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Purpose: Individuals diagnosed with cancer between 15 and 39 years (adolescent and young adult [AYA]) face unique vulnerability. Detail is lacking about care delivery for these patients, especially those with ALL. We address these knowledge gaps by describing AYA ALL care delivery details at National Cancer Institute Community Oncology Research Program (NCORP) (sub)affiliates by model of care., Methods: Participating institutions treated at least one AYA with ALL from 2012 to 2016. Study-specific criteria were used to determine the number of unique clinical facilities (CFs) per NCORP and their model of care (adult/internal medicine [IM], pediatric, mixed [both]). Surveys completed by NCORPs for each CF by model of care captured size, resources, services, and communication., Results: Among 84 participating CFs (adult/IM, n=47; pediatric, n=15; mixed, n=24), 34% treated 5-10 AYAs with ALL annually; adult/IM CFs more often treated <5 (adult/IM, 60%; pediatric, 40%; mixed, 29%). Referral decisions were commonly driven by an age/diagnosis combination (58%), with frequent ALL-specific age minimums (87%) or maximums (80%). Medical, navigational, and social work services were similar across models while psychology was available at more pediatric CFs (pediatric, 80%; adult/IM, 40%; mixed, 46%-54%). More pediatric or mixed CFs reported oncologists interacting with pediatric/adult counterparts via tumor boards (pediatric, 93%; adult/IM, 26%; mixed, 96%) or initiating contact (pediatric, 100%; adult/IM, 77%; mixed 96%); more pediatric CFs reported an affiliated counterpart (pediatric, 53%; adult, 19%). Most CFs reported no AYA-specific resources (79%) or meetings (83%-98%)., Conclusion: System-level aspects of AYA ALL care delivery have not been examined previously. At NCORPs, these characteristics differ by models of care. Additional work is ongoing to investigate the impact of these facility-level factors on guideline-concordant care in this population. Together, these findings can inform a system-level intervention for diverse practice settings.

Objective: The Pediatric Psychosocial Preventative Health Model (PPPHM) is a three-tier model of family psychosocial risk used to guide intervention approaches in pediatric healthcare settings. Screening all families to determine levels of risk supports equitable care. We review evidence from papers using the Psychosocial Assessment Tool (PAT), a brief caregiver-report measure of family psychosocial risk with scores that map to the PPPHM, to characterize the distribution of risk. We predict that across study samples the distribution of risk on the PPPHM will be approximately 60% universal (low), 30% targeted (moderate), and 10% clinical (high)., Method: We conducted a scoping review searching PubMed, MEDLINE, Emcare, and PsycInfo for articles that reported PPPHM data using the PAT., Results: Forty-seven samples from 43 papers were included, reporting on patients with 17 conditions. PPPHM scores were highly consistent with median percentages of 55% universal, 34% targeted, and 11% clinical. There is evidence of higher levels of risk for samples using the Spanish version of the PAT, from weight management programs and with families who have children with autism spectrum disorder., Conclusions: The data demonstrate consistent patterns of psychosocial risk distributions on the PPPHM and support implementation of universal family psychosocial risk screening, followed by delivery of personalized care based on level of risk. Screening all families promotes health equity in pediatric health care settings by normalizing the importance of understanding psychosocial risk and resiliencies and assuring family input in the delivery of integrated psychosocial care. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Introduction: The use of commercially available automatic speech recognition (ASR) software is challenged when dysarthria accompanies a physical disability. To overcome this issue, a mobile and personal speech assistant (mPASS) platform was developed, using a speaker-dependent ASR software., Objective: The aim of this study was to evaluate the performance of the proposed platform and to compare mPASS recognition accuracy to a commercial speaker-independent ASR software. In addition, secondary aims were to investigate the relationship between severity of dysarthria and accuracy and to explore people with dysarthria perceptions on the proposed platform., Methods: Fifteen individuals with dysarthric speech and 20 individuals with nondysarthric speech recorded 24 words and 5 sentences in a clinical environment. Differences in recognition accuracy between the two systems were evaluated. In addition, mPASS usability was assessed with a technology acceptance model (TAM) questionnaire., Results: In both groups, mean accuracy rates were significantly higher with mPASS compared to the commercial ASR for words and for sentences. mPASS reached good levels of usefulness and ease of use according to the TAM questionnaire., Conclusions: Practical applicability of this technology is realistic: the mPASS platform is accurate, and it could be easily used by individuals with dysarthria., (© 2020 S. Karger AG, Basel.)