• Users Online: 70
  • Print this page
  • Email this page


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2018  |  Volume : 19  |  Issue : 1  |  Page : 24-29

Internet addictive behaviors and subjective well-being among 1st-year medical students


1 Department of Psychiatry, Akash Institute of Medical Sciences and Research Centre, Bengaluru, Karnataka, India
2 Department of Biochemistry, Akash Institute of Medical Sciences and Research Centre, Bengaluru, Karnataka, India
3 Department of Psychiatry, Kempegowda Institute of Medical Sciences and Research Centre, Bengaluru, Karnataka, India

Date of Web Publication26-Jun-2018

Correspondence Address:
Dr. Vedalaveni Chowdappa Suresh
Department of Psychiatry, Akash Institute of Medical Sciences and Research Centre, Devanahalli, Bengaluru - 562 110, Karnataka
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/AMH.AMH_3_18

Rights and Permissions
  Abstract 


Context: Exponential rise in internet usage over the past two decades has fostered internet addictive behaviors, especially in young adults. In India, medical students undergo tremendous stressful situations and are a vulnerable group for such addictive behaviors.
Aims: The aim of the study was to assess subjective happiness of 1st-year medical students and their internet addiction levels
Settings and Design: A cross-sectional study done in a medical college in Bangalore, Karnataka, India.
Materials and Methods: Sample consisted of 150 1st-year medical students, who self-reported about their internet addictive pattern and subjective well-being on Internet Addiction Test and Subjective Happiness Scale, respectively.
Statistical Analysis: Descriptive and inferential statistical analyses were carried out. Significance is assessed at 5% level of significance. Analysis of variance, Student's t-test, and Chi-square/Fisher's Exact test have been used.
Results: Of the total sample, 42.7% of students reported of experiencing subjective happiness below the average, 41.3% had average happiness levels, and only 16% had scores above the average. Out of the students, 42.1% who had no internet addiction, 36.4% who had mild levels, and 54.8% who had moderate levels of internet addiction fell below the average happiness level.
Conclusions: Those who had higher levels of internet addiction showed reduced subjective happiness. Thus, those who experience decreased subjective happiness without overt psychological disturbances are still prone to have addictive patterns. This should be considered during screening for addictive behaviors.

Keywords: Internet addiction, medical students, subjective well-being


How to cite this article:
Suresh VC, Silvia WD, Kshamaa HG, Nayak SB. Internet addictive behaviors and subjective well-being among 1st-year medical students. Arch Ment Health 2018;19:24-9

How to cite this URL:
Suresh VC, Silvia WD, Kshamaa HG, Nayak SB. Internet addictive behaviors and subjective well-being among 1st-year medical students. Arch Ment Health [serial online] 2018 [cited 2018 Dec 14];19:24-9. Available from: http://www.amhonline.org/text.asp?2018/19/1/24/235319




  Introduction Top


Internet usage has grown significantly in the past few decades and has led to addictive behaviors.[1] Addiction potential of internet has been recognized from 1996, and subsequently criteria have been proposed to diagnose addiction, trying to focus on its uncontrollable and harmful effects.[2],[3] Harmful effects of excessive usage of internet, especially for gaming, were reported in Asian countries such as South Korea and China, and were later found to be present across various cultures and populations.[4],[5] However, it lacks a proper suitable definition, which is also due to various terminologies given to the addiction patterns such as internet addiction, internet dependency, and internet pathological use. Addictive patterns are seen in various domains such as gaming, sexual needs, and communication.[2],[6] Components such as excessive use, loss of control, withdrawal features and tolerance, associated with other addictive disorders, have also been found related to addictive internet usage, prompting a plea for its inclusion in DSM-V, and this remains inconclusive.[7],[8] Proposed etiologies also range from genetic factors, biological vulnerabilities, psychological issues, social interaction patterns, and cultural issues.[9]

Whether it should be included in classification systems or not, and subsequent consequences of either, will emerge with further research. However, there is no denying that, while on one hand internet has become an essential and indispensable commodity useful in most of our daily lives, excessive use with addiction potential and psychological disturbances associated with it have also become common.[9] While South Korean studies point to increase cardiovascular risk in addicted individuals, psychiatric comorbidities such as anxiety, depression, attention deficit hyperactive disorder, alcohol dependence, and abuse are associated with internet addiction. In addition, negative coping skills, cognitive distortions, decreased self-esteem, reduction in social interactions in real life (as opposed to virtual social communication), and an overall poor psychological status are frequent in those who have addictive usage patterns.[5],[9] Internet provides easy opportunities for leisure, virtual communication, gaming, sexual satisfaction, and even shopping giving multiple and unpredictable rewards and thus reinforcing the addictive behavior. Thus, a vicious cycle is formed from which students fail to get out.[9]

Most studies done in India regarding internet usage pattern have shown milder levels of addictive behaviors and increased psychological distress, anxiety, and depressive features.[10],[11],[12] The at-risk population is young adults, mainly belonging to age range of 18–34 years.[13],[14] This age group, in India, encompasses students who are pursuing medical course. They face various stressful conditions owing to the lengthy duration of the course, which often spans over a decade, its vast and difficult academic scope, financial difficulties regarding fee structures, high expectations from family and relatives, adjusting to a new environment away from the family, and difficulties in interpersonal relationships.[15],[16] These in turn decrease learning abilities and cause emotional and psychological distress.[17],[18] To deal with various problems, students often use faulty strategies and negative coping styles, which may lead to harmful results such as addictive behaviors. Internet addiction is one such behavior which is on the rise, especially among college students. Easy accessibility at affordable prices makes internet a potential area for addictive behavior, apart from its use as modes of communication, entertainment, and academic purposes. In medical students, psychological well-being is often compromised, which may push them toward an addictive pattern of internet use, further leading to emotional stress, decreased social interactions, poor academic performance, and a poorer mental health status overall. Internet addiction is found to be higher in those who have significant anxiety and depression; however, addictive behaviors can also be found in those who have subsyndromal levels of psychological distress.[19],[20],[21] Reduction in subjective happiness gradually paves a path to higher internet usage in search for happiness, in the form of entertainment, leisure, gaming, shopping, and virtual communication, culminating into an addictive pattern.[22] Hence, the aim of this study was to assess subjective happiness of 1st-year medical students and their internet addiction levels.

Settings and design

The study sample consisted of 150 1st-year medical students of Akash Institute of Medical Sciences and Research Centre, Bangalore. Institutional Ethical Committee clearance was obtained beforehand. Students were briefly informed about the questionnaires and doubts, if any, were timely addressed. A written informed consent was taken from the students who were willing to participate in the study. Anonymity about individual identities and information provided was ensured. Students then self-reported according to Young's Internet Addiction Test (IAT) questionnaire and Subjective Happiness Scale (SHS), which took approximately 15–20 min.


  Materials and Methods Top


Young's Internet Addiction test

This instrument was developed by Dr. Kimberly Young.[2],[23] It is a reliable measure of severity of self-reported compulsive internet usage. It consists of twenty items and each question is rated on a 5-point Likert scale from 0 to 5 (0 = Does not apply, 1 = Rarely, 2 = Occasionally, 3 = Frequently, 4 = Often, and 5 = Always). Total scores are calculated after adding the score on all twenty items, so as to get the score which ranges from 20 to 100. Based on the scoring, results are interpreted as follows: 0–19 points = normal range, 20–49 points = mild, 50–79 points = moderate, and 80–100 points = severe internet addictive behaviors. Higher the total scores, greater the level of internet addiction. The validity and reliability of the Young's IAT has been evaluated in various studies.[24],[25]

Subjective Happiness Scale

This self-rated questionnaire was developed by Lyubomirsky and Lepper.[26] It has four items and each is rated on a 7-point Likert scale as follows; item number 1 (1 = not a very happy person, to 7 = a very happy person), item number 2 (1 = less happy, to 7 = more happy), item numbers 3 and 4 (1 = not at all, to 7 = a great deal), and item number 4 is reverse coded using a descending sequence. All the scores are then added up and the total divided by 4, which gives the subjective happiness score. SHS has been validated and has shown high internal consistency across various sample populations.[27] As the author of the SHS had suggested, although the average is from 4.5 to 5.5, college students tend to score lower on the scale (averaging bit below 5), than adults and older people, who are either working or have retired (averaging 5.6). Those who have a score below or equal to 4.4 are considered to experience lower levels of subjective happiness than the average, and those who score ≥5.6 are considered to experience higher levels of subjective happiness than the average.[26]

Statistical analysis

The statistical software namely Statistical Package for the Social Sciences (SPSS) version 18.0 and R environment ver. 3.2.2 (SPSS inc, Chicago, United States of America) were used for the analysis of the data and Microsoft word and Excel have been used to generate graphs, tables, etc. Descriptive and inferential statistical analyses have been carried out in the present study. Results on continuous measurements are presented on mean ± standard deviation (min-max) and results on categorical measurements are presented in number (%). Significance is assessed at 5% level of significance. The following assumptions on data are made: (1) dependent variables should be normally distributed and (2) samples drawn from the population should be random, and cases of the samples should be independent. Analysis of variance has been used to find the significance of study parameters between three or more groups of students; Student's t-test (two-tailed, independent) has been used to find the significance of study parameters on continuous scale between two groups (intergroup analysis) on metric parameters. Chi-square/Fisher's Exact test has been used to find the significance of study parameters on categorical scale between two or more groups, nonparametric setting for qualitative data analysis. Fisher's exact test used when cell samples are very small.


  Results Top


All the 150 1st-year medical students took part in this study. Of the total sample, 42.7% of students reported of experiencing subjective happiness below the average, 41.3% had average happiness levels, and only 16% had scores above the average. [Table 1] shows the gender distribution as compared to SHS. In this study, 47.5% of males and 39.6% of females were below the average happiness score, whereas only 16.9% of males and 15.4% of females were above the average. Of the study group, 35.6% of males and 45.1% of females were in the average range of happiness. However, there was no significant difference (P = 0.508) between gender and subjective happiness.
Table 1: Subjective happiness scale distribution according to gender of students

Click here to view


[Figure 1] shows IAT levels and its comparison with SHS. Almost 12.6% (n = 19) of students had no internet addiction, 58.2% (n = 88) students had mild level of internet addiction, and 28% (n = 28) had moderate level. Only one student reported of severe levels of addiction.
Figure 1: Comparison of Internet Addiction Test with Subjective Happiness Scale in students

Click here to view


In this study, 42.1% of students who had no internet addiction and 36.4% of students who had mild levels of internet addiction had reported of being less happy subjectively, whereas 54.8% of students who had moderate level of internet addiction fell below the average happiness level. Only one student had severe level of addiction and also had a lower level of subjective happiness. In case of those students who reported of experiencing subjective happiness above the average, 21.1% had no internet addiction, 17% and 11.9% had mild and moderate levels of addiction, respectively. Those who had an average level of subjective happiness, the majority had no addiction (36.8%) and mild addiction (46.6%), and only 33.3% had a moderate addiction. Higher levels of internet addiction showed lower levels of subjective happiness.


  Discussion Top


In this study, overall subjective happiness scores among 1st-year medical students showed that only 16% reported above-average happiness. This is consistent with the observed pattern that young adults who are students show lower levels of happiness as a group.[26] Overall, 42.7% reported of lower than average range happiness, which is a matter of concern. Although statistically not significant, females tend to report higher levels of subjective happiness than males. A qualitative assessment will give us more insights about this difference between gender.

Most of the students were found to have milder levels of internet addiction. As the level of internet addiction increased, i.e., from mild to moderate, subjective happiness decreased. Out of the students who had moderate addiction levels, 54.8% had lower happiness levels compared to 36.4% of students who had mild addiction levels. One student who had severe addiction also had low levels of happiness. Levels of addictions also negatively affected those students who reported to have more happiness than average. As the level of addiction increased from no addiction to mild and moderate levels, subjective happiness also decreased, values being 21.1% for no addiction group, 17% for mild, and 11.9% for moderate levels of addiction. Although not statistically significant (P = 0.410), we observe a general trend of lower levels of subjective happiness in association with higher levels of internet addiction.

Thus, the areas of concern to be focused are:

  1. Overall lower levels of subjective happiness among medical students
  2. Increasing levels of internet usage with some addictive patterns
  3. Lower levels of subjective happiness in those who have higher levels of internet addiction.


Student life is a period of learning, developing a stable personality, and encouraging better ways of communication and social skills. Medical course in India comprises about 5–6 years of undergraduate course including internship and rural services, and further 3–6 years of postgraduate education, excluding years of preparation time for entrance examinations taken by the students at various points. Fee structures vary and often pose financial problems. Parents, guardians, and relatives of students have high expectations about their academic performances and future careers, adding to stress for the students. Further, many students face a completely new environment, staying away from home and with new peers and teachers.[28],[29] Prevalence of stress among medical students in India is reported to have a range of 20%–29%.[30]

Students use various coping mechanisms to deal with the stress they face. Appraisal-focused coping strategies are used by most of them, along with problem-solving and emotion-focused coping mechanisms. Females tend to use emotion-focused coping strategies more often. Appraisal-focused strategies may lead to efforts to minimize the problem areas by overlooking them, leading to avoidant behaviors.[31]

While addictive internet usage is associated with psychological distress and psychiatric comorbidities, those who have better coping mechanisms may not fall under the “disturbed” category when assessed. A student may not be perceiving stress as a psychological disturbance, but as a reduction in happiness, which is evident from this study. Happiness is seldom subjectively measured qualitatively and even less quantitatively. Thus, a student may feel happy but still has addictive internet usage patterns. This subsequently may increase the vulnerability of the individual, more so if he or she has faulty coping mechanisms. From this study, subjective happiness shows decline wherever there is increasing in addictive levels.

There is a deficit in the treatment of internet addictions, due to incomplete understanding of the phenomenology and associated behaviors, lack of diagnostic criteria, and treatment algorithms and guidelines. Controversies regarding diagnostic criteria and inclusion in classification systems will remain for time being, but treatment cannot be deferred.[32],[33] Strategies for psychological perspective are suggested through cognitive-behavioral therapy techniques such as setting goals, abstinence to certain behaviors, cutting reinforcements, and strengthening of support systems. Motivational interviewing to build motivation from within oneself, with learning of new behavioral skills and coping techniques, including support groups, community and family, reality therapy, and acceptance and commitment therapy helping the clients to take responsibility of their actions and time management have all been suggested and found to be helpful, but larger studies are lacking. Pharmacotherapy has shown positive results in small studies, particularly selective serotonin reuptake inhibitors such as escitalopram alone or in combination with quetiapine, bupropion, naltrexone, methylphenidate, and mood stabilizers. They address specific domains such as impulse control, hyperactivity and attention deficits, reward, and craving behaviors. Physical exercise, mindfulness, and relaxation techniques can also be used as adjunctive to treatment. Overall, a multimodal treatment approach with biopsychosocial model is preferred.[9]

Medical students should be considered as a vulnerable group.[34] Healthy internet usage behaviors, social skills training, strengthening positive coping styles, identifying pathological behaviors, and modes of seeking help should be included in their training. Moreover, screening of students to identify addictive behaviors should not only be restricted for those who report psychological distress. As seen in this study, they may have decreased in subjective happiness without overt psychological disturbances but are still prone to have addictive patterns. This should be considered during screening and while providing health education.


  Conclusions Top


Internet usage has become an important tool for academics, communication, entertainment, and various other activities among medical students. However, along with its benefits, addictive usage patterns have emerged in them. This likely to rise among students, especially those who are pursuing 1st-year medical education. In this study, we have focused on how addictive patterns can decrease their happiness or how decreased happiness may foster addictive patterns. This will help us to understand the interplay between addiction and psychological status, as this study shows that addictive patterns can emerge even in students who although not psychologically distressed but experience decrease in happiness. Thus, irrespective of their psychological status, all medical students who join the medical course should be informed about healthy internet usage patterns and should also be sensitized regarding addictive patterns. This will also guide in the development of appropriate screening methods and subsequent interventions. Thus, it becomes a primary preventive step, to nip internet addiction in the bud.

Strength of the study

This is one of the few studies, which have focused on subjective well-being of students and addictive patterns of internet usage. Decrease in subjective happiness can foster addictive pattern. Thus, this study gives a way for further research focusing on psychological/subjective well-being and addictive behaviors. Training programs should encompass all the students and should not be restricted to only those who report or shows features of psychological distress.

Limitations of the study

Small sample group, cross-sectional design, bias that may have occurred during self-report of behaviors and various confounding factors such as presence of other addictive behaviors are possible limitations. A prospective study following up medical students, their internet usage patterns, measuring their happiness, and distresses over the course of their education will show a better pattern of internet addiction longitudinally. A qualitative design looking into happiness and coping skills would enhance our understanding of why students report lower levels of happiness overall.

Acknowledgement

The authors gratefully acknowledge Dr. Satish Babu HV, Director, AIMS & RC and Dr. Vasudeva DS, Principal, AIMS & RC, for the encouragement and constant support to carry out this project. We would like to thank all the First year medical students of batch 2017-18, Akash Institute of Medical Sciences and Research Centre, Devanahalli, Bangalore Rural, for having participated in this study. We also thank Dr KP Suresh, Principal Scientist, NIVEDI, Bangalore for statistical analysis.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Kuss DJ, Griffiths MD, Karila L, Billieux J. Internet addiction: A systematic review of epidemiological research for the last decade. Curr Pharm Des 2014;20:4026-52.  Back to cited text no. 1
    
2.
Young KS. Internet addiction: The emergence of a new clinical disorder. Cyberpsychol Behav 1998;1:237-44.  Back to cited text no. 2
    
3.
Beard KW. Internet addiction: A review of current assessment techniques and potential assessment questions. Cyberpsychol Behav 2005;8:7-14.  Back to cited text no. 3
    
4.
Ho RC, Zhang MW, Tsang TY, Toh AH, Pan F, Lu Y, et al. The association between internet addiction and psychiatric co-morbidity: A meta-analysis. BMC Psychiatry 2014;14:183.  Back to cited text no. 4
    
5.
Heo J, Oh J, Subramanian SV, Kim Y, Kawachi I. Addictive internet use among Korean adolescents: A national survey. PLoS One 2014;9:e87819.  Back to cited text no. 5
    
6.
Young K, Pistner M, O'Mara J, Buchanan J. Cyber disorders: The mental health concern for the new millennium. Cyberpsychol Behav 1999;2:475-9.  Back to cited text no. 6
    
7.
Block JJ. Issues for DSM-V: Internet addiction. Am J Psychiatry 2008;165:306-7.  Back to cited text no. 7
    
8.
Dalal PK, Basu D. Twenty years of internet addiction … quo vadis? Indian J Psychiatry 2016;58:6-11.  Back to cited text no. 8
[PUBMED]  [Full text]  
9.
Cash H, Rae CD, Steel AH, Winkler A. Internet addiction: A brief summary of research and practice. Curr Psychiatry Rev 2012;8:292-8.  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.
Shettar M, Karkal R, Kakunje A, Mendonsa RD, Chandran VM. Facebook addiction and loneliness in the post-graduate students of a university in Southern India. Int J Soc Psychiatry 2017;63:325-9.  Back to cited text no. 11
    
12.
Das A, Sharma MK, Thamilselvan P, Marimuthu P. Technology addiction among treatment seekers for psychological problems: Implication for screening in mental health setting. Indian J Psychol Med 2017;39:21-7.  Back to cited text no. 12
[PUBMED]  [Full text]  
13.
Prabhakaran MC, Patel VR, Ganjiwale DJ, Nimbalkar MS. Factors associated with internet addiction among school-going adolescents in vadodara. J Family Med Prim Care 2016;5:765-9.  Back to cited text no. 13
    
14.
Gedam SR, Shivji IA, Goyal A, Modi L, Ghosh S. Comparison of internet addiction, pattern and psychopathology between medical and dental students. Asian J Psychiatr 2016;22:105-10.  Back to cited text no. 14
    
15.
Nath K, Naskar S, Victor R. A Cross-Sectional Study on the Prevalence, Risk Factors, and Ill Effects of Internet Addiction Among Medical Students in Northeastern India. The Primary Care Companion for Cns Disorders 2016:18.  Back to cited text no. 15
    
16.
Chaudhari B, Menon P, Saldanha D, Tewari A, Bhattacharya L. Internet addiction and its determinants among medical students. Ind Psychiatry J 2015;24:158-62.  Back to cited text no. 16
[PUBMED]  [Full text]  
17.
Yadav P, Banwari G, Parmar C, Maniar R. Internet addiction and its correlates among high school students: A preliminary study from Ahmedabad, India. Asian J Psychiatr 2013;6:500-5.  Back to cited text no. 17
    
18.
Goel D, Subramanyam A, Kamath R. A study on the prevalence of internet addiction and its association with psychopathology in Indian adolescents. Indian J Psychiatry 2013;55:140-3.  Back to cited text no. 18
[PUBMED]  [Full text]  
19.
Nalwa K, Anand AP. Internet addiction in students: A cause of concern. Cyberpsychol Behav 2003;6:653-6.  Back to cited text no. 19
    
20.
Gade S, Chari S, Gupta M. Perceived stress among medical students: To identify its sources and coping strategies. Arch Med Health Sci 2014;2:80.  Back to cited text no. 20
  [Full text]  
21.
Panchu P, Bahuleyan B, Vijayan V. An analysis of the factors leading to stress in Indian medical students. Int J Clin Exp Physiol 2017;4:48.  Back to cited text no. 21
  [Full text]  
22.
Prasad M, Patthi B, Singla A, Gupta R, Saha S, Kumar JK, et al. Nomophobia: A cross-sectional study to assess mobile phone usage among dental students. J Clin Diagn Res 2017;11:ZC34-9.  Back to cited text no. 22
    
23.
Widyanto L, McMurran M. The psychometric properties of the internet addiction test. Cyberpsychol Behav 2004;7:443-50.  Back to cited text no. 23
    
24.
Frangos CC, Frangos CC, Sotiropoulos I. A meta-analysis of the reliability of Young's Internet addiction test. Proc World Congr Eng 2012;1:368-71.  Back to cited text no. 24
    
25.
Pontes HM, Griffiths MD, Patrão IM. Internet addiction and loneliness among children and adolescents in the education setting: an empirical pilot study. Aloma: Revista de Psicologia, Ciències de l'Educació i de l'Esport 2014:32.  Back to cited text no. 25
    
26.
Lyubomirsky S, Lepper HS. A measure of subjective happiness: Preliminary reliability and construct validation. Soc Indic Res 1999;46:137-55.  Back to cited text no. 26
    
27.
Mattei D, Schaefer CE. An investigation of validity of the subjective happiness scale. Psychol Rep 2004;94:288-90.  Back to cited text no. 27
    
28.
Datar MC, Shetty JV, Naphade NM. Stress and coping styles in postgraduate medical students: A medical college-based study. Indian J Soc Psychiatry 2017;33:370.  Back to cited text no. 28
  [Full text]  
29.
Cherkil S, Gardens SJ, Soman DK. Coping styles and its association with sources of stress in undergraduate medical students. Indian J Psychol Med 2013;35:389-93.  Back to cited text no. 29
[PUBMED]  [Full text]  
30.
Sreeramareddy CT, Shankar PR, Binu VS, Mukhopadhyay C, Ray B, Menezes RG, et al. Psychological morbidity, sources of stress and coping strategies among undergraduate medical students of Nepal. BMC Med Educ 2007;7:26.  Back to cited text no. 30
    
31.
Ramya N, Parthasarathy R. A study on coping patterns of junior college students. Indian J Psychol Med 2009;31:45-7.  Back to cited text no. 31
[PUBMED]  [Full text]  
32.
Chakraborty K, Basu D, Vijaya Kumar KG. Internet addiction: Consensus, controversies, and the way ahead. East Asian Arch Psychiatry 2010;20:123-32.  Back to cited text no. 32
    
33.
Weinstein A, Feder LC, Rosenberg KP, Dannon P. Internet addiction disorder: Overview and controversies. In: Rosenberg KP, Feder LC, editors. Behavioral addictions: Criteria, Evidence and Treatment. Academic Press, Elsevier inc. 2014. p. 99-117.  Back to cited text no. 33
    
34.
Gupta S, Choudhury S, Das M, Mondol A, Pradhan R. Factors causing stress among students of a medical college in Kolkata, India. Educ Health (Abingdon) 2015;28:92-5.  Back to cited text no. 34
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1]



 

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
  Conclusions
   References
   Article Figures
   Article Tables

 Article Access Statistics
    Viewed412    
    Printed16    
    Emailed0    
    PDF Downloaded52    
    Comments [Add]    

Recommend this journal