Effects of Smartphone Use on Posture and Gait: A Narrative Review

Abstract

Advances in information technology and the widespread adoption of smartphones have improved human convenience and quality of life by facilitating extensive information sharing. However, the increasing frequency and duration of smartphone use is linked to a high risk of musculoskeletal disorders, particularly manifesting as changes in posture and gait. These alterations can lead to various physical issues, including spinal deformities, reduced gait stability, and increased muscle fatigue. Furthermore, excessive smartphone use can negatively affect mental health, contributing to depression, anxiety, and cognitive impairment. This narrative review primarily aims to systematically examine the effects of smartphone-related posture and gait alterations on physical function and identify associated problems. This study systematically summarized individual studies published between 2009, when smartphones first became widespread, and 2024 that investigated the effects of smartphone-induced posture and gait alterations. Through identifying issues related to these alterations, we aim to propose preventive strategies to avoid further complications.

1. Introduction

As of late 2022, approximately 6.65 billion people—representing 83% of the global population—own a smartphone The extensive adoption of this technology has sparked international concerns regarding excessive smartphone usage. Studies have shown that students who frequently engage with their smartphones tend to report elevated levels of depression and anxiety [1]. An analysis of studies published between 2010 and 2019 revealed that neck and shoulder regions are the most frequently reported areas of discomfort among users. The reported prevalence of such musculoskeletal complaints varied widely, ranging from 32.5% to 85.6% [2]. Prolonged smartphone use can cause physical (posture and gait), psychological (depression, anxiety, and stress), and social issues (decreased work efficiency and productivity) [3,4]. Since their introduction in 2009, smartphones have significantly enhanced convenience in daily life, enabling social networking and information exchange [5,6] anytime and anywhere [5]. However, prolonged smartphone use induces spinal posture and gait alterations, thereby exacerbating the risk of musculoskeletal disorders [6]. Specifically, smartphone viewing increases cervical spine flexion, intensifying muscle load in the neck and shoulders and leading to elevated muscle fatigue [7]. On average, muscle activation while using a smartphone during walking was elevated by 21.2% compared to sitting and by 41.7% compared to standing [8]. Additionally, using smartphones while walking shifts the head forward, reduces stride length, and decreases gait speed [9,10] while limiting the visibility of obstacles and reducing reaction time, potentially creating hazardous situations [11,12].

Prolonged smartphone use can alter spinal posture across various age groups, significantly elevating the risk of spinal musculoskeletal disorders [5,13]. Particularly, it negatively affects posture throughout the entire spine, including cervical, thoracic, and lumbar regions [5,6,10,14,15,16,17,18,19,20,21]. For instance, text messaging reduces cervical rotation angles by approximately 2–4 degrees on average and increases thoracic and lumbar flexion, potentially causing pain and discomfort in the neck and shoulders [20]. Increased cervical flexion due to smartphone use also leads to the sustained contraction of the upper trapezius, elevating muscle activity and fatigue, which can result in discomfort and pain [14,17,18]. Short-term spinal posture alterations will progressively intensify with the prolonged duration and increased frequency of smartphone use, ultimately leading to diverse spinal joint issues.

Excessive smartphone use also alters gait patterns [9,12,22]. Specifically, biomechanical gait changes, including reduced stride length, decreased cadence, and slower gait speed, are commonly observed [23]. Additionally, smartphone use while walking constitutes a dual-task scenario, temporarily diminishing attention and cognitive function [24,25,26]. Particularly, texting while walking heightens cognitive demands, leading to decreased overall gait speed, reduced text comprehension, and increased gait variability [26].

The primary objective of this study is to systematically review and summarize individual studies investigating the effects of smartphone use on spinal posture and gait alterations. Although reviews published since 2020 have examined either spinal posture [27] or gait alterations [27,28] due to smartphone use in healthy individuals, reviews addressing both simultaneously remain limited [27].

2. Materials and Methods

Individual studies examining the effects of smartphone use on spinal posture and gait were identified through a comprehensive narrative review. PubMed, Web of Science, Google Scholar, and CINAHL databases were systematically searched for studies published in SCIE journals listed in Journal Citation Reports between January 2009 and June 2024. The search strategy employed was as follows: “smartphone OR cellphone AND gait OR walking AND posture OR postural alignment [Title/Abstract]” across PubMed, Google Scholar, Web of science and CINAHL databases. A total of 3259 articles were initially retrieved; among these, 3067 articles unrelated to spinal posture and gait were excluded. Of the remaining 192 studies, 153 studies that did not include healthy participants were excluded, along with an additional 12 studies lacking gender specification. This process resulted in the final inclusion of 27 studies in this review.

3. Results

The abstracts and titles of the 3259 articles retrieved through the initial database search were reviewed. Of 39 studies investigating smartphone use-related spinal posture and gait alterations, 12 lacking gender specification were excluded, yielding 27 studies included in this review (Figure 1). The authors, study designs, participants, outcomes, and discussions of each selected study were thoroughly reviewed. A total of 27 studies, comprising 14 investigating the impact of smartphone use on spinal posture and 13 examining gait alterations, were selected, with their dependent variable outcomes summarized in

Table 1. Extracting relevant data from studies examining the effects of smartphone use on posture.

Author	Population (M/F)	Methods (Interventions)	Main Outcome Measures	Alteration of Parameters	Main Findings
Faeze [5] (2022)	26/54 Age: 21 years	Participants sat on a chair with and without backrest support.	Head tilt angle Neck tilt angle Gaze angle Forward head posture	Posture condition: Standing Head tilt: moderate (107.1°) Neck tilt: moderate (27.6°) FHP: moderate (14.9 cm) Gaze angle: highest (67.1°) Posture condition: sitting without backrest Head tilt: highest (109.6°) Neck tilt: lowest (22.0°) FHP: worst (15.9 cm) Gaze angle: high (66.6°) Posture condition: sitting with backrest Head tilt: lowest (100.6°) Neck tilt: optimal (32.5°) FHP: best (13.8 cm) Gaze angle: lowest (58.2°)	Using a smartphone significantly affects neck pressure, with noticeable differences in angles depending on the position.
Marina [14] (2018)	42/18 Age: 17 years	Nerve conduction velocity was measured for the right and left median nerves.	Hand grip EMG Goniometer Visual analog scale Forward Head Posture	Prolonged smartphone use (>4 h/day): FHP angle: 61.2° → 52.5° Neck pain (VAS): 1.7 → 6.13 Ulnar nerve conduction velocity: decreased Median nerve conduction velocity: no change Hand grip strength: no change	Prolonged smartphone use in adolescents decreases ulnar nerve conduction velocity, increases forward head posture, and causes neck pain, without affecting hand grip strength or median nerve conduction velocity.
Han [16] (2019)	15/13 Age: 23 years	Participants engaged in upright walking under three conditions: (1) walking without using a smartphone, (2) one-handed smartphone browsing while walking, and (3) two-handed texting while walking.	Head flexion angle	Walking while texting (two-handed): Head flexion angle: highest (38.5°) Neck load: increased demand Head motion variation: minimal dynamic range Walking while browsing (one-handed): Head flexion angle: moderate (31.1°) Neck load: elevated but less than texting Head motion variation: moderate reduction Walking upright (no smartphone): Head flexion angle: neutral (−1.2°) Neck load: lowest Head motion variation: natural oscillation maintained	Smartphone use while walking increases head flexion angle by 38.5 deg (two-handed texting), 31.3 deg (one-handed web-browsing), and by −1.2 deg (upright).
Bruhl [15] (2023)	21 (M) Age: 25 years	Participants maintained a neutral gaze (straight ahead) and performed reading tasks on a smartphone: using one hand using both hands.	Kyphosis angle Lordosis angle VP flexion Lateral deviation	Spinal posture (standing and walking): VP flexion: increased (S1H: +6.2°, S2H: +4.8° vs. GN) Thoracic kyphosis angle: increased (S1H: +9.7°, S2H: +12.5° vs. GN) Lumbar lordosis angle: no change Lateral deviation (frontal plane): no change	Smartphone use induced increased VP flexion and kyphosis angle. Smartphone use during walking induced higher kyphosis angle.
Tapanya [18] (2021)	16/16 Age: 21 years	Before being tested, participants were randomly assigned to one of four neck flexion angles: 0°, 15°, 30°, or 45°.	Gravitational moment Head tilt angle Forward head distance Craniovertebral angle Gaze angle Phone tilt angle Cervical erector spinae EMG Upper trapezius EMG	Neck flexion: 0° → 15° → 30° → 45° Gravitational moment: 2.13 → 6.80 Nm Forward head distance: 10.01 → 14.99 cm CES EMG: 7.4% → 13.9% in MVC UT EMG: 3.97% → 1.80% in MVC Neck discomfort: 2.0 → 3.6 cm in VAS Phone tilt angle: 75.9° → 22.1°	Using a smartphone while in a flexed neck posture increases the biomechanical burden on cervical kinematics, as well as gravitational moments and neck muscle loading, potentially increasing the risk of musculoskeletal discomfort.
Eardley [19] (2018)	10/10 Age: 30 years	A range of four hand grip types was assessed, depending on interaction (touchscreen, stylus, and keyboard), across three postures: sitting at a table with arms resting; standing; and lying supine (on the back).	Hand grip Hand movement	Body posture: Lying down Most phone movement (Alpha ↑, Beta ↑, Gamma ↑); least secure and comfortable posture Body posture: Single-handed (S) grip Greatest instability Body posture: Sitting at a table Moderate movement; better body support, but higher arm restriction Body posture: Symmetric bimanual (B) and asymmetric finger (AF) grips More stable than S (single-handed) Body posture: Standing Least phone movement; best for comfort and device security Body posture: AF (asymmetric finger) grip Rated most secure, followed by B (symmetric bimanual) By hand grip (across all postures) S (single-handed): most movement across all axes (Alpha, Beta, Gamma) Least secure, least comfortable AF (asymmetric finger): least movement overall, most preferred, most stable grip especially effective in standing posture B (symmetric bimanual) and asymmetric thumb (AT): moderate movement; balanced trade-off between control and flexibility	Hand movements are affected by grip type and smartphone size. Lying down body posture had the most movement followed by sitting and standing.
Yan [20] (2018)	15/22 Age: 24 years	Participants completed text-entry tasks (texting with one hand, two hands, and typing on a desktop keyboard) for 10 min per task, with 5 min rest intervals between tasks.	Word speed Accuracy Cervical spine angle Thoracic spine angle Lumbar spine angle	Bilateral texting vs. unilateral texting Cervical flexion angle: increased in bilateral texting (4°) Cervical right rotation: decreased in bilateral texting (2–4°) Postural variability (cervical): higher in unilateral texting Smartphone texting vs. computer typing Cervical and thoracic flexion: higher during smartphone texting Lumbar flexion: more in computer typing Frequency and range of cervical motion: lower in smartphone texting Participants with chronic neck–shoulder pain vs. healthy controls Cervical side flexion (right): slightly higher in the pain group Postural change range (cervical rotation): greater in the pain group	Texting on a smartphone is associated with a more static and flexed spinal posture compared to typing on a desktop, with bilateral texting increasing cervical flexion and unilateral texting causing asymmetrical posture.
Chen [29] (2023)	30/30 Age: 22 years	The study comprised 18 trial sessions, during which data were collected on neck flexion, head flexion, gaze angle, and viewing distance during smartphone use. Participants performed tasks in three postures and two hand-use conditions, with each combination repeated three times.	Upper thoracic angle Head flexion Neck flexion Gaze angle Viewing distance	Standing vs. walking (slow vs. normal) NF: standing (37.7°) NF: walking at slow (31.7°) NF: walking at normal (32.1°) HF: no change GA: no change VD: interaction with hand use (see below) Two-handed texting vs. one-handed browsing NF: increased in two-handed HF: increased in two-handed GA: increased in two-handed VD: incresed in two-handed when standing, but decreased during walking Sex differences: decreased in NF, HF, GA in women VD: decreased in women due to shorter arm length	Smartphone use during walking increased cervical kyphosis compared to standing. Two-handed texting increased neck flexion, head flexion, and gaze angle compared to one-handed browsing.
Choi [21] (2016)	8/7 Age: 24 years	A single group of participants adopted three neck postures (maximum flexion, moderate flexion, and neutral), while the muscle activity and fatigue of 15 participants were measured via surface EMG.	Splenius capitis EMG Upper trapezius EMG	EMG activity Splenius capitis EMG: no change Upper trapezius EMG: no change Muscle fatigue Right splenius capitis: highest in maximum bending Left splenius capitis: highest in maximum bending Left upper trapezius: highest in maximum bending	Smartphone use during maximum bending posture increased levels of fatigue in splenius capitis and upper trapezius compared to the middle bending posture. No differences in muscle activity of splenius capitis and upper trapezius among three postures.
Jung [30] (2021)	16/9 Age: 18 years	Participants sat on a height-adjustable chair with hips and knees at 90° for 30 min in a habitual sitting posture. Pelvic asymmetry, thoracolumbar kyphosis, and lumbar lordosis were assessed using 3D motion capture.	Lumbar lordosis angle Pelvic asymmetry angle Thoracolumbar kyphosis angle	Smartphone use for 30 min in sitting posture: Thoracolumbar kyphosis: increased in both groups (Low back pain > control) Effect size: 2.11 (low back pain) Effect size: 1.25 (control) Lumbar lordosis: decreased in both groups (Low back pain > control) Eeffect size: 2.54 (low back pain) Effect size: 1.61 (control) Pelvic asymmetry: no change	Thoracolumbar kyphosis tends to increase during smartphone use, particularly in adolescents with lower back pain.
Park [31] (2017)	18 (M) Age: 21 years	Surface EMG (Noraxon, Scottsdale, AZ, USA) and digital cameras (Sony, Tokyo, Japan) were used to measure muscle activity and angular changes in the neck and trunk during 16 min of smartphone use.	Neck angle Cervical and thoracic angle Trunk angle Cervical erector spinae EMG Thoracic erector spinae EMG Lower trapezius EMG	Smartphone gaming (16 min sitting, unsupported posture): Neck flexion angle: 66.0° → 90.3° Trunk flexion angle: 104.0° → 81.7° (more flexion) CES EMG amplitude: increased TES and LT EMG amplitude: decreased UT EMG amplitude: no change 10% APDF (CES): indicating greater sustained load 10% APDF (TES, LT): indicating load transfer to passive structures Pain (VAS): in both neck (4.2) and trunk (2.2)	Smartphone use caused flexed neck and trunk postures, reduced thoracic erector spinae and lower trapezius muscle activity, and induced pain.
Lee [17] (2015)	8/6 Age: 22 years	Each participant sat with their back against a wall, holding a smartphone with both hands. The muscle fatigue of the neck and shoulders was measured using EMG at 0°, 30°, and 50° cervical flexion angles.	Cervical angle Upper trapezius EMG Cervical erector spinae EMG Pressure pain threshold	Cervical flexion angle conditions: 0°, 30°, 50° (10 min smartphone use) Muscle fatigue: median frequency was reduced (fatigued) Right UT EMG: 42.5 → 26.3 Hz Left UT EMG: 38.2 → 18.7 Hz R/L CES EMG: no change Pressure pain threshold: decreased (more sensitive) Right UT PPT: 15.9 → 14.7 lb Left UT PPT: 16.6 → 15.1 lb R & L CES PPT: no change	Increased cervical flexion angle during smartphone use induced upper trapezius muscle fatigue and pain measured by an algometer (pressure pain threshold).
Yoon [32] (2015)	18/2 Age: 28 years	Participants walked on a treadmill for 20 min while using a smartphone. Lumbar repositioning error was measured via an electronic goniometer, and lumbar curvature was assessed using a spinal mouse, before and immediately after the task.	Lumbar spine repositioning error Lumbar curvature angle	Walking on treadmill for 20 min while using smartphone Lumbar repositioning error: increased (3.02 → 6.07) Lumbar curvature: no change	Walking while using a smartphone leads to increased lumbar repositioning errors immediately after the activity, though lumbar curvature remains unchanged.
Choi [33] (2021)	11/9 Age: 21 years	Participants walked on a treadmill under five different conditions: (1) normal walking without smartphone use (control), (2) one-handed smartphone browsing, (3) two-handed texting, (4) walking with one arm bound, and (5) walking with both arms bound.	Head sagittal angle Thorax sagittal angle Pelvis sagittal angle Thoracic kyphosis angle Lumbar lordosis angle Thorax transverse ROM Pelvis transverse ROM Lumbar erector spinae EMG	Browsing + walking/texting + walking vs. normal walking Lumbar erector spinae EMG: incrased by 16.5% during browsing, and 31.8% during texting Spinal sagittal kinematics: increased in thoracic kyphosis during texting (+1.5°), and browsing (+1.1°) Lumbar lordosis ROM: increased in texting (+1.4°), and browsing (+0.9°) Head flexion angle: increased in texting (39.3° vs. 0.4°) Pelvis and thorax transverse ROM: decreased during texting in thorax by 28.8% less (6.4° vs. 9.2° normal) Thorax ROM: decreased during texting by 28.8% (6.4° vs. 9.2° normal) Pelvis ROM: decreased during texting by 11.8% during texting (8.2° vs. 9.3° normal)	Smartphone use caused more thoracic kyphosis and lumbar lordosis. Smartphone use during walking increased lumbar erector spinae muscle activity by 16.5% (browsing) and 31.8% (texting).

Abbreviations: FHP, forward head posture; EMG, electromyography; VAS, visual analog scale; VP, vertebra prominens; GN, gaze neutral; S1H, smartphone one-handed; S2H, smartphone two-handed; CES, cervical erector spinae; UT, upper trapezius; B, Bimanual; AF, asymmetric finger; S, single-handed; AT, asymmetric thumb; VAS, visual analog scale; NF, neck flexion; HF, head flexion; GA, gaze angle; VD, viewing distance; TES, thoracic erector spinae; LT, lower trapezius; APDF, amplitude probability distribution function; ROM, range of motion; PPT, pressure pain threshold.

and

Table 2. Extracting relevant data from studies examining the effects of smartphone use on gait.

Author	Population (M/F)	Methods (Interventions)	Main Outcome Measures	Alteration of Parameters	Main Findings
Krasovsky [26] (2021)	14/15 Age: 26 years	Participants completed walking trials while texting or reading.	Gait speed Stride length Stride time Gait speed variability Words Text comprehension Task workload	Texting vs. reading during walking (dual-task condition): Gait speed: decreaed Stride length: decreased Stride time: slower rhythm Gait speed variability: decreased stability Text comprehension: decreased Perceived workload: higher in texting A dual-task condition was correlated with perceived task prioritization (r = 0.39–0.50) and cognitive flexibility (r = 0.55)	Smartphone use (texting) during walking results in decreased gait speed, increased gait variability, decreased text comprehension, and increased task workload.
Sajewicz [34] (2023)	20/22 Age: 21 years	Participants completed four walking conditions: (1) walking without a phone at a comfortable velocity, (2) walking without a phone at a fast velocity, (3) walking with a phone at a comfortable velocity, and (4) walking with a phone at a fast velocity.	Step length Step width Cadence Gait speed	Texting while walking vs. walking Step length: decreased Comfortable speed: 70.6 → 65.5 cm Fast speed: 81.3 → 74.4 cm Gait speed: decreased Comfortable speed: 1.36 → 1.27 m/s Fast speed: 1.87 → 1.67 m/s Cadence: decreased at fast speed while texting Step width: decreased at comfortable speed while texting	Smartphone use (texting) during walking induces decreased step length, step width, cadence, and gait speed.
Crowley [9] (2021)	11/9 Age: 27 years	Participants repeated six conditions consisting of self-selected normal and fast overground walking while texting on a mobile phone, talking or performing no concurrent task.	Gait speed Variability in trunk acceleration Sample entropy Maximum Lyapunov exponent	Walking only vs. walking while texting Root mean square ratio: Vertical (VT) at fast speed: increased Anteroposterior (AP): decreased Mediolateral (ML): no change Sample entropy (SaEn): VT axis: decreased while texting AP, ML axes: increased with speed Max Lyapunov exponent: VT and AP axes: increased while texting ML axis: non-significant	Higher gait speed induces increased sample entropy and trunk acceleration (vertical axis) and decreased the proportion of acceleration (anteroposterior axis). Walking while texting increased the maximum Lyapunov exponent along the vertical and anteroposterior axes. These findings indicate reduced dynamic stability of the trunk, and increased trunk variability.
Alapatt [24] (2020)	308 5 age groups: 20–29, 30–39, 40–49, 50–59, ≥60 years	Participants completed five walking conditions: (1) walking on a treadmill at a regular pace, (2) walking on a treadmill while using a mobile phone with one hand, (3) walking on a treadmill in a low-light condition, (4) walking on a treadmill while listening to favorite music using a headset, and (5) walking on a treadmill while engaged in a real voice call in their official language.	Gait speed	Walking vs. walking while texting by age groups Gait speed: decreased during walking while texting across all age groups Total population: 1.47 → 1.16 m/s (22.3%) Age ≥ 60: 1.42 → 1.00 m/s (30.4%) Age 50–59: 1.47 → 1.07 m/s (25.9%) Texting accuracy: an error rate was increased with age Age < 30: 0% errors Age 50–59: 62.7% errors Age ≥ 60: 81.0% errors	Gait speed was decreased while texting with increasing age; a percentage reduction in gait speed by 11% (20–29 yrs), 11% (30–39 yrs), 17% (40–49 yrs), 26% (50–59 yrs), 30% (≥60 yrs).
Hollman [35] (2007)	25/35 3 age groups: 25 years 48 years 81 years	Gait parameters were quantified using GaitRite (CIR Systems, Franklin, NJ, USA). In the dual-task condition, participants were required to spell five-letter words in reverse while walking across a walkway.	Gait speed Stride variability	Dual-task walking (backward spelling) vs. normal walking Gait speed: decreased (all age groups) Older adults: 20%↓ Middle-aged adults: 7%↓ Younger adults: 8%↓ Stride-to-stride variability in gait speed: increased Older adults: 2.9%↑ Middle-aged adults: 1.5%↑ Younger adults: no change Cognitive performance (spelling errors): similar across groups (non-significant), but in older adults: Cognitive error↑: Gait velocity↓ (r=–0.49) Cognitive error↑: Gait variability↑(r=0.53)	Dual-task walking results in decreased gait speed, and increased stride-to-stride variability in gait speed. Stride velocity variability was increased in older adults compared to younger groups.
Schabrun [25] (2014)	7/19 Age: 29 years	Participants walked on an 8.5 walkway ground under three walking conditions: (1) walking without the use of a phone, (2) reading text on a mobile phone, or (3) typing text on a mobile phone.	Lateral foot position Gait speed Joint ROM Stride length Stride frequency Lateral deviation	Walkig vs. reading vs. texting while walking Walking speed: texting < reading < control↓ Stride length and frequency: decreased while texting Lateral deviation: increased in an order of texting > reading > control Head flexion ROM: increased in both reading and texting while walking (~30°) Neck ROM (all planes): decreased by Texting < reading < walking Thorax ROM: decreased during texting Head–thorax ROM: increased (more head ROM) Pelvis–thorax ROM: decreased	Smartphone use (texting or reading) during walking results in greater lateral foot position, slower gait speed, greater head rotation ROM, less neck ROM, and more lateral deviation from a straight line.
Sarvestan [36] (2022)	15/14 Age: 28 years	Participants walked on a treadmill under six conditions: (1) normal walking, (2) normal walking in low-light conditions, (3) walking while looking at a phone, (4) walking while looking at a phone in low-light conditions, (5) walking and talking on a phone, and (6) walking and listening to music.	Joint angle Joint angle variability Center of pressure EMG of gluteus medius, rectus femoris, vastus medialis, biceps femoris, medial gastrocnemius, tibialis anterior	Normal walking vs. walking while looking at phone (WLP) vs. walking while looking at phone in low light conditions (WLLLP) vs. walking while talking on phone (WTP) vs. walking while listening to music (WM) Hip joint angle variability (λS, λL): increased in WLP and WLLLP Pelvis angle variability (λS, λL): increased in sagittal plane (WLLLP > NW, WM, WTP) Lower limb muscle activation variability (RF, VM, TA, GA, BF, GM): no change COM trajectory variability (λS, λL): no change	Smartphone use (condition 3) results in higher joint angle variability in the hip and pelvis. No center of mass position and EMG activation was observed between walking task conditions.
Brennan [37] (2020)	7/7 Age: 20 years	Participants completed five walking conditions of one single-task walking and four dual-task conditions: (1) walk + converse, (2) walk + read (simple), (3) walk + read (difficult), and (4) walk + text. Gait analysis was recorded with a motion capture system and peak sagittal plane lower extremity joint angles, gait velocity, and stride length were calculated.	Gait joint kinematics Gait speed Stride length	Walk+converse; walk+read; walk+text; normal walking Gait speed: decreased by task difficulty Single task: 1.41 m/s → walk + text: 1.04 m/s Stride length: decreased Single task: 1.29 m → walk + text: 1.09 m Peak hip flexion (initial contact): decreased Single task: 30.27° → walk + text: 27.27° Peak hip extension (terminal stance): de creased Single task: 13.08° → walk + text: 10.36° Peak plantarflexion (pre-swing): decreased Single task: 27.67° → walk + text: 19.83° Peak dorsiflexion (terminal stance): in creased Single task: 7.86° → walk + text: 9.87°	Smartphone use alters sagittal gait kinematics, reduces gait speed and stride length.
Giovanna [38] (2023)	20/25 Age: 22 years	Participants performed a balance task on a force platform. The impact of smartphone use was assessed during both a static test (on the force platform) and a dynamic test (Timed Up and Go; TUG). Participants were instructed to text a message and talk on a phone while standing or walking, and various variables were measured during the TUG test.	BMI Mini-mental state examination score Frontal assessment battery score Time of using the smartphone Postural balance (frontal sway, lateral sway, center of pressure sway) Frontal speed Lateral speed	No phone vs. texting vs. talking on the phone (tasks performed during standing or walking) Static standing postural control test Frontal sway: increased No phone: 1.9 cm Texting: 2.7 cm Talking: 3.9 cm Lateral sway: increased No phone: 1.7 cm Talking: 2.8 cm Center of pressure sway area: increased No phone: 2.3 cm2 Talking: 5.9 cm2 Dynamic walking test TUG test completion time: increased No phone: 9.2 s Texting: 11.8 s Talking: 11.1 s Number of steps: increased No phone: 13.2 Texting: 15.5 Talking: 14.9	Smartphone use (texting or talking) reduces both static (force plate) and dynamic (TUG) postural control tasks.
Lamberg [39] (2012)	M:13 Age: 26 years	Participants performed a dual task, such as talking or texting on a cell phone while walking, which may interfere with working memory and result in walking errors. At baseline, participants visually located a target 8 m ahead.	Gait speed Linear distance travel Lateral angular deviation from the start line	Walking while texting (TEXT) or talking (TALK) vs. walking without phone (WALK) Gait velocity: decreased TEXT: 33% (7.0 → 4.7 m/s) TALK: 16% (7.5 → 6.3 m/s) WALK: no change Lateral deviation: increased TEXT: 61% (68 → 108 cm) TALK: no change WALK: no change Linear distance traveled: increased TEXT: 13% (7.5 → 8.5 m) TALK: no change WALK: no change	Smartphone use reduces gait speed (texting: 33%; talking: 16%) and increases lateral deviation (61%) and linear distance traveled (13%).
Chen [29] (2018)	5/5 Age: 21 years	Participants engaged in two tasks: (1) walking and crossing an obstacle set at 10% of the participant’s height and (2) walking and crossing the same obstacle while responding to a text message. Whole-body motion data were collected using a 10-camera motion capture system.	Gait speed Obstacle clearance Postural sway	Obstacle crossing while texting (OC + texting) vs. obstacle crossing only (OC) Toe–obstacle clearance: increased Leading foot: 15.7 → 19.1 cm Trailing foot: 18.7 → 24.8 cm Foot placement: decreased Leading foot: 25.4 → 21.2 cm Trailing foot: no change Gait speed: decreased Approaching stride: 1.22 → 1.11 m/s Crossing stride: 1.10 → 0.94 m/s Peak COM forward velocity: 1.4 → 1.3 m/s Mediolateral COM distance: 4.5 → 6.2 cm	Smartphone use (texting) during crossing over the obstacle decreases gait speed, increases toe–obstacle clearances, and induces higher postural sway in the frontal plane.
Mourra [40] (2020)	20/28 Age: 25 years	Participants were selected to represent a range of smartphone-addiction proneness. Four smartphone-use conditions were simulated: (1) a control condition with no smartphone use, (2) an individual conversation condition, (3) a gaming condition, and (4) a group conversation condition.	Smartphone-addiction proneness scale Walking performance (missed stimuli and accuracy)	Walking performance measures (direction recognition task). Control (CC) vs. Individual conversation (ICC) vs. Gaming (GC) vs. Group conversation (GCC) Accuracy: decreased CC (baseline): 89% ICC: 86% GC: 81% (lowest) GCC: 84% Number of missed stimuli: decreased CC: 0.04 ICC: 1.40 GC: 2.42 (highest) GCC: 1.67 Psychological mediation: Emotional arousal (SAM scale): increased by GC > GCC > ICC > CC Arousal (mediated accuracy): decreased Arousal (missed stimuli): increased	Smartphone use while walking decreased accuracy on smartphone tasks and increases the number of missed stimuli. Higher smartphone addiction proneness scores were also prone to missing stimuli on smartphone use tasks.
Hashish [41] (2017)	7/13 Age: 39 years	Participants performed a series of walking trials that included a step-deck obstacle, consisting of at least three trials while texting and three trials without texting.	Gait speed Step width	Texting while ascending/descending stairs vs. no texting Stair ascent: decreased Ascent speed: 70→60 cm/s Dual-step toe clearance (vertical): 9→8 cm Dual-step toe clearance: 13→11 cm Forefoot toe distance dual-step: 28→24 cm Forefoot toe distance single-step: 6→5 cm Stair descent: decreased Descent speed: 82 → 71 cm/s Single-step heel clearance vertical: 18→17cm Single-step heel clearance forefoot:34→29cm Dual-step heel clearance forefoot: 27→21 cm Step width: no change	Smartphone use (texting) reduced gait speed (ascending and descending) and step foot clearance.

Abbreviations: VT, vertical; AP, anteroposterior; ML, mediolateral; NW, normal walking; WLP, walking while looking at the phone; WLLLP, while looking at the phone using one hand; WTP, walking while talking on phone; WM, walking while listening to music; RF, rectus femoris; VM, vastus medialis; TA, tibialis anterior; GA, gastrocnemius, BF, biceps femoris; GM, gluteus medius; TUG, timed up and go; BMI, body mass index; TEXT, texting; TALK, talking; OC, obstacle crossing; COM, center of mass; CC, control; ICC, individual conversation; GC, gaming; GCC, group conversation.

. Figure 2 and Figure 3 conveniently illustrate the overall impact of smartphone use on posture and gait, providing a comprehensive overview at a glance.

4. Discussion

Since the widespread adoption of smartphones in 2009, numerous studies over the past 15 y have explored their effects on human posture and gait. However, recent systematic reviews directly aligned with this study’s objectives—specifically, those examining smartphone-induced spinal posture and gait changes among healthy individuals—remain limited to reviews published in 2020 and 2023 [27,37]. Bruyneel’s 2020 review comprehensively assessed 46 individual studies related to smartphone-induced changes in posture and gait [27]. The current review builds on this by incorporating recent individual studies published after October 2020, which were not included in earlier reviews [5,9,10,15,18,26,30,33,34,36,38]. Bruyneel’s more recent 2023 review focused on smartphone-related gait alterations and included data from healthy participants, older adults, and individuals with cognitive impairments [27]. The current review extends this work [25] by incorporating additional studies on smartphone-induced gait alterations [27,34,35,36,38,39,40,41,42,43] and exclusively includes research involving healthy individuals, excluding studies on populations with specific clinical disorders. Smartphones have become indispensable in modern life; yet, while offering convenience, they also negatively affect physical functioning, underscoring their dual impact. Therefore, this study aims to provide a comprehensive synthesis of the literature on the effects of smartphone use on posture and gait. Through a narrative analysis, this review systematically evaluates how increased smartphone usage—both in frequency and duration—affects spinal postural alignment and key gait parameters, including walking speed [5,14,15,20,25].

4.1. Effect of Smartphone Use on Static Posture

4.1.1. Effect of Smartphone Use on Cervical Spine Posture

Seven studies have investigated the effects of smartphone use on cervical spine posture [5,11,12,13,14,15,16,17]. Prolonged smartphone use has been shown to significantly increase cervical flexion angles, thereby elevating the risk of posture-related cervical issues [15,17]. For example, using a smartphone while seated without backrest support increased cervical head flexion by approximately 2° [5]. Similarly, individuals who used smartphones for more than 4 h per day exhibited forward head posture angles that were, on average, 9° greater than those who used them for less than 4 h [14]. Collectively, these findings indicate that smartphone use shifts the head position anteriorly, increases cervical flexion, raises muscular loading around the cervical spine, and slows cervical nerve conduction velocity [14]. Additional studies have shown that smartphone usage exceeding 3 h daily contributes to greater cervical flexion angles, increasing biomechanical load and elevating the risk of cervical intervertebral disk herniation and degeneration [44,45].

4.1.2. Effect of Smartphone Use on Thoracic Spine Posture

Four studies have assessed the impact of smartphone use on thoracic spine posture [10,15,30,31]. The results indicate that thoracic flexion angles increase by approximately 5° with every additional 5 min of smartphone use, particularly during durations of 5, 10, and 15 min. These findings have been consistently supported across multiple studies examining thoracic posture during smartphone use [10,15,30,31].

4.1.3. Effect of Smartphone Use on Lumbar Spine Posture

Four studies have examined lumbar spine posture in relation to smartphone use [15,30,32,33]. Prolonged smartphone use has been associated with alterations in lumbar lordosis [15] and an increased prevalence of lumbar musculoskeletal disorders, including lumbar disk herniation, spinal stenosis, and chronic lower back pain [30,32]. The prolonged maintenance of static postures during work has been identified as a significant risk factor contributing to the increased prevalence of lumbar disorders [30]. Office workers who sit for prolonged periods may face a heightened risk of lumbar disorders due to the increased frequency and duration of smartphone use [30]. Forward trunk flexion during smartphone use increases posterior displacement forces on lumbar intervertebral disks, heightening the risk of herniation and joint stress [15]. Additionally, treadmill-based studies have shown that smartphone use can increase lumbar repositioning errors by approximately 3°, likely due to proprioceptive deficits [32]. These findings were attributed to deficits in the proprioceptive sense associated with lumbar repositioning errors [32]. Considering these results, smartphone use may pose risks by potentially causing lumbar dysfunction through proprioceptive deficits and increased joint stress. A study examining the association between spinal curvature and smartphone use found that using a smartphone with one arm restrained reduced lumbar lordosis angles by approximately 0.07 degrees. This reduction in the lumbar lordosis angle led to increased erector spinae muscle activation, potentially causing various lumbar musculoskeletal issues, such as lumbar disk disorders [33].

4.1.4. Effect of Smartphone Use on Muscle Activation and Muscle Fatigue

Four studies have investigated the impact of smartphone use on muscle activation and muscle fatigue [14,17,18,21]. Previous research focusing on cervical muscle activation revealed no statistically significant differences in activity among four muscle groups: the right splenius capitis, right upper trapezius, left splenius capitis, and left upper trapezius during maximal cervical flexion postures associated with smartphone use. However, higher average muscle fatigue values—approximately 0.2—were noted in the right splenius capitis, left splenius capitis, and left upper trapezius muscles. These findings indicate that maintaining a neutral cervical posture may be more effective in reducing muscle fatigue than adopting an excessively flexed cervical position [21]. Moreover, a study assessing the bilateral muscle activation of cervical spinal extensor muscles at four different smartphone viewing angles (0°, 15°, 30°, and 45°) found that maximum voluntary isometric contraction increased by approximately 2% with each 15° increment in the viewing angle [18]. Prolonged smartphone use, particularly at angles around 50°, can lead to the hyperactivation of cervical extensor muscles, potentially resulting in headaches and increased cervical disk pressure. Additionally, the excessive activation of the bilateral upper trapezius muscles may exacerbate neck and shoulder pain, further intensifying forward head posture and kyphosis [14,17].

4.2. Smartphone and Gait

4.2.1. Effect of Smartphone Use on Walking Speed

Six studies have reported decreased walking speeds associated with smartphone use [24,26,29,34,35,39]. Compared to single-task walking without a smartphone, dual-task walking—such as reading text messages—resulted in an approximate reduction of 0.16 m/s in walking speed [26]. Additionally, a study involving 308 participants aged 20 to 60 y indicated an average reduction of 0.31 m/s while sending text messages [24]. These findings underscore smartphone use as a significant factor contributing to reduced walking speed, highlighting substantial risks associated with texting while walking.

Notably, older adults (aged 60 and older) experienced a more pronounced decrease in walking speed, averaging 0.4 m/s slower while texting. Specifically, among older individuals, walking speed dropped by approximately 1.3 m/s when using smartphones [35]. Such outcomes illustrate that smartphone use leads to cognitive distraction and diminished situational awareness. Activities like sending or reading messages significantly impair walking speed due to diverted visual attention and cognitive overload. Therefore, it is recommended to perform these tasks while stationary. Research has also shown that smartphone use during obstacle negotiation alters the center of mass, leading to gait imbalance, increased visual distraction, and heightened pelvic movement, all of which contribute to gait instability [29]. Increased smartphone addiction further diminishes gait attention and significantly raises the risk of accidents [40]. Reduced walking speed poses safety concerns, particularly at crosswalks where focused attention is critical [34].

4.2.2. Effect of Smartphone Use on Gait Biomechanics

Four studies have examined gait biomechanics, specifically kinematic, kinetic, and electromyographic variables, in relation to smartphone use [25,33,37,38]. In a gait kinematics study, texting while walking resulted in a 4.4-degree reduction in pelvic rotation and a 1.82-degree increase in head rotation [25]. Another study comparing single-task walking with a walk-and-converse task observed a reduction in ankle dorsiflexion by 0.15 degrees and hip flexion by 0.14 degrees [37]. These findings suggest that gait kinematics can vary depending on specific smartphone use tasks. Regarding kinetics, the texting group exhibited an increased center-of-pressure sway area by approximately 1.4 cm compared to the no-cell-phone group during walking [38]. Another study demonstrated a 28.8% reduction in thoracic rotation when participants walked while using smartphones compared to normal walking conditions. This reduction in thoracic rotation increased thoracic muscle fatigue, exaggerated thoracic kyphosis, and consequently heightened pain in the thoracolumbar region [27]. Since dual tasks can induce kinematic and kinetic changes, additional studies are required to further investigate other biomechanical variables affecting gait alterations.

4.2.3. Effect of Smartphone Use on Gait Parameters

Four studies have explored the effects of smartphone use on gait parameters, specifically focusing on step length and width [7,25,34,43]. Notably, a comparison of two trials—walking without a phone at a comfortable velocity and walking with a phone at a similar velocity—demonstrated a reduction of approximately 4 cm in both right and left step lengths, alongside an increase in step width of approximately 0.93 cm [34]. Furthermore, participants who engaged in texting while walking exhibited a 0.2 m decrease in step length relative to those walking without smartphone use [25]. These findings indicate that alterations in gait kinematics, exacerbated by reduced arm swing due to screen focus, likely contribute to modifications in step length and width.

Research on diminished gait parameters has shown that changes in stride length, cadence, and double support time culminated in an approximate 33.9% reduction in walking speed compared to conditions without smartphone use. This decline in speed and stability is associated with decreased attentiveness, thereby potentially heightening fall risk [43]. Prior studies have similarly reported reduced foot clearance and compromised gait stability during smartphone use while walking [7]. Collectively, these findings suggest that negative alterations in gait parameters may decrease stability, mimic patterns observed in older populations, slow movement, impair attention, and subsequently elevate fall risks. Accordingly, exercising caution while using smartphones during ambulation is strongly recommended.

4.2.4. Effect of Smartphone Use on Cognitive Function

Three studies have investigated the impact of smartphone use on cognitive function [25,26,41]. One such study evaluated text comprehension and cognitive flexibility among 30 participants engaged in various tasks, including sending text messages, reading texts on smartphones, and writing tasks [26]. The results indicated that engaging in dual tasks involving texting while walking resulted in a reduction of approximately 23% in text comprehension compared to single-task writing or dual-task conditions involving simultaneous writing and texting with a smartphone [26]. The resultant decrease in gait stability during dual-task performance may contribute to diminished text comprehension, thereby impairing executive function and reflecting an overall decline in cognitive performance.

Moreover, additional research has shown that continuous smartphone use adversely affects cognitive function, correlating with decreased ability to walk in a straight line, attention deficits, heightened collision risk, and an increased likelihood of traffic accidents [25]. These findings suggest that activities such as reading or sending text messages may exacerbate gait variability, indicating a reduction in cognitive flexibility. Other studies have similarly reported a heightened risk of falls associated with cognitive impairment, particularly noting challenges in executing motor tasks, such as ascending and descending stairs [41].

4.3. Limitations of the Study

This study has some limitations that should be carefully considered. First, future research should include a greater number of studies capable of providing detailed evaluations of joint function. Prior investigations into posture and gait alterations have revealed three key limitations. Firstly, data collection regarding participants’ educational levels and cognitive status according to age groups was insufficient [20]. Secondly, certain studies failed to adequately reflect the unique characteristics of participants [42]. Thirdly, many studies have been limited to specific age groups or genders [7]. A specific limitation of the current study is the relatively small sample size, highlighting the need for larger cohorts in future longitudinal research. Additionally, while it is clear that smartphone use affects posture and gait, these changes may progressively impact spinal kinematics and overall physical function. Thus, follow-up studies are needed to investigate the long-term consequences of these alterations.

Beyond musculoskeletal concerns, future research should aim to collect standardized, comprehensive data using advanced technologies that incorporate neuromuscular and anatomical modeling. For instance, AI-based systems capable of visually displaying individualized neuromuscular and anatomical dysfunction metrics could offer targeted recommendations for correcting posture and gait.

Furthermore, the clinical applicability of findings should be expanded by incorporating diverse age groups—from children to older adults—into research protocols. Additional research is needed to determine which age groups are most vulnerable to posture- and gait-related musculoskeletal changes due to smartphone use and delineate how the duration of use influences these outcomes across different ages.

5. Conclusions

This narrative review primarily aimed to systematically examine the biomechanical and functional consequences of smartphone-induced posture and gait alterations on physical function. Based on the synthesis of 27 selected studies, this review identified that excessive smartphone use contributes to significant postural deviations across the cervical, thoracic, and lumbar spine, increased muscle fatigue, and impaired neuromuscular efficiency. Gait parameters—including walking speed, stride length, and joint kinematics—were also negatively affected, particularly under dual-task conditions such as texting while walking. These findings suggest that smartphone overuse poses substantial risks to musculoskeletal health, functional mobility, and overall safety. The evidence emphasizes the need for comprehensive research into the cumulative effects of posture and gait disturbances and their long-term implications for physical functioning. Additionally, this review highlights the importance of incorporating both postural and gait assessments in future studies to inform clinical practices and public health policies. Further longitudinal and interventional research is needed to better understand the progression and impact of these biomechanical changes over time.