<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03260296</url>
  </required_header>
  <id_info>
    <org_study_id>7990</org_study_id>
    <nct_id>NCT03260296</nct_id>
  </id_info>
  <brief_title>Smartphones Addiction in Assiut University Students</brief_title>
  <official_title>Smartphones Addiction and Its Correlations Among Assiut University Students</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Assiut University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Assiut University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Smartphones have become a part of our daily life, the number of people using smartphones is&#xD;
      increasing day after day. Easy access to internet is the main advantage of smartphones in&#xD;
      comparison to traditional mobile phones, so they are considered as handheld convenient&#xD;
      substitutes to computers. People use smartphones for many different purposes such as&#xD;
      communication, entertainment, browsing for information, education or business facilitation.&#xD;
      Unfortunately the excessive use of smartphones makes people 'addicted' to that type of&#xD;
      technology. Past research has shown that older people have less positive attitudes towards a&#xD;
      variety of technologies and they are less likely than younger people to embrace new&#xD;
      technology, so It seems that the problem of smartphones addiction is most likely to affect&#xD;
      young people who are fascinated with new technologies.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      What is smartphones addiction? The concept of smartphones addiction is not proposed yet for&#xD;
      inclusion in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders&#xD;
      (DSM-5) as non-substance-related disorder but it can be considered one type of technological&#xD;
      addictions which were operationally defined by Griffiths as non-chemical (behavioral)&#xD;
      addictions which involve human-machine interaction and usually contain inducing and&#xD;
      reinforcing features which may contribute to the promotion of addictive tendencies.&#xD;
&#xD;
      Furthermore, Recent work by Lin, et al identified the criteria for diagnosis smartphones&#xD;
      addiction as following:&#xD;
&#xD;
      A. Behavioral criteria (3 or more should be present):&#xD;
&#xD;
        1. Preoccupation with smartphone use, and hence keeping smartphone available all day&#xD;
&#xD;
        2. Recurrent failure to resist the impulse to use the smartphone&#xD;
&#xD;
        3. Tolerance: a markedly increase in the duration of smartphone use is needed to achieve&#xD;
           satisfaction&#xD;
&#xD;
        4. Withdrawal: as manifested by a dysphoric mood, anxiety and/or irritability after a&#xD;
           period without smartphone use&#xD;
&#xD;
        5. Smartphone use for a period longer than intended&#xD;
&#xD;
        6. Persistent desire and/or unsuccessful attempts to cut down or reduce smartphone use&#xD;
&#xD;
        7. Excessive smartphone use and/or time spent on leaving the use&#xD;
&#xD;
        8. Continued excessive smartphone use despite knowledge of having a persistent or recurrent&#xD;
           physical or psychological problems caused by smartphone use&#xD;
&#xD;
      B. Functional impairment criteria (2 or more criteria should be present):&#xD;
&#xD;
        1. Excessive use resulting in persistent or recurrent physical or psychological problems&#xD;
&#xD;
        2. Use in a physically hazardous situations (such as while driving or crossing the street)&#xD;
           or situations that have other negative impacts on daily life&#xD;
&#xD;
        3. Use that impairs social relationships or performance at school or work&#xD;
&#xD;
        4. Use that is very time-consuming or causes significant distress C. Exclusion criteria&#xD;
           Addictive behavior is not associated with obsessive-compulsive disorder or bipolar&#xD;
           disorder&#xD;
&#xD;
      Factors associated with smartphones addiction:&#xD;
&#xD;
        -  There are many psychological factors related to smartphones addiction such as anxiety,&#xD;
           stress, poor social and family relationship, depression, loneliness, shyness, degree of&#xD;
           self-esteem and satisfaction with life.&#xD;
&#xD;
        -  Studies have also shown the adverse effects of smartphones addiction on quality of&#xD;
           sleep, physical activity and academic performance.&#xD;
&#xD;
        -  Smartphones addiction also have harmful physical consequences like headache, blurred&#xD;
           vision, neck and shoulder pain and impairment of hand function.&#xD;
&#xD;
      Size of problem:&#xD;
&#xD;
      Prevalence of smartphones addiction in young people varies among countries as shown by&#xD;
      studies: 29.6% in Saudi Arabia, 44.6% in Lebanon,16.9% in Switzerland, 21.3% in China and&#xD;
      31.33% in India.&#xD;
&#xD;
      -there is no available data about the size of this of this problem in Egypt so investigators&#xD;
      need to conduct this study to determine the prevalence of smartphones addiction among young&#xD;
      people and it adverse effect on different aspects.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date type="Anticipated">October 2018</start_date>
  <completion_date type="Anticipated">October 2019</completion_date>
  <primary_completion_date type="Anticipated">May 2019</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Other</observational_model>
    <time_perspective>Cross-Sectional</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Smartphones addiction scale (SAS)</measure>
    <time_frame>6 months</time_frame>
    <description>Prevalence of smartphones addiction and its adverse effects will be evaluated by a self-administered questionnaire guided by smartphones addiction scale developed by Kwon et al.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Factors associated with smartphones addiction questionnaire</measure>
    <time_frame>6 months</time_frame>
    <description>the study will assess some associated factors that may be risk factors to smartphones addiction as depression and loneliness</description>
  </secondary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Anticipated">693</enrollment>
  <condition>Behavior Problem</condition>
  <condition>Addiction</condition>
  <arm_group>
    <arm_group_label>University students</arm_group_label>
    <description>university students who use smartphones</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>self-administered structured questionnaire</intervention_name>
    <description>Data will be collected by self-administered structured questionnaire. The aim of the study and the way of filling the questionnaire will be explained to the students, and then he/she fills the questionnaire by him/her self.&#xD;
The questionnaire will assess smartphones addiction and some of its associated factors and its health consequences</description>
    <arm_group_label>University students</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Egyptian Students of Assiut University will be the target population Target students will&#xD;
        be selected randomly by using a multistage stratified cluster sampling technique.&#xD;
&#xD;
        At the first stage, Faculties within Assiut University will be stratified into 3 strata;&#xD;
        Practical , Theoretical and Medical then faculties will be chosen randomly from each&#xD;
        stratum to end up with 4 faculties (2 theoretical, 1 practical and 1 medical).&#xD;
&#xD;
        In the second stage, cluster sample will be chosen from one academic year within each&#xD;
        faculty (practical sections or small classes). The clusters will be chosen through simple&#xD;
        random sample.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  -Egyptian students&#xD;
&#xD;
          -  Students in one selected academic year&#xD;
&#xD;
          -  Students have smartphones&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  -Non-Egyptian students&#xD;
&#xD;
          -  Students in academic years other than the selected one&#xD;
&#xD;
          -  Students having traditional mobile phones or not having mobile phones at all&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>17 Years</minimum_age>
    <maximum_age>23 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Hosnia Said, MD</last_name>
    <phone>+201062170293</phone>
    <email>hosniasa@yahoo.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Dalia Galal, MD</last_name>
    <phone>+201007120821</phone>
    <email>daliaym2001@yahoo.com</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Assiut University</name>
      <address>
        <city>Assiut</city>
        <zip>71111</zip>
        <country>Egypt</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Egypt</country>
  </location_countries>
  <results_reference>
    <citation>Lin YH, Lin YC, Lee YH, Lin PH, Lin SH, Chang LR, Tseng HW, Yen LY, Yang CC, Kuo TB. Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App). J Psychiatr Res. 2015 Jun;65:139-45. doi: 10.1016/j.jpsychires.2015.04.003. Epub 2015 Apr 10.</citation>
    <PMID>25935253</PMID>
  </results_reference>
  <results_reference>
    <citation>Griffiths M. Gambling on the internet: A brief note. J Gambl Stud. 1996 Dec;12(4):471-3. doi: 10.1007/BF01539190. No abstract available.</citation>
    <PMID>24234164</PMID>
  </results_reference>
  <results_reference>
    <citation>Demirci K, Akgonul M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addict. 2015 Jun;4(2):85-92. doi: 10.1556/2006.4.2015.010.</citation>
    <PMID>26132913</PMID>
  </results_reference>
  <results_reference>
    <citation>Kim SE, Kim JW, Jee YS. Relationship between smartphone addiction and physical activity in Chinese international students in Korea. J Behav Addict. 2015 Sep;4(3):200-5. doi: 10.1556/2006.4.2015.028.</citation>
    <PMID>26551911</PMID>
  </results_reference>
  <results_reference>
    <citation>Kim HJ; DH; Kim JS. The relationship between smartphone use and subjective musculoskeletal symptoms and university students. J Phys Ther Sci. 2015 Mar;27(3):575-9. doi: 10.1589/jpts.27.575. Epub 2015 Mar 31.</citation>
    <PMID>25931684</PMID>
  </results_reference>
  <results_reference>
    <citation>Haug S, Castro RP, Kwon M, Filler A, Kowatsch T, Schaub MP. Smartphone use and smartphone addiction among young people in Switzerland. J Behav Addict. 2015 Dec;4(4):299-307. doi: 10.1556/2006.4.2015.037.</citation>
    <PMID>26690625</PMID>
  </results_reference>
  <results_reference>
    <citation>Nikhita CS, Jadhav PR, Ajinkya SA. Prevalence of Mobile Phone Dependence in Secondary School Adolescents. J Clin Diagn Res. 2015 Nov;9(11):VC06-VC09. doi: 10.7860/JCDR/2015/14396.6803. Epub 2015 Nov 1.</citation>
    <PMID>26672469</PMID>
  </results_reference>
  <results_reference>
    <citation>Long J, Liu TQ, Liao YH, Qi C, He HY, Chen SB, Billieux J. Prevalence and correlates of problematic smartphone use in a large random sample of Chinese undergraduates. BMC Psychiatry. 2016 Nov 17;16(1):408. doi: 10.1186/s12888-016-1083-3.</citation>
    <PMID>27855666</PMID>
  </results_reference>
  <results_reference>
    <citation>Kwon M, Lee JY, Won WY, Park JW, Min JA, Hahn C, Gu X, Choi JH, Kim DJ. Development and validation of a smartphone addiction scale (SAS). PLoS One. 2013;8(2):e56936. doi: 10.1371/journal.pone.0056936. Epub 2013 Feb 27.</citation>
    <PMID>23468893</PMID>
  </results_reference>
  <verification_date>August 2017</verification_date>
  <study_first_submitted>August 20, 2017</study_first_submitted>
  <study_first_submitted_qc>August 23, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">August 24, 2017</study_first_posted>
  <last_update_submitted>August 23, 2017</last_update_submitted>
  <last_update_submitted_qc>August 23, 2017</last_update_submitted_qc>
  <last_update_posted type="Actual">August 24, 2017</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Assiut University</investigator_affiliation>
    <investigator_full_name>Mariam Gamal</investigator_full_name>
    <investigator_title>principle investigator</investigator_title>
  </responsible_party>
  <keyword>smartphones addiction</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Behavior, Addictive</mesh_term>
    <mesh_term>Problem Behavior</mesh_term>
    <mesh_term>Internet Addiction Disorder</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Undecided</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03260296
org study id: 7990
nct id: NCT03260296
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Smartphones have become a part of our daily life, the number of people using smartphones is
      increasing day after day. Easy access to internet is the main advantage of smartphones in
      comparison to traditional mobile phones, so they are considered as handheld convenient
      substitutes to computers. People use smartphones for many different purposes such as
      communication, entertainment, browsing for information, education or business facilitation.
      Unfortunately the excessive use of smartphones makes people 'addicted' to that type of
      technology. Past research has shown that older people have less positive attitudes towards a
      variety of technologies and they are less likely than younger people to embrace new
      technology, so It seems that the problem of smartphones addiction is most likely to affect
      young people who are fascinated with new technologies.
What is smartphones addiction? The concept of smartphones addiction is not proposed yet for
      inclusion in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders
      (DSM-5) as non-substance-related disorder but it can be considered one type of technological
      addictions which were operationally defined by Griffiths as non-chemical (behavioral)
      addictions which involve human-machine interaction and usually contain inducing and
      reinforcing features which may contribute to the promotion of addictive tendencies.

      Furthermore, Recent work by Lin, et al identified the criteria for diagnosis smartphones
      addiction as following:

      A. Behavioral criteria (3 or more should be present):

        1. Preoccupation with smartphone use, and hence keeping smartphone available all day

        2. Recurrent failure to resist the impulse to use the smartphone

        3. Tolerance: a markedly increase in the duration of smartphone use is needed to achieve
           satisfaction

        4. Withdrawal: as manifested by a dysphoric mood, anxiety and/or irritability after a
           period without smartphone use

        5. Smartphone use for a period longer than intended

        6. Persistent desire and/or unsuccessful attempts to cut down or reduce smartphone use

        7. Excessive smartphone use and/or time spent on leaving the use

        8. Continued excessive smartphone use despite knowledge of having a persistent or recurrent
           physical or psychological problems caused by smartphone use

      B. Functional impairment criteria (2 or more criteria should be present):

        1. Excessive use resulting in persistent or recurrent physical or psychological problems

        2. Use in a physically hazardous situations (such as while driving or crossing the street)
           or situations that have other negative impacts on daily life

        3. Use that impairs social relationships or performance at school or work

        4. Use that is very time-consuming or causes significant distress C. Exclusion criteria
           Addictive behavior is not associated with obsessive-compulsive disorder or bipolar
           disorder

      Factors associated with smartphones addiction:

        -  There are many psychological factors related to smartphones addiction such as anxiety,
           stress, poor social and family relationship, depression, loneliness, shyness, degree of
           self-esteem and satisfaction with life.

        -  Studies have also shown the adverse effects of smartphones addiction on quality of
           sleep, physical activity and academic performance.

        -  Smartphones addiction also have harmful physical consequences like headache, blurred
           vision, neck and shoulder pain and impairment of hand function.

      Size of problem:

      Prevalence of smartphones addiction in young people varies among countries as shown by
      studies: 29.6% in Saudi Arabia, 44.6% in Lebanon,16.9% in Switzerland, 21.3% in China and
      31.33% in India.

      -there is no available data about the size of this of this problem in Egypt so investigators
      need to conduct this study to determine the prevalence of smartphones addiction among young
      people and it adverse effect on different aspects.
observational model: Other
time perspective: Cross-Sectional
measure: Smartphones addiction scale (SAS)
time frame: 6 months
description: Prevalence of smartphones addiction and its adverse effects will be evaluated by a self-administered questionnaire guided by smartphones addiction scale developed by Kwon et al.
measure: Factors associated with smartphones addiction questionnaire
time frame: 6 months
description: the study will assess some associated factors that may be risk factors to smartphones addiction as depression and loneliness
arm group label: University students
description: university students who use smartphones
intervention type: Other
intervention name: self-administered structured questionnaire
description: Data will be collected by self-administered structured questionnaire. The aim of the study and the way of filling the questionnaire will be explained to the students, and then he/she fills the questionnaire by him/her self.
The questionnaire will assess smartphones addiction and some of its associated factors and its health consequences
arm group label: University students
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 17 Years
maximum age: 23 Years
healthy volunteers: No
last name: Hosnia Said, MD
phone: +201062170293
email: hosniasa@yahoo.com
last name: Dalia Galal, MD
phone: +201007120821
email: daliaym2001@yahoo.com
facility: 
country: Egypt
citation: Lin YH, Lin YC, Lee YH, Lin PH, Lin SH, Chang LR, Tseng HW, Yen LY, Yang CC, Kuo TB. Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App). J Psychiatr Res. 2015 Jun;65:139-45. doi: 10.1016/j.jpsychires.2015.04.003. Epub 2015 Apr 10.
PMID: 25935253
citation: Griffiths M. Gambling on the internet: A brief note. J Gambl Stud. 1996 Dec;12(4):471-3. doi: 10.1007/BF01539190. No abstract available.
PMID: 24234164
citation: Demirci K, Akgonul M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addict. 2015 Jun;4(2):85-92. doi: 10.1556/2006.4.2015.010.
PMID: 26132913
citation: Kim SE, Kim JW, Jee YS. Relationship between smartphone addiction and physical activity in Chinese international students in Korea. J Behav Addict. 2015 Sep;4(3):200-5. doi: 10.1556/2006.4.2015.028.
PMID: 26551911
citation: Kim HJ; DH; Kim JS. The relationship between smartphone use and subjective musculoskeletal symptoms and university students. J Phys Ther Sci. 2015 Mar;27(3):575-9. doi: 10.1589/jpts.27.575. Epub 2015 Mar 31.
PMID: 25931684
citation: Haug S, Castro RP, Kwon M, Filler A, Kowatsch T, Schaub MP. Smartphone use and smartphone addiction among young people in Switzerland. J Behav Addict. 2015 Dec;4(4):299-307. doi: 10.1556/2006.4.2015.037.
PMID: 26690625
citation: Nikhita CS, Jadhav PR, Ajinkya SA. Prevalence of Mobile Phone Dependence in Secondary School Adolescents. J Clin Diagn Res. 2015 Nov;9(11):VC06-VC09. doi: 10.7860/JCDR/2015/14396.6803. Epub 2015 Nov 1.
PMID: 26672469
citation: Long J, Liu TQ, Liao YH, Qi C, He HY, Chen SB, Billieux J. Prevalence and correlates of problematic smartphone use in a large random sample of Chinese undergraduates. BMC Psychiatry. 2016 Nov 17;16(1):408. doi: 10.1186/s12888-016-1083-3.
PMID: 27855666
citation: Kwon M, Lee JY, Won WY, Park JW, Min JA, Hahn C, Gu X, Choi JH, Kim DJ. Development and validation of a smartphone addiction scale (SAS). PLoS One. 2013;8(2):e56936. doi: 10.1371/journal.pone.0056936. Epub 2013 Feb 27.
PMID: 23468893
responsible party type: Principal Investigator
investigator affiliation: Assiut University
investigator full name: Mariam Gamal
investigator title: principle investigator
mesh term: Behavior, Addictive
mesh term: Problem Behavior
mesh term: Internet Addiction Disorder
sharing ipd: Undecided