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The Kingdom of Saudi Arabia (KSA) ranks third globally in smartphone use. Smartphones have made many aspects of life easier. However, the overuse of smartphones is associated with physical and psychosocial problems.
The aim of this paper is to estimate the prevalence and associated factors of problematic use of smartphones among adults in the Qassim region of KSA.
We enrolled 715 participants using cluster random sampling for this cross-sectional survey. We assessed the problematic use of smartphones using the short version of the Smartphone Addiction Scale.
We estimated the prevalence of problematic smartphone use among adults at 64% (453/708). Multivariable logistic regression analysis suggested that students are 3 times more likely to demonstrate problematic use compared with unemployed individuals (
We reported a very high prevalence of problematic use of smartphones in KSA. Considering its negative impact on physical and psychosocial health, public health programs should develop preventive strategies.
Smartphones are considered the most used technological tool worldwide [
One review of studies around the world found a mean problematic smartphone use prevalence of 18.9%, with a higher prevalence among women, and a trend of decreasing prevalence after the age of 20 [
In this context, this study aims to estimate the prevalence of problematic smartphone use among an adult population aged 18-65 years in the Qassim region of KSA. We also explored whether factors such as demographics, app use, and reason for app use were associated with the problematic use of smartphones.
We conducted a cross-sectional survey of adult residents of the Qassim region of KSA. We recruited our participants from the Qassim University and primary health care centers (PHC) in the Qassim region. Qassim, officially known as the Emirate of Al-Qassim, is an administrative province of KSA. It is located in the northern central part of the Kingdom and has an estimated 1.02 million people living in 65,000 square kilometers [
Male and female Saudi residents aged between 18 and 65 years were considered eligible for our study. We set an age cutoff due to limited access to residents older than 65 years. Individuals were excluded if they had any communicable respiratory illness or any other disease that made it difficult for them to participate in the study. We recruited participants from the Qassim University and PHC in the region using multistage cluster sampling. First, we developed a sampling frame comprising the primary sampling units—a list of Qassim University’s 15 colleges situated on the main campus and a list of all PHC (N=158) in Qassim. We randomly selected 6 colleges and 52 PHC from the list. We calculated our sample size using the Epi Info, version 7 (Centers for Disease Control and Prevention). For a probability value of .05 and 50% expected prevalence, we needed 384 participants from each group—university and PHC.
Data collectors visited the colleges over a period of 2 months to randomly enroll students for the study. To recruit adults from the general population, our data collector invited every third adult patient or visitor entering the selected primary health care centers during 3 consecutive days each week. Data collection continued over a period of 3 months (between December 2019 and February 2020). We ended data collection after completing 715 interviews because of the COVID-19 lockdown measures, of which 708 (99%) were considered for analysis. Participants’ characteristics are presented in
Sociodemographic characteristics of the participants (N=708).
Characteristics | Values | ||
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Male | 325 (45.9) | |
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Female | 383 (54.1) | |
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18-24 | 518 (73.2) | |
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25-34 | 114 (16.1) | |
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≥35 | 76 (10.7) | |
Mean, SD (years) | 25.1 (8.5) | ||
Median (years) | 22.0 | ||
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Single | 553 (78.4) | |
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Married | 152 (21.6) | |
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Primary | 12 (1.7) | |
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Intermediate-secondary | 511 (72.4) | |
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Higher diploma | 88 (12.5) | |
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Bachelor or higher | 95 (13.5) | |
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Unemployed | 64 (9.1) | |
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Student | 515 (72.9) | |
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Employed | 127 (18.0) | |
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1500 SAR (US $400) or less | 96 (14.2) | |
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1501-5000 SAR (US $400-$1300) | 97 (14.3) | |
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5001-10,000 SAR (US $1300-$2700) | 188 (27.8) | |
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10,001-20,000 SAR (US $2700-$5400) | 203 (30.0) | |
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>20,000 SAR (>US $5400) | 93 (13.7) |
The structured questionnaire included demographic information and the short version of the Smartphone Addiction Scale (SAS-SV) [
Our questionnaire, including the SAS-SV, was translated into Arabic and reverse translated into English, and both were compared to ensure accuracy before starting data collection. Then, we carried out field testing with 24 Saudi adults to ensure that our questionnaire was understandable by our target population. The participants for field testing were purposively sampled to ensure diverse demographics for good representation of genders, income levels, education levels, and age groups. Field testing of the preliminary questionnaire was conducted by 2 male and 2 female medical students who were native Arabic speakers. Field testing was conducted in 3 phases of 8 interviews each, with the questionnaire undergoing revision after each phase. The final survey was conducted face-to-face by 6 male and 6 female final-year medical students who were trained to use the instrument.
All researchers completed the ethics course recommended by the local institutional review board. We received ethics approval from the Institutional Review Board of the Ministry of Health, Qassim region, Saudi Arabia (Approval No. 1378136-1440). All study participants received a detailed informed consent document that explained the purposes of the study and highlighted the topics, types of questions, and the time involved in the study. Confidentiality and anonymity of all information collected from the participants were maintained, and the participants retained the right to refuse to answer specific questions or to opt out of the study at any time.
Data entry and analyses were carried out using the SPSS version 20 (IBM Corp). To classify problematic smartphone use, we first computed participants’ scores on each of the 10 SAS-SV items. Then, we used 31 and 33 as the male and female cutoff points, respectively, to determine problematic use [
We interviewed 715 adults aged 18 to 65 years. However, 7 (1%) participants were dropped from further analysis due to incomplete information.
Prevalence of problematic use of smartphones among adults aged 18-65 years in Qassim, Kingdom of Saudi Arabia (cross-sectional survey, December 2019 to February 2020). SAR: Saudi Riyal.
Regarding characteristics of smartphone use, we found that compared with individuals who use 1 to 3 apps daily, users of more than 5 apps were 2 times more likely to have problematic smartphone use (OR 2.02;
Characteristics of participants’ smartphone use in Qassim, KSAa (cross-sectional survey, December 2019-February 2020).
Smartphone use characteristics | Values, n (%) | |||
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Up to 3 years | 14 (2.0) | ||
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>3 years | 691 (98) | ||
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1-3 apps | 172 (25) | ||
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4-5 apps | 319 (46.4) | ||
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>5 apps | 197 (28.6) | ||
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No | 123 (17.8) | ||
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Yes | 567 (82.2) | ||
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No | 282 (39.9) | |
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Yes | 424 (60.1) | |
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No | 61 (8.6) | |
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Yes | 645 (91.4) | |
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No | 446 (63.2) | |
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Yes | 260 (36.8) | |
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No | 492 (69.7) | |
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Yes | 214 (30.3) | |
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No | 549 (77.8) | |
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Yes | 157 (22.2) | |
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No | 483 (68.4) | |
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Yes | 223 (31.6) | |
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No | 530 (75.1) | |
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Yes | 176 (24.9) | |
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No | 314 (44.5) | |
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Yes | 392 (55.5) |
aKSA: Kingdom of Saud Arabia.
Determinants of problematic smartphone use among adults (N=708) in Qassim, KSAa (cross-sectional survey, December 2019-February 2020).
Determinant (reference category) | Odds ratiob | 95% CI for odds ratio | ||||||||
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Lower | Upper | ||||||
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Female | .55 | 0.89 | 0.61 | 1.30 | |||||
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25-34 years | .14 | 2.06 | 0.79 | 5.36 | |||||
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>34 years | .22 | 1.98 | 0.67 | 5.87 | |||||
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Higher diploma | .29 | 1.41 | 0.75 | 2.68 | |||||
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Bachelor or above | .26 | 1.42 | 0.77 | 2.63 | |||||
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Student | .03 | 2.99 | 1.14 | 7.86 | |||||
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Employed | .22 | 1.61 | 0.75 | 3.45 | |||||
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Married | .88 | 0.95 | 0.47 | 1.92 | |||||
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1501-5000 SAR (US $400-$1300) | .27 | 0.68 | 0.35 | 1.34 | |||||
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5001-10,000 SAR (US $1300-$2700) | .01 | 0.46 | 0.25 | 0.83 | |||||
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10,001-20,000 SAR (US $2700-$5400) | .03 | 0.51 | 0.28 | 0.93 | |||||
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>20,000 SAR (US $5400) | .50 | 0.79 | 0.40 | 1.57 | |||||
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Yes | .55 | 1.15 | 0.73 | 1.79 | |||||
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4-5 apps | .13 | 1.41 | 0.91 | 2.20 | |||||
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>5 apps | .007 | 2.02 | 1.21 | 3.35 | |||||
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Yes | .17 | 1.31 | 0.89 | 1.93 | ||||
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Yes | .24 | 1.47 | 0.78 | 2.77 | ||||
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Yes | .04 | 0.66 | 0.44 | 0.98 | ||||
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Yes | .28 | 1.25 | 0.83 | 1.89 | ||||
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Yes | .32 | 1.26 | 0.80 | 2.00 | ||||
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Yes | .06 | 0.68 | 0.45 | 1.02 | ||||
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Yes | .007 | 0.55 | 0.36 | 0.85 | ||||
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Yes | .88 | 1.03 | 0.69 | 1.54 |
aKSA: Kingdom of Saud Arabia.
bMultivariable logistic regression analysis.
This study aimed to investigate the prevalence and associated factors of the problematic use of smartphones among adults aged 18-65 years in Qassim, KSA to reduce the gap in the literature. The majority of previous studies in this regard used exclusively college or university students [
We estimated the prevalence of problematic use of smartphones at 64% among adults aged 18 to 65 years in Qassim, KSA. This finding is in concordance with the findings reported by local studies conducted on university students, which were 71.9% [
Variation in prevalence could be affected by study design, sample size, or the scale used. Our study’s high prevalence could be explained by the fact that Saudi Arabia’s social media presence is one of the largest in the world. The large number of active social media users is mostly due to the high rate of smartphone ownership. With more than 84% of the population living in urbanized areas with very fast internet connections, it comes as no surprise that active social media users may number more than 25 million. According to reports from Hootsuite and We Are Social, Saudis are the largest group of active users on Instagram, Twitter, and Snapchat in the region [
Our results suggest that those with an average monthly family income of 5001 SAR (US $1300) to 20,000 SAR (US $5400) were less likely to have problematic smartphone use compared with people in the lower- or higher-income groups. In a study in China, the relationship of income with smartphone use was not clear [
Regarding characteristics related to smartphone use, we found that people using more than 5 apps were 2 times more likely to exhibit problematic smartphone use. A study in the United Kingdom showed that the use of social and communication apps significantly correlates with problematic smartphone use [
In this study, there was no statistically significant association between problematic smartphone use and gender, age, marital status, or educational attainment. However, a multicenter study among Saudi university students showed that female students were more affected [
The relationship between marital status and problematic smartphone use is understudied as most previous research has focused on the young [
With regard to age, other studies from different parts of the world have shown that the total time spent on cell phones decreases with age, with the highest times reported for people less than 20 years old. This is related to the decreased self-control found in this age group [
In this study, there was no statistically significant difference between the unemployed and employed groups. Hence, time is seemingly not an issue for those with problematic smartphone use. In Spain, a study showed that unemployed individuals were more addicted to their smartphones than people in other employment categories [
Our study had some limitations, mainly in data collection; we depended on self-reported data, which could be a source of bias. Another limitation was that the SAS-SV scale is not validated for use in this culture. A third limitation was our sampling technique; although we employed systematic random sampling to recruit study participants, accessing them only from PHC and one university in the Qassim region might have negatively affected representativeness.
The overall prevalence of problematic smartphone use was high among our study participants, and this problematic use was associated with being a student and using more than 5 apps. An average monthly family income of 5001 SAR (US $1300) to 20,000 SAR (US $5400) and using apps for academic or professional and religious purposes were found to have a protective effect against problematic smartphone use. Our findings have implications for future public health programs in KSA. Considering the high prevalence of problematic smartphone use among adults and its negative impact on physical and psychosocial health, public health programs should develop and implement appropriate preventive strategies. Further studies should focus on investigating the association between health-related quality of life and problematic use of smartphones.
Kingdom of Saudi Arabia
odds ratio
primary health care centers
Saudi Riyal
Smartphone Addiction Scale–Short Version
The authors gratefully acknowledge Qassim University, represented by the Deanship of Scientific Research, on the financial support for this research under the number (grant med-2019-2-2-I-5437) during the academic year 2019.
Conceptualization: AAM, IM, and MA; methodology: AAM and IM; formal analysis: IM; data curation, AAM, IM, and MA; writing—original draft preparation: AAM and IM; writing—review and editing: AAM and IM; visualization: IM; supervision: AAM and IM; project administration: AAM and MA; funding acquisition: AAM, IM, and MA. All authors have read and agreed to the published version of the manuscript. The authors thank Erin Strotheide for her editorial contributions to this work.
None declared.