Smartphone App for STD Medication Adherence in Adolescents

Introduction and Practice Issue

There has been growing emphasis on the use of evidence-based practice (EBP) over the past two decades (Reed & Reed, 2012). This growing emphasis is attributed in large part to the notion that EBP is widely regarded as providing the framework needed for the cost-effective delivery of high-quality care while taking patients' interests and preferences into account. In this regard, the American Psychological Association defines EBP as "the integration of the best available research with clinical expertise in the context of patient characteristics, culture, and preferences" (as cited in Reed & Reed, 2012, p. 20). Although the increased calls from the helping professions for the use of EBP are fairly recent, the use of EBP actually dates to Florence Nightingale's seminal work on the battlefields of the Crimean War in the 1850s (Rahman & Applebaum, 2012). While EBP has its share of critics, most practitioners agree that the approach represents the best available strategy for improving the quality of healthcare services in the face of scarce resources (Rahman & Applebaum, 2012).

The primary aim of this project is to identify EBP-based strategies for improving adherence rates to medication and treatment regimens for adolescent patients with sexually transmitted diseases (STDs). This aim is congruent with the tenets of EBP, which include improving patient healthcare outcomes as well as the quality of care and overall health status (Grove, Burns, & Gray, 2013).

A properly formulated PICOT question can serve to identify those studies that are most relevant for the specific purposes of an empirical analysis (Burnett, 2013). In this regard, Burnett (2013) advises that "PICOT works like a filter, targeting efforts and narrowing the search for information as it applies to a specific patient care issue" (p. 37). In the proposed study, the specific patient care issue of interest concerns adherence levels to treatment regimens among adolescents being treated for sexually transmitted diseases and identifying ways to improve those levels. The clinical question guiding the proposed study is: What technology-based strategies can be used to improve adherence rates to treatment regimens among adolescents with sexually transmitted diseases to develop corresponding evidence-based practices?

Background: STD Prevalence and Adherence Challenges

The incidence of sexually transmitted diseases among adolescents has experienced a steady increase in recent years (Kaptanglu & Suer, 2014). Because incidence rates vary by country, there are likely substantive cultural and ethnic differences in adolescents' levels of knowledge about and attitudes toward sexual health (Kaptanglu & Suer, 2014). Individual perceptions of locus of control and personal responsibility differ even among homogeneous populations, making it important to identify those factors most responsible for exacerbating STD rates (Estrada & Dupoux, 2006). Although precise figures are unavailable and many authorities believe official reports seriously underestimate the extent of the problem, current projections indicate that more than 340 million people become infected with some type of sexually transmitted disease each year (Timiun, 2012).

While prevalence rates differ across disease types, these infections all share serious and potentially fatal healthcare implications when left untreated. In the United States, the U.S. Centers for Disease Control (CDC) has reported a 19% increase in global syphilis rates among men and women, with men accounting for the vast majority (90%) of all primary and secondary cases — the most infectious stages of the disease (Reported STDs in the United States, 2015). Moreover, syphilis can seriously increase the risk of acquiring even more deadly infections, such as the human immunodeficiency virus (HIV) (Reported STDs in the United States, 2015).

Poor patient adherence to treatment regimens is widely recognized as a significant problem, especially among certain population groups such as those with mental disorders and young people who lack the medical literacy to understand the importance of adhering to treatment (Kalali & Richerson, 2016). According to Atibioke and Osinowo (2015), treatment adherence is "the extent to which a person's behavior coincides with medical or health advice, such as taking medication regularly, returning to a doctor's office for follow-up appointments, and observing preventive and healthful lifestyle changes" (p. 90). Because the treatment of sexually transmitted diseases always includes a medication intervention, adherence to treatment regimens must therefore include a focus on ensuring patients take their medications precisely as instructed (Atibioke & Osinowo, 2015).

Nonadherence to treatment regimens for sexually transmitted diseases falls into two general categories: (1) not taking prescribed medication in the recommended dosage or frequency, or not taking it at all; and (2) non-attendance or irregular attendance at appointments with healthcare providers (Kalali & Richerson, 2016). Nonadherence is well documented to adversely affect clinical outcomes. As Kalali and Richerson (2016) emphasize, "Nonadherence can result in an increased risk of relapse, hospitalization, poor therapeutic response, and delayed remission and recovery" (p. 25).

Moreover, nonadherence levels among adolescents with sexually transmitted diseases may be significantly underestimated due to fears that parents will discover their condition (Leichliter & Copen, 2017). Recent changes in the U.S. healthcare system have allowed dependent children to continue as beneficiaries of their parents' health insurance plans until age 26, creating the potential for even young adults to avoid or delay seeking treatment due to confidentiality concerns (Leichliter & Copen, 2017). Taken together, it is reasonable to assert that improving treatment regimen adherence rates will have a correspondingly positive effect on healthcare outcomes for adolescents with sexually transmitted diseases.

Evidence Review and Synthesis

The search for scholarly articles pertaining to this evidence-based project began with the university library. Search terms, medical subject headings, and keywords included "sexually transmitted diseases," "STDs," as well as chlamydia, gonorrhea, syphilis, and HIV/AIDS. Additional searches were conducted using the terms "adherence rates [and/or] levels," "nonadherent patients," "treatment regimens," and "medication regimens." Scholarly articles were limited to those published in peer-reviewed journals in the English language within the past five years. The following academic databases were consulted:

In addition, reliable governmental resources such as the U.S. Centers for Disease Control were consulted for current STD prevalence rates, as was the vendor of a technological adherence solution. The results of peer-reviewed studies deemed sufficiently relevant ("keeper studies") and satisfying the inclusion criteria were incorporated into the evaluation and synthesis tables in the appendix.

Synthesizing the evidence from the selected studies required multiple rounds of review and assessment. This process followed the iterative approach recommended by Noblit and Hare (1988) concerning the synthesis of multiple studies of different types, wherein each study evaluated informs the evaluation of subsequent studies.

A retrospective study by Leichliter and Copen (2017) analyzed data from the 2013–2015 National Survey of Family Growth and found that 12.7% of sexually experienced youths (adolescents aged 15–17 years and young adults aged 18–25 years on a parent's insurance plan) refused to access sexual and reproductive healthcare services due to concerns their parents would discover their interests and needs — a concern especially pronounced among those aged 15 to 17 years. The survey included 10,205 respondents and had a valid response rate of 69.3% (Leichliter & Copen, 2017). Confidentiality concerns adversely affected help-seeking for all types of sexually transmitted diseases, with rates highest among those who were not allowed time alone with their healthcare provider. These findings underscore the need to ensure that young people who acquire a sexually transmitted disease are provided with the information needed to make an informed decision about the importance of seeking treatment and adhering to their treatment regimen (Leichliter & Copen, 2017).

A study by Cairns and Hill (2013) conducted a preliminary investigation of the effectiveness of using the Large Allen Cognitive Level Screen (LACLS) to improve adherence levels to treatment regimens among a convenience sample of 11 young adults. All participants had been prescribed oral medications and were asked to report whether they used any medication aids (dosette/medication boxes, Webster/blister packs, or phone or electronic reminders) (Cairns & Hill, 2013). Participants were also asked to identify the medication support network that best described their circumstances:

If none of these descriptions were suitable, participants could describe their level of support in their own words (Cairns & Hill, 2013). The findings showed "a strong positive association exists between the LACLS and medication adherence" (p. 139), attributed to the screening process the LACLS provided clinicians for evaluating participants' capacity to manage their medication regimens. Cairns and Hill (2013) conclude that "the LACLS is a time-efficient screen of a person's capacity to manage medication regimens [and] successful use of the LACLS may prove a time-efficient tool for prioritizing comprehensive assessment and possible intervention to prevent medication non-adherence" (p. 139). While these findings may not be fully generalizable to a population of young adults with sexually transmitted diseases, they underscore the importance of carefully assessing patients' capacity to adhere to medication regimens.

A study by Levesque and Li (2012) used a custom questionnaire with demonstrated face validity to survey 298 patients in a northern British Columbia city. The study's guiding research questions were: (1) how often do patients adhere to prescribed medications?; (2) how often do patients adhere to recommended lifestyle changes?; (3) what is the nature of the relationship linking adherence to other determining factors?; and (4) what are the most important factors in predicting adherence? (Levesque & Li, 2012).

The results showed that: (1) adherence to lifestyle changes and participants' age presented a U-shaped relationship; (2) those who perceived themselves to be in poor health were less likely to adhere to lifestyle changes; (3) barriers such as severe winter weather, lack of transportation, and medication cost contributed negatively to adherence; and (4) adherence levels improved when physicians provided sufficient information on the benefits and use of prescribed medications and lifestyle changes and when patients reported trusting their doctors. These researchers conclude that "physicians can play an important role in promoting adherence among patients. Community health workers should make efforts in reducing barriers that interfere with patient adherence" (Levesque & Li, 2012, p. 44).

A study by Atibioke and Osinowo (2015) used a cross-sectional survey research design to investigate the psychological determinants of treatment adherence among 548 adults and children with HIV and AIDS undergoing active antiretroviral therapy in a Nigerian program. The regimen involved ingesting at least 18 pills or capsules simultaneously, with some requiring refrigerated medications taken at specific times, in some cases with food and in others on an empty stomach (Atibioke & Osinowo, 2015). The results showed that perceptions of stigmatization and discrimination did not affect treatment adherence levels, but those with adequate social support networks demonstrated significantly higher adherence to their medication regimens. While there are likely cross-cultural differences between this population and the population of interest in the proposed study, these findings underscore the need to actively involve patients' families and support networks in treatment protocols to the maximum extent possible.

Finally, a systematic review by Kalali and Richerson (2016) found that the most common reason for nonadherence to medication regimens is that patients simply forget to take their medication. Other identified reasons included:

Beyond these factors, there are significant emotional barriers to medication adherence that have been largely ignored or minimized in the research to date. Emotional barriers may include (1) a sense of losing control, (2) self-stigmatization, (3) denial, (4) poor insight, and (5) beliefs about illness and medications (Kalali & Richerson, 2016). Additional patient variables that contribute to nonadherence include suboptimal health literacy, stigma and shame about the need for treatment, and lack of patient involvement in treatment decision-making (Kalali & Richerson, 2016, p. 26).

It is important to note that adherence to medication regimens is not the sole domain of patients — it is also a function of healthcare providers and the healthcare system in which they practice (Kalali & Richerson, 2016). Active involvement on the part of healthcare providers can significantly enhance adherence levels. Many strategies used to date, such as reminder telephone calls and additional clinic visits, can be expensive and difficult to sustain given scarce organizational resources (Kalali & Richerson, 2016). Nevertheless, given the high costs associated with nonadherence, even these alternatives may be viewed as cost-effective over the long term. Innovative technological solutions hold particular promise for achieving improved adherence levels while simultaneously reducing costs to healthcare providers.

References

Atibioke, O. P., & Isinowo, H. O. (2015, September 1). Psychological determinants of treatment adherence among people living with HIV and AIDS in Ibadan, Nigeria. Ife Psychologia, 23(2), 89–91.

Burnett, A. (2013, April). From our readers: ABC's of evidence-based practice. American Nurse Today, 8(4), 37–39.

Cairns, A., & Hill, C. (2013, March). The Large Allen Cognitive Level Screen as an indicator for medication adherence among adults accessing community mental health services. British Journal of Occupational Therapy, 76(3), 137–140.

Clinical research. (2017). AiCure. Retrieved from

Estrada, L., & Dupoux, E. (2006, March). The relationship between locus of control and personal-emotional adjustment and social adjustment to college life in students with and without learning disabilities. College Student Journal, 40(1), 43–47.

Grove, S. K., Burns, N., & Gray, J. (2013). The practice of nursing research: Appraisal, synthesis, and generation of evidence (7th ed.). Retrieved from digitalbookshelf.southuniversity.edu.

Kalali, A., & Richerson, S. (2016, April). Technology offers tools for ensuring adherence to medical therapy. Current Psychiatry, 15(4), 24–27.

Kaptanglu, A. F., & Suer, K. (2014, March). Knowledge, attitudes and behaviour towards sexually transmitted diseases in Turkish Cypriot adolescents. Central European Journal of Public Health, 21(1), 54–57.

Leichliter, J. S., & Copen, C. (2017, March 10). Confidentiality issues and use of sexually transmitted disease services among sexually experienced persons aged 15–25 years — United States, 2013–2015. Morbidity and Mortality Weekly Report, 66(9), 237–241.

Levesque, A., & Li, H. Z. (2012, June). Factors related to patients' adherence to medication and lifestyle change recommendations: Data from Canada. International Journal of Psychological Studies, 4(2), 42–45.

Melnyk, B. M., & Fineout-Overholt, E. (2015). Evidence-based practice in nursing & healthcare (3rd ed.). Retrieved from https://digitalbookshelf.southuniversity.edu.

Neuman, W. L. (2009). Social research methods: Qualitative and quantitative approaches. New York: Allyn & Bacon.

Noblit, G. W., & Hare, R. D. (1988). Meta-ethnography: Synthesizing qualitative studies. Newbury Park, CA: Sage Publications.

Owusu-Edusei, K., & Chesson, H. W. (2013, March). The estimated direct medical cost of selected sexually transmitted infections in the United States, 2008. Sexually Transmitted Diseases, 40(3), 197–201.

Rahman, A., & Applebaum, R. (2012, Spring). What's all this about evidence-based practice? The roots, the controversies, and why it matters. Generations, 34(1), 6–11.

Reed, D., & Reed, D. D. (2012, Summer). Towards an understanding of evidence-based practice. The Journal of Early and Intensive Behavioral Intervention, 5(2), 20–24.

Reported STDs in the United States. (2015). U.S. Centers for Disease Control. Retrieved from https://www.cdc.gov/nchhstp/newsroom/docs/factsheets/std-trends-508.pdf.

Rotter, J. B. (1954). Social learning and clinical psychology. New York: Prentice-Hall.

Timiun, G. A. (2012, June). Sexual webs model for the examination of unsafe sexual behaviors and the spread of sexually transmitted diseases including HIV/AIDS. Asian Social Science, 8(7), 119–123.

Why AiCure? (2017). AiCure. Retrieved from https://aicure.com/.

Wittek, R., & Snijders, T. A. (2013). The handbook of rational choice social research. Stanford, CA: Stanford University Press.

Appendix: Evaluation and Synthesis Tables

Leichliter & Copen (2017) | Conceptual Framework: None | Design/Method: Retrospective analysis | Sample & Setting: National Survey of Family Growth; 10,205 respondents; 69.3% response rate | Major Variables: Receipt of sexual risk assessment in the past 12 months (defined as a provider asking about sexual orientation, number of partners, condom use, and type of sex); receipt of other STD services (chlamydia testing for females; STD testing for males; STD treatment for both) | Measurement: Percentages of 15–24-year-olds | Data Analysis: Frequency percentiles | Findings: A significantly higher percentage of youths aged 15–17 years (22.6%) said they would not seek sexual and reproductive health services due to confidentiality concerns than did those aged 20–22 years (8.2%) and 23–25 years | Appraisal: Level IV — Case-control or cohort study

Cairns & Hill (2013) | Conceptual Framework: None | Design/Method: Preliminary investigation of the association between the LACLS and medication adherence at a single assessment point | Sample & Setting: Convenience sample of 11 adults taking oral medication primarily as their own responsibility | Major Variables: Medication support type; LACLS scores | Measurement: Medication Adherence Rating Scale (MARS) | Data Analysis: Spearman rank-order correlation coefficients; scatterplot with line of best fit (STATA IC) | Findings: A significant, strong positive association between the LACLS and MARS was evident even in this small sample | Appraisal: Level III — Controlled trial without randomization

Levesque & Li (2012) | Conceptual Framework: Adherence conceptualized as a relative concept existing along a continuum | Design/Method: Correlational | Sample & Setting: 298 participants (296 included in analysis); ages 18–74, mean age 36 years; 54% women, 46% men | Major Variables: Adherence to medications (single item, past behavior); adherence to lifestyle changes (single item); barriers to adherence; physician communication | Measurement: 5-point scale (1 = never, 5 = always) | Data Analysis: T-tests and correlational analyses | Findings: Adherence and age showed a U-shaped relationship; poor self-perceived health predicted lower lifestyle adherence; barriers (weather, transportation, cost) negatively affected adherence; physician information and patient trust improved adherence | Appraisal: Level IV — Case-control or cohort study

Atibioke & Osinowo (2015) | Conceptual Framework: None | Design/Method: Cross-sectional survey | Sample & Setting: 548 adults and children with HIV/AIDS undergoing antiretroviral therapy in a Nigerian program | Major Variables: Independent: perceived stigma and discrimination, perceived social support, self-efficacy, depression and anxiety, age, sex, marital status. Dependent: treatment adherence | Measurement: Frequency percentiles | Data Analysis: Simple percentage, frequency distribution, and chi-square | Findings: Perceived stigmatization and discrimination did not affect adherence; adequate social support networks were associated with significantly higher adherence | Appraisal: Level IV — Case-control or cohort study

Kalali & Richerson (2016) | Conceptual Framework: None | Design/Method: Systematic review | Sample & Setting: Studies concerning nonadherence to medication regimens (36 peer-reviewed studies) | Major Variables: Common reasons for nonadherence | Measurement: Qualitative assessment | Data Analysis: Synthesis | Findings: Direct and indirect methods of evaluating adherence are flawed in various ways, but innovative technological solutions can provide the data needed to develop relevant EBPs | Appraisal: Level I — Systematic review or meta-analysis

Evidence Level Summary:

Intervention Descriptions:

Study Outcomes: