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Psychosocial correlates of face-touching mitigation behaviors in public and private

  • Jiahua Yang
    Correspondence
    Address correspondence to Jiahua Yang, The University of Texas at Austin, Center for Health Communication, 2504B Whitis Ave (A1150), Austin, TX 78712, USA. Phone: 512-803-6812.
    Affiliations
    The Stan Richards School of Advertising and Public Relations, Moody College of Communication, The University of Texas at Austin, Austin, TX, USA

    Center for Health Communication, The University of Texas at Austin, Austin, TXs, USA
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  • Andy J. King
    Affiliations
    Greenlee School of Journalism and Communication, Iowa State University, Ames, IA, USA
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  • Deena Kemp
    Affiliations
    The Stan Richards School of Advertising and Public Relations, Moody College of Communication, The University of Texas at Austin, Austin, TX, USA
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  • Michael Mackert
    Affiliations
    The Stan Richards School of Advertising and Public Relations, Moody College of Communication, The University of Texas at Austin, Austin, TX, USA

    Center for Health Communication, The University of Texas at Austin, Austin, TXs, USA

    Department of Population Health, Dell Medical School, The University of Texas at Austin, Austin, TX, USA
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  • Alison G. Cahill
    Affiliations
    Department of Women's Health, Dell Medical School, The University of Texas at Austin, Medical Park Tower, Austin, TX, USA
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  • Mike Henson-García
    Affiliations
    Health Promotion and Behavioral Sciences, UTHealth Science Center School of Public Health, Dallas Regional Campus, Dallas, TX, USA
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  • Lindsay M. Bouchacourt
    Affiliations
    The Stan Richards School of Advertising and Public Relations, Moody College of Communication, The University of Texas at Austin, Austin, TX, USA

    Center for Health Communication, The University of Texas at Austin, Austin, TXs, USA
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Published:January 22, 2022DOI:https://doi.org/10.1016/j.ajic.2022.01.005

      Highlights

      • This study shows that face-touching behaviors are associated with some psychosocial factors.
      • Perceived risk severity and self-efficacy of not touching face are associated with a higher likelihood of mitigation behaviors in both private public environments.
      • COVID-19 is associated with a higher likelihood of mitigation behaviors in public.
      This study investigates psychosocial factors that influence people's face-touching mitigation behaviors. A nationwide survey was conducted online, and the results showed that perceived risk severity of touching face, and barriers and self-efficacy of not touching face were stable predictors. COVID-19 was related to a higher likelihood of mitigation behavior in public spaces. This study provides important implications to health communication and promotion for COVID-19 and general infection control.

      Key Words

      Limiting face-touching is one way to control the spread of infectious diseases. Early in the COVID-19 pandemic, public health messages promoted hand hygiene and limiting face-touching,

      Centers for Disease Control and Prevention. How to protect yourself & others. Accessed June 8, 2022. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html

      as contaminated hands contacting the face is a major mechanism of viral self-infection for numerous diseases.
      • Macias AE
      • de la Torre A
      • Moreno-Espinosa S
      • Leal PE
      • Bourlon MT
      • Ruiz-Palacios GM.
      Controlling the novel A (H1N1) influenza virus: don't touch your face!.
      • Nicas M
      • Jones RM.
      Relative contributions of four exposure pathways to influenza infection risk.
      • Przekwas A
      • Chen Z.
      Washing hands and the face may reduce COVID-19 infection.
      A review of facial self-touching research suggested the need for more studies examining how face-touching behavior might be reduced,
      • Spille JL
      • Grunwald M
      • Martin S
      • Mueller SM.
      Stop touching your face! A systematic review of triggers, characteristics, regulatory functions and neuro-physiology of facial self touch.
      noting that perceived severity of infection might reduce face-touching,
      • Johnston JD
      • Eggett D
      • Johnson MJ
      • Reading JC.
      The influence of risk perception on biosafety level-2 laboratory workers’ hand-to-face contact behaviors.
      though few studies have investigated psychosocial correlates of conscious efforts to reduce direct face-touching (eg, using a cloth instead of one's fingers or hands to touch one's face).
      To address this gap in the current literature, the present study investigated whether psychosocial variables taken from the health belief model (HBM)
      • Skinner CS
      • Tiro J
      • Champion VL.
      The health belief model.
      associate with intentions to mitigate direct face-touching in public and private environments (RQ). These variables include perceived susceptibility and severity of the risk of face-touching, perceived barriers to and benefits of not touching one's face which depict the evaluation of the recommended health behavior, and self-efficacy of behavioral control over not touching one's face. By identifying the role of psychosocial elements in people's face-touching behaviors, our research could inform the design of health communication messages that advocate avoiding direct face-touching to reduce infection risk, especially during current (eg, COVID-19) and future pandemics.

      Method

      Sample

      A nationwide online survey, approved by the IRB of the University (ID: STUDY00001526), was conducted among adult participants aged 18 years or older (N = 1,060) recruited through Qualtrics Panels. The mean age of the sample is 49 years old (range 18-87). Table 1 provides full demographic information.
      Table 1Demographics of the sample and descriptive statistics of variables
      DemographicCategoryFrequency%
      GenderMale52449.5
      Female52649.7
      Other80.8
      RaceWhite of Caucasian69165.2
      Hispanic, Latino/a/x, or Spanish origin13712.9
      African American or Black12611.9
      Asian, Asian Indian, or Asian American635.9
      American Indian or Alaska Native212.0
      Middle Eastern or North African30.3
      Native Hawaiian or Pacific Islander10.1
      Other181.7
      EducationLess than high school degree212.0
      High school degree or equivalent26525.0
      Some college but no degree24322.9
      Associate degree14313.5
      Bachelor's degree24322.9
      Master's degree10610.0
      Doctorate degree242.3
      Other30.3
      Income$0464.3
      $1 - $24,99924923.5
      $25,000 - $49,99933331.4
      $50,000 - $74,99920018.9
      $75,000 - $99,999979.2
      $100,000 - $149,999747.0
      $150,000 and above494.6
      Health conditionPoor383.6
      Fair17616.6
      Average22821.5
      Good45943.4
      Excellent14814.0
      COVID vaccinationYes – fully vaccinated65862.1
      Yes – partially vaccinated747.0
      No30328.6
      Flu shot every yearYes58555.2
      No44642.1
      Descriptive statistics of dependent variablesCategoryFrequency%
      Mitigation behaviors in privateSuboptimal behaviors60657.2
      Optimal behaviors44341.8
      Mitigation behaviors in publicSuboptimal behaviors45542.9
      Optimal behaviors59456.0
      Descriptive statistics of independent variablesMeanSDRange
      Biting nails2.031.26[1.00, 5.00]
      Licking fingers while eating2.461.13[1.00, 5.00]
      Picking nose2.521.07[1.00, 5.00]
      Rubbing eyes3.100.94[1.00, 5.00]
      General hygiene practice23.5413.32[1.00, 42.00]
      Knowledge8.642.14[1.00, 11.00]
      COVID-19 impact (α = .96)5.011.57[1.00, 7.00]
      Perceived susceptibility in private3.871.83[1.00, 7.00]
      Perceived susceptibility in public4.791.79[1.00, 7.00]
      Perceived severity in private3.591.80[1.00, 7.00]
      Perceived severity in public4.811.70[1.00, 7.00]
      Benefits (α = .96)5.251.25[1.00, 7.00]
      Barriers (α = .87)3.461.79[1.00, 7.00]
      Self-efficacy (α = .89)4.361.54[1.00, 7.00]

      Measures

      Dependent variables: Face-touching mitigation behaviors

      Participants were asked to choose what they would do if they felt a sudden itch on their face in a private (e.g., home) and public (e.g., grocery store) environment. There were 5 options: (1) scratch face with fingers directly, (2) scratch face with the back of your hands directly, (3) sanitize your hands first and scratch face, (4) use a cloth and/or napkin and/or shirt to scratch your face, and (5) wait until the itch goes away. We dichotomized responses into suboptimal (1 or 2) and optimal (3-5) behaviors. Table 1 includes descriptive statistics for all study variables.

      Self-reported face-touching habits

      We asked participants to self-evaluate four habitual face-touching behaviors in the present study: biting fingernails, licking fingers while eating, picking nose, and rubbing eyes. Participants self-reported their behavioral frequency on a scale from 1 (never) to 5 (always).

      General hygiene, knowledge, and COVID-19 impact

      General hygiene practice was calculated as the product of the number of hand parts washed every time and the typical time length of washing hands. Knowledge about risks of hand-head contact was calculated as the sum of the score of 11 true or false statements. The correct answer was coded as 1 and the wrong answer was coded as 0. The impact of COVID-19 on awareness of touching face, eyes, nose, or mouth (4 items) was measured on a scale from 1 (strongly disagree) to 7 (strongly agree).

      Psychosocial correlates

      Health beliefs, including perceived susceptibility and severity of face-touching (in private and in public), as well as perceived benefits (4 items), barriers (2 items), and self-efficacy (3 items) of not touching face were measured on a scale from 1 (lowest) to 7 (highest).

      Data analysis

      We used hierarchical logistic regression analysis to examine associations of study variables with the behavioral outcomes of interest. Demographics, general hygiene, knowledge, COVID-19 impact, and self-reported face-touching were entered in Model 1. We entered the HBM variables in Model 2. All analyses were conducted with SPSS.

      Results

      Overall, people reported engaging in optimal face-touching mitigation behaviors in public more often than they did in private (Table 1). Table 2 provides full results for the models related to performing face-touching mitigation behaviors in public and private
      Table 2Variables statistics of regression models
      Mitigation behaviors in privateMitigation behaviors in public
      Model 1
      Block 1 included demographic variables, general hygiene practice, face-touching habits, and knowledge.
      : Nagelkerke R2 = .16, Classification = 65.7%
      Model 2
      Block 2 included psychosocial variables, ie, perceived susceptibility in private or public, perceived severity in private or public, benefits, barriers, and self-efficacy, in addition to variables from Block 1.
      : Nagelkerke R2 = .29, Classification = 72.4%
      Model 1
      Block 1 included demographic variables, general hygiene practice, face-touching habits, and knowledge.
      : Nagelkerke R2 = .15, Classification = 64.1%
      Model 2
      Block 2 included psychosocial variables, ie, perceived susceptibility in private or public, perceived severity in private or public, benefits, barriers, and self-efficacy, in addition to variables from Block 1.
      : Nagelkerke R2 = .22, Classification = 68.5%
      VariablesBPOR95% C.I. for ORBPOR95% C.I. for ORBPOR95% C.I. for ORBPOR95% C.I. for OR
      Gender
      For gender, male = 0 and female = 1.
      .29.0441.33[1.01, 1.76].29.0561.34[0.99, 1.81].17.2261.19[0.90, 1.56].16.2791.17[0.88, 1.56]
      Race
      For race, 0 = white and 1 = non-white.
      ,
      Age was not included in the model because of missing data on a large number of participants. We ran the analysis with and without age in the model and found that age was not a significant predictor in either final model and its inclusion did not change the significance of any results.
      -.30.0440.74[0.56, 0.99]-.15.3380.86[0.63, 1.17]-.37.014.69[0.52, 0.93]-.24.121.79[0.58, 1.07]
      Education-.07.1600.93[0.84, 1.03]-.06.3080.94[0.85, 1.05].02.6591.02[0.93, 1.13].04.4991.04[0.93, 1.15]
      Income.13.0181.13[1.02, 1.26].09.1081.10[0.98, 1.23]-.07.168.93[0.84, 1.03]-.09.107.92[0.82, 1.02]
      General hygiene.01.0301.01[1.00, 1.02].01.3311.01[0.99, 1.02].01.0061.01[1.00, 1.03].01.1321.01[1.00, 1.02]
      Biting fingernails.32< .0011.38[1.22, 1.57].23.0011.25[1.10, 1.43].17.0081.18[1.05, 1.34].13.0421.14[1.01, 1.30]
      Licking fingers.03.6751.03[0.89, 1.19]-.03.6620.97[0.83, 1.13]-.09.207.91[0.79, 1.05]-.14.060.87[0.75, 1.01]
      Picking nose.04.6421.04[0.89, 1.21].03.7481.03[0.87, 1.21].01.9281.01[0.87, 1.17].04.6221.04[0.89, 1.22]
      Rubbing eyes-.44< .0010.65[0.55, 0.76]-.39< .0010.68[0.57, 0.81]-.21.012.81[0.69, 0.96]-.15.083.86[0.73, 1.02]
      Knowledge-.17< .0010.84[0.79, 0.90]-.14.0010.87[0.80, 0.94]-.09.009.91[0.85, 0.98]-.06.171.95[0.88, 1.02]
      COVID-19 impact.25< .0011.28[1.16, 1.42].05.4621.05[0.93, 1.18].39<.0011.48[1.34, 1.64].28<.0011.33[1.18, 1.49]
      Susceptibility.05.3101.05[0.95, 1.16].03.5741.03[0.93, 1.14]
      Severity.32< .0011.37[1.24, 1.52].19.0011.21[1.08, 1.35]
      Benefits-.11.1490.89[0.76, 1.04]-.28<.001.75[0.64, 0.88]
      Barriers-.23< .0010.80[0.72, 0.88]-.20<.001.82[0.74, 0.90]
      Self-efficacy.14.0101.15[1.03, 1.28].13.0111.14[1.03, 1.26]
      low asterisk Block 1 included demographic variables, general hygiene practice, face-touching habits, and knowledge.
      Block 2 included psychosocial variables, ie, perceived susceptibility in private or public, perceived severity in private or public, benefits, barriers, and self-efficacy, in addition to variables from Block 1.
      For gender, male = 0 and female = 1.
      § For race, 0 = white and 1 = non-white.
      Age was not included in the model because of missing data on a large number of participants. We ran the analysis with and without age in the model and found that age was not a significant predictor in either final model and its inclusion did not change the significance of any results.

      Mitigation behaviors in private

      Model 1 explained 16% of the variance in mitigation behaviors in private. Model 2 (the HBM variables) increased the variance explained by 13%. In Model 2, self-reported behaviors of biting fingernails (positive) and rubbing eyes (negative), as well as knowledge of the implications of face-touching (negative), associated with engaging in optimal mitigation behaviors. The significant psychosocial correlates were perceived severity (positive), barriers (negative), and self-efficacy (positive).

      Mitigation behaviors in public

      Model 1 explained 15% of the variance in mitigation behaviors in public. Model 2 explained an additional 7% of the variance. In Model 2, self-reported behavior of biting fingernails (positive), COVID-19 impact perceptions (positive), perceived severity (positive), benefits (negative), barriers (negative), and self-efficacy (positive) were associated with optimal behaviors.

      Discussion

      In the current study, participants self-reported they were more likely to directly touch their face in private more than in public. This result is not surprising given people are likely to perceive themselves as being more cautious of their own behaviors in public since their behaviors are more observable and public spaces seem to be less clean. Our analyses found three psychosocial correlates could be a target of future health communication interventions and campaigns: perceived severity of face-touching, barriers to avoid touching one's face, and self-efficacy about avoiding face-touching. The results confirmed the potential effectiveness of emphasizing perceived severity in health promotion
      • Spille JL
      • Grunwald M
      • Martin S
      • Mueller SM.
      Stop touching your face! A systematic review of triggers, characteristics, regulatory functions and neuro-physiology of facial self touch.
      and provided novel practical insights. Based on these findings, health communication messages could be more comprehensive by highlighting the risk of direct face-touching to getting sick such as showing numbers of increased infection rates, promoting detailed and easy-to-follow hand-hygiene practices such as carrying hand sanitizer, and presenting encouragement to strengthen one's confidence in overcoming barriers and controlling the threat. The results also suggest promising effects of pandemic-related health communication—the COVID-19 pandemic has a positive impact on optimal behavior in public. Presenting COVID-19 as a specific and urgent health risk in health messages could help cultivate the habit of avoiding direct face-touching (especially the eyes, nose, and mouth area) for general infection control. Limitations of this study include self-reported biases and robustness of operationalization of some variables related to hand hygiene and face-touching.

      Acknowledgments

      The project was funded by an anonymous donor to the Dell Medical School at the University of Texas at Austin. The donor, department, and university had no input into the design or analysis of the current study.

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