Users Online: 671 Home Print this page Email this page Small font sizeDefault font sizeIncrease font size
 

 

Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 
     

 Table of Contents  
ORIGINAL ARTICLE: DR. P. C. SEN MEMORIAL AWARD PAPER ON RURAL HEALTH PRACTICE
Year : 2021  |  Volume : 65  |  Issue : 4  |  Page : 340-344  

Validation of a questionnaire on problematic use of smartphones among a rural population of West Bengal


1 Assistant Professor, Department of Community Medicine, R G Kar Medical College, Kolkata, West Bengal, India
2 Junior Resident, Department of Community Medicine, R G Kar Medical College, Kolkata, West Bengal, India
3 Senior Resident, Department of Community Medicine, R G Kar Medical College, Kolkata, West Bengal, India

Date of Submission08-Nov-2021
Date of Decision08-Nov-2021
Date of Acceptance23-Nov-2021
Date of Web Publication29-Dec-2021

Correspondence Address:
Manisha Das
Department of Community Medicine, R G Kar Medical College, 1, Khudiram Bose Sarani, Kolkata - 700 004, West Bengal
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijph.ijph_2026_21

Rights and Permissions
   Abstract 


Background: While a smartphone can be a hugely productive tool, excessive use of this device can interfere with work, education, our physical and mental health, and productivity. Nowadays, we do not just use our smartphones, but we rely on them. Objectives: The present study aims to develop and validate an instrument measuring the problematic use of smartphones among adults in a rural area of West Bengal, India. Methods: The questionnaire on problematic use of smartphone is a self-designed tool. The items were selected by literature review. The psychometric properties of the questionnaire were assessed by content validity, construct validity, and reliability. Exploratory factor analysis was performed to identify the factors. Results: Forty-two items were generated by literature review. After final analysis, the main questionnaire contained 28 items with 5 domains, namely “impulsive use of phone,” “dependence,” “impaired control,” “denial,” “decreased productivity,” and “emotional attachment.” The Cronbach's alpha value for three domains was found to be >0.7 and >0.8 for the other three domains. Conclusion: Excessive mobile phone use is associated with various adverse consequences which is emerging as a public health problem in a large number of population in India. Problematic use of smartphone questionnaire is a valid and reliable tool to assess the pattern of mobile use among Indian population.

Keywords: India, mobile phone, problematic use, smartphone


How to cite this article:
Basu R, Pattanayak SK, Rajesh De, Sarkar A, Bhattacharya A, Das M. Validation of a questionnaire on problematic use of smartphones among a rural population of West Bengal. Indian J Public Health 2021;65:340-4

How to cite this URL:
Basu R, Pattanayak SK, Rajesh De, Sarkar A, Bhattacharya A, Das M. Validation of a questionnaire on problematic use of smartphones among a rural population of West Bengal. Indian J Public Health [serial online] 2021 [cited 2022 Jan 16];65:340-4. Available from: https://www.ijph.in/text.asp?2021/65/4/340/333977




   Introduction Top


Mobile phone provides a medium of communication that has nearly universal adoption globally in both developed and developing nations. In the last decade, it has evolved from a primary tool of interpersonal communication to facilitating group communication. This transformation has been enabled by the integration of mobile Internet facilities, converting them into smartphones. India has the second-highest mobile connections in the world after China, with more than 90 connections per 100 people. The number of smartphone users in India is showing a rapidly increasing trend, with nearly one in three mobile phone users expected to be smartphone users by 2021.[1] A distinctive feature of these trends is that it is not just restricted to cities only but also in rural areas as well because of its easy use and easy availability of Internet connection. Although smartphones allow individuals to have unlimited access to information and to connect with others in a way otherwise thought impossible, data have now started emerging with respect to the negative physical and psychological consequences of excessive use of mobile phones as well.[2]

Negative aspects related to mobile phone use are often conceptualized within the umbrella term of problematic mobile phone use. Studies from various parts of the world have shown adverse physical and psychological consequences of excessive use of mobile phones such as addiction-like behavior or dependence or problematic use of mobile phones.[3] However, no systemic study is available that has evaluated the problematic mobile phone use in India and moreover in general population of rural areas. Considering the increasing interest in behavioral addiction and lack of data from India, the present study attempted to validate a questionnaire for the assessment of problematic use of smartphones among the adults of a rural area of North 24 Parganas of West Bengal in India.


   Materials and Methods Top


The Problematic Mobile Phone Use Questionnaire was developed in two phases, item generation and item reduction [Figure 1].
Figure 1: Steps of questionnaire validation on problematic use of mobile phones.

Click here to view


Item generation

Literature review

A thorough literature search was carried out to identify the most relevant areas describing the problematic use of phones using PubMed, ResearchGate, Google Scholar, and Directory of Open Access Journals. The keywords included “problematic use of phone,” “phone addiction,” “phone dependence,” and “phone overuse.” The screening of the articles was done according to the title and abstract followed by full article review and which resulted in 19 relevant studies which were used to develop the questionnaire.[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17],[18],[19],[20]

Questionnaire development

After literature review, the initial framework of the questionnaire was presented to seven public health experts. A detailed discussion was done among the experts regarding various dimensions. The questionnaire was reviewed many times to refine the words and content, and finally, the primary questionnaire contained 46 items. The items were then translated into local language and back translated into English by language expert. Responses for the items were in a 5-point Likert scale where 1 was “strongly agree” and 5 was “strongly disagree.”

Item reduction

Content validity

Content validity of the questionnaire was assessed by seven experts by calculating content validity index (CVI). It is calculated based on item (i-CVI) and scale (s-CVI) validity index. The i-CVI was calculated by seven experts who gave a score of 3 or 4 to each item on a 4-point likert scale. The s-CVI was measured by s-CVI/Ave (averaging method) by calculating the average values of i-CVI. The acceptable cutoff value for i-CVI is 0.78 with seven experts and 0.8 for s-CVI[21],[22],[23] were taken. All the experts were requested to rate the items based on a 4-point scale for this purpose.

Construct validity and reliability

Exploratory factor analysis (EFA) with varimax rotation was used to measure construct validity. It was applied to the selected items so that the items with similar characteristics can be grouped together into factors. Kaiser–Meyer–Olkin (KMO) test and Bartlett's test were done before factor analysis. The sample adequacy is measured by KMO statistics. The hypothesis for Bartlett's test is correlation matrix is an identity matrix. The KMO statistics value was found to be >0.5 and Bartlett's test value <0.05 which denotes factorial analysis can be used and variables are suitable for structure formation. The inclusion or exclusion of an item in a domain was determined by examining factor loadings and Cronbach's alpha. Multicollinearity was checked and the items that showed high correlation (>+0.9 or < -0.9) and low correlation (<±0.3) with other items were dropped out from further analysis. The internal consistency of each factor was checked by calculating Cronbach's alpha.[24] A value of 0.7 was regarded as an acceptable reliability coefficient.[25]

Pilot testing

The preliminary questionnaire was pretested on thirty individuals of the chosen study area who were not included in the main study. The simplicity, correct interpretation, and time required to answer the questionnaire by the respondents were evaluated and modifications were made in the questionnaire according to that.

Main study setting

A descriptive, cross-sectional study was conducted among rural adults of Amdanga block of North 24 Parganas of West Bengal[26] which is the field practice area of the Department of Community Medicine of R. G. Kar Medical College. In a previous study, mobile phone addiction among young adults was found to be 33.5%.[4] As phone addiction can be concluded as problematic use taking 33.5% prevalence with 5% allowable error, the calculated sample size was 342. From total 81 villages of Amdanga block, 59 accessible villages were chosen. Six persons from each of 59 villages were interviewed to achieve the required sample size. Thus, the final sample size became 354.

Individuals were selected by going to the center of the selected village and finding out the direction by lottery method. In the selected direction, consecutive houses were visited by left thumb rule. One person from one household was selected until the required number reached. Persons who did not have a smartphone were excluded.

Ethical consideration

Ethical approval was taken from the Institute's Ethical Committee of R. G. Kar Medical College. Consent was taken from the study participants before the interview.


   Results Top


Demographic characteristics

Among 354 study participants, 50.6% were female and 49.4% were male, with a maximum study population belonging to the age group of 18–40 years (73.7%). Maximum (33.9%) were homemakers according to division by occupation group and maximum individuals (31.4%) have the educational qualification higher secondary completed [Table 1].
Table 1: Distribution of the study population according to sociodemographic characteristics (n=354)

Click here to view


Questionnaire development

Content validity and pilot testing

After content validity with 7 experts, items that had i-CVI <0.78 were removed. Thus, 6 items were removed from initial questionnaire. Subsequent 36 most relevant items with s-CVI 0.86 were retained for further analysis. In pilot testing, no potential problems were found in the administration of the questionnaire or with understanding the meaning of the items among study participants.

Construct validity

After getting the responses from the study participants, some of the items were coded reversely giving the highest scores to the most favorable answer. The KMO test value was found to be 0.830, which denotes that the sample is adequate for factor analysis. Bartlett's test was found to be significant with P < 0.0001, which indicates that factor analysis can be performed.

Principal component analysis revealed six components that had eigenvalue >1 with the highest value of 15.741. The six components explained 41.258, 5.806, 5.704, 5.540, 4.942, and 3.151 of the variance, respectively. A total of 66.091% of total variance was explained by all the components [Table 2].
Table 2: Factors with total explained variance

Click here to view


The items were divided into six domains according to factor loadings, with domains 1 and 2 measured by 8 items, domains 3 and 5 by 4 items, and domain 4 and 6 by 3 items.

Final factors and reliability

The domains were labeled as “impulsive use of phone,” “dependence,” “impaired control,” “denial,” “decreased productivity,” and “emotional attachment.” The internal consistency of each domain was measured by Cronbach's alpha value. Initially, 8 items were loaded in domain 1 with Cronbach's alpha 0.609 but increased to 0.790 after dropping one item. Similarly, from domain 2, one item was dropped with the final value of 0.794. No items were dropped from subsequent four domains with scores of 0.870, 0.834, 0.812, and 0.731, respectively. Thus, the total items remained 28 with 6 domains [Table 3].
Table 3: Factor loading matrix of the items and internal consistency

Click here to view



   Discussion Top


The present study was conducted to assess the problematic use of smartphones among adults in a rural area of India by developing and validating a specific questionnaire. For this purpose after reviewing other researches, content validity, construct validity, and reliability of the questionnaire were performed. This final questionnaire has 28 items and 6 factors or domains, namely “impulsive use of phone,” “dependence,” “impaired control,” “denial,” “decreased productivity,” and “emotional attachment” that explained 66% of total variance.

Lopez-Fernandez et al.[3] had developed the Problematic Mobile Phone Use Questionnaire in the year 2018 and validated it in eight European languages. They have concluded that PMPU is situated between the absence of problems and severe problems and it is open to debate in relation to its health and educational harms in individuals' daily lives. Bianchi and Phillips[19] have introduced a 27-item Mobile Phone Problem Use Scale-27 with very good internal consistency (α > 0.9) which addresses different aspects of addiction. Particularly, the aspects of tolerance, escape from other problems, withdrawal, craving, and negative life consequences were emphasized by the authors.

For this study, an extensive literature search was carried out for generation of the items which were modified several times before administration to the target population. Regarding the sample size for questionnaire validation, some authors mentioned 5–10 persons for factor analysis of each item, while other authors propose applying the rule of Kline.[27] In the current study the sample size was 354 and it was sufficient for questionnaire validation.

The content validity measured by i-CVI and s-CVI was found to be above the acceptable cutoff value. In EFA, no item was included that had factor loading <0.4 resulting in a 28-item questionnaire with 6 domains which were labeled according to the common characteristics of the items. All the domains were found to have an internal consistency >0.7, while three domains “impaired control,” “denial,” and “decreased productivity” have internal consistency >0.8 which are considered good.[28]

However, at present, there is not much information about the problematic use of smartphone in Indian context moreover in rural population. The study was conducted among general population, whereas most of the studies in India were conducted on students or adolescents to assess addictive behaviors. With the current findings, this instrument can be considered a valid and reliable instrument for assessing the problematic use of smartphones among general population.

Our study has some limitations. The sample is a convenience sample using one rural area in West Bengal and caution needs to be taken while generalizing the study findings. The questionnaire was validated in one local language, so the meaning of the questions may differ according to other regional languages.


   Conclusion Top


Problematic use of mobile phone or phone addiction or phone dependence has been found to be an emerging public health problem. There is a need to identify it early so as to generate adequate awareness and plan educational interventions. The present study aims to validate a questionnaire for assessing problematic smartphone use among rural adults. Although more research is needed to strengthen the future development of the instrument, preliminary findings suggest that this tool is well validated and has a good internal consistency which can determine if the mobile phone use is a potential problem or not among the study population. Future studies are required in Indian population, which takes into account the combined risk arising from both the conventional mobile phone and the Internet-based applications available in smartphones.

Acknowledgment

We would like to acknowledge all the faculties of our department, our principal, and all the staff of the rural field practice area of our institute. Special thanks go to the participants who collaborated with us patiently for the study.



 
   References Top

1.
Sanou B. MDGs 2000-2015: ICT revolution and remaining gaps [Internet]. Geneva: International Telecommunication Union; 2015. Available from: https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2015.pd.  Back to cited text no. 1
    
2.
Merlo LJ, Stone AM, Bibbey A. Measuring problematic mobile phone use: Development and preliminary psychometric properties of the pump scale. J Addict 2013;2013:912807.  Back to cited text no. 2
    
3.
Lopez-Fernandez O, Kuss DJ, Pontes HM, Griffiths MD, Dawes C, Justice LV, et al. Measurement invariance of the short version of the Problematic Mobile Phone Use Questionnaire (PMPUQ-SV) across eight languages. Int J Environ Res Public Health 2018;15:1213.  Back to cited text no. 3
    
4.
(PDF) Does the Excessive use of Mobile Phones in Young Adults Reflect an Emerging Behavioral Addiction?. Available from: https://www.researchgate.net/publication/273981069_Does_the_Excessive_use_of_Mobile_Phones_in_Young_Adults_Reflect_an_Emerging_Behavioral_Addiction. [Last accessed on 2021 Aug 01].  Back to cited text no. 4
    
5.
Smetaniuk P. A preliminary investigation into the prevalence and prediction of problematic cell phone use. J Behav Addict 2014;3:41-53.  Back to cited text no. 5
    
6.
Malviya A, Dixit S, Shukla H, Mishra A, Jain A, Tripathi A. A study to evaluate internet addiction disorder among students of a medical college and associated hospital of central India. Natl J C Med 2014;5:93-5.  Back to cited text no. 6
    
7.
Dixit S, Shukla H, Bhagwat A, Bindal A, Goyal A, Zaidi AK, et al. A study to evaluate mobile phone dependence among students of a medical college and associated hospital of central India. Indian J Community Med 2010;35:339-41.  Back to cited text no. 7
[PUBMED]  [Full text]  
8.
Basu S, Garg S, Singh MM, Kohli C. Addiction-like behavior associated with mobile phone usage among medical students in Delhi. Indian J Psychol Med 2018;40:446-51.  Back to cited text no. 8
[PUBMED]  [Full text]  
9.
Takao M, Takahashi S, Kitamura M. Addictive personality and problematic mobile phone use. Cyberpsychol Behav 2009;12:501-7.  Back to cited text no. 9
    
10.
Prakash S. Internet addiction among junior doctors: A cross-sectional study. Indian J Psychol Med 2017;39:422-5.  Back to cited text no. 10
[PUBMED]  [Full text]  
11.
Choudhury S, Saha I, Som TK, Ghose G, Patra M, Paul B. Mobile phone involvement and dependence among undergraduate medical students in a Medical College of West Bengal, India. J Educ Health Promot 2019;8:1  Back to cited text no. 11
    
12.
Aggarwal M, Grover S, Basu D. Mobile phone use by resident doctors: Tendency to addiction-like behaviour. Ger J Psychiatry 2012;15:50-5.  Back to cited text no. 12
    
13.
Dasgupta P, Bhattacherjee S, Dasgupta S, Roy JK, Mukherjee A, Biswas R. Nomophobic behaviors among smartphone using medical and engineering students in two colleges of West Bengal. Indian J Public Health 2017;61:199-204.  Back to cited text no. 13
[PUBMED]  [Full text]  
14.
Nikhita CS, Jadhav PR, Ajinkya SA. Prevalence of mobile phone dependence in secondary school adolescents. J Clin Diagn Res 2015;9:C06-9.  Back to cited text no. 14
    
15.
Jenaro C, Flores N, Gomez-Vela, Gonzalez-Gil F, Caballo C. Problematic internet and cell-phone use: Psychological, behavioral, and health correlates: Addiction Research & Theory 2009;15:309-20.  Back to cited text no. 15
    
16.
Harris B, Regan T, Schueler J, Fields SA. Problematic mobile phone and smartphone use scales: A systematic review. Front Psychol 2020;11:672.  Back to cited text no. 16
    
17.
Martinotti G, Villella C, Di Thiene D, Di Nicola M, Bria P, Conte G, et al. Problematic mobile phone use in adolescence: A cross-sectional study. J Public Health 2011;19:545-51.  Back to cited text no. 17
    
18.
Foerster M, Roser K, Schoeni A, Röösli M. Problematic mobile phone use in adolescents: Derivation of a short scale MPPUS-10. Int J Public Health 2015;60:277-86.  Back to cited text no. 18
    
19.
Bianchi A, Phillips JG. Psychological predictors of problem mobile phone use. Cyberpsychol Behav 2005;8:39-51.  Back to cited text no. 19
    
20.
Jameel S, Shahnawaz MG, Griffiths MD. Smartphone addiction in students: A qualitative examination of the components model of addiction using face-to-face interviews. J Behav Addict 2019;8:780-93.  Back to cited text no. 20
    
21.
Lynn MR. Determination and quantification of content validity. Nurs Res 1986;35:382-5.  Back to cited text no. 21
    
22.
Davis LL. Instrument review: Getting the most from a panel of experts. Appl Nurs Res 1992;5:194-7.  Back to cited text no. 22
    
23.
Zamanzadeh V, Ghahramanian A, Rassouli M, Abbaszadeh A, Alavi-Majd H, Nikanfar AR. Design and implementation content validity study: Development of an instrument for measuring patient-centered communication. J Caring Sci 2015;4:165-78.  Back to cited text no. 23
    
24.
Available from: http://cda.psych.uiuc.edu/psychometrika_johnson/CronbachPaper%20(1).pdf. [Last accessed on 2021 Aug 02].  Back to cited text no. 24
    
25.
Nunnally JC, Bernstein IH. Psychometric Theory 3E. New Delhi: Tata McGraw-Hill Education; 1994. p. 784.  Back to cited text no. 25
    
26.
About Block Amdanga | NORTH 24 PARGANAS DISTRICT. Available from: http://north24parganas.gov.in/blocks/amdanga/about_block. [Last accessed on 2021 Aug 08].  Back to cited text no. 26
    
27.
Kline RB. Principles and Practice of Structural Equation Modeling 4E. New York: Guilford Publications; 2015. p. 553  Back to cited text no. 27
    
28.
Development and Validation of a Social Capital Questionnaire for Adolescent Students (SCQ-AS). Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0103785. [Last accessed on 2021 Aug 08].  Back to cited text no. 28
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
    Abstract
   Introduction
    Materials and Me...
   Results
   Discussion
   Conclusion
    References
    Article Figures
    Article Tables

 Article Access Statistics
    Viewed754    
    Printed6    
    Emailed0    
    PDF Downloaded136    
    Comments [Add]    

Recommend this journal