 0.001). Also, weak relationship was found with smartphone addiction ($r=$ 0.270, $p=$ 0.003). Additionally, it was found that the pain and discomfort felt while using the smartphone were highly positively correlated with wrist angle ($r=$ 0.692, $p=$ 0.001) and elbow angle ($r=$$-$0.525, $p=$ 0.001) (Table 2).

Table 2.

Relationship between smartphone usage time, weight, size, addiction, and usage position

		Wrist extension angle	Wrist deviation angle	Elbow angle	SM usage year	SM daily usage	SM screen usage	SM addiction	Pain
Wrist deviation	$r$	0.794**
	$p$	0.001
Elbow angle	$r$	$-$0.380**	$-$0.496**
	$p$	0.001	0.001
SM usage year	$r$	0.370**	0.467**	0.445**
	$p$	0.001	0.001	0.001
SM daily usage	$r$	0.441**	0.472**	0.380**	0.390**
	$p$	0.001	0.001	0.001	0.001
SM screen usage	$r$	0.409**	0.442**	0.360**	0.366**	0.888**
	$p$	0.001	0.001	0.001	0.001	0.001
SM addiction	$r$	0.325**	0.527**	0.270**	0.438**	0.323**	0.259**
	$p$	0.001	0.001	0.003	0.001	0.001	0.004
Pain	$r$	0.440**	0.692**	0.525 **	0.627**	0.527**	0.477**	0.722**
	$p$	0.001	0.001	0.001	0.001	0.001	0.001	0.001
Discomfort	$r$	0.440**	0.692**	0.525**	0.627**	0.527**	0.477**	0.722**	1.000**
	$p$	0.001	0.001	0.001	0.001	0.001	0.001	0.001

SM: smartphone; ^*: 0.05, ^**: 0.001. Spearmen correlation test.

A positive high relationship was found between wrist angle while using the smartphone and left-hand function ($r=$$-$0.513, $p=$ 0.001), and left-hand satisfaction ($r=$ 0.528, $p=$ 0.001), a moderate relationship with pain ($r=$$-$0.440, $p=$ 0.001) and right-hand satisfaction ($r=$ 0.349, $p=$ 0.001), a positive weak relationship with right-hand function ($r=$ 0.281, $p=$ 0.002), and with left-hand ADLs ($r=$ 0.265, $p=$ 0.003) and a negative weak relationship with work performance ($r=$$-$0.245, $p=$ 0.007). While a positive moderate relationship was found between wrist extension angle and left-hand function ($r=$ 0.342, $p=$ 0.001) and satisfaction ($r=$ 0.351, $p=$ 0.001), a weak positive relationship was found between right-hand function ($r=$ 0.288, $p=$ 0.001), pain ($r=$ 0.287, $p=$ 0.002), and right satisfaction ($r=$ 0.268, $p=$ 0.003). In addition, a positive moderate correlation was found between elbow angle and left-hand satisfaction ($r=$ 0.446, $p=$ 0.001), left-hand function ($r=$ 0.422, $p=$ 0.001), and pain ($r=$ 0.347, $p=$ 0.001). In addition, a negative low correlation was found between the elbow angle and the right ADLs ($r=$$-$0.228, $p=$ 0.012) and a positive low correlation with the left ADL ($r=$ 0.274, $p=$ 0.002). The relationship between the smartphone usage year, daily and screen usage time, addiction to smartphones, and the functional status of the hand is shown in Table 3.

Table 3.

The relationship between smartphone usage position and functional status of the hand

		Right function	Left function	Right ADLs	Left ADLs	Both hand ADLs	Work performance	Pain	Right aesthetic	Left aesthetic	Right satisfaction	Left satisfaction
Wrist ulnar deviation	$r$	0.281*	0.513**	0.111	0.265*	0.009	$-$0.245*	0.440**	$-$0.130	$-$0.130	0.349**	0.528**
	$p$	0.002	0.001	0.226	0.003	0.920	0.007	0.001	0.156	0.156	0.001	0.001
Wrist extension	$r$	0.288**	0.342**	0.171	0.107	$-$0.118	$-$0.085	0.287*	$-$0.040	$-$0.040	0.268*	0.351**
	$p$	0.001	0.001	0.062	0.247	0.198	0.354	0.002	0.665	0.665	0.003	0.001
Elbow angle	$r$	$-$0.067	0.422**	$-$0.228*	0.274*	$-$0.012	$-$0.153	0.347**	$-$0.163	$-$0.163	$-$0.003	0.446**
	$p$	0.465	0.001	0.012	0.002	0.893	0.096	0.001	0.076	0.076	0.977	0.001
SM usage yea$r$	$r$	$-$0.121	$-$0.465**	0.054	$-$0.143	0.285**	$-$0.238**	$-$0.238**	$-$0.440**	$-$0.198*	$-$0.198*	$-$0.144
	$p$	0.187	0.001	0.558	0.120	0.002	0.009	0.009	0.001	0.030	0.030	0.117
SM daily usage	$r$	$-$0.173	$-$0.509**	$-$0.121	$-$0.117	0.412**	$-$0.130	$-$0.13	$-$0.361**	$-$0.099	$-$0.099	$-$0.171
	$p$	0.059	0.001	0.187	0.203	0.001	0.159	0.159	0.001	0.283	0.283	0.062
SM screen usage	$r$	$-$0.101	$-$0.420**	$-$0.085	$-$0.171	0.355**	$-$0.035	$-$0.035	$-$0.313**	$-$0.002	$-$0.002	$-$0.111
	$p$	0.271	0.001	0.358	0.061	0.001	0.703	0.703	0.001	0.984	0.984	0.226
SM addiction	$r$	$-$0.228*	$-$0.340**	$-$0.150	$-$0.148	0.191*	$-$0.288**	$-$0.288**	$-$0.354**	$-$0.165	$-$0.165	$-$0.247**
	$p$	0.012	0.001	0.101	0.106	0.036	0.001	0.001	0.001	0.071	0.071	0.006

SM: smartphone; ^*: 0.05, ^**: 0.001. Spearmen correlation test.

4. Discussion

Most musculoskeletal diseases occur due to overuse, which causes damage to muscle fibers and muscle tone. Excessive smartphone use and repeated typing affect muscle activity and effort. This research revealed that the angle of the wrist and elbow while using the smartphone was related to the duration of smartphone use, pain, smartphone addiction, and especially hand pain, function, and satisfaction.

Using the smartphone one-handed or two-handed is becoming an increasing task in daily life. One-handed users’ physical demands are more significant than operation with two hands. Lee et al. reported that the activation of the muscles involved in wrist stabilization was greater when using one hand [23]. In addition, the static and asymmetric position adopted during smartphone use may also be a potential risk factor for musculoskeletal disorders such as pain. The percentage and severity of pain and discomfort in the participants’ elbow and hand/wrist areas while using the smartphone were found to be (34.1%, 4.26 $\pm$ 1.42 cm) and (23.3%, 4.47 $\pm$ 1.40 cm), respectively. The study conducted by Collins et al. stated that if the participants recorded the baseline VAS score between 30 and 54 mm, they would have at least moderate pain [24]. The fact that only one-handed users were included in our study, and although the prevalence of pain was low, the severity of pain was moderate, suggests that the way of holding the smartphone will cause musculoskeletal pain.

Due to the trend of using smartphones, leading phone companies are manufacturing phones with larger dimensions. The study of Walankar et al. showed that smartphone size had a significant association with musculoskeletal pain, and smartphones with larger screen sizes and the placement position of the device pose the risk of pain [2]. Also, the larger phones gave the user a wider grip on the device [25]. Kamel et al. classified smartphones based on screen size: 4.0–4.7 inches as small, 4.8–5.1 inches as medium, and 5.2–5.7 inches as large [26]. Gandhi et al. divided smartphone weights into three groups according to their grams: 180 grams as low, 180–200 grams as a medium, and over 200 grams as large in their study [27]. In our study, the average smartphone weight (206.23 $\pm$31.52 grams) and size (6.07 $\pm$ 0.71 inches) preferred by users is in the large group. The fact that larger smartphones force the user to have a wider grip on the device and more effort from the hand and elbow muscles can also cause musculoskeletal pain and discomfort.

Addiction is the inability to stop using a substance or engaging in an activity even when knowing that it harms physiological, psychological, and social well-being. In particular, smartphone addiction causes dysfunctional impulsivity in regularly checking smartphones and excessive use of them, such as spending five or more hours a day [28]. The study by Noyan et al., which included 367 university students, found that the Smartphone Addiction Scale-Short Version (SAS-SV) average score of participants who used smartphones for 5 hours or more was 35.16 $\pm$ 9.73. This score increased statistically significantly as the average daily time spent with the smartphone increased [18]. Kwon et al. reported that the participants in their study, who assessed themselves as addicted to smartphones, showed 34.02 $\pm$ 10.34 points in the SAS-SV score [17]. The fact that the average SAS-SV score (34.91 $\pm$ 9.81) in our study has similar values to these studies, the high daily smartphone use of university students, and especially the relationship between these two parameters ($r=$ 0.323, $p=$ 0.001) as the study results conducted by Alhazmi et al. [29] indicate that the participants have a smartphone addiction.

Smartphone users typically adapt their wrist and elbow postures to the constraints of the smartphone design. Especially in users with a single-hand-held, repeated and static use of the wrist and thumb can lead to increased pain and increased load on these joints and associated muscles and tendons [30]. Another study by Xiong and Muraki found that the muscle effort in the thumb varies during different tasks while using a smartphone [31]. These studies show that the wrist and thumb muscles are exposed to repetitive movements during smartphone use. Accordingly, considering the musculoskeletal symptoms that may occur due to smartphone use, our study focused on the static position to which the elbow and wrist adapt instead of muscle activation.

According to the Rapid Upper Limb Assessment (RULA) tool, developed by Corlett and McAtamney, wrist deviation from the neutral position, flexion, or extension above 15^∘ and an elbow angle of less than 60^∘ or more than 100^∘ of flexion are considered a risk factor for musculoskeletal disorders [32]. In a study conducted by Drury, wrist extension of more than 25^∘ and ulnar/radial deviation of more than 10^∘ may be a risk factor for the development of disorders such as musculoskeletal pain by causing excessive hand and wrist movements [33]. In our study, the wrist ulnar deviation angle during smartphone use was 20.33 $\pm$ 8.8^∘, and the extension angle was 28.55 $\pm$ 3.54^∘. The correlation between these angles and pain/discomfort felt while using the smartphone ($r>$ 0.440, 0.50) may be a risk factor for musculoskeletal disorders, supporting the literature. Namwongsa et al., in their study evaluating 30 smartphone users with RULA [34], stated that elbow angles were more than 100^∘. Thus, similarly to our findings, they had high ergonomic risk when they were using their smartphones. In addition, the RULA tool is a screening tool based on observation. Our study used goniometric measurement, which provides objective results for determining these angles. As a result, postural changes in the elbow and wrist can lead to sustained unideal postures in adulthood. In this case, students may develop postural and musculoskeletal system problems, which might hinder the extent to perform their professions and participate in recreational activities.

Another factor that causes musculoskeletal pain and increased wrist and elbow angle, which causes ergonomic risk, is the size of the preferred electronic device. Thus, Pereira et al. reported that as the size of the electronic device used increases, pain in the hand/wrist area and wrist flexion and extension angles increase and that a 5.3-inch device causes ulnar deviations over 25^∘ from neutral [35]. Young et al. also found wrists being extended between 14.6^∘ and 24.4^∘ for a touch screen range of 3.5–7 inches [36]. The mean value of the smartphone size preferred by the university students in our study is 6.07 $\pm$ 0.71 inch, which explains the increasing angular values. For university students, electronic devices’ weight and screen size must be balanced according to their specific intended predominant use. First of all, smartphone usage should be changed so that it can be used on the other hand for a certain period or with both hands to distribute the physical stress evenly. The neutral or alternative holding position required while using the smartphone should be taught to students, and postural awareness should be created. With these modifications, awkward postures can be avoided, and therefore, lower mechanical loading frequency and amplitude on wrist and elbow muscles can be reduced during use.

Using mobile touch devices brings physical strain to both the elbow and wrist. Nevertheless, to our knowledge, our study is the first to investigate the relationship between smartphone holding position and hand function. A relationship was found between all angles measured while holding the smartphone and the pain parameter of the MHQ, and it was determined that increasing the wrist and elbow angles tends to increase stiffness pain. However, the study that included participants who used the smartphone with their right hand observed that the satisfaction and function scores in both hands (except for the elbow angle) increased positively with the angle away from neutral. This study also found that the right-hand aesthetic of single-handed users changed negatively, especially as the yearly, daily, and screen usage and addiction to smartphone use increased. The fact that some parameters of the MHQ changed negatively and others changed positively with wrist and elbow angles suggests that the low mean age of the university students is still insufficient to explain the change in hand function. İnal et al. evaluated hand function on 102 university students using a different questionnaire than our study. Although they found a relationship between smartphone addiction and hand function, they did not find any difference in hand functions between high smartphone users and non-users [30]. The questionnaire is insufficient to evaluate the hand’s functional status, which is essential in our daily activities, especially in the healthy young population. Future studies are needed to evaluate hand function with more detailed objective measurements.

Generally, the typical smartphone posture involves holding the device below eye level with one or both hands, neck flexion to look at the device, elbow flexion, and wrist extension to keep the phone, and using the thumb to touch the screen. The literature focused on neck and upper back posture during smartphone use [37, 38, 39], and studies on wrist and elbow posture have been insufficient. In this regard, the strengths of our study are the examination of the change in the distal part of the upper extremity adapted to smartphone use and the evaluation of the ergonomic risk of elbow and wrist angles with a goniometer, which gives objective results rather than observationally, it also has some limitations. First, grip type, thumb posture, and hand size when holding the smartphone were not controlled, and participants were free to use the most comfortable grip when using the device. However, despite this variability, we still observed that the change in postural angles affected many parameters. Secondly, it was insufficient to evaluate the hand function of healthy university students with a questionnaire. Therefore, studies are needed for hand functional evaluations that give more detailed and objective results, such as grip strength and fine hand skills.

5. Conclusion

Sustained muscle load and posture are considered risk factors for developing musculoskeletal disorders. Smartphone users with excessive addiction have this risk, which may contribute to these disorders. Therefore, health professionals should be aware of the effect of smartphone use on physical health problems. As a result of our study conducted in this direction determined that the wrist and elbow angle during smartphone use was related to usage time, pain, smartphone addiction, and especially hand pain, function, and satisfaction. Due to the increased use of smartphones in today’s environment, improving how they are used is necessary. Also, a preventive program should be developed to avoid texting for extended periods, along with frequent breaks to rest the hands, and stretching exercises for the upper extremities should be performed during rest.

Author contributions

Study conception and design: all authors. Data collection and analysis: OD. Drafting of the manuscript: EA. Critical revision of the manuscript: all authors. All authors read and approved the final manuscript.

Data availability

Data are available from the corresponding author upon reasonable request.

Ethical approval

This study was approved by the Eastern Mediterranean University Research and Publication Ethics Board (decision number ETK00-2023-0183).

Funding

The authors report no funding.

Informed consent

All participants provided written informed consent.

Conflict of interest

The authors declare that they have no conflict of interest.