The study, led by Sara A. Flores, Rachelle Brick, and Sallie J. Weaver of the National Cancer Institute’s Healthcare Delivery Research Program, together with Michelle Doose of the institute’s Behavioral Research Program, examined a unique natural experiment. Following the release of the standards, the NCI funded 18 supplemental research projects across the country with a twofold mission: to assess how well existing survivorship services and programs aligned with the new standards, and to identify the barriers and facilitators that shape implementation. Because each project team independently developed its own approach to measuring alignment, the resulting portfolio offered researchers an unprecedented window into how the field actually operationalizes the standards when left to its own devices.

To make sense of this diversity, the research team conducted a systematic synthesis of the measurement tools used across the funded projects. Trained abstractors applied a standardized codebook to extract detailed characteristics at both the project level and the measure level, including which specific national standards were assessed, what types of data were collected, which methods were used, and who the respondents were. Fourteen of the 18 projects ultimately contributed materials to the analysis, yielding a total of 91 distinct measurement tools spanning surveys, interview protocols, environmental scan protocols, and variables drawn from electronic health records and administrative data.

The first striking finding concerns which parts of the standards attracted the most measurement attention. The 2024 National Standards are organized into three domains: policy, processes, and evaluation and assessment. When the researchers categorized the 91 tools, they found that the overwhelming majority, 82.4 percent, addressed the health system process standards, which describe how survivorship care should actually be delivered to patients. By contrast, only 31.9 percent of tools addressed health system policy standards, which concern the organizational structures and commitments that underpin survivorship programs, and a mere 15.4 percent addressed the evaluation and assessment standards, which call on systems to monitor and improve their own performance.

This imbalance matters because the three domains are conceptually interdependent. Policy standards create the institutional scaffolding, such as leadership support and dedicated resources, that allows process standards to be implemented sustainably. Evaluation standards, in turn, generate the feedback loops that tell a health system whether its processes are working and for whom. A measurement landscape dominated by process checks risks producing a skewed picture of alignment, one in which a cancer center might appear to be delivering survivorship services while lacking the governance and self-assessment infrastructure to sustain or improve them. The authors suggest that this pattern likely reflects both the relative concreteness of process standards and the practical difficulty of writing tools for abstract organizational commitments.

The second major finding concerns the depth of measurement rather than its breadth. When the team classified what each tool actually captured, they found that 72.5 percent assessed the existence or occurrence of care elements, essentially yes-or-no questions about whether something happens. Does the program have a survivorship care plan? Was a referral made? Did a visit occur? Far less commonly captured was the quality or degree to which a standard was met, or how care processes actually unfolded in practice. This distinction is fundamental to quality measurement. Knowing that a service exists says nothing about whether it is timely, appropriate, equitable, or responsive to patient needs, and the study’s findings suggest that the field’s current toolkit is far better at detecting presence than at judging performance.

The methodological diversity documented in the study is itself informative. The 91 tools ranged from validated patient-reported outcome instruments to bespoke interview guides and electronic health record queries, reflecting the absence of any shared, ready-made measurement approach at the time the standards were released. This kind of grassroots innovation is valuable, but it comes at a cost: without common operational definitions, findings from one health system cannot be directly compared with those from another, and the field cannot aggregate local insights into a national picture of survivorship care quality. The problem echoes well-documented challenges in hospital accreditation research, where measuring the effects of complex, system-level interventions has proven notoriously difficult, and in quality measurement more broadly, where misalignment across state and regional measure sets has long hampered comparison.

The study’s implications reach beyond survivorship care into the broader science of implementation. Implementation researchers have long argued that strong measurement infrastructure is a prerequisite for learning health systems, in which care delivery continuously improves through the systematic collection and use of data. The NCI supplement portfolio demonstrates both the promise and the peril of funding implementation pilots ahead of measurement standardization. On one hand, the projects generated a rich, ground-level understanding of how diverse cancer care delivery settings interpret the standards and what barriers they face. On the other hand, the heterogeneity of the resulting tools means that synthesizing those insights requires exactly the kind of labor-intensive coding exercise this study performed, and some information may resist aggregation altogether.

The authors point toward several concrete opportunities for strengthening the measurement foundation. Chief among them is the development of shared operational definitions for each standard, phrased concretely enough to be applied consistently across settings that range from large academic cancer centers to community oncology practices. Such definitions would need to accommodate legitimate variation in how survivorship care is organized while preserving the core intent of each recommendation. The team also highlights the value of measures that move beyond existence checks toward assessments of quality and fidelity, drawing on established frameworks for evaluating health care quality and on growing experience with electronic clinical data standards that make process measurement more feasible at scale.

For the growing community of cancer survivors and the clinicians who care for them, the stakes of this seemingly technical work are substantial. Survivorship care encompasses surveillance for recurrence, management of late and long-term treatment effects, attention to psychosocial wellbeing, and coordination among many providers, often over decades. Standards that exist only on paper cannot close the well-documented gaps in how this care is delivered, and gaps that cannot be measured cannot be systematically addressed. By mapping how the first wave of implementation projects measured alignment with the 2024 National Standards for Survivorship Care, this study provides the field with an honest self-portrait: a committed and creative research community that has, so far, been measuring the easiest things most often. The path forward, the authors argue, lies in building the shared measurement infrastructure that will let every cancer care setting see clearly where it stands, and where it needs to go, in serving the millions of Americans who live beyond a cancer diagnosis.

Subject of Research: Measurement of alignment with the 2024 National Standards for Cancer Survivorship Care across NCI-funded implementation projects

Article Title: Measuring uptake of the 2024 national standards for survivorship care: Insights from National Cancer Institute funded pilot projects

Article References: Flores, S. A., Doose, M., Brick, R., & Weaver, S. J. (2026). Measuring uptake of the 2024 national standards for survivorship care: Insights from National Cancer Institute funded pilot projects. Journal of Cancer Survivorship. https://doi.org/10.1007/s11764-026-02130-1

Image Credits: AI Generated

DOI: 10.1007/s11764-026-02130-1

Keywords: cancer survivorship, survivorship care standards, National Cancer Institute, quality measurement, health care delivery, implementation science, electronic health records, care processes, health systems, measurement infrastructure, cancer care quality, patient-reported outcomes

The starting point for the argument is well established in developmental science. Children are not passive recipients of their environments; they actively shape the experiences and interactions they encounter. Research on parenting has long acknowledged that children are not only moulded by parents but also shape parenting in return. Yet far fewer studies have considered the inputs that children and groups of children bring to ECEC services. When children walk through the door of a preschool or childcare centre, they carry with them unique individual characteristics and experiences of their home and community. These influence their behaviour and their capacity to engage in learning, for better or worse. Because ECEC is a group setting, the characteristics and circumstances of all children in the room influence the demands placed on educators and their capacity to facilitate high-quality, responsive learning experiences. When classroom resources are limited, or even equal across classrooms where some children need far more individualised support, inequity is inevitable.

The stakes are high. Children spend long hours in ECEC services, and government investment in early education rests on the promise that these settings can deliver optimal developmental opportunities, especially for children whose home and community circumstances may limit their educational prospects. The review’s central claim is that delivering on that promise requires abandoning one-size-fits-all models of quality. The authors are careful to stress that the aim is not to assert that children, families, or communities have deficits, but that ECEC should be responsive to the requirements of each—and that responsiveness may require different levels and types of resourcing to achieve equity.

Teaching and learning in the early years centres on the relationship between educator and child, a relationship one pair of researchers has memorably described as “a dance.” Interactions in ECEC set the foundations of ongoing learning, extending beyond constrained curriculum content to unconstrained skills such as regulating emotions, getting along with others, and learning how to learn—skills with enduring effects. Structural characteristics like curriculum, physical resources, staffing levels, and qualifications are enablers of quality, but the evidence places interactional quality between educator and child as the key predictor of child development. Crucially, that relationship is reciprocal and bidirectional: educators, each child, and the collective of children co-create quality.

Yet standard measurement tools tell a different story. The review analyses widely used instruments such as the Classroom Assessment Scoring System for pre-kindergarten and the Early Childhood Environment Rating Scale, and finds that they disproportionately weight educator actions. In the Instructional Support domain of CLASS-PreK, for example, three of four dimensions are described entirely in terms of what the teacher does, with only one dimension focusing on genuine educator-child interaction. The scales also place heavy weight on verbal interactions, which limits their capacity to capture non-verbal strategies such as pauses and silences that encourage children to drive their own learning, and may fail to capture cultural variation in relationship norms and interaction styles. These limitations may explain why professional development interventions, which have succeeded in changing educator behaviours to align with standard definitions of quality, have delivered negligible effects on children’s developmental outcomes. The problem, the authors argue, is treating quality as standard rather than responsive.

To understand how the field arrived here, the review updates a 2020 systematic review of classroom composition and quality, extending the search to 2025. The combined literature reveals a consistent pattern: with the exception of gender, studies report significant associations between demand on educators—indexed by younger child age, higher learning needs, greater disadvantage, and minority status—and reduced interactional quality. Heterogeneity of class composition is likewise associated with poorer observed quality. But the authors also document a striking trend: publications examining demographic composition peaked between 2010 and 2020 and then declined precipitously. They hypothesise that researchers have recognised the limits of demographic designs, which consistently replicate a problem without informing the actions needed to fix it.

Demographic variables, the review argues, serve only as distal proxies for demand. They do not measure intersectionality, directly index child requirements, or capture the influence of an individual child on an educator or classmates. Evidence from school-sector studies is instructive. A behavioural-genetic twin study of children aged five to twelve found that children’s challenging behaviour—irritability, negativity, impulsivity, distractibility, and hyperactivity—rather than ability, was the major source of demand on teachers, and that a single child presenting behavioural challenges can limit the educator time available to every classmate. An experimental study manipulating classroom grouping found that students placed with children with behavioural difficulties had poorer academic outcomes. Importantly, such behavioural challenges are often social in origin, predicted by adverse and traumatic events, hunger, and tiredness. And the consequences flow back to the workforce: children who place higher demand on classrooms can diminish educator wellbeing and even catalyse staff turnover, which in turn disrupts the attachment relationships that underpin quality.

What would better science look like? The review proposes finer-grained, individualised measurement of each child’s input across the varied activities of the ECEC day, paired with research designs that disaggregate child and educator contributions. Borrowing logic from behavioural genetics, the authors outline three designs. A “same educator, different day” design exploits the fact that class composition changes daily in daycare, holding the educator constant while composition varies. A “same educator, different event” design observes the same educator across activities that carry different levels of demand—transitions, mealtimes, and sleep times are known to be more challenging than free play. Finally, a “same child, different educator” design follows focal children longitudinally as they transition between educators, isolating the child’s contribution to quality. A school-sector study of the same teacher working with different mathematics classes offers a template, finding that student characteristics contributed seven to thirteen percent of the variance in instructional quality across individual lessons.

The policy implications are equally significant. Because children requiring higher levels of educator support are not evenly distributed across communities, the authors argue for proportionate universalism: universal access to ECEC, but with greater intensity of resourcing for services experiencing higher complexity and demand. Targeted, wrap-around interventions in highly disadvantaged communities have demonstrated improved equity in child outcomes, providing empirical support for the approach. Enacting it, however, requires better measurement. Administrative data on child developmental vulnerability at school entry can guide community-level tailoring, but geographic indices may miss children who need support outside low socio-economic areas. Quality Rating and Improvement Systems offer a finer-grained lever, but the review documents how early test-based approaches have proven costly, inefficient, vulnerable to gaming, and stressful for educators. Emerging collaborative models of quality improvement, which gather localised information from families, providers, and educators, present an opportunity to co-create quality between government agencies and ECEC services.

For practice, the message is that supporting educators is inseparable from supporting children. Educator wellbeing is consistently associated with the capacity to be responsive, and is shaped by personal circumstances—most educators are women whose pay and conditions are generally poor—and by organisational decisions about leadership, staffing, agency, and professional development. Children’s wellbeing matters too: a hungry child cannot take advantage of learning opportunities, making food provision an essential component of the program rather than an optional extra. Deep engagement with families and communities takes time and resources that are often unrecognised. The review’s conclusion is blunt: when children and educators enter an ECEC service, they do not leave their personal and community circumstances at the door. High-quality early education is fundamentally responsive, and achieving it requires not only well-trained educators but tailored resourcing that enables quality to be enacted at the frontline—delivered, measured, and funded with the child, the children, and the community at the centre.

Subject of Research: The role of child and classroom contributions in shaping equitable, high-quality early childhood education and care

Article Title: Community, Children, Child: New Directions for Equitable Delivery Of High-Quality Early Childhood Education and Care (ECEC)

Article References: Bly, S., Houen, S., Staton, S., & Thorpe, K. (2026). Community, Children, Child: New Directions for Equitable Delivery Of High-Quality Early Childhood Education and Care (ECEC). Educational Psychology Review, 38(1), Article 120. https://doi.org/10.1007/s10648-026-10215-7

Image Credits: AI Generated

DOI: 10.1007/s10648-026-10215-7

Keywords: early childhood education and care, ECEC quality, educator-child interactions, classroom composition, child contributions, educator wellbeing, interactional quality, equity, proportionate universalism, quality measurement, challenging behaviour, classroom research design