15 Oct Depression Screening in Adolescent Primary Care: Evidence Synthesis

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Depression Screening in Adolescent Primary Care: Evidence Synthesis

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Depression Screening in Adolescent Primary Care: Evidence Synthesis

Adolescent depression stands as a pressing national practice problem in the United States, profoundly impacting the physical, emotional, and social well-being of young individuals during a critical developmental phase. Providers have a role in addressing this issue using evidence-based solutions to improve the primary care unit by detecting and responding to it early. The two articles reviewed in the paper are quantitative research: a descriptive study by Davis et al. (2022) on screening rates and risk factors in a large pediatric network and a correlational longitudinal cohort study by Riehm et al. (2022) on post-screening diagnoses and treatment adherence among adolescents. The purpose of this paper is to analyze the practice problem, summarize evidence based on these quantitative studies, evaluate the relevance or applicability of the evidence, and provide a summary of the key lessons that should be learned to inform advanced practice. Comment by Author: The assignment requirements are met for the introduction section.

Analysis of the Practice Problem

The significance of adolescent depression as a national practice problem cannot be overstated, given its far-reaching effects on individual health trajectories and broader societal costs. Untreated depression in adolescence is associated with impaired academic performance, disrupted peer and family relationships, increased substance abuse, and heightened risk of chronic mental health disorders into adulthood. Additionally, it is one of the foremost causes of suicide; it is the third leading cause of death among adolescents, and more than half of those who die by suicide had a history of depression. In terms of health care, the condition contributes to significant resource consumption, such as emergency care and hospitalization, adding to health care costs estimated in the billions every year in the U.S. Socioeconomic inequalities also make the problem worse, because low-income teenagers are at greater risk because they have few resources and because they experience more stressors. Primary care practices, where most adolescents obtain routine health care, would be a perfect place of intervention, but screening inconsistencies impede changes, and it is essential to improve the intervention based on evidence to avoid morbidity in the long term.

Prevalence and incidence data underscore the epidemic scale of adolescent depression in the U.S. and globally. In the United States, approximately 20.1% of adolescents aged 12 to 17—equating to 5.0 million individuals—experienced at least one major depressive episode in the past year. Recent data from 2021–2023 indicate a 13.1% prevalence of depression symptoms in the past two weeks among those aged 12 and older. Incidence has surged, with rates of clinically diagnosed depression increasing by about 60% over recent years, and overall depression rates rising from 8.1% in 2009 to 15.8% in 2019. Globally, the World Health Organization reports depression prevalence at 1.3% among adolescents aged 10–14 and 3.4% among those aged 15–19, with one in seven 10–19-year-olds experiencing a mental disorder overall. In 2021, an estimated 57 million adolescents worldwide had depression, highlighting a global burden that mirrors and informs U.S. trends. These figures, drawn from the selected articles and authoritative sources like the Centers for Disease Control and Prevention and WHO, emphasize the urgent need for robust screening in primary care to address this growing crisis. Comment by Author: This is important data to support the prevalence and incidence of the practice problem. In-text citations are needed to inform the reader of the origin of this important data. Please return to course resources (Prepare; Explore) located in the week 5 content. Also, view the Let's Check-In: Tips for Success (Week 5) recording located in Course Announcements. These resources have examples of each section of the paper. Writing strong content and supporting them with in-text citations is demonstrated in the week 5 course lesson resources. Before submitting the week 7 paper, return to the course resources and construct sentences where they are supported with the WHO iand CDC in-text citations.

Evidence Synthesis Comment by Author: Please return to the instructions for this section of this written assignment. ———————————— Evidence Synthesis: 2-3 paragraphs. Include the following:  a Using the two quantitative (descriptive or correlational) articles, write a synthesis of evidence to address the selected practice problem. b Do not use the non-research evidence here in the synthesis.  c Identify the main themes and salient evidence that emerge from the two articles. (Cited)  d Compare and contrast the main points from your two articles. (Cited)  e Present an objective synthesis of research evidence about the practice problem. (Cited)  f This synthesis must be a summary of the merged themes and findings of the two articles and cannot be a review of each article separately. (Cited)  ———————————— You need to rewrite this section as you write the week 7 written assignment. Rely on the course resources mentioned in my guidance. There are examples in the course resources to guide you shift your writing style from summarizing a single source to synthesizing across your appraised research studies.

Routine depression screening in adolescent primary care facilitates earlier identification of at-risk youth but reveals persistent disparities in implementation and limited translation to treatment. The evidence synthesizes around themes of screening accessibility, sociodemographic influences on risk and uptake, and post-screening clinical outcomes. Davis et al. (2022) conducted a descriptive analysis of 82,531 adolescents across 122,682 well-visits in a U.S. pediatric network, finding an overall screening rate of 81.48% using the Patient Health Questionnaire-Modified for Teens (PHQ-9-M). Positive screens for depression symptoms occurred in 5.92% of cases, and for suicidality in 7.19%, with higher risks among females, older adolescents (15–17 years), Black and Hispanic/Latino youth, urban residents, and those with Medicaid insurance. Riehm et al. (2022), in a correlational longitudinal cohort study of 57,732 adolescents using insurance claims data, reported that screened individuals were 30% more likely to receive a depression diagnosis (risk ratio [RR] = 1.30) and 17% more likely a mood-related diagnosis (RR = 1.17) within six months, with effects more pronounced in females.

Comparing the studies, both underscore gender and socioeconomic disparities, yet differ in focus and methodology. Davis et al. (2022) emphasize descriptive patterns in screening completion, noting higher odds among females (odds ratio [OR] = 1.05), younger adolescents (12–14 years; OR = 1.17), White and Hispanic/Latino groups, and Medicaid-insured patients, while highlighting barriers like electronic health record inconsistencies. In contrast, Riehm et al. (2022) employ propensity score matching to explore correlations, revealing no significant increase in treatments such as antidepressants (RR = 1.04) or psychotherapy (RR = 1.01) post-screening, suggesting a disconnect between detection and intervention. Where Davis provides a snapshot of who gets screened and at risk, Riehm extends this to outcomes, showing stronger diagnostic associations in females (RR = 1.40 for depression) but overall modest treatment uptake. These findings collectively point to systemic gaps, such as resource limitations in follow-up care, that advanced practitioners must address.

An objective synthesis of the research evidence indicates that while screening enhances diagnostic yield, its effectiveness is moderated by implementation inequities and post-screening support structures. Merged themes reveal that universal screening protocols, when adopted, identify vulnerable subgroups, particularly females and minorities, but fail to consistently lead to therapeutic engagement, potentially due to stigma, provider time constraints, or access barriers. This integrated view supports the adoption of targeted enhancements, like integrated behavioral health services in primary care, to close the detection-to-treatment loop and reduce the overall burden of adolescent depression.

Appraisal of the Evidence to Address the Practice Problem Comment by Author: Requirements are met for this section of the paper.

The evidence from Davis et al. (2022) and Riehm et al. (2022) is applicable to describing and addressing the practice problem of adolescent depression screening in primary care, offering practical insights from large, representative U.S. samples. The descriptive design by Davis et al. (2022) effectively outlines the variability of screening disparities and positive screen prevalence, helping advanced practitioners to design interventions based on high-risk populations such as Medicaid-insured youth, but is not without limitations due to single-system data and using electronic records. The correlational approach adopted by Riehm et al. (2022), which provides powerful statistical controls, demonstrates the diagnostic benefits of screening but indicates treatment discontinuities, which are informative in the development of the overall care pathways. The two good quality (B) Level III studies in both their methodology and relevance will have generalizable outcomes, despite the scope and follow-up limitation, to support evidence-based changes in primary care.

Conclusion Comment by Author: Requirements are met for the conclusion section of the paper.

Finally, adolescent depression is a national practice concern that has been characterized by the growing rates of prevalence and disastrous outcomes and must be screened during primary care. Evidence synthesis of two quantitative studies reveals the value of screening in detection under disparities and treatment gaps, and appraisal confirms the value of screening in enhancing advanced practice. These understandings can inform policies to maximize early intervention and outcomes.

References Comment by Author: Requirements are met for the references list.

Centers for Disease Control and Prevention. (2025). Depression prevalence in adolescents and adults. https://www.cdc.gov/nchs/products/databriefs/db527.htm

Davis, M., Siegel, J., Sullivan, U. M., Nicholson, J. M., & Hinton, T. E. (2022). Adolescent depression screening in primary care: Who is screened and who is at risk? Journal of Affective Disorders, 299, 318-325. https://doi.org/10.1016/j.jad.2021.12.022

Doan, T. T., Penfold, R. B., Anderson, T. S., Hye, A., & Rane, M. S. (2023). Preferences and experiences of pediatricians on implementing national guidelines on universal routine screening of adolescents for major depressive disorder: A qualitative study. General Hospital Psychiatry, 85, 62-70. https://doi.org/10.1016/j.comppsych.2023.152412

National Institute of Mental Health. (n.d.). Major depression. https://www.nimh.nih.gov/health/statistics/major-depression

Riehm, K. E., Braden, J. B., Chi, W., Stuart, E. A., Tom, S. E., Ong, M. K., Varghese, M., & Mojtabai, R. (2022). Diagnoses and treatment after depression screening in primary care among youth. American Journal of Preventive Medicine, 62(4), 511-518. https://doi.org/10.1016/j.amepre.2021.09.008

World Health Organization. (2025). Mental health of adolescents. https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health

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Johns Hopkins Individual Evidence Summary Tool

	EBP Project Practice Question:
Reviewer Name(s)	Article Number	Author, Date, and Title	Type of Evidence	Population, size, and setting	Intervention	Findings that help answer the EBP question	Measures used	Limitations	Evidence level & quality	Notes to Team
	EXAMPLE 1	EXAMPLE Michaud, T.L., Siahpush, M., Schwab, R. J., Eiland, L. A., DeVany, M., Hansen, G., Slachetka, T. S., Boilesen, E., Tak, H. J., Wilson, F. A., Wang, H., Pagán, J. A., & Su, D. (2018). Remote patient monitoring and clinical outcomes for post-discharge patients with type 2 diabetes. Population Health Management, 21(5), 387–394. https://doi.org/10.1089/pop.2017.0175 Permalink https://chamberlain.primo.exlibrisgroup.com/permalink/01CUCON_INST/f6kb8f/cdi_proquest_miscellaneous_2019041682	EXAMPLE Quantitative research with a retrospective, observational design.	EXAMPLE Sample/size = 955 patients 19 years of age and older with T2D that were discharged from the inpatient setting within 30 days Sample Size = 955 Setting = Nebraska	EXAMPLE This study looked at the effects of utilizing a remote patient monitoring system on the health outcomes of patients with T2D.	EXAMPLE After the study, 69% of those who began the study with an HbA1c of >9% ended the study with an HbA1c of ≤9%. Similarly, from baseline to the end of the study, patients’ mean weight had decreased from 225lb to 222lb, and mean BMI had decreased from 35.59 to 35.23. Patient activation scores rose from 63.37 at baseline to 69.17 at the end of the study.	EXAMPLE The researchers measured HbA1c, weight, BMI, BP, and patient activation scores.	EXAMPLE One limitation is inconsistent devices used, as some patients could use their glucometer rather than the one provided in the study. Other limitations include that there was no expectation to complete measurements on the weekends.	EXAMPLE Level III, Quality C

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Johns Hopkins Evidence-Based Practice Model for Nursing and Healthcare Professionals

Individual Evidence Summary Tool

Appendix G

Johns Hopkins Nursing Evidence-Based Practice

Individual Evidence Summary Tool (Appendix G)

EBP Question:
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