Development of the Mobile Technology Vulnerability Scale among Youth and Young Adults Living with HIV

Nadra E Lisha, Torsten B Neilands, Xavier A Erguera, Parya Saberi, Nadra E Lisha, Torsten B Neilands, Xavier A Erguera, Parya Saberi

Abstract

Introduction: Youth and young adults living with HIV (YLWH) in the US have the lowest viral suppression percentage. Lack of sufficient technology access may be correlated with HIV health outcomes in this population.

Methods: We developed a Mobile Technology Vulnerability Scale (MTVS; 18 items) among 18-29-year-olds. Exploratory factor analysis (EFA) was performed on baseline data (N = 79), followed by a confirmatory factor analysis (CFA) of 6-month follow-up data (N = 69). Cronbach's alpha for internal consistency and test-retest reliability were examined. We also correlated the scale with self-report antiretroviral therapy (ART) adherence.

Results: EFA yielded a single-factor solution at baseline after dropping one item. CFA at follow-up corroborated the single-factor. Cronbach's alpha was high and MTVS was correlated with ART adherence at both time points. MTVS at baseline and 6 months were correlated.

Conclusion: The 17-item MTVS scale was found to be valid and reliable and related to ART adherence.

Keywords: adherence; antiretroviral therapy; mobile telephone; scale development; technology; youth living with HIV.

Conflict of interest statement

The authors declare no conflict of interest.

References

    1. Harris N.S., Johnson A.S., Huang Y.-L.A., Kern D., Fulton P., Smith D.K., Valleroy L.A., Hall H.I. Vital signs: Status of human immunodeficiency virus testing, viral suppression, and HIV preexposure prophylaxis—United States, 2013–2018. Morb. Mortal. Wkly. Rep. 2019;68:1117. doi: 10.15585/mmwr.mm6848e1.
    1. Doshi R.K., Milberg J., Jumento T., Matthews T., Dempsey A., Cheever L.W. For many served by the Ryan White HIV/AIDS Program, disparities in viral suppression decreased, 2010–2014. Health Aff. 2017;36:116–123. doi: 10.1377/hlthaff.2016.0655.
    1. Doshi R.P., Aseltine R.H., Sabina A.B., Graham G.N. Racial and ethnic disparities in preventable hospitalizations for chronic disease: Prevalence and risk factors. J. Racial Ethn. Health Disparities. 2017;4:1100–1106. doi: 10.1007/s40615-016-0315-z.
    1. Castel A.D., Kalmin M.M., Hart R.L., Young H.A., Hays H., Benator D., Kumar P., Elion R., Parenti D., Ruiz M.E. Disparities in achieving and sustaining viral suppression among a large cohort of HIV-infected persons in care—Washington, DC. AIDS Care. 2016;28:1355–1364. doi: 10.1080/09540121.2016.1189496.
    1. Castellsagué X., Muñoz N., De Stefani E., Victora C.G., Castelletto R., Rolón P.A., Quintana M.J. Independent and joint effects of tobacco smoking and alcohol drinking on the risk of esophageal cancer in men and women. Int. J. Cancer. 1999;82:657–664. doi: 10.1002/(SICI)1097-0215(19990827)82:5<657::AID-IJC7>;2-C.
    1. Zanoni B.C., Mayer K.H. The adolescent and young adult HIV cascade of care in the United States: Exaggerated health disparities. AIDS Patient Care STDs. 2014;28:128–135. doi: 10.1089/apc.2013.0345.
    1. Crepaz N., Tang T., Marks G., Mugavero M.J., Espinoza L., Hall H.I. Durable viral suppression and transmission risk potential among persons with diagnosed HIV infection: United States, 2012–2013. Clin. Infect. Dis. 2016;63:976–983. doi: 10.1093/cid/ciw418.
    1. Saberi P., Catz S.L., Leyden W.A., Stewart C., Ralston J.D., Horberg M.A., Grothaus L., Silverberg M.J. Antiretroviral therapy adherence and use of an electronic shared medical record among people living with HIV. AIDS Behav. 2015;19:177–185. doi: 10.1007/s10461-014-0982-x.
    1. Saberi P., Johnson M.O. Correlation of internet use for health care engagement purposes and HIV clinical outcomes among HIV-positive individuals using online social media. J. Health Commun. 2015;20:1026–1032. doi: 10.1080/10810730.2015.1018617.
    1. Pew Research Center Mobile Fact Sheet. Internet & Technology. [(accessed on 9 April 2021)]; Available online:
    1. Colasanti J., Kelly J., Pennisi E., Hu Y.-J., Root C., Hughes D., Del Rio C., Armstrong W.S. Continuous retention and viral suppression provide further insights into the HIV care continuum compared to the cross-sectional HIV care cascade. Clin. Infect. Dis. 2016;62:648–654. doi: 10.1093/cid/civ941.
    1. Hobfoll S.E. Conservation of resources: A new attempt at conceptualizing stress. Am. Psychol. 1989;44:513. doi: 10.1037/0003-066X.44.3.513.
    1. Young S., Wheeler A.C., McCoy S.I., Weiser S.D. A review of the role of food insecurity in adherence to care and treatment among adult and pediatric populations living with HIV and AIDS. AIDS Behav. 2014;18:505–515. doi: 10.1007/s10461-013-0547-4.
    1. Erguera X.A., Johnson M.O., Neilands T.B., Ruel T., Berrean B., Thomas S., Saberi P. WYZ: A pilot study protocol for designing and developing a mobile health application for engagement in HIV care and medication adherence in youth and young adults living with HIV. BMJ Open. 2019;9:e030473. doi: 10.1136/bmjopen-2019-030473.
    1. Reeder C., Neilands T.B., Palar K., Saberi P. Food Insecurity and Unmet Needs Among Youth and Young Adults Living With HIV in the San Francisco Bay Area. J. Adolesc. Health. 2019;65:262–266. doi: 10.1016/j.jadohealth.2019.02.023.
    1. Wilson I.B., Lee Y., Michaud J., Fowler F.J., Rogers W.H. Validation of a new three-item self-report measure for medication adherence. AIDS Behav. 2016;20:2700–2708. doi: 10.1007/s10461-016-1406-x.
    1. Muthén L., Muthén B. MPlus User’s Guide. 5th ed. Muthén & Muthén; Los Angeles, CA, USA: 2007.
    1. Comrey A.L., Lee H.B. A First Course in Factor Analysis. Psychology Press; Hove, UK: 2013.
    1. Hu L., Bentler P.M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equ. Model. Multidiscip. J. 1999;6:1–55. doi: 10.1080/10705519909540118.

Source: PubMed

赞助者和合作者

医疗条件

药物干预

3
订阅