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Mobile phones are now widely used. Healthcare workers, in particular, use them for rapid communication in many hospital settings. As mobile phones increase in popularity, a number of concerns have been raised, including noise and distraction in the clinical environment, confidentiality of patient information, and data security among others.[1]
Of the various concerns regarding mobile phone use in hospitals, one of the most important is that mobile phones may serve as vehicles for nosocomial transmission of micro‐organisms.[2, 3] One report showed that over 90% of healthcare workers' cell phones were contaminated with micro‐organisms, and 14.3% of cell phones were contaminated with bacteria that can cause nosocomial infection.[2]
Smart phones, which are rapidly flooding the mobile phone market, are useful in the hospital setting, as they could provide rapid access to medical information, quicker consultation and responding, feedback of results to the patient, and ongoing monitoring of chronic diseases (eg, asthma and diabetes).[4, 5, 6, 7, 8]
However, as most smart phones have wide, full, touch screens and are used more often by their owners than non‐smart phones are, bacterial contamination rates may be higher than those of non‐smart phones. The aim of this study was to compare the contamination rates by bacteria with pathogenic potential in smart phones versus non‐smart phones.
MATERIALS AND METHODS
Study Design and Participants
This cross‐sectional study was conducted from March 1, 2011 to June 30, 2011, in 3 teaching hospitals affiliated with Seoul National University School of Medicine, namely Seoul National University Hospital, Bundang Seoul National University Hospital, and Seoul National University Boramae Medical Center. Hospital staff working in general wards as well as in intensive care units of the 3 hospitals were invited to participate in this study. The study protocol was approved by the institutional review board of each of the 3 participating hospitals. Informed consent was obtained from all participants.
Questionnaire
We designed a questionnaire inquiring about demographics (age, gender, occupation) as well as behavior regarding cell phone use (type of cell phone, frequency and reasons for use, cleaning of cell phones).
Bacterial Culture, Identification, and Drug Susceptibility Testing
Both the anterior and posterior surfaces of each participant's mobile phone were touched onto blood agar plates. The sampled culture plates were subsequently incubated aerobically at 36C for 48 hours. To identify cultivated micro‐organisms and for the assessment of antibiotic susceptibility, VITEK2 (bioMrieux, Inc., Durham, NC) systems were used.
Classification of Isolated Micro‐organisms
We classified the micro‐organisms isolated from healthcare workers' mobile phones as bacteria with pathogenic potential (probable pathogens) or nonpathogens.[4, 9] Among probable pathogenic micro‐organisms, representative drug‐resistant strains such as methicillin‐resistant Staphylococcus aureus (MRSA), vancomycin‐resistant Enterococcus (VRE), and imipenem‐resistant Acinetobacter baumannii (IRAB) were categorized as drug‐resistant pathogens.
Classification of Smart Phones Versus Non‐Smart Phones
Mobile phones that ran complete mobile operating systems and software that provided a standardized interface and a platform for application developers, were classified as smart phones.[10] All others were classified as non‐smart phones.
Statistical Analysis
The participants' clinical variables were analyzed using descriptive statistics. The results are expressed as meanstandard deviation or median value with range. Variables were compared between the smart phone and non‐smart phone users. Categorical variables were compared by [2] analysis, and continuous variables were compared using Student t test or the Mann‐Whitney test. Variables with P<0.20 after univariate analysis or clinically significant variables were subjected to multiple logistic regression to determine the risk factors for contamination of cell phones with potentially pathogenic bacteria. For all analyses, P values <0.05 were considered significant. Homer‐Lemeshow goodness of fit (GOF) test was performed to confirm the fitness of the final model. The Statistical Package for the Social Sciences version 17.0 (IBM SPSS, Armonk, NY) was used for all statistical analysis.
RESULTS
Participants and Their Behaviors Regarding Cell Phone Use
In total, 203 healthcare workers participated in this study; 80 (39.4%) were physicians, 106 (52.2%) were nurses, and 17 (8.4%) were assistants. The median age of the participants was 29 years, 43 (21.2%) were males, 115 (56.7%) participants used smart phones, and 88 (43.3%) were non‐smart phone users (Table 1).
| Smart Phone Users (N=115) | Non‐Smart Phone Users (N=88) | P Valuea | |
|---|---|---|---|
| |||
| Age, median (range), y | 28 (2048) | 29 (1952) | 0.03 |
| Gender, female | 92 (80.0%) | 68 (77.3%) | 0.64 |
| ICU workers | 78 (67.8%) | 57 (64.8%) | 0.65 |
| Occupation | 0.93 | ||
| Physicians | 45 (39.1%) | 35 (39.8%) | |
| Nurses | 63 (54.8%) | 43 (48.9%) | |
| Others | 7 (6.1%) | 10 (11.4%) | |
| Direct contact with patients | 110 (95.7%) | 84 (95.5%) | 0.95 |
| Using phones during work hours | 53 (46.1%) | 45 (51.1%) | 0.48 |
| Frequency of using phones during working | 0.46 | ||
| 13 | 8 (7.0%) | 10 (11.4%) | |
| 46 | 11 (9.6%) | 6 (6.8%) | |
| 79 | 8 (7.0%) | 1 (1.1%) | |
| Over 10 times | 26 (22.6%) | 28 (31.8%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Reason of using phones | 0.04 | ||
| Calling | 30 (26.1%) | 42 (47.7%) | |
| Mail check or searching information | 3 (2.6%) | 0 | |
| Both reasons | 20 (17.4%) | 3 (3.4%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Routine cleaning of phones | 15 (13.2%) | 11 (12.8%) | 0.94 |
| Frequency of cleaning hands (times/day) | 0.21 | ||
| 03 | 1 (0.9%) | 4 (4.5%) | |
| 46 | 18 (15.7%) | 14 (15.9%) | |
| 710 | 13 (11.3%) | 13 (14.8%) | |
| Over 10 | 83 (72.2%) | 57 (64.8%) | |
| Methods of cleaning hands | 0.72 | ||
| Washing with soaps | 48 (41.7%) | 34 (38.6%) | |
| Disinfectant | 42 (36.5%) | 33 (37.5%) | |
| Both | 25 (21.8%) | 21 (23.8%) | |
Smart phone users were slightly younger than non‐smart phone users. The distribution of occupations did not differ between the two groups. The frequency of use, reasons for using cell phones, the proportion of participants who routinely cleaned their phone, and the frequency of hand washing were also similar (Table 1).
Bacteria Isolated From Cell Phones
Bacteria were isolated from all 203 mobile phones; 3 or more different types of bacteria were isolated from 155 (76.4%) phones, 2 types from 39 (19.2%) phones, and 1 type from 9 (4.4%) phones. The most commonly cultured micro‐organism was coagulase‐negative Staphylococcus, which was isolated from 194 (95.6%) cell phones. The isolation of Gram‐positive bacilli and Micrococcus species was also frequent.
Probable pathogenic bacteria were isolated from 58 (28.6%) mobile phones. Among probable pathogens, Staphylococcus aureus (S. aureus) was the most commonly isolated. Of the 50 mobile phones that were contaminated with S. aureus, 8 were contaminated with a methicillin‐resistant strain. Five (2.4%) phones yielded Acinetobacter baumannii (Table 2).
| Organisms | Total, N=203 | No. of Drug Resistant Strains |
|---|---|---|
| Probable pathogen | ||
| Gram‐positive bacteria | ||
| Staphylococcus aureus | 50 (24.6%) | 8 (16%) |
| Streptococcus agalactiae | 1 (0.5%) | 0 |
| Enterococcus faecium | 1 (0.5%) | 1 (100%) |
| Gram‐negative bacteria | ||
| Acinetobacter baumannii | 5 (2.4%) | 1 (20%) |
| Pseudomonas aeruginosa | 1 (0.5%) | 0 |
| Enterobacter cloacae | 2 (1.0%) | 0 |
Although all mobile phones were contaminated with bacteria, probable pathogens were isolated more often from smart phones (34.8% vs 20.5% of non‐smart phones, P=0.03). The total colony count of probable pathogens from smart phones was also higher (average, 5.5 vs 5.0 from non‐smart phones, P=0.01). The isolation rate of drug‐resistant pathogens appeared to be higher from smart phones (7.0% vs 2.3% from non‐smart phones), but this difference did not reach statistical significance (P=0.19).
Risk Factors for Contamination With Probable Pathogens
In the final model constructed to determine the risk factors for contamination with probable pathogenic bacteria, data regarding cell phone users' age, gender, occupation (ie, physician or not), duration of working in the same place, daily work hours, whether the phone was a smart phone, and frequency of cell phone use during working hours were included. Among these factors, only the phone's being a smart phone was found to be a risk factor for contamination by bacteria with pathogenic potential (adjusted odds ratio (OR), 4.02; 95% CI, 1.43‐11.31; P=0.01). The fitness of this model was confirmed with the Hosmer‐Lemeshow GOF test (P=0.94). Using the cell phone more than 10 times during working hours appeared to be associated with pathogen contamination; however, this correlation failed to reach statistical significance (OR, 2.9; 95% CI, 0.9‐9.3; P=0.07).
DISCUSSION
Our study showed that smart phones were more frequently contaminated with bacteria than were non‐smart phones. In addition, total colony count of probable pathogens from smart phones was also higher. The colony count as well as contamination rate of pathogens are clinically relevant, because both factors can attribute to increased transmission of pathogens.[11]
Previous studies have attempted to identify user risk factors associated with bacterial contamination of cell phones.[12, 13, 14] Many variables, including gender, frequency of use, type of phone, work time, and the medical specialty of the user were considered; however, none of these factors was associated with an increased risk of bacterial contamination.[2, 14, 15]
In our study, none of the above‐mentioned factors was associated with contamination of cell phones by potentially pathogenic bacteria. Smart phones were the sole predictor of contamination by such bacteria. The reason that smart phones were more frequently contaminated with bacteria with pathogenic potential than were non‐smart phones is not clear. We propose two hypotheses to explain this observation. First, smart phones generally have wide screens, whereas non‐smart phones have relatively small screens with keypads. Larger screens may afford more opportunity for contamination by micro‐organisms. The mean size of a monitor in the smart phone group was 6633.2 340.1 cm2 and 5729.4564.7 cm2 in the non‐smart phone group (P<0.01). However, in a multivariate model including size with other variables above, the smart phone remained a significant risk factor for the pathogen contamination (odds ratio [OR], 4.17; 95% CI, 1.06‐16.33; P=0.04). Cell phones are manufactured in a standardized form and the size cannot be changed or controlled. Therefore, we did not include the size in the final model of logistic regression in the main result. Our second explanation is in regard to the pattern of use of smart phones. Considering a single use, smart phones are used for longer periods and require a higher number of finger touches compared with non‐smart phones. The intensive use of phones with large screens could facilitate contamination of smart phones by pathogens from the healthcare workers' fingers or palms.
A recent study showed that cleaning cell phones on a daily basis decreased contamination rates. However, it did not decrease contamination by potentially pathogenic bacteria.[12] The role of the hospital environment as a reservoir of nosocomial pathogens and the effect of sanitization on decreasing clinical infection are still controversial.[16, 17, 18, 19] Thus, further studies are needed to recommend routine cell phone sanitizing and to declare that it is relevant in terms of reduction of hospital‐acquired infections potentially associated with the mobile phones of healthcare workers.
Our study is subject to limitation. Lack of association between hand washing and pathogen contamination might be a result of false reporting on hand washing behavior as well as the small number of participants. The bacterial contamination rate of the folding type of non‐smart phones may have been underestimated, as their keypads could not contact agar plates because they would not opened flatly (we touched the exterior surface of the folding type phones, which did not harbor the keypad, to the agar plate). However, given that folding phones are usually stored in their folded position, bacteria on the outside of the phones are likely more relevant than those within keypads insofar as transmission is concerned.
In summary, our data showed that over one‐fourth of the mobile phones examined in this study were found to harbor potentially pathogenic micro‐organisms. In particular, smart phones of healthcare workers were more frequently contaminated with potentially pathogenic bacteria than were non‐smart phones even after adjusting for the phone size. Preventive measures to minimize the possibility of bacterial transmission via cell phones should be devised.
Disclosure
This study was funded by grant 04‐2011‐1020 from the Seoul National University College of Medicine Research Fund (Seoul, South Korea). The sponsor of the study had no role in the tudy design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. The authors declare that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.
- , , , et al. Evidence‐based policy? The use of mobile phones in hospital. J Public Health (Oxf). 2006;28:299–303.
- , , , , . Is your phone bugged? The incidence of bacteria known to cause nosocomial infection on healthcare workers' mobile phones. J Hosp Infect. 2006;62:123–125.
- , , , , . Bacterial contamination of mobile communication devices in the operative environment. J Hosp Infect. 2007;66:397–398.
- , , , . Review of mobile communication devices as potential reservoirs of nosocomial pathogens. J Hosp Infect. 2009;71:295–300.
- , , . Use of SMS text messaging to improve outpatient attendance. Med J Aust. 2005;183:366–368.
- , , , et al. The use of text messaging to improve attendance in primary care: a randomized controlled trial. Fam Pract. 2006;23:699–705.
- , , , . Mobile phone text messaging in the management of diabetes. J Telemed Telecare. 2004;10:282–285.
- , , , , . Mobile phone text messaging can help young people manage asthma. BMJ. 2002;325:600.
- , , , et al. Use of cellular telephones and transmission of pathogens by medical staff in New York and Israel. Infect Control Hosp Epidemiol. 2007;28:500–503.
- Feature phone. Phone Scoop Web site. Available at: http://www.phonescoop.com/glossary/term.php?gid=310. Accessed June 22, 2011.
- , , . Comparison of two possible routes of pathogen contamination of spinach leaves in a hydroponic cultivation system. J Food Prot 2011;74:1536–1542.
- , , , et al. Use of mobile phones by medical staff at Queen Elizabeth Hospital, Barbados: evidence for both benefit and harm. J Hosp Infect. 2008;70:160–165.
- , , , . Pathogenic bacteria on personal pagers. Am J Infect Control. 2000;28:387–388.
- , , , , , . Bacterial contamination of health care workers' pagers and the efficacy of various disinfecting agents. Pediatr Infect Dis J. 2006;25: 1074–1075.
- , , . Preventing transmission of multidrug‐resistant bacteria in health care settings: a tale of 2 guidelines. Clin Infect Dis. 2006;42:828–835.
- . Environmental contamination makes an important contribution to hospital infection. J Hosp Infect. 2007;65(suppl 2):50–54.
- , , , . Widespread environmental contamination associated with patients with diarrhea and methicillin‐resistant Staphylococcus aureus colonization of the gastrointestinal tract. Infect Control Hosp Epidemiol. 2007;28:1142–1147.
- , , , , . Computer keyboards and faucet handles as reservoirs of nosocomial pathogens in the intensive care unit. Am J Infect Control. 2000;28:465–471.
- , , , , , . Routine disinfection of patients' environmental surfaces. Myth or reality? J Hosp Infect. 1999;42:113–117.
Mobile phones are now widely used. Healthcare workers, in particular, use them for rapid communication in many hospital settings. As mobile phones increase in popularity, a number of concerns have been raised, including noise and distraction in the clinical environment, confidentiality of patient information, and data security among others.[1]
Of the various concerns regarding mobile phone use in hospitals, one of the most important is that mobile phones may serve as vehicles for nosocomial transmission of micro‐organisms.[2, 3] One report showed that over 90% of healthcare workers' cell phones were contaminated with micro‐organisms, and 14.3% of cell phones were contaminated with bacteria that can cause nosocomial infection.[2]
Smart phones, which are rapidly flooding the mobile phone market, are useful in the hospital setting, as they could provide rapid access to medical information, quicker consultation and responding, feedback of results to the patient, and ongoing monitoring of chronic diseases (eg, asthma and diabetes).[4, 5, 6, 7, 8]
However, as most smart phones have wide, full, touch screens and are used more often by their owners than non‐smart phones are, bacterial contamination rates may be higher than those of non‐smart phones. The aim of this study was to compare the contamination rates by bacteria with pathogenic potential in smart phones versus non‐smart phones.
MATERIALS AND METHODS
Study Design and Participants
This cross‐sectional study was conducted from March 1, 2011 to June 30, 2011, in 3 teaching hospitals affiliated with Seoul National University School of Medicine, namely Seoul National University Hospital, Bundang Seoul National University Hospital, and Seoul National University Boramae Medical Center. Hospital staff working in general wards as well as in intensive care units of the 3 hospitals were invited to participate in this study. The study protocol was approved by the institutional review board of each of the 3 participating hospitals. Informed consent was obtained from all participants.
Questionnaire
We designed a questionnaire inquiring about demographics (age, gender, occupation) as well as behavior regarding cell phone use (type of cell phone, frequency and reasons for use, cleaning of cell phones).
Bacterial Culture, Identification, and Drug Susceptibility Testing
Both the anterior and posterior surfaces of each participant's mobile phone were touched onto blood agar plates. The sampled culture plates were subsequently incubated aerobically at 36C for 48 hours. To identify cultivated micro‐organisms and for the assessment of antibiotic susceptibility, VITEK2 (bioMrieux, Inc., Durham, NC) systems were used.
Classification of Isolated Micro‐organisms
We classified the micro‐organisms isolated from healthcare workers' mobile phones as bacteria with pathogenic potential (probable pathogens) or nonpathogens.[4, 9] Among probable pathogenic micro‐organisms, representative drug‐resistant strains such as methicillin‐resistant Staphylococcus aureus (MRSA), vancomycin‐resistant Enterococcus (VRE), and imipenem‐resistant Acinetobacter baumannii (IRAB) were categorized as drug‐resistant pathogens.
Classification of Smart Phones Versus Non‐Smart Phones
Mobile phones that ran complete mobile operating systems and software that provided a standardized interface and a platform for application developers, were classified as smart phones.[10] All others were classified as non‐smart phones.
Statistical Analysis
The participants' clinical variables were analyzed using descriptive statistics. The results are expressed as meanstandard deviation or median value with range. Variables were compared between the smart phone and non‐smart phone users. Categorical variables were compared by [2] analysis, and continuous variables were compared using Student t test or the Mann‐Whitney test. Variables with P<0.20 after univariate analysis or clinically significant variables were subjected to multiple logistic regression to determine the risk factors for contamination of cell phones with potentially pathogenic bacteria. For all analyses, P values <0.05 were considered significant. Homer‐Lemeshow goodness of fit (GOF) test was performed to confirm the fitness of the final model. The Statistical Package for the Social Sciences version 17.0 (IBM SPSS, Armonk, NY) was used for all statistical analysis.
RESULTS
Participants and Their Behaviors Regarding Cell Phone Use
In total, 203 healthcare workers participated in this study; 80 (39.4%) were physicians, 106 (52.2%) were nurses, and 17 (8.4%) were assistants. The median age of the participants was 29 years, 43 (21.2%) were males, 115 (56.7%) participants used smart phones, and 88 (43.3%) were non‐smart phone users (Table 1).
| Smart Phone Users (N=115) | Non‐Smart Phone Users (N=88) | P Valuea | |
|---|---|---|---|
| |||
| Age, median (range), y | 28 (2048) | 29 (1952) | 0.03 |
| Gender, female | 92 (80.0%) | 68 (77.3%) | 0.64 |
| ICU workers | 78 (67.8%) | 57 (64.8%) | 0.65 |
| Occupation | 0.93 | ||
| Physicians | 45 (39.1%) | 35 (39.8%) | |
| Nurses | 63 (54.8%) | 43 (48.9%) | |
| Others | 7 (6.1%) | 10 (11.4%) | |
| Direct contact with patients | 110 (95.7%) | 84 (95.5%) | 0.95 |
| Using phones during work hours | 53 (46.1%) | 45 (51.1%) | 0.48 |
| Frequency of using phones during working | 0.46 | ||
| 13 | 8 (7.0%) | 10 (11.4%) | |
| 46 | 11 (9.6%) | 6 (6.8%) | |
| 79 | 8 (7.0%) | 1 (1.1%) | |
| Over 10 times | 26 (22.6%) | 28 (31.8%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Reason of using phones | 0.04 | ||
| Calling | 30 (26.1%) | 42 (47.7%) | |
| Mail check or searching information | 3 (2.6%) | 0 | |
| Both reasons | 20 (17.4%) | 3 (3.4%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Routine cleaning of phones | 15 (13.2%) | 11 (12.8%) | 0.94 |
| Frequency of cleaning hands (times/day) | 0.21 | ||
| 03 | 1 (0.9%) | 4 (4.5%) | |
| 46 | 18 (15.7%) | 14 (15.9%) | |
| 710 | 13 (11.3%) | 13 (14.8%) | |
| Over 10 | 83 (72.2%) | 57 (64.8%) | |
| Methods of cleaning hands | 0.72 | ||
| Washing with soaps | 48 (41.7%) | 34 (38.6%) | |
| Disinfectant | 42 (36.5%) | 33 (37.5%) | |
| Both | 25 (21.8%) | 21 (23.8%) | |
Smart phone users were slightly younger than non‐smart phone users. The distribution of occupations did not differ between the two groups. The frequency of use, reasons for using cell phones, the proportion of participants who routinely cleaned their phone, and the frequency of hand washing were also similar (Table 1).
Bacteria Isolated From Cell Phones
Bacteria were isolated from all 203 mobile phones; 3 or more different types of bacteria were isolated from 155 (76.4%) phones, 2 types from 39 (19.2%) phones, and 1 type from 9 (4.4%) phones. The most commonly cultured micro‐organism was coagulase‐negative Staphylococcus, which was isolated from 194 (95.6%) cell phones. The isolation of Gram‐positive bacilli and Micrococcus species was also frequent.
Probable pathogenic bacteria were isolated from 58 (28.6%) mobile phones. Among probable pathogens, Staphylococcus aureus (S. aureus) was the most commonly isolated. Of the 50 mobile phones that were contaminated with S. aureus, 8 were contaminated with a methicillin‐resistant strain. Five (2.4%) phones yielded Acinetobacter baumannii (Table 2).
| Organisms | Total, N=203 | No. of Drug Resistant Strains |
|---|---|---|
| Probable pathogen | ||
| Gram‐positive bacteria | ||
| Staphylococcus aureus | 50 (24.6%) | 8 (16%) |
| Streptococcus agalactiae | 1 (0.5%) | 0 |
| Enterococcus faecium | 1 (0.5%) | 1 (100%) |
| Gram‐negative bacteria | ||
| Acinetobacter baumannii | 5 (2.4%) | 1 (20%) |
| Pseudomonas aeruginosa | 1 (0.5%) | 0 |
| Enterobacter cloacae | 2 (1.0%) | 0 |
Although all mobile phones were contaminated with bacteria, probable pathogens were isolated more often from smart phones (34.8% vs 20.5% of non‐smart phones, P=0.03). The total colony count of probable pathogens from smart phones was also higher (average, 5.5 vs 5.0 from non‐smart phones, P=0.01). The isolation rate of drug‐resistant pathogens appeared to be higher from smart phones (7.0% vs 2.3% from non‐smart phones), but this difference did not reach statistical significance (P=0.19).
Risk Factors for Contamination With Probable Pathogens
In the final model constructed to determine the risk factors for contamination with probable pathogenic bacteria, data regarding cell phone users' age, gender, occupation (ie, physician or not), duration of working in the same place, daily work hours, whether the phone was a smart phone, and frequency of cell phone use during working hours were included. Among these factors, only the phone's being a smart phone was found to be a risk factor for contamination by bacteria with pathogenic potential (adjusted odds ratio (OR), 4.02; 95% CI, 1.43‐11.31; P=0.01). The fitness of this model was confirmed with the Hosmer‐Lemeshow GOF test (P=0.94). Using the cell phone more than 10 times during working hours appeared to be associated with pathogen contamination; however, this correlation failed to reach statistical significance (OR, 2.9; 95% CI, 0.9‐9.3; P=0.07).
DISCUSSION
Our study showed that smart phones were more frequently contaminated with bacteria than were non‐smart phones. In addition, total colony count of probable pathogens from smart phones was also higher. The colony count as well as contamination rate of pathogens are clinically relevant, because both factors can attribute to increased transmission of pathogens.[11]
Previous studies have attempted to identify user risk factors associated with bacterial contamination of cell phones.[12, 13, 14] Many variables, including gender, frequency of use, type of phone, work time, and the medical specialty of the user were considered; however, none of these factors was associated with an increased risk of bacterial contamination.[2, 14, 15]
In our study, none of the above‐mentioned factors was associated with contamination of cell phones by potentially pathogenic bacteria. Smart phones were the sole predictor of contamination by such bacteria. The reason that smart phones were more frequently contaminated with bacteria with pathogenic potential than were non‐smart phones is not clear. We propose two hypotheses to explain this observation. First, smart phones generally have wide screens, whereas non‐smart phones have relatively small screens with keypads. Larger screens may afford more opportunity for contamination by micro‐organisms. The mean size of a monitor in the smart phone group was 6633.2 340.1 cm2 and 5729.4564.7 cm2 in the non‐smart phone group (P<0.01). However, in a multivariate model including size with other variables above, the smart phone remained a significant risk factor for the pathogen contamination (odds ratio [OR], 4.17; 95% CI, 1.06‐16.33; P=0.04). Cell phones are manufactured in a standardized form and the size cannot be changed or controlled. Therefore, we did not include the size in the final model of logistic regression in the main result. Our second explanation is in regard to the pattern of use of smart phones. Considering a single use, smart phones are used for longer periods and require a higher number of finger touches compared with non‐smart phones. The intensive use of phones with large screens could facilitate contamination of smart phones by pathogens from the healthcare workers' fingers or palms.
A recent study showed that cleaning cell phones on a daily basis decreased contamination rates. However, it did not decrease contamination by potentially pathogenic bacteria.[12] The role of the hospital environment as a reservoir of nosocomial pathogens and the effect of sanitization on decreasing clinical infection are still controversial.[16, 17, 18, 19] Thus, further studies are needed to recommend routine cell phone sanitizing and to declare that it is relevant in terms of reduction of hospital‐acquired infections potentially associated with the mobile phones of healthcare workers.
Our study is subject to limitation. Lack of association between hand washing and pathogen contamination might be a result of false reporting on hand washing behavior as well as the small number of participants. The bacterial contamination rate of the folding type of non‐smart phones may have been underestimated, as their keypads could not contact agar plates because they would not opened flatly (we touched the exterior surface of the folding type phones, which did not harbor the keypad, to the agar plate). However, given that folding phones are usually stored in their folded position, bacteria on the outside of the phones are likely more relevant than those within keypads insofar as transmission is concerned.
In summary, our data showed that over one‐fourth of the mobile phones examined in this study were found to harbor potentially pathogenic micro‐organisms. In particular, smart phones of healthcare workers were more frequently contaminated with potentially pathogenic bacteria than were non‐smart phones even after adjusting for the phone size. Preventive measures to minimize the possibility of bacterial transmission via cell phones should be devised.
Disclosure
This study was funded by grant 04‐2011‐1020 from the Seoul National University College of Medicine Research Fund (Seoul, South Korea). The sponsor of the study had no role in the tudy design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. The authors declare that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.
Mobile phones are now widely used. Healthcare workers, in particular, use them for rapid communication in many hospital settings. As mobile phones increase in popularity, a number of concerns have been raised, including noise and distraction in the clinical environment, confidentiality of patient information, and data security among others.[1]
Of the various concerns regarding mobile phone use in hospitals, one of the most important is that mobile phones may serve as vehicles for nosocomial transmission of micro‐organisms.[2, 3] One report showed that over 90% of healthcare workers' cell phones were contaminated with micro‐organisms, and 14.3% of cell phones were contaminated with bacteria that can cause nosocomial infection.[2]
Smart phones, which are rapidly flooding the mobile phone market, are useful in the hospital setting, as they could provide rapid access to medical information, quicker consultation and responding, feedback of results to the patient, and ongoing monitoring of chronic diseases (eg, asthma and diabetes).[4, 5, 6, 7, 8]
However, as most smart phones have wide, full, touch screens and are used more often by their owners than non‐smart phones are, bacterial contamination rates may be higher than those of non‐smart phones. The aim of this study was to compare the contamination rates by bacteria with pathogenic potential in smart phones versus non‐smart phones.
MATERIALS AND METHODS
Study Design and Participants
This cross‐sectional study was conducted from March 1, 2011 to June 30, 2011, in 3 teaching hospitals affiliated with Seoul National University School of Medicine, namely Seoul National University Hospital, Bundang Seoul National University Hospital, and Seoul National University Boramae Medical Center. Hospital staff working in general wards as well as in intensive care units of the 3 hospitals were invited to participate in this study. The study protocol was approved by the institutional review board of each of the 3 participating hospitals. Informed consent was obtained from all participants.
Questionnaire
We designed a questionnaire inquiring about demographics (age, gender, occupation) as well as behavior regarding cell phone use (type of cell phone, frequency and reasons for use, cleaning of cell phones).
Bacterial Culture, Identification, and Drug Susceptibility Testing
Both the anterior and posterior surfaces of each participant's mobile phone were touched onto blood agar plates. The sampled culture plates were subsequently incubated aerobically at 36C for 48 hours. To identify cultivated micro‐organisms and for the assessment of antibiotic susceptibility, VITEK2 (bioMrieux, Inc., Durham, NC) systems were used.
Classification of Isolated Micro‐organisms
We classified the micro‐organisms isolated from healthcare workers' mobile phones as bacteria with pathogenic potential (probable pathogens) or nonpathogens.[4, 9] Among probable pathogenic micro‐organisms, representative drug‐resistant strains such as methicillin‐resistant Staphylococcus aureus (MRSA), vancomycin‐resistant Enterococcus (VRE), and imipenem‐resistant Acinetobacter baumannii (IRAB) were categorized as drug‐resistant pathogens.
Classification of Smart Phones Versus Non‐Smart Phones
Mobile phones that ran complete mobile operating systems and software that provided a standardized interface and a platform for application developers, were classified as smart phones.[10] All others were classified as non‐smart phones.
Statistical Analysis
The participants' clinical variables were analyzed using descriptive statistics. The results are expressed as meanstandard deviation or median value with range. Variables were compared between the smart phone and non‐smart phone users. Categorical variables were compared by [2] analysis, and continuous variables were compared using Student t test or the Mann‐Whitney test. Variables with P<0.20 after univariate analysis or clinically significant variables were subjected to multiple logistic regression to determine the risk factors for contamination of cell phones with potentially pathogenic bacteria. For all analyses, P values <0.05 were considered significant. Homer‐Lemeshow goodness of fit (GOF) test was performed to confirm the fitness of the final model. The Statistical Package for the Social Sciences version 17.0 (IBM SPSS, Armonk, NY) was used for all statistical analysis.
RESULTS
Participants and Their Behaviors Regarding Cell Phone Use
In total, 203 healthcare workers participated in this study; 80 (39.4%) were physicians, 106 (52.2%) were nurses, and 17 (8.4%) were assistants. The median age of the participants was 29 years, 43 (21.2%) were males, 115 (56.7%) participants used smart phones, and 88 (43.3%) were non‐smart phone users (Table 1).
| Smart Phone Users (N=115) | Non‐Smart Phone Users (N=88) | P Valuea | |
|---|---|---|---|
| |||
| Age, median (range), y | 28 (2048) | 29 (1952) | 0.03 |
| Gender, female | 92 (80.0%) | 68 (77.3%) | 0.64 |
| ICU workers | 78 (67.8%) | 57 (64.8%) | 0.65 |
| Occupation | 0.93 | ||
| Physicians | 45 (39.1%) | 35 (39.8%) | |
| Nurses | 63 (54.8%) | 43 (48.9%) | |
| Others | 7 (6.1%) | 10 (11.4%) | |
| Direct contact with patients | 110 (95.7%) | 84 (95.5%) | 0.95 |
| Using phones during work hours | 53 (46.1%) | 45 (51.1%) | 0.48 |
| Frequency of using phones during working | 0.46 | ||
| 13 | 8 (7.0%) | 10 (11.4%) | |
| 46 | 11 (9.6%) | 6 (6.8%) | |
| 79 | 8 (7.0%) | 1 (1.1%) | |
| Over 10 times | 26 (22.6%) | 28 (31.8%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Reason of using phones | 0.04 | ||
| Calling | 30 (26.1%) | 42 (47.7%) | |
| Mail check or searching information | 3 (2.6%) | 0 | |
| Both reasons | 20 (17.4%) | 3 (3.4%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Routine cleaning of phones | 15 (13.2%) | 11 (12.8%) | 0.94 |
| Frequency of cleaning hands (times/day) | 0.21 | ||
| 03 | 1 (0.9%) | 4 (4.5%) | |
| 46 | 18 (15.7%) | 14 (15.9%) | |
| 710 | 13 (11.3%) | 13 (14.8%) | |
| Over 10 | 83 (72.2%) | 57 (64.8%) | |
| Methods of cleaning hands | 0.72 | ||
| Washing with soaps | 48 (41.7%) | 34 (38.6%) | |
| Disinfectant | 42 (36.5%) | 33 (37.5%) | |
| Both | 25 (21.8%) | 21 (23.8%) | |
Smart phone users were slightly younger than non‐smart phone users. The distribution of occupations did not differ between the two groups. The frequency of use, reasons for using cell phones, the proportion of participants who routinely cleaned their phone, and the frequency of hand washing were also similar (Table 1).
Bacteria Isolated From Cell Phones
Bacteria were isolated from all 203 mobile phones; 3 or more different types of bacteria were isolated from 155 (76.4%) phones, 2 types from 39 (19.2%) phones, and 1 type from 9 (4.4%) phones. The most commonly cultured micro‐organism was coagulase‐negative Staphylococcus, which was isolated from 194 (95.6%) cell phones. The isolation of Gram‐positive bacilli and Micrococcus species was also frequent.
Probable pathogenic bacteria were isolated from 58 (28.6%) mobile phones. Among probable pathogens, Staphylococcus aureus (S. aureus) was the most commonly isolated. Of the 50 mobile phones that were contaminated with S. aureus, 8 were contaminated with a methicillin‐resistant strain. Five (2.4%) phones yielded Acinetobacter baumannii (Table 2).
| Organisms | Total, N=203 | No. of Drug Resistant Strains |
|---|---|---|
| Probable pathogen | ||
| Gram‐positive bacteria | ||
| Staphylococcus aureus | 50 (24.6%) | 8 (16%) |
| Streptococcus agalactiae | 1 (0.5%) | 0 |
| Enterococcus faecium | 1 (0.5%) | 1 (100%) |
| Gram‐negative bacteria | ||
| Acinetobacter baumannii | 5 (2.4%) | 1 (20%) |
| Pseudomonas aeruginosa | 1 (0.5%) | 0 |
| Enterobacter cloacae | 2 (1.0%) | 0 |
Although all mobile phones were contaminated with bacteria, probable pathogens were isolated more often from smart phones (34.8% vs 20.5% of non‐smart phones, P=0.03). The total colony count of probable pathogens from smart phones was also higher (average, 5.5 vs 5.0 from non‐smart phones, P=0.01). The isolation rate of drug‐resistant pathogens appeared to be higher from smart phones (7.0% vs 2.3% from non‐smart phones), but this difference did not reach statistical significance (P=0.19).
Risk Factors for Contamination With Probable Pathogens
In the final model constructed to determine the risk factors for contamination with probable pathogenic bacteria, data regarding cell phone users' age, gender, occupation (ie, physician or not), duration of working in the same place, daily work hours, whether the phone was a smart phone, and frequency of cell phone use during working hours were included. Among these factors, only the phone's being a smart phone was found to be a risk factor for contamination by bacteria with pathogenic potential (adjusted odds ratio (OR), 4.02; 95% CI, 1.43‐11.31; P=0.01). The fitness of this model was confirmed with the Hosmer‐Lemeshow GOF test (P=0.94). Using the cell phone more than 10 times during working hours appeared to be associated with pathogen contamination; however, this correlation failed to reach statistical significance (OR, 2.9; 95% CI, 0.9‐9.3; P=0.07).
DISCUSSION
Our study showed that smart phones were more frequently contaminated with bacteria than were non‐smart phones. In addition, total colony count of probable pathogens from smart phones was also higher. The colony count as well as contamination rate of pathogens are clinically relevant, because both factors can attribute to increased transmission of pathogens.[11]
Previous studies have attempted to identify user risk factors associated with bacterial contamination of cell phones.[12, 13, 14] Many variables, including gender, frequency of use, type of phone, work time, and the medical specialty of the user were considered; however, none of these factors was associated with an increased risk of bacterial contamination.[2, 14, 15]
In our study, none of the above‐mentioned factors was associated with contamination of cell phones by potentially pathogenic bacteria. Smart phones were the sole predictor of contamination by such bacteria. The reason that smart phones were more frequently contaminated with bacteria with pathogenic potential than were non‐smart phones is not clear. We propose two hypotheses to explain this observation. First, smart phones generally have wide screens, whereas non‐smart phones have relatively small screens with keypads. Larger screens may afford more opportunity for contamination by micro‐organisms. The mean size of a monitor in the smart phone group was 6633.2 340.1 cm2 and 5729.4564.7 cm2 in the non‐smart phone group (P<0.01). However, in a multivariate model including size with other variables above, the smart phone remained a significant risk factor for the pathogen contamination (odds ratio [OR], 4.17; 95% CI, 1.06‐16.33; P=0.04). Cell phones are manufactured in a standardized form and the size cannot be changed or controlled. Therefore, we did not include the size in the final model of logistic regression in the main result. Our second explanation is in regard to the pattern of use of smart phones. Considering a single use, smart phones are used for longer periods and require a higher number of finger touches compared with non‐smart phones. The intensive use of phones with large screens could facilitate contamination of smart phones by pathogens from the healthcare workers' fingers or palms.
A recent study showed that cleaning cell phones on a daily basis decreased contamination rates. However, it did not decrease contamination by potentially pathogenic bacteria.[12] The role of the hospital environment as a reservoir of nosocomial pathogens and the effect of sanitization on decreasing clinical infection are still controversial.[16, 17, 18, 19] Thus, further studies are needed to recommend routine cell phone sanitizing and to declare that it is relevant in terms of reduction of hospital‐acquired infections potentially associated with the mobile phones of healthcare workers.
Our study is subject to limitation. Lack of association between hand washing and pathogen contamination might be a result of false reporting on hand washing behavior as well as the small number of participants. The bacterial contamination rate of the folding type of non‐smart phones may have been underestimated, as their keypads could not contact agar plates because they would not opened flatly (we touched the exterior surface of the folding type phones, which did not harbor the keypad, to the agar plate). However, given that folding phones are usually stored in their folded position, bacteria on the outside of the phones are likely more relevant than those within keypads insofar as transmission is concerned.
In summary, our data showed that over one‐fourth of the mobile phones examined in this study were found to harbor potentially pathogenic micro‐organisms. In particular, smart phones of healthcare workers were more frequently contaminated with potentially pathogenic bacteria than were non‐smart phones even after adjusting for the phone size. Preventive measures to minimize the possibility of bacterial transmission via cell phones should be devised.
Disclosure
This study was funded by grant 04‐2011‐1020 from the Seoul National University College of Medicine Research Fund (Seoul, South Korea). The sponsor of the study had no role in the tudy design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. The authors declare that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.
- , , , et al. Evidence‐based policy? The use of mobile phones in hospital. J Public Health (Oxf). 2006;28:299–303.
- , , , , . Is your phone bugged? The incidence of bacteria known to cause nosocomial infection on healthcare workers' mobile phones. J Hosp Infect. 2006;62:123–125.
- , , , , . Bacterial contamination of mobile communication devices in the operative environment. J Hosp Infect. 2007;66:397–398.
- , , , . Review of mobile communication devices as potential reservoirs of nosocomial pathogens. J Hosp Infect. 2009;71:295–300.
- , , . Use of SMS text messaging to improve outpatient attendance. Med J Aust. 2005;183:366–368.
- , , , et al. The use of text messaging to improve attendance in primary care: a randomized controlled trial. Fam Pract. 2006;23:699–705.
- , , , . Mobile phone text messaging in the management of diabetes. J Telemed Telecare. 2004;10:282–285.
- , , , , . Mobile phone text messaging can help young people manage asthma. BMJ. 2002;325:600.
- , , , et al. Use of cellular telephones and transmission of pathogens by medical staff in New York and Israel. Infect Control Hosp Epidemiol. 2007;28:500–503.
- Feature phone. Phone Scoop Web site. Available at: http://www.phonescoop.com/glossary/term.php?gid=310. Accessed June 22, 2011.
- , , . Comparison of two possible routes of pathogen contamination of spinach leaves in a hydroponic cultivation system. J Food Prot 2011;74:1536–1542.
- , , , et al. Use of mobile phones by medical staff at Queen Elizabeth Hospital, Barbados: evidence for both benefit and harm. J Hosp Infect. 2008;70:160–165.
- , , , . Pathogenic bacteria on personal pagers. Am J Infect Control. 2000;28:387–388.
- , , , , , . Bacterial contamination of health care workers' pagers and the efficacy of various disinfecting agents. Pediatr Infect Dis J. 2006;25: 1074–1075.
- , , . Preventing transmission of multidrug‐resistant bacteria in health care settings: a tale of 2 guidelines. Clin Infect Dis. 2006;42:828–835.
- . Environmental contamination makes an important contribution to hospital infection. J Hosp Infect. 2007;65(suppl 2):50–54.
- , , , . Widespread environmental contamination associated with patients with diarrhea and methicillin‐resistant Staphylococcus aureus colonization of the gastrointestinal tract. Infect Control Hosp Epidemiol. 2007;28:1142–1147.
- , , , , . Computer keyboards and faucet handles as reservoirs of nosocomial pathogens in the intensive care unit. Am J Infect Control. 2000;28:465–471.
- , , , , , . Routine disinfection of patients' environmental surfaces. Myth or reality? J Hosp Infect. 1999;42:113–117.
- , , , et al. Evidence‐based policy? The use of mobile phones in hospital. J Public Health (Oxf). 2006;28:299–303.
- , , , , . Is your phone bugged? The incidence of bacteria known to cause nosocomial infection on healthcare workers' mobile phones. J Hosp Infect. 2006;62:123–125.
- , , , , . Bacterial contamination of mobile communication devices in the operative environment. J Hosp Infect. 2007;66:397–398.
- , , , . Review of mobile communication devices as potential reservoirs of nosocomial pathogens. J Hosp Infect. 2009;71:295–300.
- , , . Use of SMS text messaging to improve outpatient attendance. Med J Aust. 2005;183:366–368.
- , , , et al. The use of text messaging to improve attendance in primary care: a randomized controlled trial. Fam Pract. 2006;23:699–705.
- , , , . Mobile phone text messaging in the management of diabetes. J Telemed Telecare. 2004;10:282–285.
- , , , , . Mobile phone text messaging can help young people manage asthma. BMJ. 2002;325:600.
- , , , et al. Use of cellular telephones and transmission of pathogens by medical staff in New York and Israel. Infect Control Hosp Epidemiol. 2007;28:500–503.
- Feature phone. Phone Scoop Web site. Available at: http://www.phonescoop.com/glossary/term.php?gid=310. Accessed June 22, 2011.
- , , . Comparison of two possible routes of pathogen contamination of spinach leaves in a hydroponic cultivation system. J Food Prot 2011;74:1536–1542.
- , , , et al. Use of mobile phones by medical staff at Queen Elizabeth Hospital, Barbados: evidence for both benefit and harm. J Hosp Infect. 2008;70:160–165.
- , , , . Pathogenic bacteria on personal pagers. Am J Infect Control. 2000;28:387–388.
- , , , , , . Bacterial contamination of health care workers' pagers and the efficacy of various disinfecting agents. Pediatr Infect Dis J. 2006;25: 1074–1075.
- , , . Preventing transmission of multidrug‐resistant bacteria in health care settings: a tale of 2 guidelines. Clin Infect Dis. 2006;42:828–835.
- . Environmental contamination makes an important contribution to hospital infection. J Hosp Infect. 2007;65(suppl 2):50–54.
- , , , . Widespread environmental contamination associated with patients with diarrhea and methicillin‐resistant Staphylococcus aureus colonization of the gastrointestinal tract. Infect Control Hosp Epidemiol. 2007;28:1142–1147.
- , , , , . Computer keyboards and faucet handles as reservoirs of nosocomial pathogens in the intensive care unit. Am J Infect Control. 2000;28:465–471.
- , , , , , . Routine disinfection of patients' environmental surfaces. Myth or reality? J Hosp Infect. 1999;42:113–117.