Mobile technology and cumulative trauma symptomology among millennials

Abstract

Introduction

Technology use among the millennial population is increasing and related postural compromise may lead to cumulative trauma disorder symptomology. The aim of this study was to explore trends of hand-held mobile technology use and upper extremity cumulative trauma disorder symptomology among a sample of millennials.

Methods

A convenience sample of graduate students (n = 42) was used for the study. Demographic and technology use information was obtained through self-report using the smartphone screen time tracking feature. Cumulative trauma disorder symptomology was assessed through administration of various orthopedic special tests.

Results

On average, participants spent 2 h and 23 min per day using hand-held mobile devices. Out of 42 participants, 54.8% tested positive for at least one orthopedic special test. The symptomatic group spent 2 h and 29 min using hand-held mobile devices, while the asymptomatic group spent 2 h and 4 min. The most common positive orthopedic special tests were Finkelstein’s test (n = 19; 36%), hyperabduction (Wright’s) test (n = 13; 25%), and the elbow flexion test (n = 10; 18.9%), indicating symptoms associated with De Quervain’s tenosynovitis, thoracic outlet syndrome, and cubital tunnel syndrome, respectively.

Discussion

Results were consistent with prior research on time spent using hand-held mobile technology and cumulative trauma disorder among millennials. Additionally, a difference in mean time spent using mobile technology between the asymptomatic and symptomatic groups was found, suggesting a relationship which warrants further research.

Keywords

Orthopedics quantitative research trauma

Introduction

In 2018, the Nielsen Total Audience Report released first quarter data examining overall media consumption from various digital platforms by Americans across the lifespan. They found increased technology use across all age groups, but the young adult population, classified as 18- to 34-year-olds, spent the most time with digital devices when compared to other demographics. Time spent across all media increased with 3 h and 48 min per day spent on digital devices, with application/website usage on smartphones accounting for 62% (2 h, 22 min) of that time for adults (18+).¹ Specifically, young adults spent 43% of their day using digital devices, more time than any previous generation consuming media from a smartphone platform.² The Pew Research Center and American Life Project found that 97% of young adults (age 18–24 years) with cell phones send or receive approximately 110 text messages per day.³ Additionally, text messaging has been identified as the primary mode of communication among university students.⁴ The multitude of usability options available via hand-held devices has encouraged users to spend the majority of their time on these devices.⁵ Whilst hand-held devices have revolutionized communication, there may also be a link between technology use and musculoskeletal issues in the upper extremity. Sharan et al.⁵ reported “the incidence of musculoskeletal disorders of the UE [upper extremities] have been increasing across the globe due to prolonged forceful, low amplitude, repetitive use of hand-held devices”.

Hand-held devices are defined as “devices which are used for communication and entertainment purposes such as media, internet access and gaming”.⁵ In today’s society, hand-held technology has become an increasingly important form of education, communication, and social participation, which facilitates occupational engagement and quality of life. However, the convenience and efficiency of technology may contribute to cumulative trauma disorders (CTDs) of the upper extremity (UE), related to postural compromise and repetitive motion. Upper extremity CTDs may be defined as conditions resulting from wear and tear of muscles, tendons, and nerve tissues of the thumb, elbow, wrist, fingers, hand, forearm, shoulder, and the arm. Due to repetitive motion, the anatomical structures listed have limited ability to heal causing discomfort, pain, and functional impairment over time.⁶ Millennials, defined as individuals born between the years 1981 and 1996,⁷ may be at a higher risk of technology-related CTD symptoms, having integrated technology into academic and daily life from a young age.

Symptoms related to CTDs (pain, tenderness, joint stiffness, muscle weakness, and/or paresthesia) may impact an individual’s ability to work or participate in meaningful occupations. Along with occupational limitations, CTDs may also cause financial strain. Low back pain and upper extremity injuries are known to be expensive to treat, but the cost for upper extremity CTDs related to computer usage are 80% more expensive than other workers’ compensation claims.⁸ Prior research reveals prevalence of specific CTDs, presented in Table 1.

Table 1.

Prevalence of cumulative trauma disorders.

Cumulative trauma disorder	Population	Prevalence
Cubital tunnel⁹	General population	24.7 per 100,000
Thoracic outlet syndrome¹⁰	General population of male and female	Total pop: 1–2%3:1 female/male ratio
De Quervain’s Tenosynovitis¹¹	18- to 25-year-old mobile phone users	46%
Carpal tunnel¹²	General population	276 per 100,000 per year9.2% in women and 6% in men
Medial epicondylitis¹³	General populationOccupational settings	1%1.5–8.2%
Lateral epicondylitis¹⁴	General population	15.1 cases per 10,000
Carpometacarpal arthritis¹⁵	General population	20–65%

Posture whilst using hand-held technology, also referred to as mobile tech posture, typically involves rounding of the shoulders with the neck and elbows flexed, wrist ulnarly deviated, with frequent repetitive use of the thumb. Mobile tech posture deviates from ideal posture, which can contribute to various pathology and musculoskeletal imbalances.¹⁶ This positioning may contribute to adaptive shortening of shoulder anterior musculature, weakness of the scapular stabilizers, cumulative trauma from repetitive motions, and risk for injury along the UE kinetic chain.

Graduate students may be particularly susceptible to musculoskeletal issues associated with mobile tech posture due to demands in areas of education, social participation, and leisure activities. Therefore, the purpose of this study was to examine trends of technology use and upper extremity CTD symptomology among a group of millennial graduate students.

Methods

The study used an observational cross-sectional design as to describe mobile technology use and upper extremity CTD symptomology among a sample of healthy graduate students.

A convenience sample of graduate students was recruited via university email for the study. To maintain anonymity during data collection and analysis, participants were assigned numbered participant codes. All participant information was kept in locked storage cabinets on university property, and password protected devices.

Upon ethical approval from the Institutional Review Board of Huntington University, a convenience sample of graduate student participants were recruited for the study via email. The inclusion criteria were healthy graduate level students enrolled in the Huntington University occupational therapy doctoral program between the ages of 22 and 38 who used a smartphone. Participants who had a current, previously diagnosed upper extremity pathology were excluded. Demographic and technology use information was obtained using self-report. Participants reported phone usage data from their smartphone screen time tracking feature. Standardized instructions were given as a part of survey completion to obtain usage data. Participants also self-reported estimated laptop use, providing a gross approximation of additional time spent using technology outside of interaction with a mobile device. Estimates included in-class use (at an ergonomically designed student workstation) and outside of class (unknown positional setup). Laptop use is presented as a secondary finding with the focal point of findings highlighting verifiable use of mobile technology.

Information related to CTD symptomology was obtained through orthopedic special tests including: Wright’s test,¹⁷ elbow flexion test,¹⁸ Maudsley’s test, medial epicondylitis test, Phalen’s test,¹⁹ Finkelstein’s test,²⁰ and Lever test.²¹ These orthopedic special tests were chosen based on clinical relevance, sensitivity, and specificity. Table 2 gives a description of individual special test technique and psychometric properties. As the various special tests are not diagnostically conclusive, with varying degrees of specificity and sensitivity, the purpose was to assess symptomology, as opposed to definitive diagnosis, among the sample. The orthopedic special tests were performed by occupational therapy (OT) students following a competency checkout with a licensed OT certified hand therapist (CHT) and under the supervision of a licensed OT/CHT during data collection. Participants were categorized as “asymptomatic” if none of the orthopedic special tests were positive and “symptomatic” with one or more positive special test(s).

Table 2.

Orthopedic special test technique and psychometrics.

Assessment	Technique	Sensitivity	Specificity
Hyperabduction (Wright’s) test¹⁷	Passive end-range shoulder abduction with palpation of radial pulse; monitoring for pain and/or parasthesia in the upper extremity	Pulse: 70%Pain: 90%	Pulse: 53%Pain: 29%
Elbow flexion test¹⁸	Passive elbow flexion; monitoring for parasthesia through ulnar nerve distribution of hand	75%	Unknown
Maudsley’s test	Resisted extension of the 3rd digit; monitoring for pain at extensor origin/lateral epicondyle	Unknown	Unknown
Medial epicondylitis test	Elbow extended with forearm supinated; passive wrist and digit extension; monitoring for pain at flexor origin/medial epicondyle	Unknown	Unknown
Phalen’s test¹⁹	Passive wrist flexion; monitoring for parasthesias through median nerve distribution of hand	34–77%	40–100%
Finkelstein’s test²⁰	Thumb held flexed in palm by digits with active ulnar deviation of wrist; monitoring for pain at 1st dorsal compartment	81–100%	50–100%
Lever test²¹	Radial and ulnar mobilization of 1st metacarpal; monitoring for pain and crepitus at CMC	82%	81%

Statistical analysis

Descriptive statistics were used to reflect demographic characteristics, time spent using mobile technology, and UE CTD symptomology of the sample. Following review of CTD symptomology assessment, participants were assigned to two groups, symptomatic (one or more positive special test(s)) and asymptomatic (no positive special tests). Mean time spent using hand-held mobile technology was compared between the symptomatic and asymptomatic group. The range of each group was determined to demonstrate the variability of the data distribution. Additionally, prevalence of specific CTD symptomology was described for the symptomatic group.

To examine association between special test results, two-tailed Fisher’s exact tests were performed with an alpha of 0.05 to assess statistical significance. For cases where a significant association was found, an odds ratio (OR) was calculated, as well as the 95% confidence interval (CI) for the odds ratio. A Haldane–Anscombe correction was applied in cases where a cell within the 2 × 2 contingency table had a “0” count.²²

Results

A total of 46 participants completed the demographic and technology self-report survey. The average age of the sample was 24 years (SD = 1.86) with two male and 44 female participants (Table 3). The predominant female representation in the sample reflects the high ratio of females to males among occupational therapy students from which the sample of convenience was drawn. The majority of participants were predominantly right handed (n = 41; 89.1%), 2nd year graduate students (n = 28; 60.9%), and White (n = 39; 85%) (Table 3). A total of 41 individuals participated in the orthopedic special test assessment and completed the demographic and technology use survey. Due to technological criteria, one participant was excluded from phone use data collection, but was included in the orthopedic special test assessment and demographic survey.

Table 3.

Sample demographics.

Characteristics	Number or Score
Participants	46
Mean age (y)	24
Gender
Male	2 (23.0%)
Female	44 (95.7%)
Handedness
Right	41 (89.1%)
Ambidextrous	1 (2.2%)
Left	4 (8.7%)
Year in graduate program
1st	17 (37.0%)
2nd	28 (60.9%)
3rd	1 (2.2%)
Ethnicity
Hispanic or Latino	3 (6.5%)
Native American/American Islander	1 (2.2%)
Black or African American	2 (4.3%)
Asian/Pacific Islander	1 (2.2%)
White	39 (84.8%)

On average the sample (n = 41) spent 2 h and 23 min per day using mobile hand-held technology (Table 4). Additionally, the majority of the sample reported laptop usage inside the classroom as 1 to 10 h per day, and 1 to 5 h per day outside of the classroom (Table 5).

Table 4.

Daily hand-held mobile device use (minutes).

Sample	(n)	Mean	Range	Standard dev.
Entire sample	41	143.3	6.2–378.6	70.4
Symptomatic group	21	149.4	54.2–378.6	72.5
Asymptomatic group	16	124.1	6.2–240.9	69.2

Table 5.

Self-reported laptop use.

Whole sample	Laptop data	Number or score
	Sample size (n)	41
	Reported time spent using laptop in class
	1–5 h	18 (39.1%)
	6–10 h	17 (37.0%)
	7–15 h	8 (17.4%)
	16+ h	3 (6.5%)
	Reported time spent using laptop outside of class
	1–5 h	32 (69.6%)
	6–10 h	7 (15.2%)
	7–15 h	6 (13.0%)
	16+ h	1 (2.2%)

A total of 42 participants were able to complete the orthopedic special test assessment, with more than half of the sample (54.8%) testing positive for at least one orthopedic special test, suggesting UE CTD symptomology. The most common positive orthopedic special tests were Finkelstein’s test (n = 19; 36%), hyperabduction (Wright’s) test (n = 13; 25%), and the elbow flexion test (n = 10; 18.9%), indicating symptoms associated with De Quervain’s tenosynovitis, thoracic outlet syndrome, and cubital tunnel syndrome, respectively (Table 6).

Table 6.

Frequency of positive orthopedic special tests.

Orthopedic special test	Frequency of positive test (left and right)	Percentage
Medial epicondylitis test	2	3.8
Maudsley’s test	2	3.8
Elbow flexion test	10	18.9
Phalen’s test	7	13.2
Hyperabduction (Wright’s) test	13	24.5
Finkelstein’s test	19	35.8
Lever test	0	0.0
Total	53

On average, the participants who did display UE CTD symptomology, categorized by at least one positive orthopedic special test (n = 23), spent 2 h and 29 min (149 min) using mobile technology, and the participants who did not display UE CTD symptomology (n = 19) spent 2 h and 4 min (124 min) using mobile technology per day (Table 4). There was a 25-minute difference spent using hand-held mobile technology per day between the symptomatic and asymptomatic participants; however, this finding was not statistically significant (p < 0.05).

A statistically significant association was found between the medial epicondyle and elbow flexion tests (p = 0.03; OR = 29.62; 95% CI: 1.27, 689.81), indicating increased odds of a positive medial epicondylitis test for participants with a positive elbow flexion test. An association was also identified between Phalen’s and Finkelstein’s tests (p = 0.01; OR = 16.50; 95% CI: 1.62, 168.49), indicating increased odds of a positive Phalen’s test for participants with a positive Finkelstein’s test. There were no other statistically significant associations between tests (p ≥ 0.18).

Discussion

The results of this study support prior research regarding mobile technology use and CTD symptoms among millennials. The large-scale Nielsen Total Audience Report, based on modeling representative of the entire U.S. population, found adults (18+) spend an average of 2 h, 22 min using smartphone technology while the 18- to 34-year-old demographic spends slightly more time with the same technology (2 h, 34 min). The findings of the current study concur, with the sample spending 2 h, 23 min using smartphone technology, representing a substantial portion of waking hours.¹

Dockrell, Bennett, and Culleton–Quin found 52.8% of students who utilize computers (desktop or laptop) were found to have musculoskeletal symptoms related to computer use. Though a larger sample (n = 241), the symptoms were identified solely based on self-report using the Nordic Musculoskeletal Questionnaire without further clinical assessment.²³ The results of the current study build on these subjective findings with additional orthopedic special testing providing similar evidence of symptomatic trends (54.8% “symptomatic”). Though the special tests were not diagnostically conclusive, a positive response included pain or parasthesias, confirming symptoms consistent with the particular cumulative trauma disorder. Interestingly, both studies utilized a group of millennials who were occupational and physical therapy students. That the self-report and orthopedic special test rates of symptomology are nearly identical with a similar, albeit cross-cultural, demographic lends validity to increasing rates of cumulative trauma symptoms with increased technology use as the potential common contributor.

Furthermore, participants that tested positive for one or more orthopedic special test(s) (symptomatic group; n = 21) demonstrated more time spent using mobile technology (149 min per day) versus the asymptomatic group (124 min per day). Although not statistically significant (p < 0.05) for this sample, further examination may be warranted. Perhaps there is a threshold of time for which one can spend interacting with mobile technology, which is less likely to contribute to cumulative trauma symptoms or other variables which may contribute.

The symptomatic trends also represent potential impact on work and leisure, common occupations among millennials. The aforementioned study also found self-reported negative effect to work (18.3%) and leisure activities (23.6%) among the sample.²³ These statistics highlight the potential impact of CTDs, extending beyond discomfort, into functional impairment. Additional research may also focus on the qualitative impact of CTD symptoms on overall well-being, focus, and motivation.

The predominant positive orthopedic special tests were Finkelstein’s, hyperabduction (Wright’s), and elbow flexion. These specific symptoms and potential underlying pathologies (De Quervain’s tenosynovitis, thoracic outlet syndrome, and cubital tunnel syndrome) align with anatomical risk factors identified by prior research describing mobile tech posture through goniometric measurement.¹⁶ The wrist presented in ulnar deviation with the thumb abducted, predisposing the abductor pollicis longus (APL) and extensor pollicis brevis (EPB) to cumulative trauma with repetitive texting. Additionally, significant scapular protraction and cervical spine flexion was identified, with potential neurovascular compression in the axilla area (thoracic outlet syndrome). Lastly, static elbow flexion at 90° was also identified, increasing pathological forces on the ulnar nerve at the cubital tunnel. These described and clinically-accepted positional anatomical risk factors align with findings of the study regarding symptomology. Tests for epicondylitis, carpal tunnel syndrome, and thumb carpometacarpal (CMC) osteoarthritis were not prevalent and were not identified as anatomical risk factors.

The statistically significant association found between the medial epicondylitis and elbow flexion test supports prior research, suggesting ulnar neuropathy may be concomitant with medial epicondylitis, particularly in individuals sustaining repetitive force to the medial elbow.²⁴ While carpal tunnel syndrome and De Quervain’s tenosynovitis are both associated with repetitive use of the hands, the two conditions are not frequently concomitant, relative to other pathologies.²⁵ These results were supplementary to the main findings of the study and should be considered relative to the small sample size.

Confirming prior identified trends regarding mobile technology use and CTDs, findings also raise practical clinical considerations. Clinicians working with the millennial population may want to be aware of and screen for CTDs as well as implement interventions to discourage prolonged postural compromise. Screen time tracking of mobile device use also provides the opportunity to increase awareness of time spent using mobile technology and adjust behaviors as necessary to prevent undesired impact. As specialist clinicians addressing upper extremity functional trends, pathology, and intervention, CHTs are uniquely qualified to address this seemingly universal trend and its potential impact.

Limitations

There are a number of limitations that may have impacted the findings of this study. The sample was smaller and comprised predominantly female students in a single discipline, limiting generalizability. Additionally, the orthopedic special tests utilized presented with various levels of sensitivity and specificity, with the potential for a false positive or false negative result.

Conclusion

The findings of this study strongly align with prior research regarding trends of technology use and cumulative trauma symptoms among millennials. The descriptive trends encourage further empirical examination of the relationship between technology use and cumulative trauma disorders among millennials and encourage clinical awareness.

Footnotes

Acknowledgements

The authors would like to acknowledge the Huntington University OTD Program faculty and students for their support of this study.

Contributorship

NS conceived and designed the study. All authors contributed to data collection, data analysis, article preparation, and revisions.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

Ethical approval for this study was obtained from the Huntington University Institutional Review Board (Case #10–8-18)

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Guarantor

NS.

Informed consent

Written informed consent was obtained from all subjects before the study.

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