Opportunity gaps in out-of-school learning: How structural and process features of programs relate to race and socioeconomic status

Abstract

Out-of-school learning programs can be a context for positive development and learning for children and youth. However, research points to potential racial and socioeconomic disparities, or opportunity gaps, in this context. In this study, we use survey and video data from 106 staff across 30 out-of-school programs to examine how three features, staff, activities, and adult–child interactions, differ based on the racial and socioeconomic makeup of programs. We find that staff at programs serving children from low-income families on average have less experience and education. Also, programs serving children from African American and low-income families tend to offer more academic-focused activities. Finally, we found no differences in adult–child interaction quality across programs in the sample. Our findings suggest that a racial and socioeconomic opportunity gap may exist in the out-of-school context. This has implications for educational equity and the positive development of children that participate in this context.     

Parenting interventions to promote early child development in the first three years of life: A global systematic review and meta-analysis

BackgroundParents are the primary caregivers of young children. Responsive parent–child relationships and parental support for learning during the earliest years of life are crucial for promoting early child development (ECD). We conducted a global systematic review and meta-analysis to evaluate the effectiveness of parenting interventions on ECD and parenting outcomes.Methods and findingsWe searched MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, and Global Health Library for peer-reviewed, published articles from database inception until November 15, 2020. We included randomized controlled trials (RCTs) of parenting interventions delivered during the first 3 years of life that evaluated at least 1 ECD outcome. At least 2 reviewers independently screened, extracted data, and assessed study quality from eligible studies. ECD outcomes included cognitive, language, motor, and socioemotional development, behavior problems, and attachment. Parenting outcomes included parenting knowledge, parenting practices, parent–child interactions, and parental depressive symptoms. We calculated intervention effect sizes as the standardized mean difference (SMD) and estimated pooled effect sizes for each outcome separately using robust variance estimation meta-analytic approaches. We used random-effects meta-regression models to assess potential effect modification by country-income level, child age, intervention content, duration, delivery, setting, and study quality. This review was registered with PROSPERO (CRD42018092458 and CRD42018092461). Of the 11,920 articles identified, we included 111 articles representing 102 unique RCTs. Pooled effect sizes indicated positive benefits of parenting interventions on child cognitive development (SMD = 0.32, 95% CI [confidence interval]: 0.23, 0.40, P < 0.001), language development (SMD = 0.28, 95% CI: 0.18 to 0.37, P < 0.001), motor development (SMD = 0.24, 95% CI: 0.15 to 0.32, P < 0.001), socioemotional development (SMD = 0.19, 95% CI: 0.10 to 0.28, P < 0.001), and attachment (SMD = 0.29, 95% CI: 0.18 to 0.40, P < 0.001) and reductions in behavior problems (SMD = −0.13, 95% CI: −0.18 to −0.08, P < 0.001). Positive benefits were also found on parenting knowledge (SMD = 0.56, 95% CI: 0.33 to 0.79, P < 0.001), parenting practices (SMD = 0.33, 95% CI: 0.22 to 0.44, P < 0.001), and parent–child interactions (SMD = 0.39, 95% CI: 0.24 to 0.53, P < 0.001). However, there was no significant reduction in parental depressive symptoms (SMD = −0.07, 95% CI: −0.16 to 0.02, P = 0.08). Subgroup analyses revealed significantly greater effects on child cognitive, language, and motor development, and parenting practices in low- and middle-income countries compared to high-income countries; and significantly greater effects on child cognitive development, parenting knowledge, parenting practices, and parent–child interactions for programs that focused on responsive caregiving compared to those that did not. On the other hand, there was no clear evidence of effect modification by child age, intervention duration, delivery, setting, or study risk of bias. Study limitations include considerable unexplained heterogeneity, inadequate reporting of intervention content and implementation, and varying quality of evidence in terms of the conduct of trials and robustness of outcome measures used across studies.ConclusionsParenting interventions for children during the first 3 years of life are effective for improving ECD outcomes and enhancing parenting outcomes across low-, middle-, and high-income countries. Increasing implementation of effective and high-quality parenting interventions is needed globally and at scale in order to support parents and enable young children to achieve their full developmental potential.

In a systematic review and meta-analysis, Joshua Jeong and colleagues study the effectiveness of parenting interventions in children 3 years and younger in promoting early childhood development and parenting outcomes.     

Plant Growth Regulators in Citriculture: Factors Regulating Endogenous Levels in Citrus Tissues

Since the review on endogenous growth substances of citrus tissues by Goldschmidt in 1976 (HortScience, 11: 95-99), much information regarding this topic has been published in a wide array of journals. The present review provides a comprehensive overview of published information on endogenous levels of the five classes of plant growth substances (i.e., auxins, cytokinins, gibberellins, ethylene, and abscisic acid), plus polyamines and other endogenous substances that appear to have a role in regulating citrus growth and development. It is the first in a three-part series that next examines hormonal regulation of physiological processes in citrus followed by review of current uses and commercial applications of plant growth regulators in citrus production. In this article, a brief history of the detection and characterization of each class of plant growth substances is given. Following this, variation in endogenous levels associated with different organs (and/or tissues), stages of development, species, cultivars, cultural practices, and environmental factors is reviewed. For each class, current knowledge regarding biosynthesis, metabolism and transport in citrus tissues is summarized. The concluding section deals with future research directions.     

Children’s book series and associated curricula support elementary education and outreach in water resources

Background: Water resources are of fundamental importance to society, and are better managed by stakeholders who understand resource issues. Gaining such knowledge is a lifelong process best begun at an early age and best supported by educational approaches integrating across science, technology, engineering and mathematics (STEM). Research scientists can bring resource education to young audiences through children’s books and curricula that emphasise and integrate across STEM principals.

Aims: To encourage empathy for the environment in younger students, researchers at the Niwot Ridge Long Term Ecological Research site have developed a children’s book series and methods for training teachers in water science education.

Methods: Children’s books in the My Water series are paired with curricula, hands-on learning kits, teacher development training and dissemination of materials through school districts to further water science education.

Results: Thousands of children and educators have received training through the My Water book series, and a more broadly focused, federally funded Schoolyard Children’s Book Series has grown out of these efforts towards water resource education.

Conclusions: Children’s books and curricula that integrate STEM principals can play a key role in the development of environmental empathy and lifelong learning to support resource management.     

AI applications to medical images: From machine learning to deep learning

PurposeArtificial intelligence (AI) models are playing an increasing role in biomedical research and healthcare services. This review focuses on challenges points to be clarified about how to develop AI applications as clinical decision support systems in the real-world context.MethodsA narrative review has been performed including a critical assessment of articles published between 1989 and 2021 that guided challenging sections.ResultsWe first illustrate the architectural characteristics of machine learning (ML)/radiomics and deep learning (DL) approaches. For ML/radiomics, the phases of feature selection and of training, validation, and testing are described. DL models are presented as multi-layered artificial/convolutional neural networks, allowing us to directly process images. The data curation section includes technical steps such as image labelling, image annotation (with segmentation as a crucial step in radiomics), data harmonization (enabling compensation for differences in imaging protocols that typically generate noise in non-AI imaging studies) and federated learning. Thereafter, we dedicate specific sections to: sample size calculation, considering multiple testing in AI approaches; procedures for data augmentation to work with limited and unbalanced datasets; and the interpretability of AI models (the so-called black box issue). Pros and cons for choosing ML versus DL to implement AI applications to medical imaging are finally presented in a synoptic way.ConclusionsBiomedicine and healthcare systems are one of the most important fields for AI applications and medical imaging is probably the most suitable and promising domain. Clarification of specific challenging points facilitates the development of such systems and their translation to clinical practice.     

Qualitative evidence syntheses of attitudes and preferences to inform guidelines on infant feeding in the context of Ebola Virus Disease (EVD) transmission risk

BackgroundBreast-feeding holds considerable potential to reduce infant mortality. Feeding choices, already complex, take on additional complexity against a backdrop of the risk of transmissible Ebola Virus. This review describes the factors that influence infant feeding and attitudes of pregnant women, mothers, family members and health practitioners, policy makers and providers (midwives) concerning infant feeding when there is a risk of Mother-to-Child (MTC) transmission of Ebola Virus Disease (EVD).MethodologyA systematic review of qualitative studies identified through rigorous searches of thirteen online databases and additional citation searches of included studies was undertaken. Search terms included breast-feeding, breast-feeding, infant feeding; Ebola; and qualitative, interview(s) and findings. Independent extraction of data by two reviewers using predefined extraction forms. Studies were assessed using the CASP Qualitative checklist.Principal findings5219 references were screened. 38 references related specifically to Ebola, and five papers met the inclusion criteria with data gathered from two settings: Guinea and Sierra Leone. The EVD outbreak had a significant impact on beliefs, attitudes, and resources to support infant feeding practices negatively affecting the nutritional status of children. The evidence from these studies highlight the need for guidance and appropriate psychosocial support need to be available to mothers who display symptoms and become infected and to front-line staff who are giving advice. Communities need to be engaged because stigma and fear may hinder uptake of appropriate interventions. The EVD outbreak caused multi-level system disruption akin to that seen following a natural disaster, meaning that logistics and coordination are critical and need adequate resourcing. Food production and distribution, and malnutrition screening are also disrupted and thereby compounding compromised nutritional status. The limited number of relevant studies highlights the need for further primary research, particularly in translation of messages to local settings.ConclusionsAn EVD outbreak causes multi-level disruption that negatively impacts infant feeding and child care practices. Negative impacts have multiple causes and successful planning for Ebola outbreaks requires that nutrition of infants and young children is a priority. Lessons from the Ebola pandemic have wider applicability to other pandemic contexts including Covid-19.     

AI for COVID-19 Detection from Radiographs: Incisive Analysis of State of the Art Techniques,Key Challenges and Future Directions

Background and objectiveIn recent years, Artificial Intelligence has had an evident impact on the way research addresses challenges in different domains. It has proven to be a huge asset, especially in the medical field, allowing for time-efficient and reliable solutions. This research aims to spotlight the impact of deep learning and machine learning models in the detection of COVID-19 from medical images. This is achieved by conducting a review of the state-of-the-art approaches proposed by the recent works in this field.MethodsThe main focus of this study is the recent developments of classification and segmentation approaches to image-based COVID-19 detection. The study reviews 140 research papers published in different academic research databases. These papers have been screened and filtered based on specified criteria, to acquire insights prudent to image-based COVID-19 detection.ResultsThe methods discussed in this review include different types of imaging modality, predominantly X-rays and CT scans. These modalities are used for classification and segmentation tasks as well. This review seeks to categorize and discuss the different deep learning and machine learning architectures employed for these tasks, based on the imaging modality utilized. It also hints at other possible deep learning and machine learning architectures that can be proposed for better results towards COVID-19 detection. Along with that, a detailed overview of the emerging trends and breakthroughs in Artificial Intelligence-based COVID-19 detection has been discussed as well.ConclusionThis work concludes by stipulating the technical and non-technical challenges faced by researchers and illustrates the advantages of image-based COVID-19 detection with Artificial Intelligence techniques.     

Malleability,plasticity, and individuality: How children learn and develop in context1

ABSTRACT

This article synthesizes foundational knowledge from multiple scientific disciplines regarding how humans develop in context. Major constructs that define human development are integrated into a developmental system framework, this includes—epigenetics, neural malleability and plasticity, integrated complex skill development and learning, human variability, relationships and attachment, self-regulation, science of learning, and dynamics of stress, adversity and resilience. Specific attention is given to relational patterns, attunement, cognitive flexibility, executive function, working memory, sociocultural context, constructive development, self-organization, dynamic skill development, neural integration, relational pattern making, and adverse childhood experiences. A companion article focuses on individual-context relations, including the role of human relationships as key drivers of development, how social and cultural contexts support and/or undermine individual development, and the dynamic, idiographic developmental pathways that result from mutually influential individual-context relations across the life span. An understanding of the holistic, self-constructive character of development and interconnectedness between individuals and their physical, social, and cultural contexts offers a transformational opportunity to study and influence the children’s trajectories. Woven throughout is the convergence of the science of learning – constructive developmental web, foundational skills, mindsets (sense of belonging, self-efficacy, and growth mindset), prior knowledge and experience, motivational systems (intrinsic motivation, achievement motivation, and the Belief-Control-Expectancy Framework), metacognition, conditions for learning , cultural responsiveness and competence, and instructional and curricular design- and its importance in supporting in integrative framework for children’s development. This scientific understanding of development opens pathways for new, creative approaches that have the potential to solve seemingly intractable learning and social problems.     

The Meaning of Companion Animals for Children and Adolescents with Autism: The Parents' Perspective

ABSTRACT

The aim of this study was to understand parents' perspectives on how children and adolescents with autism spectrum disorders (ASD) benefit from a relationship with companion animals. Parents were invited to participate in focus-group discussions. One open-ended question with follow-up questions was asked and the parents' responses were subsequently categorized. Three main themes emerged: the quality of the relationship with the companion animal; increased interaction with people; and optimization of the child's function and development. The results show that companion animals can contribute to social and behavioral development support, and improved mental health and quality of life. The children's and adolescents' interests and activities with companion animals were more social than nonsocial and of different quality than the restricted and repetitive activities in which children with ASD are normally engaged. Our findings describe a complementary developmental support for this vulnerable group of children and adolescents, which give them possibilities for expanded social contacts, diminished anxiety and depression, and facilitated learning.     

Sibling and environmental correlates of adolescents’ perceptions of family environments: Ethnic group differences

Abstract

Hierarchical regression analyses and response surfaces were used in an investigation of relationships between sibling variables and adolescents’ perceptions of their family environments, after the impact on the perceptions of earlier family measures was taken into account. The analyses involved Australian adolescents and included 260 Anglo‐Australian, 120 Greek, and 90 Southern Italian families. Regression models included terms to test for possible linear, interaction, and curvilinear associations between the sibling and family environment variables. The analysis suggested the propositions that: (a) parents from different ethnic groups create different learning environments for their children and that there are ethnic‐group variations in how children perceive their family environments, (b) there are ethnic‐group variations in relationships between sibling variables and adolescents’ perceptions of their parents’ support for learning, and (c) within ethnic groups the relationships between sibling variables and perceived parental support for learning differ, depending on whether the support of fathers or mothers is being considered.     

Advances in micro-CT imaging of small animals

PurposeMicron-scale computed tomography (micro-CT) imaging is a ubiquitous, cost-effective, and non-invasive three-dimensional imaging modality. We review recent developments and applications of micro-CT for preclinical research.MethodsBased on a comprehensive review of recent micro-CT literature, we summarize features of state-of-the-art hardware and ongoing challenges and promising research directions in the field.ResultsRepresentative features of commercially available micro-CT scanners and some new applications for both in vivo and ex vivo imaging are described. New advancements include spectral scanning using dual-energy micro-CT based on energy-integrating detectors or a new generation of photon-counting x-ray detectors (PCDs). Beyond two-material discrimination, PCDs enable quantitative differentiation of intrinsic tissues from one or more extrinsic contrast agents. When these extrinsic contrast agents are incorporated into a nanoparticle platform (e.g. liposomes), novel micro-CT imaging applications are possible such as combined therapy and diagnostic imaging in the field of cancer theranostics. Another major area of research in micro-CT is in x-ray phase contrast (XPC) imaging. XPC imaging opens CT to many new imaging applications because phase changes are more sensitive to density variations in soft tissues than standard absorption imaging. We further review the impact of deep learning on micro-CT. We feature several recent works which have successfully applied deep learning to micro-CT data, and we outline several challenges specific to micro-CT.ConclusionsAll of these advancements establish micro-CT imaging at the forefront of preclinical research, able to provide anatomical, functional, and even molecular information while serving as a testbench for translational research.     

Preclinical safety evaluations supporting pediatric drug development with biopharmaceuticals: strategy,challenges, current practices

Evaluation of pharmaceutical agents in children is now conducted earlier in the drug development process. An important consideration for this pediatric use is how to assess and support its safety. This article is a collaborative effort of industry toxicologists to review strategies, challenges, and current practice regarding preclinical safety evaluations supporting pediatric drug development with biopharmaceuticals. Biopharmaceuticals include a diverse group of molecular, cell‐based or gene therapeutics derived from biological sources or complex biotechnological processes. The principles of preclinical support of pediatric drug development for biopharmaceuticals are similar to those for small molecule pharmaceuticals and in general follow the same regulatory guidances outlined by the Food and Drug Administration and European Medicines Agency. However, many biopharmaceuticals are also inherently different, with limited species specificity or immunogenic potential which may impact the approach taken. This article discusses several key areas to aid in the support of pediatric clinical use, study design considerations for juvenile toxicity studies when they are needed, and current practices to support pediatric drug development based on surveys specifically targeting biopharmaceutical development. Birth Defects Res (Part B) 92:359–380, 2011. © 2011 Wiley‐Liss, Inc.     

Consensus Statement by the American Association of Clinical Endocrinology (AACE) and the American Head and Neck Society Endocrine Surgery Section (AHNS) on Pediatric Benign and Malignant Thyroid Surgery

ObjectivesTo provide a clinical disease state review of recent relevant literature and to generate expert consensus statements regarding the breadth of pediatric thyroid cancer diagnosis and care, with an emphasis on thyroid surgery. To generate expert statements to educate pediatric practitioners on the state-of-the-art practices and the value of surgical experience in the management of this unusual and challenging disease in children.MethodsA literature search was conducted and statements were constructed and subjected to a modified Delphi process to measure the consensus of the expert author panel. The wording of statements, voting tabulation, and statistical analysis were overseen by a Delphi expert (J.J.S.).ResultsTwenty-five consensus statements were created and subjected to a modified Delphi analysis to measure the strength of consensus of the expert author panel. All statements reached a level of consensus, and the majority of statements reached the highest level of consensus.ConclusionPediatric thyroid cancer has many unique nuances, such as bulky cervical adenopathy on presentation, an increased incidence of diffuse sclerosing variant, and a longer potential lifespan to endure potential complications from treatment. Complications can be a burden to parents and patients alike. We suggest that optimal outcomes and decreased morbidity will come from the use of advanced imaging, diagnostic testing, and neural monitoring of patients treated at high-volume centers by high-volume surgeons.     

When to use what: Methods for weighting and aggregating sustainability indicators

ContextSustainability indices (SIs) have become increasingly important to sustainability research and practice. However, while the validity of SIs is heavily dependent on how their components are weighted and aggregated, the typology and applicability of the existing weighting and aggregation methods remain poorly understood.ObjectivesTo close the knowledge gap regarding when to use which weighting and aggregation methods for constructing SIs, we review the most commonly used methods for weighting and aggregating SIs, discuss their benefits and drawbacks, and suggest a process-oriented approach for choosing appropriate weighting and aggregation methods depending on research objectives.MethodsOur review synthesis was based on peer-reviewed journal articles, books, and reports by international organizations, governmental agencies, and research institutions. After carefully examining their principles, characteristics, and applications, we selected and classified the frequently used methods for indicator weighting and aggregation.ResultsWe systematically discuss the benefits and drawbacks of nine weighting methods and three aggregation methods. We propose a four-step process for choosing the most suitable weighting and aggregation methods based on: research purposes, spatial and temporal scales, and sustainability perspectives.ConclusionsIn this research, we chose the most commonly used methods for weighting and aggregating SIs and analyzed the characteristics, strengths and weaknesses of each method. We found that choosing appropriate weighting and aggregation methods for a specific sustainability assessment project is an extremely important and challenging task. To meet this challenge, we propose a process-oriented approach for properly selecting methods according to the purpose, scale and sustainability concept. This approach can facilitate the proper selection of these methods in sustainability research and practice.     

Drivers of human development: How relationships and context shape learning and development1

ABSTRACT

This article synthesizes knowledge on the role of relationships and key macroand micro-contexts - poverty, racism, families, communities, schools, and peers - in supporting and/or undermining the healthy development of children and youth, using a relational developmental systems framework. Relationships with parents, siblings, peers, caregivers, and teachers are explored in the context of early care and childhood settings, schools, classrooms, and school-based interventions. Additional contextual factors include; chronic stress, institutionalized racism, stereotype threat, and racial identity. A companion article focuses on how the human brain develops, and the major constructs that define human development, the constructive nature of development, and the opportunities for resilience. Human development occurs through reciprocal coactions between the individual and their contexts and culture, with relationships as the key drivers. Relationships and contexts, along with how children appraise and interpret them, can be risks and assets for healthy learning and development, and their influence can be seen across generations and can produce intra- as well as intergenerational assets and risks. This knowledge about the individual’s responsiveness to context and experience has both positive and negative implications across early childhood, adolescence and into adulthood. Sensitive periods for brain growth and development are considered within the contextual factors that influence development including; parental responsiveness and attunement, intentional skill development, mindfulness, reciprocal interactions, adversity, trauma, and enriching opportunities. The accumulated knowledge on human development and the power of context and culture can inform child-serving systems that support positive adaptations, resilience, learning, health, and well-being.     

Big Data to Knowledge: Application of Machine Learning to Predictive Modeling of Therapeutic Response in Cancer

BackgroundIn recent years, the availability of high throughput technologies, establishment of large molecular patient data repositories, and advancement in computing power and storage have allowed elucidation of complex mechanisms implicated in therapeutic response in cancer patients. The breadth and depth of such data, alongside experimental noise and missing values, requires a sophisticated human-machine interaction that would allow effective learning from complex data and accurate forecasting of future outcomes, ideally embedded in the core of machine learning design.ObjectiveIn this review, we will discuss machine learning techniques utilized for modeling of treatment response in cancer, including Random Forests, support vector machines, neural networks, and linear and logistic regression. We will overview their mathematical foundations and discuss their limitations and alternative approaches in light of their application to therapeutic response modeling in cancer.ConclusionWe hypothesize that the increase in the number of patient profiles and potential temporal monitoring of patient data will define even more complex techniques, such as deep learning and causal analysis, as central players in therapeutic response modeling.     

Effect of classroom language diversity on head start ELL and non-ELL children’s social-emotional development

Abstract

This study used the FACES 2009 cohort to examine the effect of classroom language diversity on the social-emotional development (defined as social skills, approaches to learning, and behavior problems) of the ELL and non-ELL children. A three-level hierarchical linear modeling in which time was nested within the child and the child was nested within the classroom was conducted. The children’s ELL status was determined based on their home language and English proficiency. Results showed that the non-ELL children demonstrated a decline in the developmental trajectory of social skills in the classrooms with high language diversity. On the other hand, the ELL children with English proficiency demonstrated a low trajectory of social skills in the classrooms with low language diversity. These findings suggest that the effect of classroom language diversity on the children’s social-emotional development depends on the children’s language status. Implications and future research are discussed.     

Familial Accumulation of Social Anxiety Symptoms and Maladaptive Emotion Regulation

BackgroundSocial anxiety is thought to be strongly related to maladaptive emotion regulation (ER). As social anxiety symptoms accumulate in families, we hypothesize that maladaptive ER is also more prevalent in families with anxious children. Thus, we analyze differences in emotion regulation of both child and mother in relation to social anxiety, as well as both their ER strategies in dealing with anxiety. Further, a positive relation between child and maternal ER strategies is assumed.MethodChildren (aged 9 to 13 years) with social, anxiety disorder (SAD; n = 25) and healthy controls (HC, n = 26) as well as their mothers completed several measures of social anxiety and trait ER strategies towards anxiety. As ER of children is still in development, age is considered as covariate.ResultsSAD children and their mothers reported more maladaptive ER strategies than HC dyads. Maternal maladaptive ER was related negatively to child adaptive ER which was further moderated by the child’s age.DiscussionMaladaptive ER strategies seem to contribute to the exacerbation of social anxiety in both mother and child. Mothers reporting maladaptive ER may have difficulties supporting their child in coping with social anxiety while simultaneously also experiencing heightened levels of anxiety. Deeper understanding of interactional processes between mothers and children during development can assist the comprehension of factors maintaining SAD. Implications for future research and possible consequences for interventions are discussed.     

A commentary on ‘Mineral soil carbon fluxes in forests and implications for carbon balance assessments’: a deeper look at the data

Forestry practitioners contacted us with their concerns about a recent review article by Buchholz T, Friedland AJ, Hornig CE, Keeton WS, Zanchi G, Nunery J (2013) GCB Bioenergy who questioned the way soil carbon is treated in many models and protocols, and indicated that an increasing number of research studies showed meaningful soil organic carbon (SOC) loss as a result of forest management. We revisit the major studies cited in the review and present a more complete look at the results, consistently treat forest floor carbon as a separate pool, discuss differences in interpretation, and suggest opportunities to advance the state of knowledge regarding SOC and forest carbon accounting. Overall, we conclude that the literature continues to support the current default assumption of little or no change in mineral SOC when sound forest management practices are followed.     

A Review of Frailty Analysis in Older Adults: From Clinical Tools Towards Fully Automated Preventive Systems

ObjectivesFrailty is a geriatric syndrome characterized by sarcopenia and physiological impairment. Although the majority of older adults wish to age at home, being frail threatens this choice since it increases the risk of falls and loss of functional independence. Hence, frailty screening and early detection are needed to stop or at least slow down the physical weakening process. In this paper, we present a review in which we discuss the proposed methods from the literature that targets frailty detection and analysis, starting from traditional clinical tools then introducing data-driven studies before highlighting the importance of fully automated systems.Material and methodsWe conducted a review study by searching several databases such as Google Scholar, IEEE Xplore, MDPI, and ScienceDirect to name a few. This work presents clinical tools and classical performance tests to assess the health status and the physical function, as well as statistical and observational studies to analyze the frailty syndrome. Moreover, we discuss briefly the work of our research team in this context, represented by the development of a telemonitoring system which aims at the transition from a curative to a preventive model.ResultsFirstly, this review points out the absence of a gold standard to detect frailty in older individuals. Secondly, it discusses the limitations of self-reported measures/questionnaires and other traditional performance tests which are based on subjective data and done under supervised conditions. Thirdly, our study emphasizes the lack of robust approaches that target the early detection of frailty and the prediction of a future risk of physical worsening. We propose new research directions based, on the one hand, on automatic activity identification and tracking and, on the other hand, on the analysis of spontaneous speech of elderly.ConclusionThis paper describes research findings and highlights the existing gaps in the context of frailty, and serves as a state of the art for researchers. Additionally, this work suggests future research directions regarding the early detection and prevention of frailty.