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  • Opinion
  • Open Access

27 April 2024

Measurement-Based Care in Youth: An Opportunity for Better Clinical Outcomes?

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,
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and
1
Clínica de Neurociências e Saúde Mental, Hospital Cruz Vermelha, 1500-048 Lisboa, Portugal
2
Faculdade de Ciências Humanas, Universidade Católica Portuguesa, 1649-023 Lisboa, Portugal
*
Author to whom correspondence should be addressed.
Healthcare2024, 12(9), 910;https://doi.org/10.3390/healthcare12090910
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Abstract

Measurement-based care (MBC) is a procedure in which systematic and routine assessments are performed. Through this practice, clinicians can verify the progress of the symptomatology of the patient and adapt the appointments and the intervention to the current symptoms. Studies have reflected on the importance and the benefits of this type of procedure in the adult population, and have shown positive results. However, there is a lack of evidence concerning the remaining populations. Regarding youth, for instance, few articles have evaluated the benefits of using this procedure in clinical practice. However, research focused on this topic has revealed positive results, especially when clinicians were loyal to the MBC procedures. Still, further research is needed. This letter aims to share the methodology used by our multidisciplinary team, composed of psychologists and psychiatrists, in a clinical context at the Hospital Cruz Vermelha, Lisboa, applied to the adult population; the objective is to share and discuss some alterations that could be made to our evaluation protocol to enable the same to be used with the youth population. We believe that implementing MBC for youth is crucial for several reasons, including enhanced treatment efficacy, more personalized treatment, a reduced reliance on subjectivity, and empowerment not only of patients but also families.

1. Measurement-Based Care (MBC)

According to the American Psychological Association [1], Measurement-Based Care (MBC) is a systematic assessment performed during the therapeutic process. It provides a better understanding of mental disorders, collecting data about the symptoms at the time of assessment; namely, the severity, frequency, and impact on the functioning of the individual [2]. Additionally, MBC supports the procedure of engaging the patient in the decision-making process and in discussions about the overall treatment [1,3]. In general, this assessment is based on the patient’s self-report, considering their perspective on symptomatology and functioning [1,3]. This evidence-based practice has some key components, such as collecting data routinely, sharing the results with the patient, and acting in accordance with the data [1]. The benefits of using this clinical process have been well described in the literature; namely, improved response rates [4], decreased response time [5], decreased costs associated with the therapeutic process [6], higher levels of engagement [7], enhanced overall functionality [8,9], and increased quality of therapeutic alliance [10].
Moreover, the MBC has been shown to have transtheoretical and transdiagnostic relevance across clinical settings [2]. A recent theoretical review of MBC in psychiatry identified additional advantages of MBC when compared to the usual care, such as identification of the patients who are improving or deteriorating; improvement of role functioning, satisfaction with care, quality of care, and quality of life; communication between providers and patients; improvement of collaborative care efforts among providers; improvement of the accuracy of clinical judgment; enhanced individualized treatment; and the viability of implementing MBC on a large scale [11]. Besides the benefits, Aboraya and colleagues also listed some potential barriers, particularly related to the fact that the measures are time-consuming (the most commonly cited drawback by psychiatrists), ratings produced by the measures might not always be clinically relevant, and administering rating scales might interfere with establishing rapport with patients; additionally, there is the perception that the measures are not more useful than clinical assessment; the perception that MBC is over-systematizing and depersonalizing; the limited formal training (included in the top two barriers for residents and faculty); the lack of protocols and training manuals; the lack of consensus as to which instrument to use for a particular disorder; the absence of a requirement to use MBC—particularly since few work settings require MBC; the lack of incentives to use MBC; and the complexity of patients with multiple overlapping comorbidities.

2. The MBC Protocol Applied at the Hospital Cruz Vermelha

In the Clínica de Neurociências e Saúde Mental of Hospital Cruz Vermelha (Lisboa, Portugal) this practice is applied to adults (patients 18 years or older) who attend psychology or psychiatry appointments or who are forwarded from other hospital services.
Initially, a more extensive version of the protocol is applied (Time 0). The average application time has been one hour. This protocol includes self-report questionnaires, such as the Patient Health Questionnaire-9 (PHQ-9) [12,13] to assess the severity of depressive symptoms, the General Anxiety Disorder questionnaire (GAD-7) [14,15] to assess anxiety, the Center for Epidemiologic Studies Anxiety Scale (CESA) [16] to assess anxiety, the WHO Disability Assessment Schedule (WHODAS 2.0) [17,18] to assess patient functionality, the Sick-Control-One stone-Fat-Food (SCOFF) [19] to assess eating behavior, the DSM-5-TR Self-Rated Level 1 Cross-Cutting Symptom Measure—Adult [20] to assess somatic symptoms, psychotic symptoms, personality disorders, bipolar disorders, and obsessive-compulsive disorder, the Adult Self Report Scale (ASRS–V1.1) [21,22] to assess hyperactivity disorder and attention deficit, the Pittsburg Sleep Quality Index (PSQI-PT) [23,24] to assess the quality of sleep, and the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) [25,26] to assess the involvement of substance use. This protocol also includes questions that aim to evaluate symptomatology related to panic disorder, obsessive-compulsive disorder, post-traumatic stress disorder, mania, and personality traits. Other relevant information is collected during the clinical process, such as adherence to psychiatric pharmacological treatment (if applied) (questionnaire adapted [27]), presence of comorbidities of physical illnesses (questionnaire adapted [28]), family history of mental illness, and previous use of specialty psychology and/or psychiatry services. To complete the protocol, a screening of cognitive dysfunction is performed through a tablet utilizing the program THINC-IT [29,30]. In the case of severe difficulties, or if the patient is 65 years or older, this test is replaced by the Montreal Cognitive Assessment (MoCA) [31,32].
In order to automate the scoring and interpretation of the results, our team has developed a software tool, Psymap 1.1, which, based on the individual scoring results, automatically generates a clinical note for the patient’s electronic health records (EHRs) and an individualized visual report for patient education. This greatly contributes to engaging patients in discussions about treatment strategies and goals. The software tool also helps attenuate the burden of completing EHRs, thus optimizing appointment time, which leads to an increase in the response capacity of the mental health service.
The protocol is applied at the time of the first appointment. The Psymap software automatically scores the scales and presents the results of the clinician. This allows for including a broad collection of symptoms covering different areas of functioning, thus facilitating a differential diagnosis and the identification of possible comorbidities during the patient’s first visit without overburdening the mental health professional. At the time of each follow-up visit (Time 1 and subsequent), a shorter version of the protocol is applied, comprising the assessments that are more sensitive to change. This smaller questionnaire has an average application time of between 10 and 15 minutes and is usually completed by the patient in the waiting room. It is comprised of the Patient Health Questionnaire-9 (PHQ-9) [12,13], the General Anxiety Disorder questionnaire (GAD-7) [14,15], the Center for Epidemiologic Studies Anxiety Scale (CESA) [16], and the WHO Disability Assessment Schedule (WHODAS 2.0) [17,18]. Every six months, the full protocol is re-applied.

3. MBC in Youth

According to the National Survey of Children’s Health, 16.5% of youth suffer from at least one mental disorder [33]. The literature suggests that 11.2% of the youth population meets the criteria for mood disorders, 8.3% for anxiety disorders and 9.6% for behavioral disorders [34]. However, mental illness in youth largely remains untreated or unrecognized, leading to an increase in social exclusion, discrimination, and educational difficulties [35,36,37,38,39]. Therefore, it is extremely important to enhance the psychological assessments applied to this population. Thus, it could be important to use the same method applied to the adult population when applying an MBC protocol to youth; this could be done in different contexts such as schools, minimizing the potential impact on public health [40].
As in the other areas, the benefits of MBC are less studied in youth when compared to the adult population. However, there is a growing body of literature supporting its implementation in the youth population as well. According to Jensen-Doss and colleagues [41], the MCB assessment is well suited for working with youth. Both the Transdiagnostic Treatment of Emotional Disorders in Adolescents [42] and Parent–Child Interaction Therapy (PCIT) [43] resort to MBC to identify treatment goals and to review the progress of the patients. The randomized controlled trial performed by Bickman and colleagues [44], found benefits of MBC in a sample composed of youth participants, such as faster improvements, enhanced monitoring of the therapeutic relationship, and adjustment of the clinician’s approach according to the patient’s needs. Moreover, in a second randomized controlled trial, the results were only positive, when the clinicians were loyal to the MBC procedures [45].
The literature suggests that MBC in youth, when shared with stakeholders (such as developers, researchers, and consumers), optimizes the clinical outcomes through supported clinical decision-making [46]. It can also be applied to young patients as well as caregivers, supervisors, and administrators [47], and may be applied in different contexts, such as schools.
Thus, the evidence supports that MBC is useful in improving mental health outcomes in the youth population [40]. However, despite all the evidence in its favor, clinicians rarely engage in this practice [40] with an estimated adherence by mental health professionals of only 20% [6]. Table 1 summarizes some studies that support the use of MBC in clinical practices with the youth population.
Table 1. Summary of studies that support the use of MBC in clinical practice with youth.

4. MBC Protocol When Applied to a Youth Population

When developing a protocol for psychological assessment to be applied to a youth population, it is important to consider a variety of methods including interviews, psychometric tests, and observation; all these methods must be applied to the patient and, if justified, to significant figures such as caregivers or teachers [48]. It is also important to select short-form questionnaires, reducing fatigue levels and increasing the likelihood of adherence, whether by the person or by the informants [11].
All the questionnaires must be carefully selected, validated for the intended population (considering aspects like age and nationality), present good psychometric qualities, and be sensitive to change, enabling the systematic assessment [11].
Before starting the assessment, it is important to ensure that informed consent is obtained [49]; this must be provided by the patient or the legal guardians, depending on the age and the local laws. Moreover, and even when the informed consent form is signed by their legal guardians, it is of utmost importance to ask the child or adolescent if they want to participate. It is also important to clarify the limits of confidentiality [50].
During the psychological assessment, it is important to guarantee a sensitive and empathetic approach and a comfortable environment, with the use of appropriate language and avoiding technical nomenclature, granting the understanding and comprehension of the instructions and questions [51]. The active participation of the young patients must be encouraged by providing a safe place where they feel heard. To guarantee the security of the patients, it is extremely important to assess the safety risks (suicide risk, self-harm, abuse, or violence) [52].
When contemplating the results obtained, it is crucial to proceed with contextualization, considering the developmental norms for different age groups [53], and the cultural and ethnic differences that might influence the answers to the assessment [54]. It is also important to give feedback to the patient or other relevant figures who might be concerned, discuss the results, and provide post-assessment care, if necessary [1].
Along with these important considerations, there is a rising body of evidence supporting the implementation of MBC in youth mental health care [55]. Several articles have tried to discuss the possible components of the MBC protocol in youth. A systematic review and meta-analysis reviewed 12 studies and concluded that there were promising early findings to support MBC in the youth population [56]. In fact, the National Institute of Mental Health, in consultation with the Welcome Trust [57] and other funders of mental health research, acknowledged a minimum list of ideal instruments to use in mental health settings. For research participants younger than 18, they suggest assessing the age; the sex at birth; the mental health domains, using the DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure Parent/Guardian Report and the Youth Self Report [20]; and the levels of anxiety and low mood, using the Revised Children’s Anxiety and Depression Scale (RCADS-25) (both the Parent/Caregiver Report and the Youth Self Report) [58,59].

5. Conclusions

It is our understanding that implementing MBC in youth is vital for several reasons: it allows the enhancement of treatment efficacy, provides a more personalized and individualized treatment, reduces the reliance on subjectivity, and empowers not only patients but also their families.
As in other areas, the benefits of MBC are less studied in youth compared to the adult population. However, there is a growing body of literature supporting its implementation in the youth population as well. To sum up, we believe the alterations necessary to make it suitable for young individuals should consider:
  • Tailored Assessments for Youth:
    o
    Psychological assessments for youth should be tailored to their developmental stage and needs.
    o
    Consideration should be given to age-appropriate language and comprehension levels.
    o
    Use of short-form questionnaires to minimize fatigue and increase adherence.
    o
    Take into consideration the informed consent process and ensure the child or adolescent’s willingness to participate even if legal guardians provide consent.
    o
    Encourage active participation from young patients to ensure they feel heard and understood.
  • Consider Safety Assessment:
    o
    Assess safety risks including suicide risk, self-harm, abuse, or violence to ensure the well-being of the patient.
  • Contextualization of Results:
    o
    Contextualize assessment results considering developmental norms, cultural, and ethnic differences.
    o
    Provide feedback to the patient and discuss assessment results comprehensively.
    o
    Provide and offer post-assessment care if necessary.
Thus, and considering the aforementioned information, with this letter, we would like to increase the debate around the use of MBC and increase the discussion regarding the best questionnaires/assessment tools to be used in the youth population.

Author Contributions

Conceptualization, R.F.; methodology, R.F. and C.C.; software, R.F. and C.d.C.G.; validation, R.F., C.C., S.B., C.d.C.G. and A.V.-L.; formal analysis, R.F. and C.C.; investigation, R.F. and C.C.; resources, R.F. and C.C.; data curation, R.F. and C.C.; writing—original draft preparation, R.F. and C.C.; writing—review and editing, S.B., C.d.C.G. and A.V.-L.; visualization, R.F., C.C., S.B., C.d.C.G. and A.V.-L.; supervision, R.F.; project administration, R.F.; funding acquisition, R.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No new data was created.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. American Psychological Association. Measurement-Based Care. Available online: https://www.apaservices.org/practice/measurement-based-care (accessed on 7 November 2023).
  2. Scott, K.; Lewis, C.C. Using Measurement-Based Care to Enhance Any Treatment. Cogn. Behav. Pract. 2015, 22, 49–59. [Google Scholar] [CrossRef] [PubMed]
  3. Martin-Cook, K.; Palmer, L.; Thornton, L.; Rush, A.J.; Tamminga, C.A.; Ibrahim, H.M. Setting Measurement-Based Care in Motion: Practical Lessons in the Implementation and Integration of Measurement-Based Care in Psychiatry Clinical Practice. Neuropsychiatr. Dis. Treat. 2021, 17, 1621–1631. [Google Scholar] [CrossRef] [PubMed]
  4. Fortney, J.C.; Unützer, J.; Wrenn, G.; Pyne, J.M.; Smith, G.R.; Schoenbaum, M.; Harbin, H.T. A Tipping Point for Measurement-Based Care. Psychiatr. Serv. 2017, 68, 179–188. [Google Scholar] [CrossRef]
  5. de Jong, K.; Conijn, J.M.; Gallagher, R.A.; Reshetnikova, A.S.; Heij, M.; Lutz, M.C. Using progress feedback to improve outcomes and reduce drop-out, treatment duration, and deterioration: A multilevel meta-analysis. Clin. Psychol. Rev. 2021, 85, 102002. [Google Scholar] [CrossRef]
  6. Lewis, C.C.; Boyd, M.; Puspitasari, A.; Navarro, E.; Howard, J.; Kassab, H.; Hoffman, M.; Scott, K.; Lyon, A.; Douglas, S.; et al. Implementing Measurement-Based Care in Behavioral Health. JAMA Psychiatry 2019, 76, 324–335. [Google Scholar] [CrossRef] [PubMed]
  7. Moltu, C.; Veseth, M.; Stefansen, J.; Nøtnes, J.C.; Skjølberg, Å.; Binder, P.-E.; Castonguay, L.G.; Nordberg, S.S. This is what I need a clinical feedback system to do for me: A qualitative inquiry into therapists’ and patients’ perspectives. Psychother. Res. 2018, 28, 250–263. [Google Scholar] [CrossRef]
  8. Holliday, S.B.; Hepner, K.A.; Farmer, C.M.; Mahmud, A.; Kimerling, R.; Smith, B.N.; Rosen, C. Discussing measurement-based care with patients: An analysis of clinician-patient dyads. Psychother. Res. 2021, 31, 211–223. [Google Scholar] [CrossRef] [PubMed]
  9. Guo, T.; Xiang, Y.-T.; Xiao, L.; Hu, C.-Q.; Chiu, H.F.; Ungvari, G.S.; Correll, C.U.; Lai, K.Y.; Feng, L.; Geng, Y.; et al. Measurement-Based Care Versus Standard Care for Major Depression: A Randomized Controlled Trial With Blind Raters. Am. J. Psychiatry 2015, 172, 1004–1013. [Google Scholar] [CrossRef] [PubMed]
  10. Brattland, H.; Koksvik, J.M.; Burkeland, O.; Klöckner, C.A.; Lara-Cabrera, M.L.; Miller, S.D.; Wampold, B.; Ryum, T.; Iversen, V.C. Does the working alliance mediate the effect of routine outcome monitoring (ROM) and alliance feedback on psychotherapy outcomes? A secondary analysis from a randomized clinical trial. J. Couns. Psychol. 2019, 66, 234–246. [Google Scholar] [CrossRef]
  11. Aboraya, A.; Nasrallah, H.A.; Elswick, D.E.; Ahmed, E.; Estephan, N.; Aboraya, D.; Berzingi, S.; Chumbers, J.; Berzingi, S.; Justice, J.; et al. Measurement-based Care in Psychiatry-Past, Present, and Future. Innov. Clin. Neurosci. 2018, 15, 13–26. [Google Scholar]
  12. Kroenke, K.; Spitzer, R.L.; Williams, J.B. The PHQ-9: Validity of a brief depression severity measure. J. Gen. Intern. Med. 2001, 16, 606–613. [Google Scholar] [CrossRef] [PubMed]
  13. Monteiro, S.; Torres, A.; Pereira, A.; Albuquerque, E.; Morgadinho, R. 2077—Preliminary validation study of a portuguese version of the patient health questionnaire (PHQ-9). Eur. Psychiatry 2013, 28, 1. [Google Scholar] [CrossRef]
  14. Sousa, T.V.; Viveiros, V.; Chai, M.V.; Vicente, F.L.; Jesus, G.; Carnot, M.J.; Gordo, A.C.; Ferreira, P.L. Reliability and validity of the Portuguese version of the Generalized Anxiety Disorder (GAD-7) scale. Health Qual. Life Outcomes 2015, 13, 50. [Google Scholar] [CrossRef] [PubMed]
  15. Spitzer, R.L.; Kroenke, K.; Williams, J.B.W.; Löwe, B. A Brief Measure for Assessing Generalized Anxiety Disorder. Arch. Intern. Med. 2006, 166, 1092–1097. [Google Scholar] [CrossRef] [PubMed]
  16. Faro, A.; Eaton, W.W. A Diagnostic-Oriented Screening Scale for Anxiety Disorders: The Center for Epidemiologic Studies Anxiety Scale (CESA). Front. Psychol. 2020, 11, 957. [Google Scholar] [CrossRef]
  17. Castro, S.S.; Leite, C.; Osterbrock, C.; Santos, M.T.; Adery, R. Avaliação de Saúde e Deficiência: Manual do WHO Disability Assessment Schedule (WHODAS 2.0); Organização Mundial da Saúde: Geneva, Switzerland, 2015. [Google Scholar]
  18. Üstün, T.B. World Health Organization. Measuring Health and Disability: Manual for WHO Disability Assessment Schedule WHODAS 2.0; WHO: Geneva, Switzerland, 2010. [Google Scholar]
  19. Morgan, J.F.; Reid, F.; Lacey, J.H. The SCOFF questionnaire: Assessment of a new screening tool for eating disorders. BMJ 1999, 319, 1467–1468. [Google Scholar] [CrossRef]
  20. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders; American Psychiatric Association: Arlington, VA, USA, 2013. [Google Scholar] [CrossRef]
  21. Neves, M.R.; Ponte, A.; Rodrigues, A.; Jesus, G. Escala de Auto-Avaliação da Perturbação de Hiperatividade e Défice de Atenção para o Adulto-V1.1 (ASRS-V1.1); Organização Mundial da Saúde: Geneva, Switzerland, 2003. [Google Scholar]
  22. Kessler, R.C.; Adler, L.; Ames, M.; Demler, O.; Faraone, S.; Hiripi, E.; Howes, M.J.; Jin, R.; Secnik, K.; Spencer, T.; et al. The World Health Organization adult ADHD self-report scale (ASRS): A short screening scale for use in the general population. Psychol. Med. 2005, 35, 245–256. [Google Scholar] [CrossRef] [PubMed]
  23. Buysse, D.J.; Reynolds, C.F., III; Monk, T.H.; Berman, S.R.; Kupfer, D.J. The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Res. 1989, 28, 193–213. [Google Scholar] [CrossRef]
  24. João, K.A.D.R.; Becker, N.B.; Jesus, S.d.N.; Martins, R.I.S. Validation of the Portuguese version of the Pittsburgh Sleep Quality Index (PSQI-PT). Psychiatry Res. 2017, 247, 225–229. [Google Scholar] [CrossRef]
  25. Mostardinha, A.R.; Bártolo, A.; Bonifácio, J.; Pereira, A. Validação do The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) em Estudantes Universitários. Acta Medica Port. 2019, 32, 279–288. [Google Scholar] [CrossRef]
  26. WHO ASSIST Working Group. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): Development, reliability and feasibility. Addiction 2002, 97, 1183–1194. [Google Scholar] [CrossRef] [PubMed]
  27. Wisniewski, S.R.; Rush, A.J.; Balasubramani, G.K.; Trivedi, M.H.; Nierenberg, A.A. Self-Rated Global Measure of the Frequency, Intensity, and Burden of Side Effects. J. Psychiatr. Pract. 2006, 12, 71–79. [Google Scholar] [CrossRef]
  28. Sangha, O.; Stucki, G.; Liang, M.H.; Fossel, A.H.; Katz, J.N. The self-administered comorbidity questionnaire: A new method to assess comorbidity for clinical and health services research. Arthritis Care Res. 2003, 49, 156–163. [Google Scholar] [CrossRef] [PubMed]
  29. Baune, B.T.; Malhi, G.S.; Morris, G.; Outhred, T.; Hamilton, A.; Das, P.; Bassett, D.; Berk, M.; Boyce, P.; Lyndon, B.; et al. Cognition in depression: Can we THINC-it better? J. Affect. Disord. 2018, 225, 559–562. [Google Scholar] [CrossRef] [PubMed]
  30. McIntyre, R.S.; Best, M.W.; Bowie, C.R.; Carmona, N.E.; Cha, D.S.; Lee, Y.; Subramaniapillai, M.; Mansur, R.B.; Barry, H.; Baune, B.T.; et al. The THINC-Integrated Tool (THINC-it) Screening Assessment for Cognitive Dysfunction. Br. J. Psychol. 2017, 78, 873–881. [Google Scholar] [CrossRef] [PubMed]
  31. Freitas, S.; Simões, M.R.; Martins, C.; Vilar, M.; Santana, I. Estudos de adaptação do Montreal Cognitive Assessment (MoCA) para a população portuguesa. Avaliação Psicológica 2010, 9, 345–357. [Google Scholar]
  32. Nasreddine, Z.S.; Phillips, N.A.; Bédirian, V.; Charbonneau, S.; Whitehead, V.; Collin, I.; Cummings, J.L.; Chertkow, H. The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment. J. Am. Geriatr. Soc. 2005, 53, 695–699. [Google Scholar] [CrossRef]
  33. Whitney, D.G.; Peterson, M.D. US National and State-Level Prevalence of Mental Health Disorders and Disparities of Mental Health Care Use in Children. JAMA Pediatr. 2019, 173, 389–391. [Google Scholar] [CrossRef] [PubMed]
  34. youth.gov. Prevalence of Mental Health Disorders Among Youth. Available online: https://youth.gov/youth-topics/prevalence-mental-health-disorders-among-youth (accessed on 1 February 2024).
  35. Asarnow, L.D.; Mirchandaney, R. Sleep and Mood Disorders Among Youth. Child Adolesc. Psychiatr. Clin. N. Am. 2021, 30, 251–268. [Google Scholar] [CrossRef]
  36. Długosz, P. Mental Health Disorders among Students from Rural Areas Three Months after Returning to School: A Cross-Sectional Study among Polish Students. Youth 2022, 2, 271–278. [Google Scholar] [CrossRef]
  37. Koutra, K.; Pantelaiou, V.; Mavroeides, G. Why Don’t Young People Seek Help for Mental Illness? A Cross-Sectional Study in Greece. Youth 2023, 3, 157–169. [Google Scholar] [CrossRef]
  38. Franzoi, I.G.; Sauta, M.D.; Barbagli, F.; Avalle, C.; Granieri, A. Psychological Interventions for Higher Education Students in Europe: A Systematic Literature Review. Youth 2022, 2, 236–257. [Google Scholar] [CrossRef]
  39. WHO. Mental Health of Adolescents; WHO: Geneva, Switzerland, 2021. [Google Scholar]
  40. Lyon, A.R.; Pullmann, M.D.; Whitaker, K.; Ludwig, K.; Wasse, J.K.; McCauley, E. A Digital Feedback System to Support Implementation of Measurement-Based Care by School-Based Mental Health Clinicians. J. Clin. Child Adolesc. Psychol. 2019, 48, S168–S179. [Google Scholar] [CrossRef] [PubMed]
  41. Jensen-Doss, A.; Douglas, S.; Phillips, D.A.; Gencdur, O.; Zalman, A.; Gomez, N.E. Measurement-based Care as a Practice Improvement Tool: Clinical and Organizational Applications in Youth Mental Health. Evid.-Based Pract. Child Adolesc. Ment. Health 2020, 5, 233–250. [Google Scholar] [CrossRef] [PubMed]
  42. Ehrenreich-May, J.; Kennedy, S.M.; Sherman, J.A.; Bilek, E.L.; Buzzella, B.A.; Bennett, S.M.; Barlow, D.H. Unified Protocols for Transdiagnostic Treatment of Emotional Disorders in Children and Adolescents: Therapist Guide; Oxford University Press: Oxford, UK, 2017. [Google Scholar]
  43. Eyberg, S.M.; Funderburg, B. Parent–Child Interaction Therapy Protocol; PCIT International: Orlando, FL, USA, 2011. [Google Scholar]
  44. Bickman, L.; Kelley, S.D.; Breda, C.; de Andrade, A.R.; Riemer, M. Effects of Routine Feedback to Clinicians on Mental Health Outcomes of Youths: Results of a Randomized Trial. Psychiatr. Serv. 2011, 62, 1423–1429. [Google Scholar] [CrossRef] [PubMed]
  45. Bickman, L.; Douglas, S.R.; De Andrade, A.R.V.; Tomlinson, M.; Gleacher, A.; Olin, S.; Hoagwood, K. Implementing a Measurement Feedback System: A Tale of Two Sites. Adm. Policy Ment. Health Ment. Health Serv. Res. 2016, 43, 410–425. [Google Scholar] [CrossRef] [PubMed]
  46. Lyon, A.R.; Lewis, C.C.; Boyd, M.R.; Hendrix, E.; Liu, F. Capabilities and Characteristics of Digital Measurement Feedback Systems: Results from a Comprehensive Review. Adm. Policy Ment. Health Ment. Health Serv. Res. 2016, 43, 441–466. [Google Scholar] [CrossRef] [PubMed]
  47. McLeod, B.D.; Jensen-Doss, A.; Lyon, A.R.; Douglas, S.; Beidas, R.S. To Utility and Beyond! Specifying and Advancing the Utility of Measurement-Based Care for Youth. J. Clin. Child Adolesc. Psychol. 2022, 51, 375–388. [Google Scholar] [CrossRef]
  48. Alexander, L.A.; McKnight, P.E.; Disabato, D.J.; Kashdan, T.B. When and How to use Multiple Informants to Improve Clinical Assessments. J. Psychopathol. Behav. Assess. 2017, 39, 669–679. [Google Scholar] [CrossRef]
  49. Johnsongreene, D. Informed consent in clinical neuropsychology practice: Official statement of the National Academy of Neuropsychology. Arch. Clin. Neuropsychol. 2005, 20, 335–340. [Google Scholar] [CrossRef]
  50. Darby, W.C.; Weinstock, R. The Limits of Confidentiality: Informed Consent and Psychotherapy. Focus 2018, 16, 395–401. [Google Scholar] [CrossRef] [PubMed]
  51. Sharma, E.; Srinath, S.; Jacob, P.; Gautam, A. Clinical practice guidelines for assessment of children and adolescents. Indian J. Psychiatry 2019, 61, 158–175. [Google Scholar] [CrossRef]
  52. Royal College of Psychiatrists. Rethinking Risk to Others in Mental Health Services; Royal College of Psychiatrists: London: UK, 2016. [Google Scholar]
  53. Reyes, V.P.; Krishnamurthy, R.; Puente, A.E. Age as Diversity in Psychological Assessment. In Diversity-Sensitive Personality Assessment; Routledge: London, UK, 2018; pp. 203–219. [Google Scholar] [CrossRef]
  54. Smith, J.D. Introduction to the Special Section on Cultural Considerations in Collaborative and Therapeutic Assessment. J. Pers. Assess. 2016, 98, 563–566. [Google Scholar] [CrossRef] [PubMed]
  55. Parikh, A.; Fristad, M.A.; Axelson, D.; Krishna, R. Evidence Base for Measurement-Based Care in Child and Adolescent Psychiatry. Child Adolesc. Psychiatr. Clin. N. Am. 2020, 29, 587–599. [Google Scholar] [CrossRef] [PubMed]
  56. Tam, H.; Ronan, K. The application of a feedback-informed approach in psychological service with youth: Systematic review and meta-analysis. Clin. Psychol. Rev. 2017, 55, 41–55. [Google Scholar] [CrossRef] [PubMed]
  57. National Institute of Mental Health. Data Archive. NIMH Data Archive—NDA Home Page. Available online: https://nda.nih.gov/ (accessed on 17 April 2024).
  58. Chorpita, B.F.; Yim, L.; Moffitt, C.; Umemoto, L.A.; Francis, S.E. Assessment of symptoms of DSM-IV anxiety and depression in children: A revised child anxiety and depression scale. Behav. Res. Ther. 2000, 38, 835–855. [Google Scholar] [CrossRef]
  59. Chorpita, B.F.; Moffitt, C.E.; Gray, J. Psychometric properties of the Revised Child Anxiety and Depression Scale in a clinical sample. Behav. Res. Ther. 2005, 43, 309–322. [Google Scholar] [CrossRef]
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Hazard Flagging as a Risk Mitigation Strategy for Violence against Emergency Medical Services
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