Observational studies and clinical trials have shown that soft contact lens (SCL) wearers younger than 25 years of age are at increased risk for corneal infiltrative events.1–7 However, the age-related risk profile for all types of SCL-related complications among children and early adolescent SCL wearers (age 8–14 years) appears to be lower than for 15- to 25-year-old wearers.7–9 Despite these facts, the underlying behavioral, biological, or environmental factors that may potentially drive age-related complications are not well understood.
In the next decade, increasing numbers of children, teenagers, and young adults around the world will receive contact lenses for both cosmetic and medical purposes (myopia control10–17, drug delivery18,19). With the trend toward fitting SCLs to patients at a younger age, it will be even more important to understand the relationship between SCL-related behaviors, patterns of use, environmental exposures, and health outcomes with SCL wear. Understanding how the general population uses SCLs is a critical step toward reducing SCL complications by allowing practitioners to use preventive prescribing strategies and targeted education to at risk wearers to improve health outcomes.
In 2011, the Contact Lens Assessment in Youth (CLAY) study team developed the CLAY Contact Lens Risk Survey (CLRS)20,21 to assess known or presumed risk factors for SCL complications. The survey was administered to a nonclinical population of SCL wearers aged 12 to 33 years. Here, the team investigated if any of the surveyed factors vary by age and, if so, determined if their age-related prevalence correlated to the age profile of wearers who developed a corneal infiltrative event from a previous study.7–9
Survey items were developed following a literature review of risk factors for SCL-related corneal infectious and inflammatory events (CIEs). A gap analysis was then conducted by the study team after a review of clinical charts of 168 patients who presented with CIEs identified in the CLAY retrospective chart review.7,20,21 After potential survey items were developed, focus groups were conducted with both eye care providers and young SCL wearers to establish that no additional risk factors were identified, demonstrating saturation.22 The focus groups reported on the ability to comprehend each question stem23 and the appropriateness of the proposed response options. The study was piloted in South Florida and, following modest revisions, administered study-wide.
The CLAY CLRS tool queried potential risk factors for contact lens complications including patient demographics such as age, hand-washing before application or removal of SCLs, lens and case exposures to water, lens and case hygiene, closed-eye contact lens wear, lens replacement, overnight wear patterns, wearer sleep habits, frequency of colds and flu, stress level, living situation, and access to eye care. Photographic aides, previously reported to improve recall of contact lens and lens care brand names,24 were used to help wearers identify lens and lens care products. The 31-question electronic survey incorporated branching logic and allowed multiple responses when applicable. Response options included yes/no, Likert-type scales and multiple-choice responses.
This study followed the tenets of the Declaration of Helsinki. The Institutional Review Board at each participating institution approved the research before data collection. Informed consent was obtained from the participants or their parents after explanation of the study. The nonclinical sample was comprised of participants between 12 and 33 years (inclusive) who reported that they wore SCLs in the past week. Wearers who were currently enrolled in another clinical trial or who were optometry students, faculty or staff or family/household members of an eye care professional, resident, or student were excluded from study participation.
The self-administered survey was fielded to SCL wearers in five geographically diverse cities proximal to the clinic sites where the CLAY observational data was gathered7–9: Forest Grove, OR; Fullerton, CA; Bloomington, IN; Fort Lauderdale, FL; and New York, NY. Subjects were recruited from the general population to represent the typical SCL wearing population, rather than from optometric clinics. Recruitment strategies were site-specific and intended to capture a heterogeneous population from multiple local locations rather than a homogenous population from one specific site. Study personnel confirmed that each participant met the inclusion and exclusion criteria before enrollment. There were two administrations of the survey; the first was to 363 SCL wearers aged 18 to 33 years from October 4, 2011 to January 1, 2012 and the second was to a different pool of 179 SCL wearers 12 to 21 years old from June 28, 2012 to October 9, 2012.
Each of the five sites enrolled an age-balanced sample of approximately 72 participants (18–33 years of age) for the first administration and 36 participants (12–21 years of age) for the second administration. Enrollment targets utilized 4-year bins for adults (18–21, 22–25, 26–29, 30–33) and 2-year bins for minors (12–13, 14–15, 16–17) to ensure better precision in age-related SCL wearing behaviors in the younger, less studied population. More women than men were enrolled to model the distribution of gender (two thirds female) among SCL wearers in the US.25 Eighteen- to twenty-one-year-olds were surveyed in both administrations to allow for subsequent comparisons between the two samples.
Descriptive statistics (means, standard deviations, and frequency distributions) were generated to describe the study sample. Response frequency to each survey item was compared by age groups (12–14, 15–17, 18–21, 22–25, 26–29, and 30–33 years) using chi-square analyses. Pearson correlations were used to assess the linear relationship between prevalence of survey responses and age for survey items whose response options were ordinal (e.g., Likert-type scale response options). After visual inspection of the distribution of survey item responses, age-specific post hoc comparisons were performed where appropriate.
The relationship between risk of CIE and age was determined as part of the CLAY retrospective chart review of 3549 contact lens wearers and has been reported in a previous publication.7 For each behavior where age was significantly associated with survey response, the function expressing the previously established relationship between age and risk of CIE7 was superimposed on the bar chart showing survey response by age group. No formal statistical test was used to assess the agreement between these two curves (risk of CIE vs. age and survey response vs. age).
Five hundred forty-two participants were enrolled. Enrollment totals were similar across all study locations, with enrollment ranging from 106 to 115 wearers per site. Approximately half the surveyed population was Caucasian, but there was a mix of race and ethnicity across all age groups (Table 1). Smoking was reported infrequently and did not vary significantly with age. Older participants reported more years of SCL wear (p < 0.0001). Most respondents (82%) wore lenses 4 to 7 days per week; however, older patients were more likely to wear their lenses three or fewer days per week (p < 0.001). Lens care solution type varied across age group (p = 0.011), with 12–21-year-olds being less likely to use hydrogen peroxide disinfection. The majority of participants used multipurpose solution. A total of 69 daily disposable wearers reported using contact lens solution (74% of all daily disposable lens wearers), but there was not a difference in this behavior by age (p = 0.21, Table 1).
SCL-Related Hygiene and Wearing Behaviors
Approximately 10% of the sample reported infrequently or never washing their hands before applying contact lenses and 17% reported omitting hand washing before removing lenses (Table 2). Young adults (18–25-year-olds) were significantly less likely to wash their hands before applying (p = 0.023) their lenses when compared to older adults (26–33-year-olds).
Sharing contact lens solution, rubbing lenses with solution, and discarding leftover solution did not vary significantly with age (all p > 0.10). Across all ages, about one in 10 wearers reported “topping off” solution each night, a known risk factor for SCL complications,26 but there were no significant differences by age.
Overall, 14% of subjects reported “reactive lens replacement,” that is, only replacing lenses when there was a problem, rather than according to the manufacturer’s recommended replacement schedule based on lens brand. In addition, the relationship between reactive replacement and recommended replacement was dependent on age (Cochran–Mantel–Haenszel p < 0.0001). As shown in Fig. 1, reactive replacement was most likely among those wearing 2 weekly lenses in all age groups except 18–21-year-olds where reactive replacement was most likely among monthly lens wearers. In fact, the percentage of 2 weekly lens wearers replacing only when there was a problem was significantly higher than the daily or monthly replacement in the 12–14-year, 15–17-year, and 22–25-year age groups (p values < 0.002). In addition, 2 weekly lens wearers in both the 18–21-year and 26–29-year age group were significantly more likely to stretch their lens wear than either daily or monthly replacement wearers (p values < 0.001). A similar pattern was observed in the 30–33-year age group; however, it was not statistically significant (p = 0.077). A Cochran–Mantel–Haenszel test did not indicate an impact of recommended replacement schedule on the relationship between reactive replacement and age (p = 0.35).
While only 8% of wearers reported that their eye care practitioner recommended their lenses for extended wear, between 14% (12–14-year-olds) and 31% (18–21-year-olds) reported sleeping while wearing their contact lenses at least sometimes, but these findings did not vary significantly with age (p = 0.24). However, older adolescent and young adult wearers were significantly more likely than others to report napping while wearing their contact lenses (p < 0.001). There were also significant age effects with respect to sleeping in lenses more frequently when drinking alcohol (p = 0.031), sleeping away from home (p = 0.024), and traveling (p = 0.001). Specifically, wearers aged 18 to 25 years were significantly more likely than those over 25 years to sleep in their contact lenses after consuming alcohol (p = 0.013) and while traveling (p = 0.017, Table 3).
Living arrangements varied significantly by age group (p < 0.0001). Not surprisingly, minors reported living with their family (100% of 12–14-year-olds and 97% of 15–17-year-olds) while three quarters of college-aged participants (18–21-year-olds) reported living in “high density” housing such as dormitories, fraternities, or sororities. Adults aged 22 and older predominantly (60%) lived in nuclear family situations. Participants aged 18 to 21 years were also more likely to share a bathroom with three or more people (p < 0.0001).
A majority of participants of all ages wore their SCLs in the shower at least sometimes, but the behavior peaked among the 15- to 25-year-old participants with more than 60% reporting “always” or “fairly often” showering while wearing lenses (p < 0.001, Table 4). While not significantly different by age, upwards of one in five SCL wearers reported rinsing their contact lenses with water at least sometimes, and one in 25 stored their contact lenses in water at least sometimes (p > 0.30, Table 4).
Health: General Wellness and Access to Care
College-aged SCL wearers (18–21 years) were more likely to sleep fewer than 6 hours per night (p < 0.001, Table 5) and reported higher levels of stress than younger or older participants (p < 0.001) and more frequent occurrences of cold or flu compared to other age groups (p = 0.049).
As would be expected, minors and college-age participants were more likely to report that their parents paid for their contact lenses (p < 0.001, Table 5). Private practice settings were the highest source of SCL purchase, but minors were significantly more likely than adult wearers to report purchasing lenses from their eye care provider (vs. internet, phone, and retail establishment not affiliated with the provider) (p < 0.001).
Response to Hypothetical Red Eye Event
As a means of assessing self-management during SCL complications, participants were queried regarding their reaction(s) to a hypothetical red eye associated with SCL wear. Possible actions included removing, rinsing, and reapplying lens; removing and replacing lens with a new one; removing lens and wearing spectacles; and calling eye care practitioner or parents. Subjects could respond to one or more of these options. There were no age differences in the percentage of wearers who reported they would remove, rinse, and reapply their lens (p = 0.14) or who reported they would remove and replace their lens (p = 0.25). Those in the younger age groups (12–17-year-olds) were less likely to remove their lenses and wear spectacles when compared to the other age groups (p < 0.001, Table 5). College age wearers (18- to 25-year-olds) were slightly less likely to call/tell their practitioner or parents than older wearers (p = 0.044).
Correlation With Risk of Red Eye
In preparation for the next phase of our research, we investigated whether the surveyed risk factors were correlated with our previously established age-related risk profile for CIEs.7 To match the known age-related risk profile, a distribution should show a rise in behaviors from 12- to 17-year-olds, peaking among 18- to 25-year-olds, and declining in 26- to 33-year-olds. The risk curve is modeled in Fig. 2A–F overlaid with the current survey responses by age bins.
Visual inspection showed good agreement between the age-related risk curve and age-binned survey responses for showering and napping in SCLs (Fig. 2A, B). There was also good agreement with number of reported colds/flu for the younger ages; however, the oldest group did not follow the expected decline (Fig. 2C). Examining overnight wear behaviors, there was reasonable agreement between CIE risk and sleeping fewer than 6 hours (Fig. 2D) as well as patients’ reported increases in overnight wear when consuming alcohol and when away from home (Fig. 2E, F).
Although the presence of risky SCL wearing behaviors does not imply a causal relationship, the prevalence of specific behaviors by age mirrors the age-related risk of having an inflammatory event from a previous study.7–9 Thus, these behaviors could be key indicators of potential behaviors to target. These initial comparisons suggest that further work is needed to directly correlate age-related behaviors and risks of contact lens complications. Some characteristics did not vary significantly across age and are likely driving CIEs across all ages of wearers. Specifically, factors such as topping-off solution, overnight wear, and rinsing or storing SCLs in water are likely driving the rate of CIEs upwards for all wearers but may not be related to the spike in complications for 15- to 25-year-olds. These factors that were independent of age have been associated with some of the most serious SCL-related lens complications such as Fusarium and Acanthamoeba keratitis.26,53
The frequency of many other noncompliant SCL-related behaviors was highly associated with patient age, with the highest prevalence being reported by 15- to 25-year-olds, the age group that in previous studies also carried the highest risk for CIEs7 and other complications.8 Behaviors such as napping in SCLs, unplanned sleeping with SCLs when away from home or after alcohol consumption, and wearing SCLs in the shower were more common in that at-risk age group.
The CLAY CLRS also explored some biological factors that could influence risks for adverse events, although we were unable to perform clinical tests in this nonclinical sample. In general, the older teen and young adult age groups were more likely to report behaviors indicative of “burning the candle at both ends”, as they reported fewer than 6 hours sleep per night, more frequent napping, higher levels of stress, and suffered colds and flu more often than younger and older SCL wearers. Previous studies have suggested that these physiological factors may reflect a compromised immune system that can lead an individual to be more susceptible to infections and inflammatory responses,27,28 although this has not been directly tested in SCL wearers.
Although napping while wearing SCLs is not often assessed in clinical studies or queried in routine clinical care, the closed-eye environment could increase the risk of SCL complications especially with lenses that are not designed for closed eye wear.29,30 Napping while wearing modern SCLs with high oxygen transmissibility may also allow the wearer to experience reasonable comfort after waking and encourage subsequent unplanned overnight use of lenses.
Older teen and young adult wearers also reported sleeping in lenses when traveling, not sleeping at home, and after alcohol use, possibly indicating poor planning or a more impulsive lifestyle at that age. Healthy behaviors and risk avoidance have been cited as important determinants of health in adolescents.31 College student alcohol consumption and the environmental conditions that promote it are well described in the literature; alcohol consumption is reported to have a significant negative impact on behavior and health32 although its relationship to complications with SCLs has not been explored previously. Questions related to alcohol consumption were included following the clinical chart review of CIEs and focus groups, an important aspect of the development of the CLRS.
Nearly one in four college-age SCL wearers may be sharing lens care products with friends or roommates without the knowledge or direction of their eye care provider. More concerning, reactive replacement of lenses, replacing lenses only when the wearer perceived they had a problem, was highest for 12- to 21-year-olds and then began to decrease with age. Also, consistent with previous reports33,34 daily disposable lens wearers were generally compliant with replacement schedules. Reactive replacement of SCLs may stem from a lack of funds to purchase a lens supply among young wearers, poor education by practitioners, or lack of understanding of the risk of waiting until there is a problem before replacing lenses. Many of the college-aged wearers surveyed reported living away from home but indicated that their parents purchased their contact lenses; the reactive replacement schedule may be a result of a miscommunication between parent and college-aged child, limiting access to lenses when they need to replenish the supply.35
The fact that adult wearers were less likely to report purchasing lenses from their eye care provider is also of interest. Previous investigators have reported increased risks of microbial keratitis36 as well as a decreased awareness of the prescribed contact lens follow-up schedule37 among individuals who purchase from a source other than their eye care provider.
The living environment where SCL wearers care for and handle their lenses (e.g., living with multiple roommates and sharing a bathroom with many people) may have some impact on their risk of developing CIEs. Wearers who live in crowded living settings may not have control over the cleanliness and level of contamination of their general living environment such as doorknobs, desk, and bathroom surfaces. Touching contaminated surfaces could facilitate the transfer of microorganisms on the hand from the lens to the eye and potentiate the development of SCL-related corneal infiltrates. Shared bathroom facilities, especially in college, may be an incremental risk factor for complications in this age group as the bathroom environment can harbor pathogens in a moist environment and may interfere with the patient’s ability to maintain a hygienic space to handle their lenses.38 The majority of the children and younger teens in the sample also shared a bathroom; however, we speculate that the cleanliness of the family home is likely very different than shared college facilities. In addition to exacerbating the transmission of disease,39–43 it is believed that crowding contributes to stress, which in turn is also a contributor to illness and a lowering of immunity.44
Exposure to water is a known risk factor for Acanthamoeba keratitis in SCL wearers.45–53 Contact lens wearers of all ages in this sample reported alarming levels of exposure to tap water while wearing contact lenses, but SCL wear in the shower peaked in college-age wearers. While few respondents stored SCLs in tap water, one in five college-aged wearers rinsed their SCLs in tap water at least “sometimes.” It is unclear if tap water exposure is a result of a lack of education and awareness of proper handling or a blatant disregard for contact lens safety.
The results of this survey support previous work which reported that young adult wearers are more prone to higher risk taking and that that risk taking may be associated with noncompliance with lens care.54 In this current sample, poor contact lens wear and care behaviors and contaminated environments were experienced at times by most SCL wearers, but were especially frequent in older teenage and young adult wearers. Fortunately, many of the factors that increase our patients’ risk of suffering serious SCL complications are modifiable through appropriate patient education and preventive prescribing. For example, wearers who are at high risk because of a high-density living environment could benefit from daily disposable lenses that require less care. Patients who unwittingly increase their risk of developing Acanthamoeba keratitis or other water-borne infections through tap water exposure require better and more focused education. Targeted, age-specific education regarding modifiable risk factors should be considered for both new and established SCL wearers as they return for annual examinations. For example, SCL-related health promotion could be targeted at young wearers and be incorporated into high school and college health “wellness campaigns.” This approach would be consistent with the World Health Organization’s Jakarta Declaration, through which health promotion is understood as public health action directed towards improving modifiable determinants of health. This approach includes personal behaviors as well as public policy and living conditions, which influence behavior.55,56
This survey of a nonclinical SCL population highlights significant age effects in lens wearing behaviors, environmental exposures, and health across a nonclinical population of wearers aged 12 to 33 years. Querying these factors in a clinical population of SCL wearers who present with active CIEs is a natural next step in this research. Comparison of responses from patients when they have CIEs and healthy controls in the same clinical population will further inform cause and effect of these behaviors. The ultimate goal of the CLAY study group work is to identify and disseminate “best practices” to promote safe and healthy SCL wear across all ages.
Nova Southeastern University
3200 South University Dr
Ft. Lauderdale, FL 33328
CLAY Study Group for the Contact Lens Risk Survey Clinical Sites
Indiana University School of Optometry, Bloomington, IN: Meredith E. Jansen, OD, MS (Principal Investigator 2009–2012); Samuel Hargus (survey data collection 2011–present); Fraser McKay (survey data collection 2011–present).
Nova Southeastern University College of Optometry, Ft. Lauderdale, FL: Heidi Wagner, OD, MPH (Principal Investigator); Margi A. Patel (pilot survey data collection 2009–2011); Maggie Lee (survey data collection 2011); Victoria Trieu (survey data collection 2011); Lindsey Vernillo (survey data collection 2011–2012); Amorette Hanna (survey data collection 2012).
Pacific University College of Optometry, Forest Grove, OR: Beth T. Kinoshita, OD (Principal Investigator); Firas Basha (survey data collection 2011); Breanne McLain (survey data collection 2011); Kate Dalrymple (survey data collection 2012); MacKenzie Macintyre III (survey data collection 2012); David Ruckman (survey data collection 2012).
Southern California College of Optometry at Marshall B. Ketchum University, Fullerton, CA: Dawn Y. Lam, MSc, OD (Principal Investigator); Fabian Corona (survey data collection 2011–2012); Daniel Brinchman (survey data collection 2011–2012).
State University of New York College of Optometry, New York, NY: Kathryn Richdale, OD, PhD (Principal Investigator); Kerinna Coffey, BA (survey data collection 2011); Chelsea Stewart, BS (survey data collection 2011); Jessica Troilo (survey data collection 2012); Tyler Maxon, BA (survey data collection 2012).
Biostatistics and Data Coordinating Center
The Ohio State University College of Optometry, Columbus, OH: G. Lynn Mitchell, MAS (Director); Austen L. Tanner (Student Assistant).
Heidi Wagner, OD, MPH (Co-Chair 2009-present); Robin L. Chalmers, OD (Co-Chair 2009–2012); Kathryn Richdale, OD PhD (Co-Chair 2012-present); G. Lynn Mitchell, MAS (2009-present).
Luigina Sorbara, OD, MSc, University of Waterloo School of Optometry and Vision Science, Waterloo, ON, Canada; Robin L. Chalmers, OD, Atlanta, GA.
This project was supported by an unrestricted grant from Alcon Research, Ltd., as well as Nova Southeastern University (Pilot testing: Chancellors Research and Development Grant; Health Professions Division Research Grant). The CLAY Study team also received logistical support from the American Academy of Optometry Research Committee and the American Optometric Association Council on Research. Portions of this work were presented at the American Academy of Optometry (AAO) annual meeting in October 2012, Phoenix, Arizona, E-abstract #120976.
Submitted: August 27, 2013; accepted November 6, 2013.
1. Cutter GR, Chalmers RL, Roseman M. The clinical presentation, prevalence, and risk factors of focal corneal infiltrates in soft contact lens wearers. CLAO J 1996; 22: 30–7.
2. Stapleton F, Dart JK, Minassian D. Risk factors with contact lens related suppurative keratitis. CLAO J 1993; 19: 204–10.
3. McNally JJ, Chalmers RL, McKenney CD, Robirds S. Risk factors for corneal infiltrative events with 30-night continuous wear of silicone hydrogel lenses. Eye Contact Lens 2003; 29: S153–6.
4. Chalmers RL, McNally JJ, Schein OD, Katz J, Tielsch JM, Alfonso E, Bullimore M, O’Day D, Shovlin J. Risk factors for corneal infiltrates with continuous wear of contact lenses. Optom Vis Sci 2007; 84: 573–9.
5. Chalmers RL, Keay L, Long B, Bergenske P, Giles T, Bullimore MA. Risk factors for contact lens complications in US clinical practices. Optom Vis Sci 2010; 87: 725–35.
6. Stapleton F, Keay L, Jalbert I, Cole N. The epidemiology of contact lens related infiltrates. Optom Vis Sci 2007; 84: 257–72.
7. Chalmers RL, Wagner H, Mitchell GL, Lam DY, Kinoshita BT, Jansen ME, Richdale K, Sorbara L, McMahon TT. Age and other risk factors for corneal infiltrative and inflammatory events in young soft contact lens wearers from the Contact Lens Assessment in Youth (CLAY) study. Invest Ophthalmol Vis Sci 2011; 52: 6690–6.
8. Lam DY, Kinoshita BT, Jansen ME, Mitchell GL, Chalmers RL, McMahon TT, Richdale K, Sorbara L, Wagner H. Contact lens assessment in youth: methods and baseline findings. The CLAY Study Group. Optom Vis Sci 2011; 88: 708–15.
9. Wagner H, Chalmers RL, Mitchell GL, Jansen ME, Kinoshita BT, Lam DY, McMahon TT, Richdale K, Sorbara Lthe Clay Study Group. Risk factors for interruption to soft contact lens wear in children and young adults. Optom Vis Sci 2011; 88: 973–80.
10. Aller TA, Wildsoet C. Bifocal soft contact lenses as a possible myopia control treatment: a case report involving identical twins. Clin Exp Optom 2008; 91: 394–9.
11. Anstice NS, Phillips JR. Effect of dual-focus soft contact lens wear on axial myopia progression in children. Ophthalmology 2011; 118: 1152–61.
12. Cho P, Cheung SW, Edwards M. The longitudinal orthokeratology research in children (LORIC) in Hong Kong: a pilot study on refractive changes and myopic control. Curr Eye Res 2005; 30: 71–80.
13. Li SM, Ji YZ, Wu SS, Zhan SY, Wang B, Liu LR, Li SY, Wang NL, Wang JJ. Multifocal versus single vision lenses intervention to slow progression of myopia in school-age children: a meta-analysis. Surv Ophthalmol 2011; 56: 451–60.
14. Sankaridurg P, Holden B, Smith E 3rd, Naduvilath T, Chen X, de la Jara PL, Martinez A, Kwan J, Ho A, Frick K, Ge J. Decrease in rate of myopia progression with a contact lens designed to reduce relative peripheral hyperopia: one-year results. Invest Ophthalmol Vis Sci 2011; 52: 9362–7.
15. Tarrant J, Severson H, Wildsoet CF. Accommodation in emmetropic and myopic young adults wearing bifocal soft contact lenses. Ophthalmic Physiol Opt 2008; 28: 62–72.
16. Walline JJ, Jones LA, Sinnott L, Manny RE, Gaume A, Rah MJ, Chitkara M, Lyons S. A randomized trial of the effect of soft contact lenses on myopia progression in children. The ACHIEVE Study Group. Invest Ophthalmol Vis Sci 2008; 49: 4702–6.
17. Walline JJ, Lindsley K, Vedula SS, Cotter SA, Mutti DO, Twelker JD. Interventions to slow progression of myopia in children. Cochrane Database Syst Rev 2011; CD004916.
18. Hui A, Boone A, Jones L. Uptake and release of ciprofloxacin-HCl from conventional and silicone hydrogel contact lens materials. Eye Contact Lens 2008; 34: 266–71.
19. Phan CM, Subbaraman LN, Jones L. In vitro uptake and release of natamycin from conventional and silicone hydrogel contact lens materials. Eye Contact Lens 2013; 39: 162–8.
20. Wagner H, Chalmers RL, Mitchell GL, Jansen ME, Kinoshita BT, Lam DY, McMahon TT, Richdale KL, Sorbara Lthe CLAY Study Group. Gaps in the contact lens case history: identifying items for a soft contact lens (SCL) risk questionnaire. Invest Ophthalmol Vis Sci 2011; 52:E-Abstract 6500
21. Richdale K, Mitchell GL, Wagner H, Sorbara L, Lam DY, Kinoshita BT, Jansen ME, Chalmers RL. Development of a soft contact lens risk assessment survey. Optom Vis Sci 2012; 89:E-Abstract 125021.
22. Guest G, Bunce A, Johnson L. How many interviews are enough? An experiment with data saturation and variability. Field Methods 2006; 18: 59–82.
24. Dumbleton KA, Woods M, Woods CA, Jones LW, Fonn D. Ability of patients to recall habitual contact lens products and enhancement of recall using photographic aids. Cont Lens Anterior Eye 2011; 34: 236–40.
25. Morgan PB, Efron N, Helland M, Itoi M, Jones D, Nichols JJ, van der Worp E, Woods CA. Demographics of international contact lens prescribing. Cont Lens Anterior Eye 2010; 33: 27–9.
26. Chang DC, Grant GB, O’Donnell K, Wannemuehler KA, Noble-Wang J, Rao CY, Jacobson LM, Crowell CS, Sneed RS, Lewis FM, Schaffzin JK, Kainer MA, et al. Multistate outbreak of Fusarium keratitis associated with use of a contact lens solution. JAMA 2006; 296: 953–63.
27. Faraut B, Boudjeltia KZ, Vanhamme L, Kerkhofs M. Immune, inflammatory and cardiovascular consequences of sleep restriction and recovery. Sleep Med Rev 2012; 16: 137–49.
28. Segerstrom SC, Miller GE. Psychological stress and the human immune system: a meta-analytic study of 30 years of inquiry. Psychol Bull 2004; 130: 601–30.
29. Jansen ME, Chalmers R, Mitchell GL, Kinoshita BT, Lam DY, McMahon TT, Richdale K, Sorbara L, Wagner H. Characterization of patients who report compliant and non-compliant overnight wear of soft contact lenses. Cont Lens Anterior Eye 2011; 34: 229–35.
30. Schein OD, Glynn RJ, Poggio EC, Seddon JM, Kenyon KR. The relative risk of ulcerative keratitis among users of daily-wear and extended-wear soft contact lenses. A case-control study. Microbial Keratitis Study Group. N Engl J Med 1989; 321: 773–8.
31. Raphael D. Determinants of health of North-American adolescents: evolving definitions, recent findings, and proposed research agenda. J Adolesc Health 1996; 19: 6–16.
32. Wechsler H, Nelson TF. What we have learned from the Harvard School of Public Health College Alcohol Study: focusing attention on college student alcohol consumption and the environmental conditions that promote it. J Stud Alcohol Drugs 2008; 69: 481–90.
33. Wu Y, Carnt N, Stapleton F. Contact lens user profile, attitudes and level of compliance to lens care. Cont Lens Anterior Eye 2010; 33: 183–8.
34. Dumbleton K, Richter D, Woods C, Jones L, Fonn D. Compliance with contact lens replacement in Canada and the United States. Optom Vis Sci 2010; 87: 131–9.
35. Schnider CM, Jedraszczak AM. The “pantry load” effect—can it help drive more compliant contact lens replacement? Optom Vis Sci 2012; 89:E-abstract 120652.
36. Stapleton F, Keay L, Edwards K, Naduvilath T, Dart JK, Brian G, Holden BA. The incidence of contact lens-related microbial keratitis in Australia. Ophthalmology 2008; 115: 1655–62.
37. Szczotka-Flynn LB, Pearlman E, Ghannoum M. Microbial contamination of contact lenses, lens care solutions, and their accessories: a literature review. Eye Contact Lens 2010; 36: 116–29.
38. Wu YT, Zhu H, Willcox M, Stapleton F. Impact of air-drying lens cases in various locations and positions. Optom Vis Sci 2010; 87: 465–8.
39. Altwin I. Crowding. Monterey, CA: Brooks/Cole Pub. Co; 1975.
40. Mitchell RE. Some social implications of high density housing. Am Sociol Rev 1971; 36: 18 –29.
41. Rimsza ME, Kirk GM. Common medical problems of the college student. Pediatr Clin North Am 2005; 52: 9 –24.
42. Round A, Evans MR, Salmon RL, Hosein IK, Mukerjee AK, Smith RWJ, Palmer SR. Public health management of an outbreak of group C meningococcal disease in university campus residents. Eur J Public Health 2001; 11: 431–6.
43. Turner JC. How colleges can plan for the bird flu. Chronicle Rev 2005; 52: B20.
44. Dubos R. The social environment. In: Proshansky HM, Ittelson WH, Rivlin LG, eds. Environmental Psychology: Man and His Physical Setting. New York: Holt, Rinehart and Winston; 1970: 202–08.
45. Seal DV, Kirkness CM, Bennett HG, Peterson M, Keratitis Study G. Population-based cohort study of microbial keratitis in Scotland: incidence and features. The Keratitis Study Group. Cont Lens Anterior Eye 1999; 22: 49–57.
46. Cheng KH, Leung SL, Hoekman HW, Beekhuis WH, Mulder PG, Geerards AJ, Kijlstra A. Incidence of contact-lens-associated microbial keratitis and its related morbidity. Lancet 1999; 354: 181–5.
47. Lam DS, Houang E, Fan DS, Lyon D, Seal D, Wong E. Incidence and risk factors for microbial keratitis in Hong Kong: comparison with Europe and North America. Eye 2002; 16: 608–18.
48. Awwad ST, Petroll WM, McCulley JP, Cavanagh HD. Updates in Acanthamoeba keratitis. Eye Contact Lens 2007; 33: 1–8.
49. Hammersmith KM. Diagnosis and management of Acanthamoeba keratitis. Curr Opin Ophthalmol 2006; 17: 327–31.
50. Stehr-Green JK, Bailey TM, Visvesvara GS. The epidemiology of Acanthamoeba keratitis in the United States. Am J Ophthalmol 1989; 107: 331–6.
51. Schaumberg DA, Snow KK, Dana MR. The epidemic of Acanthamoeba keratitis: where do we stand? Cornea 1998; 17: 3–10.
52. Centers for Disease Control and Prevention. Fusarium keratitis—multiple states, 2006. MMWR Morb Mortal Wkly Rep 2006; 55: 400–1.
53. Joslin CE, Tu EY, Shoff ME, Booton GC, Fuerst PA, McMahon TT, Anderson RJ, Dworkin MS, Sugar J, Davis FG, Stayner LT. The association of contact lens solution use and Acanthamoeba keratitis. Am J Ophthalmol 2007; 144: 169–80.
54. Carnt N, Keay L, Willcox M, Evans V, Stapleton F. Higher risk taking propensity of contact lens wearers is associated with less compliance. Cont Lens Anterior Eye 2011; 34: 202–6.
55. World Health Organization. Jakarta Declaration on Leading Health Promotion into the 21st Century. Geneva, Switzerland: World Health Organization; 1997.
56. Nutbeam D. Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century. Health Promot Int 2000; 15: 259–67.
Keywords:© 2014 American Academy of Optometry
age; soft contact lens; corneal inflammatory event; risk; survey