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Haqueetal.
Bulletin of Faculty of Physical Therapy (2024) 29:39
https://doi.org/10.1186/s43161-024-00197-4
ORIGINAL RESEARCH ARTICLE Open Access
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Bulletin of Faculty
of Physical Therapy
Eects ofAndroid phone vs. iPhone
use onBlackBerry thumb symptoms
amonguniversity students inBangladesh
Md Ariful Haque1,2, Liton Baroi3* , Ismat Ara Chowdhury Koly4, Md Shakibul Hasan5, Faiza Mahmud6,
Sifat Ara Eva7, Moinul Karim Labib6, Hazika Tuz‑Zohura Nafisa8, Salwa Islam9, Irfat Islam Eva10,
Md. Rafiqul Islam11, Lita Bose12 and Faming Tian13
Abstract
Background In Bangladesh, the most prevalent musculoskeletal condition among office employees is consid‑
ered as BlackBerry thumb (BBT). Alike official perspectives, our educational system was significantly regulating
with the digital interfaces at COVID‑19 lockdown, where a greater reliance on Android phones were experienced
among the adults. Numerous studies have been conducted in studying the incidences of BBT in young individuals
as a result of hazards of Android phone usage (HAPU) in Bangladesh.
Objective This research sought to determine the relationship between BBT symptoms and the risks associated
with the using Android phones among Bangladeshi university students.
Methods A nationwide cross‑sectional study was undertaken on a group of university students between the ages
of 18 and 25 to determine if BBT symptoms were present based on the Finkelstein test and HAPU, which were
also assessed using a well‑designed questionnaire. We calculated the crude and adjusted prevalence ratios (aPR)
and used a generalized linear model from the Poisson family, using their respective 95% confidence intervals (CI).
Results There were 2455 individuals in this research, with a median age of 20 and an interquartile range (IQR) of 19
to 23. Of them, 1185 males (48.27%) and 1270 women (51.75%) made up the study’s participant population. Physi‑
cal exams showed that 1300 individuals had positive Finkelstein test results (52.95%), whereas 1040 people had
occasional risks from using an Android phone and 115 participants had occasional risks from using an iPhone. In
our generalized linear model, we observed that participants with occasional and frequent HAPU had higher rates
of BBT symptoms than responders without HAPU (aPR = 1.73, 95% CI: 1.47–2.05, and aPR = 1.61, 95% CI: 1.29–2.00),
respectively.
Conclusion The current study found that Bangladeshi university students experiencing BlackBerry thumb symptoms
were more likely to have risks associated with using Android phones.
Keywords BlackBerry thumb, De Quervain disease, Smartphone, Android phone, University students, Bangladesh
*Correspondence:
Liton Baroi
litonbaroi0991@gmail.com
Full list of author information is available at the end of the article
Page 2 of 10
Haqueetal. Bulletin of Faculty of Physical Therapy (2024) 29:39
Introduction
e COVID-19 outbreak and the lockdown guidelines
worldwide have bought about some major challenges
socially, economically, physiologically, and psychologi-
cally in people’s lives. One significant lifestyle shift was
the aggravated use and reliance on Android phones to
access information, as an educational platform, means
of communication, and entertainment [1]. e posture
of smartphone usage requires fixing the device with
hands, looking at the device, and repetitive and consist-
ent thumb and wrist movements [2]. Prolonged dura-
tion and frequency of Android phone use with frequent
movement of the upper limbs are major risk factors for
musculoskeletal manifestations [3], such as BlackBerry
thumb [3]. Prolong or repetitive body movements are
highly responsible for musculoskeletal pain [4–6]. In this
pandemic, many of one affected on musculoskeletal dis-
order directly or indirectly in Bangladesh [7].
BlackBerry thumb is a painful inflammatory condi-
tion involving the tendons of the abductor pollicis longus
and extensor pollicis brevis in the first dorsal compart-
ment. Although the BlackBerry thumb syndrome origin
is debatable, it is attributed to myxoid degeneration with
fibrous tissue deposits and increased vascularity [3]. A
positive Finkelstein test may be used for the diagnosis of
this condition [8]. BlackBerry thumb syndrome is often
associated with repetitive wrist movements, specific
motion requiring thumb radial abduction, and simul-
taneous extension and radial wrist deviation [8]. Blunt
trauma, biomechanical compression, overexertion from
repetitive work activities, anatomical variations or abnor-
malities, genetic predisposition, cold temperatures, and
pathogens are said to be some of the potential causes of
BlackBerry thumb [8]. e predicted BlackBerry thumb
prevalence is 0.5% and 1.3% for men and women respec-
tively [15], with peak prevalence among the younger gen-
eration [9].
During the COVID-19 pandemic, preventive meas-
ures such as countrywide lockdowns, social distanc-
ing, closure of educational institutes, and restrictions in
movements to limit the spread of the virus have led to
a drastic increase in the usage of smartphones to access
information, purchase essential products, and seeking
medical counseling, as a source of communication and
entertainment [2], which eventually directed to rise
in reliance and addiction to smartphones and devices.
Many of news spared through social media which
made negative impact on population for vaccination
in Bangladesh [10]. Studies have reported that during
COVID-19, Android phone addiction increased from
26.1 to 46.7%, compared to the pre-epidemic period
in children and adolescents. Moreover, the usage of
Android phones multiplied to 8–12h per day among
medical students. Hazards of Android phone use were
associated with an increase in daily Internet use time
among university students [11]. Furthermore, the time
spent on social media apps such as Facebook, Twitter,
and Instagram has increased, females were found to
spend more time on social media and launching social
media apps than males, and the use of gaming apps on
Android phones has increased exponentially since the
pandemic [11].
e frequent and unrestrained use of Android phones
during COVID-19 is not only deleterious to psycho-
logical health but is attributable to a musculoskel-
etal disorder such as BlackBerry thumb [12], due to
repetitive strain injuries caused by repeatedly pressing
their thumbs or using a combination of thumb/finger
motions. It was reported the incidence of BlackBerry
thumb increased by overuse of the thumb muscle dur-
ing prolonged Internet browsing, frequent texting, and
gaming on Android phones [12]. Several studies have
reported the prevalence of BlackBerry thumb among
Android phone users, and Iqbal etal. stated that more
than half of the undergraduates (58.1%) using Android
phones had BlackBerry thumb with the 67% of the peo-
ple who used the Android phone for texting tested pos-
itive for Finkelstein’s test whereas found 19.1% Android
phone users tested positive for Finkelstein’s test, and
pain was positively correlated with the degree of smart-
phone use [13]. Woo etal. reported that overuse of
smartphones and gadgets puts excessive force on the
median nerve and leads to nerve compression if repeti-
tive movements persisted for longer periods [14]. Addi-
tionally, on average, musculoskeletal complaints were
usually made by people who used Android phones for
more than 3h, providing insights into how BlackBerry
thumb can be a common phenomenon among Android
phone users [14].
Ever since the COVID-19 pandemic, smartphone
dependency has increased immensely which has
become an emerging cause for BlackBerry thumb
among people. Although there have been several stud-
ies that linked BlackBerry thumb with smartphone
usage, there has been a dearth of studies that assessed
the prevalence of BlackBerry thumb among smartphone
users during COVID-19. Hence, it is imperative to con-
duct research that further explores the incidence of
BlackBerry thumb during COVID-19 among Android
phone users. e present study aimed to assess the
occurrence rate and explore the risk factors of Black-
Berry thumb among smartphone users during COVID-
19, which will help in early diagnosis and appropriate
management of BlackBerry thumb possible.
Page 3 of 10
Haqueetal. Bulletin of Faculty of Physical Therapy (2024) 29:39
Methods
Study design
A comprehensive cross-sectional investigation was con-
ducted on a group of university students between the
ages of 18 and 25, especially those who spend around
4.15h on average in cell phones everyday, and have been
using mobile phone for at least 4years. In the districts
of Dhaka, Chattagram, Rajshahi, Khulna, Sylhet, Barishal,
Mymensingh, and Rangpur, both state and private col-
leges were surveyed. e colleges were chosen to improve
the likelihood of locating participants who fit the neces-
sary years of age and possess cell phones. e survey was
conducted between August 2022 and May 2023.
Subjects andsampling
People who used a cell phone with a minimum of two
social networking platforms, like Facebook, WhatsApp,
Instagram, or Twitter, were eligible to engage in the
research. Participants with thumb or wrist injuries in
the 3months before the assessment, those who used a
painkiller medication in the final week before the evalu-
ation for any reason, and those working in jobs with an
increased BBT danger were eliminated. Figure1
A preliminary research study involving 50 participants
yielded the data required to calculate the size of the sam-
ple. ere were 36% (18/50) cases of sporadic or regular
HAPU. A total of 32% (10/32) of those in the group who
did not use HAPU had significant BBT signs and symp-
toms, compared to 45% (8/18) of those who used HAPU
frequently or occasionally. An initial sample of 468 indi-
viduals would be required to identify prevalence ratios
greater than 1.4 with an 80% statistically significant level
of power using these values and a 95% confidence level.
After adding 4% to account for the potential for incom-
plete responses, the total sample size, which was selected
employing a non-probabilistic method of sampling, was
488 people.
In determining the sample size, Krejcie and Morgan
method [15] was considered:
Here,
n = the sample size, N = population si ze, P = popula-
tion portion (if unknown then 0.5), d2 = desired margin of
error (expressed as portion), and χ2 = chi-square for spec-
ified confidence level at 1 degree of freedom [15].
Variables considered
e existence or lack of BBT symptomatology was our
outcome variable, and it had two groups. e Finkel-
stein test, which measures the prevalence of symptoms
of tenosynovitis in the extensor pollicis brevis and the
abductor pollicis longus tendons, was used to analyze
the result. e wrist must stay at the end of the bench on
the instructor’s side, while the forearm is extended and
rotated in neutral during the Finkelstein test. e subject
was then instructed to deviate their wrist, and the evalu-
ator then grabbed their thumb and passively and aggres-
sively flexed it into their hand. e Finkelstein test was
carried out on both the dominant and nondominant
wrists and is deemed affirmative if the subject reports
n
=χ
2
NP(1−P)
d2
(
N−1
)
+
χ
2P
(
1−P
)
Fig. 1 Diagrammatic illustration of the process used to choose the participants for the study
Page 4 of 10
Haqueetal. Bulletin of Faculty of Physical Therapy (2024) 29:39
pain to us [16]. We utilized it for testing in determining
the presence of BBT because the EU Handguide Group
identified it as the most effective test for this reason con-
cerning this issue [16]. In a prospective cohort study with
a 3-year follow-up, ultrasonographic and clinical assess-
ments of 100 patients’ positive Finkelstein test findings
were contrasted. e test’s sensitivity was determined to
be 89% and its specificity to be 14% [17].
e observations similar to the cell phone device use
survey, which asks about the use of and reliance on this
technology, were used to assess the HAPU [18]. Ten ele-
ments make up the test, which has a Cronbach’s alpha of
0.81 and a maximum result of 40 points. us, we divide
the participants into three groups: (a) those absent of
HAPU (10 to 15 points), (b) those with infrequent HAPU
(16 to 23 points), and (c) those with recurrent HAPU
(from 24 to 40 points). We chose to utilize the three cat-
egories provided by the modalities for the study’s objec-
tives, so we split up the entire population into the three
research groups.
Data collection
Before the data gathering, the Finkelstein maneuver
instruction with a health expert was done to standard-
ize the evaluators. Before the research started, a pilot
study with 50 participants was carried out to determine
the participants’ general level of understanding of the
topics and the study’s average completion time. en,
our research team went to the colleges to invite the tar-
get audience. e proportion of participants who did
not respond as well as their age, gender, and occupation
was recorded to assess the possibility of selection bias.
e participants orally gave their informed permission
before starting their participation in the study. e first
stage of the poll was then carried out using the cell phone
device—the surrounding experiences questionnaire. e
Finkelstein maneuver was then carried out, followed by
a short discussion of protective ergonomic advice and
wrist pain management tips.
To guarantee a higher poll count and prevent poten-
tial losses due to lost or erroneous data input, all the col-
lected data was separately moved to Excel without IDs.
Statistical analysis
e statistical analysis of the quantitative variables was
conducted using STATA v. 14 (StataCorp, Texas, USA).
In contrast to quantitative variables, which were por-
trayed as medians alongside an interquartile range if they
had irregular distributions or as means with standard
deviation if they had symmetric distributions, qualita-
tive variables were depicted as absolute and relative rates.
One-way analysis of variance was applied when compar-
ing number factors with uniform distributions; otherwise,
the Kruskal–Wallis test was applied. To assess the quali-
tative variables, the chi-square test was employed. e
aim of the research was evaluated using an improved
linear model from the Poisson family with trustworthy
standard deviations. Prevalence ratios (PR) in their raw
and modified forms, along with corresponding 95% con-
fidence intervals (CI), were given [19, 20]. e modified
model contained the previously chosen confounding fac-
tors. After studying the scholarly literature, the following
factors were determined to be confounding factors: years
of age; gender; hours of usage of cell phone device per
day; the number of messages delivered per day; previous
week’s history of inflammation due to cell phone device
use; use of social networking platforms such as Insta-
gram, Twitter, Facebook Messenger, and WhatsApp; use
of digital video games; and use of the Internet. Similarly,
the confounding factors’ collinearity associations con-
cerning the variables chosen to be included in the modi-
fied model were assessed. e results obtained from both
the qualitative and quantitative measurements were fur-
ther analyzed for verifying the statistical precision using
GraphPad Prism 8.1.2 [21–23] and R-Studio [24–26]. In
that cases, two-way ANOVA [27–29] and Tukey’s t-test
for multiple variable analysis were preferred [30–32].
Result
In this study, 2455 participants were included out of
2830 invited. e median age was 20 (IQR: 19–23), with
48.27% men and 51.75% women. Participants spent a
median of 6h per day on their cell phones, sending an
average of 200 messages daily. e most popular plat-
forms were WhatsApp, Facebook, and Facebook chat,
with 90.63%, 90.63%, and 88.80% users respectively.
Additionally, Twitter, Instagram, video games, and Inter-
net were used by 54.18%, 64.56%, 43.58%, and 45.82%
of participants. e hazards of Android phone use were
assessed using the ERMUQ, resulting in a median score
of 15 (range: 12–18). Half of the respondents were non-
hazardous Android phone users (52.95%), while 42.36%
had occasional hazards and 4.68% had frequent hazards.
Physical examinations showed 52.95% positive Finkel-
stein test results. Additionally, 37.88% reported pain due
to mobile phone use in the last week (Table1).
Association ofthestudy variables withhazards ofAndroid
phone use
e study included 1300 participants, with 51.54%
men and 48.46% women, and a median age of 20
(IQR = 19–23). Most participants did not show hazards
of Android phone use (HAPU). Among those with occa-
sional HAPU, there were more females than males, and
they spent an average of 12h per day on their phones.
Frequent HAPU was more common in females, with
Page 5 of 10
Haqueetal. Bulletin of Faculty of Physical Therapy (2024) 29:39
longer daily phone use and higher message counts. Pain
due to smartphone usage was reported by a minority of
participants, with higher prevalence among those with
HAPU. e main online platforms used were What-
sApp, Facebook, Facebook chat, Twitter, Instagram,
video games, and the Internet (Table2). e prevalence
of occasional HAPU among users of various online plat-
forms was highest for Facebook, Facebook chat, and
WhatsApp, while the prevalence of frequent HAPU was
highest for WhatsApp, Facebook, and Facebook chat
(Table2).
Association ofthevariables withtheresult
oftheFinkelstein test
e physical examination of participants showed that
52.95% had a positive Finkelstein test, with a median age
of 20 (IQR = 19–22), while 47.05% had negative results,
with a median age of 21 (IQR = 19–23). ose with
positive results spent an average of 8h per day on their
phones and sent an average of 300 messages per day,
compared to 5h per day and 150 messages per day for
those with negative results. e majority of those with
positive tests reported wrist pain due to phone use, and
they were more frequent users of online applications
and the Internet compared to those with negative results
(Table3).
Generalized linear model crude andadjusted prevalence
ratio fortheassociation betweenhazards ofAndroid
phone use andthepositive Finkelstein test
The participants with occasional hazards of Android
phone use had a crude prevalence ratio (cPR) of 2.08
and an adjusted prevalence ratio (aPR) of 1.73, while
those with frequent hazards of Android phone use
had a cPR of 2.52 and an aPR of 1.61, with partici-
pants having no HAPU as the referent category. Vari-
ables related to Android phone use showed significant
associations, with the number of hours using the cell
Table 1 General characteristics of the sample included in the
study
Median (interquartile range). ERMUQ Experiences Related to Android Phone Use
Questionnaire
Variables N = 2455 (%)
Age (years) 20 (19–23)
Male 1185 (48.27)
Variables related to Android phone use
Number of hours using the Android phone per day 6 (4–10)
Number of messages sent per day 200 (50–500)
Use of social networks and Internet
WhatsApp 2225 (90.63)
Facebook 2220 (90.63)
Facebook chat 2180 (88.80)
Twitter 1330 (54.18)
Instagram 1585 (64.56)
Video games 1070 (43.58)
Internet 1125 (45.82)
Hazards of Android phone use
ERMUQ questionnaire (total score) 15 (12–18)
No problems with Android phone use 1300 (52.95)
Occasional problems with Android phone use 1040 (42.36)
Frequent problems with Android phone use 115 (4.68)
Positive Finkelstein test 1300 (52.95)
Pain due to the use of the Android phone in the last
week 930 (37.88)
Table 2 Distribution of the study variables according to hazards of Android phone use
Median (interquartile range), number (percentage). HAPU hazards of Android phone use
Variables No HAPU (N = 1300) Occasional
HAPU (N = 1040) Frequent HAPU (N = 115) p-value
Age (years) 20 (19–23) 20 (19–22) 19 (18–20) < 0.01
Male 670 (51.54) 480 (46.15) 35 (30.43) 0.11
Variables related to Android phone use
Number of hours using the Android phone per day 6 (4–8) 7 (4–10) 12 (5–18) < 0.01
Number of messages sent per day 200 (50–400) 178 (40–600) 700 (300–1000) < 0.01
Pain due to the use of the Android phone in the last week 400 (30.77) 460 (44.23) 70 (60.87) < 0.01
Use of social media and Internet
WhatsApp 1190 (91.54) 920 (88.46) 115 (100) 0.15
Facebook 1175 (90.38) 935 (89.90) 110 (95.65) 0.67
Facebook chat 1185 (91.15) 890 (85.58) 105 (91.30) 0.15
Twitter 670 (51.54) 595 (57.21) 65 (56.52) 0.46
Instagram 765 (58.85) 735 (70.67) 85 (73.91) 0.02
Video games 560 (43.08) 445 (42.79) 65 (56.52) 0.44
Internet 595 (45.77) 465 (44.71) 65 (56.52) 0.56
Page 6 of 10
Haqueetal. Bulletin of Faculty of Physical Therapy (2024) 29:39
phone per day and pain due to smartphone use in the
last week having notable adjusted prevalence ratios.
Additionally, specific online platforms such as What-
sApp and Instagram also showed significant associa-
tions (Table4).
Discussion
is study examined the prevalence and causative factors
of BlackBerry thumb among Android phone users dur-
ing the COVID-19 pandemic and revealed that 52.95%
tested positive for BlackBerry thumb using the Finkel-
stein test as a standard diagnostic test. is study’s find-
ings are similar to those of Bendezu-Quispe et al., who
found that 53% of young adults who used the same diag-
nostic test had positive results [33]. General characteris-
tics (age, gender), variables related to Android phone use
(hours using the smartphone per day, messages sent per
day), frequently used social networks, hazards of Android
phone use and their distribution according to variables,
the Finkelstein test result distributions, the association
Table 3 Distribution of the variables according to the result of the Finkelstein test
Median (interquartile range), number (percentage)
Positive (N = 1300) Negative (N = 1155) p-value
Age (years) 20 (19–22) 21 (19–23 0.03
Male 625 (52.74) 560 (47.26) 0.93
Variables related to Android phone use
Number of hours usin the Android phone per day 8 (5–12) 5 (4–8) < 0.01
Number of messages sent per day 300 (60–600) 150 (50–340) < 0.01
Pain due to the use of the Android phone in the last week 830 (89.25) 100 (10.75) < 0.01
Use of social networks and Internet
WhatsApp 1195 (53.71) 1030 (46.29) 0.30
Facebook 1195 (53.71) 1030 (46.29) 0.65
Facebook chat 1135 (52.06) 1045 (47.94) 0.27
Twitter 670 (50.38) 660 (49.62) 0.21
Instagram 900 (56.78) 685 (43.22) 0.02
Video games 615 (57.48) 455 (39.39) 0.07
Internet 645 (57.33) 480 (42.67) 0.07
Table 4 Generalized linear model crude and adjusted for the association between hazards of Android phone use and the positive
Finkelstein test
CI condence intervals, Ref reference, PR prevalence ratio. The variable Facebook does not enter the model adjusted for being collinear with the variable WhatsApp
Variables Crude PR (95% CI)p-value Adjusted PR (95% CI)p-value
No hazards of Android phone use Ref Ref
Occasional hazards of Android phone use 2.08 (1.73–2.51) < 0.01 1.73 (1.47–2.05 < 0.01
Frequent hazards of Android phone use 2.52 (1.99–3.16) < 0.01 1.61 (1.29–2.00) < 0.01
Age (years) 0.96 (0.92–0.99) 0.02 0.98 (0.95–1.02) 0.39
Male 0.99 (0.84–1.17) 0.92 1.05 (0.92–1.21) 0.47
Variables related to Android phone use
Number of hours using the Android phone per day 1.05 (1.04–1.07) < 0.01 1.02 (1.01–1.04) < 0.01
Number of messages sent per day 1.00 (0.99–1.01) 0.52 1.00 (0.99–1.01) 0.37
Pain due to the use of the Android phone in the last week 2.89 (2.43–3.45) < 0.01 2.68 (2.25–3.18) < 0.01
Use of social networks and Internet
WhatsApp 1.18 (0.85–1.63) 0.33 1.63 (1.24–2.13) < 0.01
Facebook 1.01 (0.77–1.33) 0.93 ‑ ‑
Facebook chat 0.86 (0.69–1.10) 0.23 0.72 (0.55–0.94) 0.02
Twitter 0.90 (0.76–1.06) 0.21 0.77 (0.67–0.89) < 0.01
Instagram 1.23 (1.02–1.49) 0.03 1.15 (0.97–1.36) 0.10
Video games 1.16 (0.98–1.37) 0.08 1.06 (0.91–1.23) 0.44
Internet 1.16 (0.99–1.38) 0.07 1.07 (0.93–1.23) 0.32
Page 7 of 10
Haqueetal. Bulletin of Faculty of Physical Therapy (2024) 29:39
between hazards of Android phone use, and the positive
Finkelstein test were observed among Android phone
users, with a significant association found with Black-
Berry thumb [33].
In our study, the majority of the participants were
women (51.75%) with a median age of 20, and in another
review article, Morgan et al. perceived that females
mostly experienced BlackBerry thumb in the age group
of 16–20years (89%) [34]. Participants spend 6 (4–10)
median hours on Android phones while texting 200 (50–
500) messages per day in our study, while Ali etal. found
that 56% of students text more than 50 messages per day.
According to Alexander etal., WhatsApp is a condition
caused by excessive use of the popular instant messag-
ing app and characterized by typical wrist pain, is a new
emerging disease, and is also known as BlackBerry thumb
or tenosynovitis [35]. Additionally, Facebook chat, Twit-
ter, Instagram, and the Internet were frequently used for
social communications, connections, and collecting the
latest information around the world during the pandemic
in our study. According to Katz and Nandi, these social
networking sites helped to provide formal and informal
education, discussion groups, and physician and patient
consultations [36]. Chan et al. expressed that social
media played a vital role in the dissemination of knowl-
edge during the COVID-19 pandemic [36]. Based on the
Experiences Related to Mobile Phone Use Questionnaire
(ERMUQ), the participants’ median score was 15, and
those who faced occasional and frequent Android phone
usage problems were 42.36% and 4.68%, respectively. A
total of 37.88% of participants complained of pain due to
Android phone use in the last week; on the other hand,
42% of participants experienced thumb or wrist pain,
according to Ali and his teammates [10]. e prevalence
of BlackBerry thumb among smartphone users of differ-
ent university students in Lahore was 55%, and this study
was conducted by Tahir and Ahmad [37].
Association ofthestudy variables withhazards ofAndroid
phone use
e participants who had occasional and frequent prob-
lems with Android phone usage were mostly female, and
their frequency was 53.85% and 69.57%, respectively.
Long etal. revealed that the overall prevalence of hazards
of Android phone use (HAPU) in their study was 21.3%
among whom 53.1% were female [38]. e average age
of no HAPU and occasional HAPU participants was 20,
while the average age of frequent HAPU participants was
19, which is significant. In our study, participants with
occasional and frequent HAPU spent 7 and 12 median
hours per day, while those without HAPU spent 6 median
hours per day; on the other hand, 52.4% of students, who
had HAPU, used more than 4h per day in a study done
by Long et al. [38]. Our study revealed that frequent
HAPU-experienced participants sent 700 texts per day,
and among them, 60.87% experienced pain last week due
to their smartphones. At the same time, occasional and
no HAPU sent 178 and 200 texts per day, respectively,
while 44.23% and 30.77% of them experienced pain. Sar-
fraz et al. discovered that 39.8% of university students
had mild pain, 73 (38.2%) had moderate pain, and 4
(2.1%) had severe pain [39]. WhatsApp was widely used
by all HAPU groups, particularly by all frequent HAPU
users. Facebook, Facebook chat, and Instagram were
highly used by all categories of HAPU, and the percent-
age varies from 85 to 92%. Twitter, video games, and
users ranged from 42 to 58% among all types of HAPU.
A study conducted in Bangladesh during the COVID-19
pandemic by Hosen etal. revealed that 96.7% of partici-
pants remained online for messaging at the same time
that 95.5% and 92.5% of students used Android phones
for social media browsing and video watching respec-
tively, among hazards of Android phone users [11]. In
another study conducted by Marengo etal., they found
a positive association between hazards of Android phone
usage and social networking sites like WhatsApp, Face-
book, Facebook chat, and Instagram [40].
Association ofthevariables withtheresult
oftheFinkelstein test
Participants who showed positive test results of the Fin-
kelstein test were 1300; among the male and female par-
ticipants, 52.74% and 53.15% were positive, respectively,
and the median age was 20 years. On the other hand,
Ahmed etal. found that the participants’ overall median
age was 22.0 years [41], and among those who showed
positive test results of the Finkelstein test, 66.5% were
female. Participants who received a positive test result
spent an average of 8 (IQR 5–12) h per day on their
smartphones, sending an average of 300 (IQR 60–600)
text messages, which was a very significant number. A
study conducted by Ahmed et al. found that 23.7% of
positive respondents spent more than 8h per day, and
15.2% sent more than 200 test messages per day [41]. e
respondents to our study who tested positive and expe-
rienced pain last week were 89.25%, and this was a very
significant number. Another study by Baabdullah etal.
found that excessive use of smartphones and smartphone
addiction lead to pain in the thumb/wrist [42]. e per-
centage of participants who used WhatsApp, Facebook,
Facebook chat, Twitter, Instagram, the Internet, and
video games varies from 50 to 58%, while the percentage
of participants who used negative test results varies from
39 to 50%. Shen etal. conducted a study on mobile gam-
ing and found that it can be one of the potential risk fac-
tors for De Quervain’s tenosynovitis [43]. According to
Page 8 of 10
Haqueetal. Bulletin of Faculty of Physical Therapy (2024) 29:39
Bendezu-Quispe etal., higher detection of De Quervain’s
tenosynovitis correlated with the number of hours spent
on a smartphone [33], WhatsApp usage, and experienc-
ing pain last week due to a smartphone.
Generalized linear model crude andadjusted prevalence
ratio fortheassociation betweenhazards ofAndroid
phone use andthepositive Finkelstein test
We used a generalized linear model to calculate a crude
and adjusted prevalence ratio for different variables. In
this model, we used no HAPU group as a reference to
find the association between hazards of Android phone
users and the positive Finkelstein test. e crude preva-
lence ratio (cPR) and adjusted prevalence ratio (aPR) for
the occasional HAPU were 2.08 and 1.73, respectively,
and the frequent HAPU were 2.52 and 1.61, respectively,
and these have significant p-value. Fischer-Grote etal.
found no strong evidence for age or gender as potential
risk factors for developing BlackBerry thumb and HAPU
[44]. With a significant p-value, the number of hours
spent on a cell phone per day had a cPR of 1.05 and an
aPR of 1.02. e prevalence of positive Finkelstein test
increased with the time spent on smartphones, as found
by Reada and the team [8]. e cPR and aPR for the
respondents who experienced pain due to the use of the
smartphone in the last week were 2.89 and 2.68, respec-
tively, and they had a significant p-value. According to
Zirek et al. [45], the prevalence of BlackBerry thumb,
other musculoskeletal complaints, and pain could be
increased because of extended computer and electronic
gadget usage, professional demands like athletes, medi-
cal professionals, and others. In our study, the number of
messages sent per day had the same cPR and aPR, which
is 1.00. Different social networking sites and the Inter-
net had different cPR and aPR, but they did not have
any significant p-value in our study, while another done
by Long etal. expressed that social networking, playing
video games, and Internet surfing might lead to HAPU
and increase the prevalence of BlackBerry thumb [38].
Frequent usage of social networking media might influ-
ence the increment of hazards of Android phone usage
suggested by Marino etal. [46].
This study focused on the prevalence of BlackBerry
thumb among smartphone users in Bangladesh dur-
ing the pandemic. This study had some limitations, as
they were not able to cover all the possible risk factors
due to time and resource constraints, and the partici-
pants’ responses might be affected by recall bias and
their psychological status. Further study is required
to develop a deeper understanding of the potential
risk factors and their association with BlackBerry
thumb to provide awareness, education, and effective
interventions.
Conclusion
e current study addresses the elevated prevalence of
“BlackBerry thumb” among users of Android phones,
detected through the Finkelstein test. An investigation
scrutinized the hazards linked to Android phone usage,
sociodemographic traits, and factors like daily phone
usage duration and discomfort. e study revealed note-
worthy associations between positive Finkelstein test
outcomes and factors associated with Android phone
usage, underscoring the necessity for a more extensive
inquiry to substantiate findings and promote awareness.
Abbreviations
BBT BlackBerry thumb
HAPU Hazards of Android phone usage
PR Prevalence ratios
aPR Adjusted prevalence ratios
cPR Crude prevalence ratio
CI Confidence intervals
IQR Interquartile range
EU European Union
ERMUQ Experiences Related to Mobile Phone Use Questionnaire
Acknowledgements
The authors are grateful to the RPG Interface Lab Authority for providing all
unconditional support in statistical software tools, grammatical checking, and
plagiarism issues. We also acknowledge Dr. Salauddin Al Azad for language
editing the final paper and Dr. Sharmin Ahmed for help with back‑translating
the study questionnaire.
Authors’ contributions
Md Ariful Haque, Liton Baroi, Ismat Ara Chowdhury Koly, Shakibul Hasan, Faiza
Mahmud, Sifat Ara Eva, Monirul Karim Labib, Hazika Tuz‑Zohura Nafisa, Salwa
Islam, Irfat Islam Eva, Rafiqul Islam, Lita Bose, Faming Tian was involved in the
conceptualization of the study, the formal analysis and visualization of the
data as well as writing the original manuscript draft. Dr. Sharmin Ahmed was
involved in the conceptualization of the study, the project administration and
supervision and in reviewing/editing of the manuscript. Dr. Md. Ariful Islam
was involved in the conceptualization of the study and reviewing/editing of
the manuscript. Dr. Salauddin Al Azad was involved in the conceptualization
of the study, the training and supervision of the survey staff, data curation and
reviewing/editing of the manuscript. Salwa Islam was involved in conceptu‑
alization of the study, funding acquisition and reviewing/editing of the final
manuscript. Dr. Md. Ariful Islam was responsible for the conceptualization of
the study, funding acquisition, project administration, supervision, and review‑
ing/editing of the final manuscript.
Funding
The research received no funding from any institution, organization, and even
individual sponsor.
Availability of data and materials
All necessary data are properly conserved by the corresponding author, which
will be shared upon reasonable request with the journal authority.
Declarations
Ethics approval and consent to participate
The Jessore Medical College Hospital Ethics Committee issued the official
ethical approval to the study (Code No. EA0021/2022–2023, Phase‑1A/
BMDC25), and all its techniques were carried out in compliance with the
applicable regulations and guidelines of the Declaration of Helsinki and the
ethical requirements for human experimentation. At the start of the survey, all
subjects were asked if they would be willing to participate in the study, and
the study’s goals were fully stated to them. The information that was gathered
was kept private and was solely utilized to further the goals of the study. The
Page 9 of 10
Haqueetal. Bulletin of Faculty of Physical Therapy (2024) 29:39
surveys also excluded any personal information or other means of identifica‑
tion from the subjects. Study populations were offered the option to either
stay in the study or leave at any moment.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Department of Orthopedic Surgery, Yan’an Hospital Affiliated to Kunming
Medical University, Kunming, Yunnan, China. 2 Department of Public Health,
Atish Dipankar University of Science & Technology, Dhaka, Bangladesh. 3 James
P Grant School of Public Health, BRAC University, 6Th Floor, Medona Tower,
Mohakhali, Dhaka 1212, Bangladesh. 4 North South University, Bashundhara,
Dhaka 1229, Bangladesh. 5 Noakhali Science and Technology University,
Noakhali, Bangladesh. 6 Dhaka Medical College & Hospital, Dhaka 1212, Bang‑
ladesh. 7 Bangladesh Medical and Dental College, Dhanmondi, Dhaka 1209,
Bangladesh. 8 Department of Microbiology, University of Dhaka, University
Street, Nilkhet Rd, Dhaka 1000, Bangladesh. 9 Independent University Bang‑
ladesh (IUB), Bashundhrara R/A, Plot#16, Aftabuddin Ahmed Road, Block‑B,
Dhaka 1229, Bangladesh. 10 Department of Medicine, Dhaka Medical College
and Hospital, Dhaka 1000, Bangladesh. 11 Department of Physiotherapy, State
College of Health Sciences, Dhanmondi, Dhaka 1209, Bangladesh. 12 National
Institution of Social and Preventive Medicine (NIPSOM), National Nutritional
Surveillance Project, Mohakhali, Dhaka 1212, Bangladesh. 13 School of Public
Health, North China University of Science and Technology, Tangshan, Hebei,
People’s Republic of China.
Received: 28 June 2023 Accepted: 26 April 2024
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