Abstract
Background
Adolescents and young adults often lack appropriate healthcare transition preparation, a concern amplified by prevalent mental health issues. Our study aimed to assess the relationship between transition readiness and behavioral health screening across multiple domains in adolescents within a primary care medical home.
Methods
We conducted a retrospective cohort study (October 2021-December 2024) for new, preventive and follow-up visits where patients (ages 14–25 years) completed validated depression, transition readiness screening, Transition Readiness Assessment Questionnaire (TRAQ) and the Patient Questionnaire-9 (PHQ-9). Nonparametric median tests for continuous variables and chi-squared tests for categorical variables assessed for differences for patient age, race/ethnicity, legal sex, and insurance type. Linear and linear logistic regression was also performed.
Results
Patients (median 17.0 years; 62.8 % female; Hispanic 44.9 %; public insurance 62.2 %) completed the TRAQ and PHQ-9 for 3010 visits. Patients with PHQ-9 > 10 were more likely to be female, non-Hispanic White at follow up visits with private insurance; p < 0.001. There was no significant relationship between PHQ-9 and TRAQ scores. Linear regression showed significance for age at visit, legal sex (female), non-Hispanic White, visit type (follow up); p < 0.001 and English language (p = 0.017); logistic regression showed significance for age at visit, legal sex (female), non-Hispanic white, follow up visits (p < 0.001)
Conclusions
Age, legal sex, race/ethnicity, and insurance status significantly influence transition readiness among AYA. While positive depression screens do not show a direct association with transition readiness, depression may still affect health factors that indirectly shape readiness for transition.
Keywords: Patient questionnaire-9 (PHQ-9), Transition readiness assessment questionnaire (TRAQ), Health care transition (HCT)
Highlights
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Patients with PHQ-9 were more likely to be female, non-Hispanic White and have private insurance compared to those with negative PHQ-9 screens.
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Being older, female, non-Hispanic White, speaking English, private insurance coming for a follow-up visit were related to positive TRAQ items.
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Positive depression screens are not directly correlated to lower TRAQ scores emphasizing role of other factors in the transition process.
1. Introduction
Previous work in healthcare transition has largely focused on adolescents and young adults (AYA) with special health care needs as individuals with chronic illness often have multiple touchpoints in the healthcare realm and require intensified focus on self-management, support teams, and checklists to navigate the transition process1, 2. While transition work has typically focused on individuals with certain chronic conditions including sickle cell disease and asthma, there is a need for all individuals to go through the healthcare transition process in preparation for adulthood and confidence going to adult health models of care3, 4. Such preparation is required in promoting both independence and self-efficacy within the healthcare community. Without thoughtful transitions to adult care, all AYA, not just those with chronic conditions or special health care needs, are more at risk for medical complications, disruptions in continuity of care, medication adherence, preventable hospital, and emergency department use, and decreased overall health and wellbeing5.
Despite established guidelines including Got Transition®, AYA with and without special health care needs are receiving appropriate health care transitions (HCT) < 20 % of the time6, 7. Providers cite lack of training, lack of communication between adolescent and adult providers, and lack of resources on transition5. In contrast, patients report wanting to be prepared to implement a care plan, to be cared for by medical providers, and to have accountability from the health care system8.
Adolescence is a time of growth and change, and while most adolescents adapt well, others are susceptible to mental health concerns including depression. The mental health needs of adolescents are often overwhelming, and the burden increased during the years of the COVID-19 pandemic with 20–30 % of adolescents experiencing some type of mental or behavioral health issue9. Screening for depression is recommended at least annually10 with validated tools such as the Pediatric Health Questionnaire-9 (PHQ-9)11.
Struggles with mental health can have a profound effect on daily life and overall health with effects on self-concept, self-efficacy, maintaining healthy relationships and performing simple daily tasks12, 13. Individuals may also struggle with the ability to make plans and consider future parts of their lives. These hindrances become relevant as adolescents work toward adulthood in their general life but also as they navigate the healthcare system.
There have been a handful of studies focused on transitions to adult mental health care providers and lack of HCT for AYA suffering with mental health disorders to date there have been no studies assessing overall HCT readiness in a primary care medical home with additional evaluation of individuals suffering with mental health concerns14, 15. The aim of our study is to assess the relationship between behavioral health screening and transition readiness across multiple domains in adolescents within a primary care medical home. We hypothesize that patients with an elevated PHQ-9 will have lower TRAQ scores and subsequently lower transition readiness for adult health care models.
2. Methods
2.1. Design
This study is a retrospective cohort study performed in an adolescent primary care clinic (October 2021-December 2024) to assess patients who completed the Patient Health Questionnaire-9 (PHQ-9) and the validated 20-item Transition Readiness Assessment Questionnaire (TRAQ). The clinic is in a suburban setting neighboring a large metro area with two-thirds of patients/families having public insurance. Questionnaires are completed on tablets that integrate with the clinic electronic health record (EHR). The screen is completed at every clinic visit.
2.2. Participants and setting
All patient visits (ages 14–25 years) for new patient, established preventive, and follow-up to the Adolescent Medicine primary care clinic were included in the study as AYA often do not have annual preventive visits. The clinic serves as a medical home for primary care patients and offers an integrated behavioral health team. The TRAQ is assigned beginning at age 14 years, so younger patients were excluded. Sick visits were excluded as the TRAQ is not completed at these visit types. The clinic is run by adolescent medicine specialists with pediatrics residents and adolescent medicine fellows. The clinic has an established transition medicine program including a full-time program manager who meets with patients during and between visits regarding individual transition items and overall transition readiness.
2.3. Data collection
Data was collected for patients (ages 14–25 years) seen in the Adolescent Medicine Clinic at CHCO from October 2021-December 2024. Patients who completed the PHQ-9 and TRAQ at non-acute primary care visits (establish care/well visits, follow-up) were included. In addition to visit type, patient age, race, ethnicity, gender, and insurance type were collected for each patient encounter. Patients may have attended more than one visit during the study period, thus we selected one visit per patient by first eliminating visits where the TRAQ and PHQ-9 were incomplete (<3 % of all included visits) and then for remaining visits, we randomly selected one visit per person using RANDOM.ORG, a true random number service that generates randomness via atmospheric noise (Randomness and Integrity Services Ltd. Dublin, Ireland; www.random.org).
During visit check-in, all patients receive a tablet to complete clinic questionnaires including the PHQ-9 and TRAQ. Patient scores for the PHQ-9 and TRAQ were integrated into the clinic EHR (EPIC© electronic health record product; (Epic Corporation, Madison, WI).
All patient identifiers were removed, and a REDCap (Research Electronic Data Capture) database was created for safe and confidential storage of all data located on the password protected computer of the primary investigator16. The study was approved by the Colorado Multiple Institutional Review Board with exempt status.
2.4. Outcome measure(s)
The primary outcome measure is to determine the association(s) of positive depression screening on transition readiness outcomes. Secondary outcomes include effects of patient age, race, ethnicity, gender, language spoken, insurance status and visit type on depression screening and transition readiness.
2.5. Data analysis
Data collected were evaluated for total sample size of patient visits during the assessment period (October 2021-December 2024) and for PHQ-9 and TRAQ completion. Data was analyzed for any significant differences using nonparametric median tests for continuous variables and chi-squared tests for (categorial variables) differences for patient age, race, ethnicity, legal sex, and insurance type. Race and ethnicity were self-reported by patient and/or family. All Statistical analyses were performed using IBM SPSS Version 28.0. Logistic and linear regression were conducted to examine the associations. Because of the large number of comparisons, applying a Bonferroni correction translates to interpreting statistical significance with p < 0.00117.
2.6. TRAQ
TRAQ questions are grouped into subscales: managing medications, keeping appointments, managing health issues, and communicating with providers (‘no’ for ‘do not know how/want to learn/am learning to do’; ‘yes’ for ‘have started/always do.’ Managing medications includes 5 questions: explain medications, fill medications, reorder medications, report medication reactions, and speak to a pharmacist; appointments includes 3 questions: make appointments, keep appointments, arrange rides to appointments; health history includes 6 questions: explain health history, explain medication history, make medical decisions, report unusual health changes, follow up on lab results/referrals; communication includes 6 questions: explain how feel, answer staff questions, ask staff questions, ask for explanations from staff, attend appointments by self, contact the office if have concerns.
2.7. PHQ-9
For the PHQ-9, a score of ≥5 is a positive screen for mild depression, with a score of ≥10 considered at least moderate depression; the latter is often used when deciding to consider treatment (medication/therapy)18. Question 9 for the PHQ-9 “Thoughts that you would be better off dead or of hurting yourself in some way in the past 2 weeks” is considered positive with a value of > 1. If one or more questions on a PHQ-9 questionnaire were missing, a PHQ-9 score of 0–1 was scored as negative as the score could not be > 4; a PHQ-9 score of 2–4 was deleted as the score could be less or greater than 5.
3. Results
From October 2021-December 2024, there were 18,346 clinic visits for patients 14–25 years old; 3010 patients filled out both the PHQ-9 and the TRAQ questionnaire at 5654 visits {median visits per patient = 1 (range 1–15)}. Patients (median age 17.0 years; Hispanic 44.9 %; public insurance 62.2 %; 62.8 % female; English as preferred language 85.0 %) were seen for follow up (48 %), preventive (25.1 %), and new visits (26.8 %); Table 1. The median score on the PHQ-9 for all patients was a 3, consistent with a negative screen. Patients (43.8 %) with a PHQ-9 > 5 were statistically similar to patients with negative screens. Patients (20.6 %) with a PHQ-9 > 10 were more likely to seek care at follow up visits (56.2 % v. 45.9 %), be female (76.7 % v. 59.2 %), non-Hispanic White (40.4 % v. 20.9 %), and have private insurance (38.5 % v. 31.1 %); all significant p < 0.001 compared to patients with PHQ-9 < 10. Patients with a PHQ-9 > 10 were more likely to have positive question 9 answers regarding feelings of being better off dead compared to those with PHQ-9 < 10 (36.8 % v. 2.0 %); p < 0.001.
Table 1.
Demographics for patient visits (n = 3010) who completed both PHQ9 and TRAQ.
| Variable | Total N = 3010 or median (range) |
PHQ-9 < 10 n = 2389; 79.4 % % or median (range) |
PHQ-9 ≥ 10 n = 621; 20.6 % % or median (range) |
p-value |
|---|---|---|---|---|
| LEGAL SEX Female Male |
62.8 % 37.2 % |
59.2 % 40.8 % |
76.7 % 23.2 % |
< 0.001 |
| Age (years) | 17.0(14–25) | 17(14–25) | 16.9(14–24) | 0.42 |
| RACE/ETHNICITY Hispanic Non-Hispanic: White Black Asian Mixed Heritage Other Unknown American Indian/Alaskan Native Native Hawaiian/Pacific Islander |
44.9 % 25.0 % 19.3 % 2.6 % 3.0 % 2.8 % 1.7 % 0.4 % 0.3 % |
47.0 % 20.9 % 20.7 % 2.7 % 3.1 % 3.0 % 1.7 % 0.4 % 0.4 % |
36.7 % 40.4 % 14.0 % 2.1 % 2.6 % 1.9 % 1.8 % 0.5 % 0 % |
< 0.001 |
| ETHNICITY Hispanic Non-Hispanic Unknown |
44.9 % 53.5 % 1.6 % |
47.0 % 51.2 % 1.7 % |
36.7 % 62.0 % 1.3 % |
< 0.001 |
| LANGUAGE English Spanish Other |
85.0 % 13.2 % 1.8 % |
83.5 % 14.6 % 2.0 % |
91.0 % 8.1 % 1.0 % |
< 0.001 |
| INSURANCE Public Private Tricare Indigent Self-Pay |
62.2 % 32.6 % 2.2 % 2.0 % 1.0 % |
64.0 % 31.1 % 1.9 % 2.1 % 0.9 % |
55.1 % 38.5 % 3.4 % 1.6 % 1.4 % |
< 0.001 |
| VISIT TYPE Follow Up New Patient Well Visit |
48.0 % 26.8 % 25.1 % |
45.9 % 26.5 % 27.7 % |
56.2 % 28.3 % 15.5 % |
< 0.001 |
| PHQ−9 total score | 3(0−27) | 2(0−9) | 14(10–27) | < 0.001 |
| PHQ−9 ≥ 5 | 43.7 % | 28.1 % | 100 % | < 0.001 |
| PHQ−9 item 9 positive (≥1) | 9.2 % | 2.0 % | 36.8 % | < 0.001 |
Patients reported starting transition readiness tasks at various levels and were > 50 % positive (always do/started to do) for all items 60.5 % of the time; Table 2. The medication domain had the lowest transition readiness items with > 50 % positive items for less than half of all patients (44.3 %). In contrast, nearly 80 % of patients had ‘yes’ scores for > 50 % positive items in the Communication domain. There were no significant differences between patients with a PHQ-9 > 10 and PHQ-9 < 10 for total TRAQ scores or for TRAQ subscales. The health subscale was trending toward significance for patients with PHQ-9 > 10; these patients had higher transition readiness than those with lower depression screening scores (68.3 % v. 61.7 %; p = 0.002).
Table 2.
Transition readiness and comparisons for positive and negative depression screening.
| TRAQ Subscales and Total | Total N = 3010 or median (range) |
PHQ-9 < 10 n = 2389; 79.4 % % or median (range) |
PHQ-9 ≥ 10 n = 621; 20.6 % % or median (range) |
p-value |
|---|---|---|---|---|
| Medications (% of 5 items positive) |
40.0 % (0 – 100 %) | 40.0 % (0–100 %) | 40.0 % (0–100 %) | 0.25 |
| Medications (≥50 % positive) |
44.3 % | 43.6 % | 46.7 % | 0.17 |
| Appointments (% of 3 items positive) |
66.7 % (0–100 %) | 60.0 % (0–100 %) | 66.7 % (0–100 %) | 0.33 |
| Appointments (≥50 % positive) |
61.8 % | 61.3 % | 63.3 % | 0.47 |
| Health (% of 6 items positive) |
83.3 % (0–100 %) | 83.3 % (0–100 %) | 83.3 % (0–100 %) | 0.93 |
| Health (≥50 % positive) | 63.0 % | 61.7 % | 68.3 % | 0.002 |
| Communication (% of 6 items positive) |
83.3 % (0–100 %) | 83.3 % (0–100 %) | 83.3 % (0–100 %) | 0.24 |
| Communication (≥50 % positive) |
79.9 % | 79.9 % | 80.1 % | 0.92 |
| All items (% of 20 items positive) |
63.6 % (0–100 %) | 59.2 % (0–100 %) | 65.0 % (0–100 %) | 0.047 |
| All items (≥50 % positive) | 60.5 % | 59.6 % | 63.8 % | 0.059 |
A linear regression was performed to identify factors associated with the average number of positive TRAQ items including age at visit, legal sex (female), race/ethnicity (non-Hispanic White), English language, visit type (follow up), private insurance, and positive PHQ-9 > 10. Significant variables were age at visit, legal sex (female), race/ethnicity (non-Hispanic White), and visit type (follow up) (all p < 0.001), and English language (p = 0.017); Table 3. A logistic regression was also performed to identify independent predictors of > 50 % TRAQ items positive with significant variables age at visit, legal sex (female), race/ethnicity non-Hispanic White and visit type (follow up); all p < 0.001.
Table 3.
Linear and logisitic regression for TRAQ > 50 % for all items.
| LINEAR REGRESSION for average number of positive TRAQ items | ||
|---|---|---|
| VARIABLES | p | β (95 % CI) |
| AGE AT VISIT | 0.001 | 0.050 (0.046, 0.055) |
| LEGAL SEX (FEMALE) | 0.001 | 0.112 (0.090, 0.134) |
| RACE/ETHNICITY (NON-Hispanic WHITE) | 0.001 | 0.078 (0.052, 0.104) |
| VISIT TYPE (FOLLOW UP) | 0.001 | 0.079 (0.057, 0.100) |
| LANGUAGE (ENGLISH) | 0.017 | 0.037 (0.007, 0.068) |
| INSURANCE CONTRACT (PRIVATE) | 0.130 | 0.018 (−0.005, 0.042) |
| POSTIVE PHQ9 > 10 | 0.701 | −0.005 (−0.032, 0.021) |
| LOGISTIC REGRESSION for ≥ 50 % TRAQ items positive | ||
| VARIABLES | p | ADJUSTED ODDS RATIO (95 % CI) |
| AGE AT VISIT | 0.001 | 1.422 (1.363, 1.483) |
| LEGAL SEX (FEMALE) | 0.001 | 2.051 (1.740, 2.417) |
| RACE/ETHNICITY (NON-Hispanic WHITE) | 0.001 | 1.779 (1.470, 2.152) |
| VISIT TYPE (FOLLOW UP) | 0.001 | 1.623 (1.380, 1.910) |
| LANGUAGE (ENGLISH) | 0.192 | 1.162 (0.928, 1.455) |
| INSURANCE (PRIVATE) | 0.334 | 1.093 (0.913, 1.309) |
| PHQ−9 > 10 | 0.809 | 0.975 (0.796, 1.195) |
4. Discussion
4.1. Mental health and transition
In our study, female, non-Hispanic white patients presenting for follow up visits with private insurance and English as their preferred language had higher rates of depression screening. Like previous studies, female patients had higher scores on depression screening. This is unsurprising given that female patients undergo puberty at an earlier rate than boys and the differential in female>male depression is seen by early adolescence. There are numerous proposed factors including reaction to stressful life events and bullying victimization19.
Our study also showed the highest rates of positive depression screening for non-Hispanic white patients with English as the preferred language. The exact reason for this finding is uncertain as past studies have shown that the PHQ-9 measures a common concept of depression for multiple racial and ethnic groups20. Important considerations include culture norms and stigma, differences in access to care, and levels of understanding of resources with consideration for social determinants of health21. Patients with private insurance presenting for follow up visits also had higher positive screening rates which is consistent with prior findings emphasizing individuals with private insurance are more likely to have an established primary care provider with regular visits22.
Higher transition readiness on the TRAQ was more likely for patients at follow-up visits who were older, female, Non-Hispanic White, and spoke English (Table 3). As adolescents continue development, it is expected they learn more transition readiness skills. Similarly, female AYA present for health care visits more often than male counterparts23. Patients present to clinic most often for follow up visits compared to preventive care, so this result is unsurprising. As individuals historically known to have fewer barriers for utilizing healthcare systems, non-Hispanic white and English-speaking patients had higher TRAQ scores. Notable is the lack of a significant relationship between higher total positive TRAQ scores and PHQ-9 scores. Health subscale items were trending toward significance (p = 0.002) for > 50 % of items on the TRAQ. These results are consistent with potentially more contact with the healthcare system and understanding chronic conditions.
In prior studies focusing on individuals with chronic health conditions, patient TRAQ scores exhibited low transition readiness across multiple domains despite frequent visits and communication with their healthcare teams24. When comparing individuals with both chronic health conditions and mental health comorbidities, patients with mental health comorbidities had higher overall median TRAQ scores compared to their peers without behavioral health concerns25. In our study, patients with a PHQ-9 > 10 had a TRAQ > 50 % positive for all items (63.8 %), but the PHQ-9 > 10 was not a significant variable in the regression models which emphasized other patient traits appear to play a key role for transition readiness.
Adolescents and young adults (AYA) face many complex, interrelated factors that shape their readiness to transition from pediatric to adult health care. While our study did not find an association between positive depression screening and transition readiness, we did observe associations with other demographic factors. These findings highlight that transition readiness is influenced by a nuanced interplay of individual, social, and structural factors beyond mental health alone including AYA personal knowledge and emotional readiness, family involvement, pediatric and adult provider roles, health system supports, and broader social context5, 26. Even without a direct correlation in our sample, it remains critically important to prioritize both depression screening and transition readiness in clinical practice, as addressing mental health needs and preparing youth for adult-oriented care are both essential components of comprehensive adolescent health care. The presence of depression and other mood disorders may affect other aspects of AYA well-being that subsequently lowers transition readiness.
4.2. Limitations
This study does have limitations, including the focus on one clinical setting that specifically cares for AYA with adolescent medicine certified providers. Although not fully generalizable to other populations, the concepts relating to provision of best care are translatable. The study was also a retrospective review, which did not allow for direct patient interaction or patient-specific data and can identify associations, but not causation. Depression screeners capture a snapshot in time of an individual’s mental health, and do not fully reflect all the potential factors that could affect an existing behavioral health diagnosis, nor do they allow for distinction of newly positive v. established positive screeners. Studies have shown that a patient with major depression is six times more likely than a patient without major depression to have a PHQ-9 score of > 9 and thirteen times more likely to have a score of 15 or higher18. The TRAQ also gives a snapshot of transition readiness, but actual transition outcomes may differ from the individuals’ perceptions and further work is necessary to assess possible association(s)27. The self-report nature of both the TRAQ and PHQ-is also a limitation which emphasizes the need for medical, behavioral health, and transition team members to work together in the primary care setting for discussion and shared-decision making with AYA.
5. Conclusion
Adolescents and young adults face a complex set of challenges in achieving transition readiness as they move from pediatric to adult health care, requiring attention not only to their self-management skills but also to their overall health and well-being. Further considerations include change in transition readiness over time with attention to differences by age and sex, impact of social determinants, and the relationship between perceived transition readiness and actual transition outcomes with transfer to adult care. Future research should continue to place adolescents and young adults at the forefront by exploring these factors in greater depth to inform tailored, equitable strategies that support successful transitions and promote positive long-term outcomes.
Cost of participation
There is no cost of participation for subjects.
Funding
The project was funded by Medicaid Upper Payment Limit Dollars, Section of Adolescent Medicine, University of Colorado School of Medicine. Study data were collected and managed using REDCap electronic data capture tools hosted at the University of Colorado School of Medicine supported by NIH/NCATS Colorado CTSA Grant Number UL1 TR002535.
Ethical Statement
All co-authors verify that neither this manuscript nor parts of it have been published previously. It is not under consideration for publication elsewhere. The article's publication is approved by all authors and if accepted, the article will not be published elsewhere in the same form, in English or in any other language, including electronically without the written consent of the copyright-holder.
CRediT authorship contribution statement
Sheeder Jeanelle: Writing – review & editing, Software, Investigation, Formal analysis, Conceptualization. Bogart Amanda: Writing – review & editing, Software, Resources, Project administration, Investigation, Conceptualization. Catherine Clark: Writing – review & editing, Resources, Project administration, Methodology, Investigation, Data curation, Conceptualization. Batt Courtney: Writing – review & editing, Writing – original draft, Resources, Project administration, Investigation, Conceptualization. Woods Jennifer: Writing – review & editing, Writing – original draft, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization.
Declaration of Competing interest
The authors declare that we have no financial interests or personal relationships that could be perceived as a conflict of interest regarding the subject matter of this research. We are not currently employed by or have any consulting agreements with any companies that may be impacted by the findings of this study.
Data availability
The data that has been used is confidential.
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The data that has been used is confidential.