Conceptual Framework for Insomnia: A Cognitive Model in Practice.
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ABSTRACT:
SUBMITTER: Vaziri Z
PROVIDER: S-EPMC8339273 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background/Study Context: Conceptual frameworks are analytic models at a high level of abstraction. Their operationalization can inform randomized trial design and sample size considerations.MethodsThe Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) conceptual framework was empirically tested using structural equation modeling (N=2,802). ACTIVE was guided by a conceptual framework for cognitive training in which proximal cognitive abilities (memory, inductive reasoning, speed of processing) mediate treatment-related improvement in primary outcomes (everyday problem-solving, difficulty with activities of daily living, everyday speed, driving difficulty), which in turn lead to improved secondary outcomes (health-related quality of life, health service utilization, mobility). Measurement models for each proximal, primary, and secondary outcome were developed and tested using baseline data. Each construct was then combined in one model to evaluate fit (RMSEA, CFI, normalized residuals of each indicator). To expand the conceptual model and potentially inform future trials, evidence of modification of structural model parameters was evaluated by age, years of education, sex, race, and self-rated health status.ResultsPreconceived measurement models for memory, reasoning, speed of processing, everyday problem-solving, instrumental activities of daily living (IADL) difficulty, everyday speed, driving difficulty, and health-related quality of life each fit well to the data (all RMSEA < .05; all CFI > .95). Fit of the full model was excellent (RMSEA = .038; CFI = .924). In contrast with previous findings from ACTIVE regarding who benefits from training, interaction testing revealed associations between proximal abilities and primary outcomes are stronger on average by nonwhite race, worse health, older age, and less education (p < .005).ConclusionsEmpirical data confirm the hypothesized ACTIVE conceptual model. Findings suggest that the types of people who show intervention effects on cognitive performance potentially may be different from those with the greatest chance of transfer to real-world activities.
| S-EPMC5793899 | biostudies-literature
Project description:The aim of this paper is to explore a new framework for personality assessment that may function as sanity nosology of personality traits: the Positive Personality Model (PPM). The recent publication of DSM-5 created the opportunity to assess personality traits as dimensional constructs (American Psychiatric Association, 2013). In Section III, five maladaptive personality traits are proposed as the maladaptive versions of Five Factor Model (FFM) traits (Costa and McCrae, 1985). This approach draws on the existing idea of conceptualizing pathological and typical personality traits as part of a continuum. It places DSM-5's maladaptive traits in a sickness pole and FFM's traits in a "typical" pole. This spectrum, however, does not include a positive perspective that represents healthy behavior: a sanity nosology. The Positive Traits Inventory-5 (PTI-5; de la Iglesia and Castro Solano, 2018) is a measure designed to assess the positive reverse of the Personality Inventory for DSM-5-Adult (PID-5; Krueger et al., 2013). The 220 positive personality criteria were studied psychometrically using a sample of 1902 Argentinean adults from the general population (M age = 39.10, SD = 13.81, Min = 18, and Max = 83; 50.1% females, 49.9% males). Exploratory and confirmatory factor analyses resulted in a five-factor solution. The dimensions were labeled Sprightliness, Integrity, Serenity, Moderation, and Humanity and subsumed under the denomination of PPM. Analyses of convergent validity provided some grounds for interpreting the five positive traits as positive versions of the pathological traits and the typical traits. When tested for its predictive capability on mental health, the PPM outperformed the variance explained by the FFM. It is concluded that the PPM may constitute a positive pole in the continuum of personality traits -possibly functioning as a sanity nosology- and that it is somewhat more related to optimal functioning than typical trait models. The PPM should be confirmed in other populations, its predictive capability ought to be tested with other relevant variables, and longitudinal studies should be done to analyze the stability of the traits over time.
| S-EPMC6209641 | biostudies-literature
Project description:Chronic insomnia (symptoms for ≥ 6 months) is the most common sleep disorder, affecting 6% to 10% of adults in the general population, with even higher rates in patients with comorbid conditions (eg, hypertension, 44%; cardiac disease, 44.1%; breathing problems, 41.5%). Traditionally, chronic insomnia occurring with another condition has been considered secondary and rarely received direct treatment because treatment of the primary condition was expected to improve the insomnia. However, this approach often failed because chronic insomnia is maintained by behaviors, cognitions, and associations that patients adopt as they attempt to cope with poor sleep but that end up backfiring (eg, increasing caffeine, spending more time in bed, trying harder to sleep). Cognitive behavioral treatment of insomnia (CBTi) targets those behaviors, cognitions, and associations and is effective across a variety of populations, including those with medical and psychologic comorbidities. Thus, in 2005, a National Institutes of Health expert consensus panel on chronic insomnia recommended dropping the term "secondary insomnia" in favor of the term "comorbid insomnia." Because CBTi does not carry the risks associated with some sleep medications (eg, dependency, polypharmacy, cognitive and psychomotor impairment), it is an attractive option for patients with other conditions. Through the Society of Behavioral Sleep Medicine (www.behavioralsleep.org) and the American Board of Sleep Medicine (www.absm.org), it is possible to find practitioners with expertise in CBTi (as well as other aspects of behavioral sleep medicine) and other behavioral sleep resources. Given the currently limited number of trained practitioners, exploration of alternative delivery methods (eg, briefer protocols, self-help, Internet) to improve access to this highly effective treatment and expanded training in these treatments are warranted.
| S-EPMC4694188 | biostudies-other
Project description:Communities of Practice (CoPs) are groups of people that interact regularly to deepen their knowledge on a specific topic. Thanks to information and communication technologies, CoPs can involve experts distributed across countries and adopt a 'transnational' membership. This has allowed the strategy to be applied to domains of knowledge such as health policy with a global perspective. CoPs represent a potentially valuable tool for producing and sharing explicit knowledge, as well as tacit knowledge and implementation practices. They may also be effective in creating links among the different 'knowledge holders' contributing to health policy (e.g., researchers, policymakers, technical assistants, practitioners, etc.). CoPs in global health are growing in number and activities. As a result, there is an increasing need to document their progress and evaluate their effectiveness. This paper represents a first step towards such empirical research as it aims to provide a conceptual framework for the analysis and assessment of transnational CoPs in health policy.The framework is developed based on the findings of a literature review as well as on our experience, and reflects the specific features and challenges of transnational CoPs in health policy. It organizes the key elements of CoPs into a logical flow that links available resources and the capacity to mobilize them, with knowledge management activities and the expansion of knowledge, with changes in policy and practice and, ultimately, with an improvement in health outcomes. Additionally, the paper addresses the challenges in the operationalization and empirical application of the framework.
| S-EPMC3819672 | biostudies-literature
Project description:To explore the minds of others, which is traditionally referred to as Theory of Mind (ToM), is perhaps the most fundamental ability of humans as social beings. Impairments in ToM could lead to difficulties or even deficits in social interaction. The present study focuses on two core components of ToM, the ability to infer others' beliefs and the ability to infer others' emotions, which we refer to as cognitive and affective ToM respectively. Charting both typical and atypical trajectories underlying the cognitive-affective ToM promises to shed light on the precision identification of mental disorders, such as depressive disorders (DD) and autism spectrum disorder (ASD). However, most prior studies failed to capture the underlying processes involved in the cognitive-affective ToM in a fine-grained manner. To address this problem, we propose an innovative conceptual framework, referred to as visual theory of mind (V-ToM), by constructing visual scenes with emotional and cognitive meanings and by depicting explicitly a four-stage process of how humans make inferences about the beliefs and emotions of others. Through recording individuals' eye movements while looking at the visual scenes, our model enables us to accurately measure each stage involved in the computation of cognitive-affective ToM, thereby allowing us to infer about potential difficulties that might occur in each stage. Our model is based on a large sample size (n > 700) and a novel audio-visual paradigm using visual scenes containing cognitive-emotional meanings. Here we report the obtained differential features among healthy controls, DD and ASD individuals that overcome the subjectivity of conventional questionnaire-based assessment, and therefore could serve as valuable references for mental health applications based on AI-aided digital medicine.
| S-EPMC10955940 | biostudies-literature
Project description:BACKGROUND:Prognostic research has many important purposes, including (i) describing the natural history and clinical course of health conditions, (ii) investigating variables associated with health outcomes of interest, (iii) estimating an individual's probability of developing different outcomes, (iv) investigating the clinical application of prediction models, and (v) investigating determinants of recovery that can inform the development of interventions to improve patient outcomes. But much prognostic research has been poorly conducted and interpreted, indicating that a number of conceptual areas are often misunderstood. Recent initiatives to improve this include the Prognosis Research Strategy (PROGRESS) and the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Statement. In this paper, we aim to show how different categories of prognostic research relate to each other, to differentiate exploratory and confirmatory studies, discuss moderators and mediators, and to show how important it is to understand study designs and the differences between prediction and causation. MAIN TEXT:We propose that there are four main objectives of prognostic studies - description, association, prediction and causation. By causation, we mean the effect of prediction and decision rules on outcomes as determined by intervention studies and the investigation of whether a prognostic factor is a determinant of outcome (on the causal pathway). These either fall under the umbrella of exploratory (description, association, and prediction model development) or confirmatory (prediction model external validation and investigation of causation). Including considerations of causation within a prognostic framework provides a more comprehensive roadmap of how different types of studies conceptually relate to each other, and better clarity about appropriate model performance measures and the inferences that can be drawn from different types of prognostic studies. We also propose definitions of 'candidate prognostic factors', 'prognostic factors', 'prognostic determinants (causal)' and 'prognostic markers (non-causal)'. Furthermore, we address common conceptual misunderstandings related to study design, analysis, and interpretation of multivariable models from the perspectives of association, prediction and causation. CONCLUSION:This paper uses a framework to clarify some concepts in prognostic research that remain poorly understood and implemented, to stimulate discussion about how prognostic studies can be strengthened and appropriately interpreted.
| S-EPMC7325141 | biostudies-literature
Project description:Over the past century, the environment of the Gulf of Mexico has been significantly altered and impaired by extensive human activities. A national commitment to restore the Gulf was finally initiated in response to the unprecedented Deepwater Horizon oil spill in 2010. Consequently, there is a critical need for an assessment framework and associated set of indicators that can characterize the health and sustainability of an ecosystem having the scale and complexity of the Gulf. The assessment framework presented here was developed as an integration of previous ecological risk- and environmental management-based frameworks for assessing ecosystem health. It was designed to identify the natural and anthropogenic drivers, pressures, and stressors impinging on ecosystems and ecosystem services, and the ecological conditions that result, manifested as effects on valued ecosystem components. Four types of societal and ecological responses are identified: reduction of pressures and stressors, remediation of existing stressors, active ecosystem restoration, and natural ecological recovery. From this conceptual framework are derived the specific indicators to characterize ecological condition and progress toward achieving defined ecological health and sustainability goals. Additionally, the framework incorporates a hierarchical structure to communicate results to a diversity of audiences, from research scientists to environmental managers and decision makers, with the level of detail or aggregation appropriate for each targeted audience. Two proof-of-concept studies were conducted to test this integrated assessment and decision framework, a prototype Texas Coastal Ecosystems Report Card, and a pilot study on enhancing rookery islands in the Mission-Aransas Reserve, Texas, USA. This Drivers-Pressures-Stressors-Condition-Responses (DPSCR4 ) conceptual framework is a comprehensive conceptual model of the coupled human-ecological system. Much like its predecessor, the ecological risk assessment framework, the DPSCR4 conceptual framework can be tailored to different scales of complexity, different ecosystem types with different stress regimes, and different environmental settings. Integr Environ Assess Manag 2019;15:544-564. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
| S-EPMC6852332 | biostudies-literature
Project description:The value proposition for biosimilars can be characterized as a concept that moves beyond the argument of cost reduction relative to the innovator biologic drug and into a framework that incorporates the diverse needs of key healthcare stakeholders during the transition from clinical development to commercialization in the marketplace.To identify factors that facilitate and inhibit the development, commercialization, and adoption of biosimilars, and to recommend modifications in program design that are likely to support the demonstration of the value of biosimilars for payers, providers, and patients.The primary data sources for this article include surveys conducted by Boston Healthcare Associates with payers and clinicians in the United States and the European Union 5 markets and blinded international protocol feasibility assessments completed by Worldwide Clinical Trials. Survey methodology used either convenience or purposeful sampling as appropriate, with participants extracted from diverse audiences, representative of those who generate or evaluate clinical data shaping the economic exchange and preferential status influencing physician adoption and patient access to biosimilars. Patient characteristics and psychosocial issues influencing patients' perception of small-molecule generics were extracted from the available literature to inform exploratory hypotheses, given the relative absence of such information for biosimilars.This article reviews the current evidence and summarizes results of surveys conducted with payers, providers, and drug investigation sites in the United States. Based on a review of published literature, as well as these survey results, conflicting and convergent demands exist for gathering data related to biosimilars. The motivations and data needs for these new agents are diverse, requiring adjudication of regulatory, economic, and clinical incentives beginning at program inception and extending through commercialization of the final biosimilar agent.The development and commercialization of biosimilars represent an international activity that can encounter unanticipated challenges, as well as opportunities to achieve clinical and commercial success. Evolving regulatory guidance mapped in relation to payer, physician, and patient sentiments may inform the biosimilar development program designs, implementation, and positioning of the new drug.
| S-EPMC4467014 | biostudies-other
Project description:BackgroundPeople with inflammatory bowel disease (IBD) commonly experience pain influenced by complex interactions among factors, including disease activity, sleep, psychopathology, and changes in pain processing pathways. Treatments for pain in IBD are limited, highlighting the need for research that explores modifiable factors linked to pain. The aim of this study was to investigate relationships among multiple patient factors and to construct a conceptual model for pain interference in IBD.MethodsA cross-sectional survey of adults with IBD. Study domains included demographic, comorbidity, psychological, IBD, insomnia, fatigue, and pain features. Structural equation modeling (SEM) was used to examine relationships and interactions among active IBD, insomnia, fatigue, pain experiences (severity, catastrophizing, and interference), and additional patient factors (demographics and psychological).ResultsOne hundred and seventy-four participants, aged 18-85 years, reported the presence of pain. Combining the questionnaire data using SEM resulted in a final model with an excellent fit (χ 2(8) = 9.579, P = .297, χ 2/N = 1.197, CFIN = 0.997, TLI = 0.987, RMSEA = 0.034). The presence of anxiety and depression was the additional patient factors to be retained in the path analysis. SEM results indicated that greater pain interference was directly influenced by greater fatigue, worse pain catastrophizing, and worse pain severity. Pain interference was indirectly impacted by IBD activity, worse insomnia, and the presence of depression and anxiety.ConclusionsThe proposed conceptual model highlights the role of multiple potentially modifiable factors, including insomnia, pain catastrophizing, and fatigue, contributing to worse pain interference in people with IBD.
| S-EPMC9802206 | biostudies-literature
Project description:ObjectivePolicy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster.MethodsWe developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties.ResultsThe conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature.ConclusionsThe work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).
| S-EPMC8743042 | biostudies-literature