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Background: The Dixon-Woods et al. Candidacy Framework, a valuable tool since its 2006 introduction, has been widely utilized to analyze access to various services in diverse contexts, including healthcare. This social constructionist approach examines micro, meso, and macro influences on access, offering concrete explanations for access challenges rooted in socially patterned influences. This study employed the Candidacy Framework to explore the experiences of individuals living with rheumatoid arthritis (RA) and their formal care providers. The investigation extended to assessing supports and innovations in RA diagnosis and management, particularly in primary care. Methods: This systematic review is a Critical Interpretive Synthesis (CIS) of qualitative and mixed methods literature. The CIS aimed to generate theory from identified constructs across the reviewed literature. The study found alignment between the seven dimensions of the Candidacy Framework and key themes emerging from the data. Notably absent from the framework was an eighth dimension, identified as the "embodied relational self." This dimension, central to the model, prompted the proposal of a revised framework specific to healthcare for chronic conditions. Results: The CIS revealed that the eight dimensions, including the embodied relational self, provided a comprehensive understanding of the experiences and perspectives of individuals with RA and their care providers. The proposed Candidacy 2.0 (Chronic Condition (CC)) model demonstrated how integrating approaches like Intersectionality, concordance, and recursivity enhanced the framework when the embodied self was central. Conclusions: The study concludes that while the original Candidacy Framework serves as a robust foundation, a revised version, Candidacy 2.0 (CC), is warranted for chronic conditions. The addition of the embodied relational self dimension enriches the model, accommodating the complexities of accessing healthcare for chronic conditions. Trial Registration: This study did not involve a health care intervention on human participants, and as such, trial registration is not applicable. However, our review is registered with the Open Science Framework at https://doi.org/10.17605/OSF.IO/ASX5C. [ABSTRACT FROM AUTHOR]

To inform future learning opportunities, we performed a scoping review to identify competencies relevant to physical activity (PA) specialists in supporting the PA and mental health of people experiencing mental health concerns. CINAHL, PsycINFO, and SPORTDiscus databases were searched up to June 22, 2022, for research studies and commentaries. Pertinent text was extracted and subject to content analysis using an inductive approach. Sixty-two competencies from 62 publications were organized into four domains: (a) interacting with mental health care services/systems, (b) responding to mental health concerns, (c) employing PA counseling/coaching to promote mental health among people with diverse mental health needs, and (d) building relationships that are responsive to diverse mental health needs. These findings may serve as a road map for stakeholders interested in developing PA specialists' confidence to meet the challenges of navigating mental health contexts. Despite consistency across sources, points of divergence warrant consideration from learning institutions and professional bodies. [ABSTRACT FROM AUTHOR]

Background: Children's exposure to toxic stress (e.g., parental depression, violence, poverty) predicts developmental and physical health problems resulting in health care system burden. Supporting parents to develop parenting skills can buffer the effects of toxic stress, leading to healthier outcomes for those children. Parenting interventions that focus on promoting parental reflective function (RF), i.e., parents' capacity for insight into their child's and their own thoughts, feelings, and mental states, may understand help reduce societal health inequities stemming from childhood stress exposures. The Attachment and Child Health (ATTACHTM) program has been implemented and tested in seven rapid-cycling pilot studies (n = 64) and found to significantly improve parents' RF in the domains of attachment, parenting quality, immune function, and children's cognitive and motor development. The purpose of the study is to conduct an effectiveness-implementation hybrid (EIH) Type II study of ATTACHTM to assess its impacts in naturalistic, real-world settings delivered by community agencies rather than researchers under more controlled conditions.Methods: The study is comprised of a quantitative pre/post-test quasi-experimental evaluation of the ATTACHTM program, and a qualitative examination of implementation feasibility using thematic analysis via Normalization Process Theory (NPT). We will work with 100 families and their children (birth to 36-months-old). Study outcomes include: the Parent Child Interaction Teaching Scale to assess parent-child interaction; the Parental Reflective Function and Reflective Function Questionnaires to assess RF; and the Ages and Stages Questionnaire - 3rd edition to examine child development, all administered pre-, post-, and 3-month-delayed post-assessment. Blood samples will be collected pre- and post- assessment to assess immune biomarkers. Further, we will conduct one-on-one interviews with study participants, health and social service providers, and administrators (total n = 60) from each collaborating agency, using NPT to explore perceptions and experiences of intervention uptake, the fidelity assessment tool and e-learning training as well as the benefits, barriers, and challenges to ATTACHTM implementation.Discussion: The proposed study will assess effectiveness and implementation to help understand the delivery of ATTACHTM in community agencies.Trial Registration: Name of registry: https://clinicaltrials.gov/.Registration Number: NCT04853888 . Date of registration: April 22, 2021. [ABSTRACT FROM AUTHOR]

Background: The dementias are long-term, chronic conditions caused by progressive neurological degeneration. Current literature suggests that cardiovascular disease risk factors may contribute to the onset of dementia; however, evidence of these associations is inconsistent.Objectives: This study aimed to examine the impact of risk factors on dementia onset in older adults diagnosed and managed in Canadian primary care settings.Methods: A retrospective cohort study was employed utilizing electronic medical records data in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). Patients aged 65+ years with no dementia diagnosis at baseline who were followed from 2009 to 2017 with a run-in year to exclude existing undiagnosed dementia cases. Multivariate Cox proportional hazard models were used to estimate risk.Results: Age was associated with an increased incidence risk of dementia in both examined age groups: 65-79 years (13%) and 80+ years (5%). History of depression increased dementia risk by 38% and 34% in the age groups. There were significant associations with lower social deprivation area quintile, smoking history, osteoarthritis, and diabetes mellitus in patients aged 65-79 years but not in those aged 80+ years. Sex, hypertension, obesity, dyslipidemia, and the use of antihypertensive medications and statins were not associated with risk of incident dementia diagnosis.Conclusions: The association between chronic health conditions and dementia onset is complicated. Primary care electronic medical record data might be useful for research in this topic, though follow-up time is still relatively short to observe a clear causal relationship. Future studies with more complete data may provide evidence for dementia preventive strategies within primary care practice. [ABSTRACT FROM AUTHOR]

Background: Most antibiotics dispensed by community pharmacies in Canada are prescribed by family physicians, but using the prescribing information contained within primary care electronic medical records (EMRs) for secondary purposes can be challenging owing to variable data quality. We used antibiotic medications as an exemplar to validate a machine-learning approach for cleaning and coding medication data in a pan-Canadian primary care EMR database., Methods: The Canadian Primary Care Sentinel Surveillance Network database contained an estimated 42 million medication records, which we mapped to an Anatomic Therapeutic Chemical (ATC) code by applying a semisupervised classification model developed using reference standard labels derived from the Health Canada Drug Product Database. We validated the resulting ATC codes in a subset of antibiotic records (16 119 unique strings) to determine whether the algorithm correctly classified the medication according to manual review of the original medication record., Results: In the antibiotic subset, the algorithm showed high validity (sensitivity 99.5%, specificity 92.4%, positive predictive value 98.6%, negative predictive value 97.0%) in classifying whether the medication was an antibiotic., Interpretation: Our machine-learning algorithm classified unstructured antibiotic medication data from primary care with a high degree of accuracy. Access to cleaned EMR data can support important secondary uses, including community-based antibiotic prescribing surveillance and practice improvement., Competing Interests: Competing interests: None declared., (© 2023 CMA Impact Inc. or its licensors.)