Applying Psychological Theories to Promote Long-Term Maintenance of Health Behaviors.
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ABSTRACT:
SUBMITTER: Joseph RP
PROVIDER: S-EPMC5313056 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND: Suboptimal treatment adherence remains a barrier to the control of many infectious diseases, including tuberculosis and HIV/AIDS, which contribute significantly to the global disease burden. However, few of the many interventions developed to address this issue explicitly draw on theories of health behaviour. Such theories could contribute to the design of more effective interventions to promote treatment adherence and to improving assessments of the transferability of these interventions across different health issues and settings. METHODS: This paper reviews behaviour change theories applicable to long-term treatment adherence; assesses the evidence for their effectiveness in predicting behaviour change; and examines the implications of these findings for developing strategies to improve TB and HIV/AIDS medication adherence. We searched a number of electronic databases for theories of behaviour change. Eleven theories were examined. RESULTS: Little empirical evidence was located on the effectiveness of these theories in promoting adherence. However, several models have the potential to both improve understanding of adherence behaviours and contribute to the design of more effective interventions to promote adherence to TB and HIV/AIDS medication. CONCLUSION: Further research and analysis is needed urgently to determine which models might best improve adherence to long-term treatment regimens.
| S-EPMC1925084 | biostudies-other
Project description:BackgroundPsychological models are used to understand and predict behaviour in a wide range of settings, but have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. This study explored the usefulness of a range of models to predict an evidence-based behaviour -- the placing of fissure sealants.MethodsMeasures were collected by postal questionnaire from a random sample of general dental practitioners (GDPs) in Scotland. Outcomes were behavioural simulation (scenario decision-making), and behavioural intention. Predictor variables were from the Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Stage Model, and knowledge (a non-theoretical construct). Multiple regression analysis was used to examine the predictive value of each theoretical model individually. Significant constructs from all theories were then entered into a 'cross theory' stepwise regression analysis to investigate their combined predictive value.ResultsBehavioural simulation - theory level variance explained was: TPB 31%; SCT 29%; II 7%; OLT 30%. Neither CS-SRM nor stage explained significant variance. In the cross theory analysis, habit (OLT), timeline acute (CS-SRM), and outcome expectancy (SCT) entered the equation, together explaining 38% of the variance. Behavioural intention - theory level variance explained was: TPB 30%; SCT 24%; OLT 58%, CS-SRM 27%. GDPs in the action stage had significantly higher intention to place fissure sealants. In the cross theory analysis, habit (OLT) and attitude (TPB) entered the equation, together explaining 68% of the variance in intention.SummaryThe study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that may predict clinical behaviour and so provide possible targets for knowledge translation interventions. Results suggest that more evidence-based behaviour may be achieved by influencing beliefs about the positive outcomes of placing fissure sealants and building a habit of placing them as part of patient management. However a number of conceptual and methodological challenges remain.
| S-EPMC2864198 | biostudies-literature
Project description:BackgroundPsychological models can be used to understand and predict behaviour in a wide range of settings. However, they have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. The aim of this study was to explore the usefulness of a range of psychological theories to predict health professional behaviour relating to management of upper respiratory tract infections (URTIs) without antibiotics.MethodsPsychological measures were collected by postal questionnaire survey from a random sample of general practitioners (GPs) in Scotland. The outcome measures were clinical behaviour (using antibiotic prescription rates as a proxy indicator), behavioural simulation (scenario-based decisions to managing URTI with or without antibiotics) and behavioural intention (general intention to managing URTI without antibiotics). Explanatory variables were the constructs within the following theories: Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-Regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Stage Model (SM), and knowledge (a non-theoretical construct). For each outcome measure, multiple regression analysis was used to examine the predictive value of each theoretical model individually. Following this 'theory level' analysis, a 'cross theory' analysis was conducted to investigate the combined predictive value of all significant individual constructs across theories.ResultsAll theories were tested, but only significant results are presented. When predicting behaviour, at the theory level, OLT explained 6% of the variance and, in a cross theory analysis, OLT 'evidence of habitual behaviour' also explained 6%. When predicting behavioural simulation, at the theory level, the proportion of variance explained was: TPB, 31%; SCT, 26%; II, 6%; OLT, 24%. GPs who reported having already decided to change their management to try to avoid the use of antibiotics made significantly fewer scenario-based decisions to prescribe. In the cross theory analysis, perceived behavioural control (TPB), evidence of habitual behaviour (OLT), CS-SRM cause (chance/bad luck), and intention entered the equation, together explaining 36% of the variance. When predicting intention, at the theory level, the proportion of variance explained was: TPB, 30%; SCT, 29%; CS-SRM 27%; OLT, 43%. GPs who reported that they had already decided to change their management to try to avoid the use of antibiotics had a significantly higher intention to manage URTIs without prescribing antibiotics. In the cross theory analysis, OLT evidence of habitual behaviour, TPB attitudes, risk perception, CS-SRM control by doctor, TPB perceived behavioural control and CS-SRM control by treatment entered the equation, together explaining 49% of the variance in intention.ConclusionThe study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that predict clinical behaviour. However, a number of conceptual and methodological challenges remain.
| S-EPMC2042498 | biostudies-literature
Project description:Over 20 million archival tissue samples are stored annually in the United States as formalin-fixed, paraffin-embedded (FFPE) tissue blocks, but only recently has whole-genome expression profiling from these samples become technically feasible. Here, we introduce novel general methods for assessing, summarizing, and visualizing expression data quality from archival samples. We validated these methods in technical study of 144 clinical breast cancer and autopsy samples and in an overview of all current publicly available FFPE whole-genome expression data. We additionally performed a case study incorporating over 1,000 colorectal cancer (CRC) samples collected from patients across the United States over a period of more than 25 years, integrating clinicopathological information, tumor molecular data, and archival tissue gene expression on an unparalleled scale. Both large-scale clinical studies presented a much greater range of data quality than previous smaller studies, emphasizing the need for rigorous quality control in translational applications of archival tissue gene expression profiling. This series includes 1,003 FFPE-preserved CRC tumors, assayed by Illumina HumanRef-v3 WG-DASL microarray.
2012-10-02 | E-GEOD-32651 | biostudies-arrayexpress
Project description:AimsThe number of ventilator-dependent patients is rapidly increasing globally. As a result, long-term mechanical ventilation (LTMV) patients face the choice of receiving health care in respiratory care wards (RCWs) rather than at home. In this study, we applied Andersen's behavioral theoretical model (ABM) to investigate the determinants of the health care service decisions of patients receiving LTMV.MethodsA cross-sectional research design and cluster random sampling were used to select 365 participants from nine RCWs and eight home care facilities in northern Taiwan. Data were collected in face-to-face interviews using a structured questionnaire.ResultsOf the predisposing factors, advanced age and an education level of at least junior high school influenced the choice to use RCW services. Being married, living with extended family, and medium or higher socioeconomic status were associated with the decision to use home care services. Of the enabling factors, patients with more caregivers, those whose family caregivers held strong beliefs about providing care, and those who perceived greater social support from health care providers were more likely to choose home care services. Of the need factors examined, poor cognitive function and higher dependence on assistance for activities of daily living (ADL) increased the probability of patients choosing RCW services. Hierarchical logistic regression analysis indicated that our final model accounted for 44.8% of the observed variance in health care service choice.ConclusionsABM enables an improved understanding of the health care service choices of LTMV patients. Our findings also highlight the importance of rigorously assessing patient needs and helping patients choose the most appropriate health care service.
| S-EPMC9462724 | biostudies-literature
Project description:BACKGROUND:Although physical activity has been shown to contribute to long-term disease control and health in breast cancer survivors, a majority of breast cancer survivors do not meet physical activity guidelines. Past research has focused on promoting physical activity components for short-term breast cancer survivor benefits, but insufficient attention has been devoted to long-term outcomes and sustained exercise adherence. We are assessing a health coach intervention (iMOVE) that uses mobile technology to increase and sustain physical activity maintenance in initially inactive breast cancer survivors. OBJECTIVE:This pilot randomized controlled trial (RCT) is an initial step in evaluating the iMOVE intervention and will inform development of a full-scale pragmatic RCT. METHODS:We will enroll 107 physically inactive breast cancer survivors and randomly assign them to intervention or control groups at the University Health Network, a tertiary cancer care center in Toronto, Canada. Participants will be women (age 18 to 74 years) stratified by age (55 years and older/younger than 55 years) and adjuvant hormone therapy (AHT) exposure (AHT vs no AHT) following breast cancer treatment with no metastases or recurrence who report less than 60 minutes of preplanned physical activity per week. Both intervention and control groups receive the 12-week physical activity program with weekly group sessions and an individualized, progressive, home-based exercise program. The intervention group will additionally receive (1) 10 telephone-based health coaching sessions, (2) smartphone with data plan, if needed, (3) supportive health tracking software (Connected Wellness, NexJ Health Inc), and (4) a wearable step-counting device linked to a smartphone program. RESULTS:We will be assessing recruitment rates; acceptability reflected in selective, semistructured interviews; and enrollment, retention, and adherence quantitative intervention markers as pilot outcome measures. The primary clinical outcome will be directly measured peak oxygen consumption. Secondary clinical outcomes include health-related quality of life and anthropometric measures. All outcome measures are administered at baseline, after exercise program (month 3), and 6 months after program (month 9). CONCLUSIONS:This pilot RCT will inform full-scale RCT planning. We will assess pilot procedures and interventions and collect preliminary effect estimates. TRIAL REGISTRATION:ClinicalTrials.gov NCT02620735; https://clinicaltrials.gov/ct2/show/NCT02620735 (Archived by WebCite at https://clinicaltrials.gov/ct2/show/NCT02620735).
| S-EPMC5590009 | biostudies-literature
Project description:Memories are stored, at least partly, as patterns of strong synapses. Given molecular turnover, how can synapses maintain strong for the years that memories can persist? Some models postulate that biochemical bistability maintains strong synapses. However, bistability should give a bimodal distribution of synaptic strength or weight, whereas current data show unimodal distributions for weights and for a correlated variable, dendritic spine volume. Thus it is important for models to simulate both unimodal distributions and long-term memory persistence. Here a model is developed that connects ongoing, competing processes of synaptic growth and weakening to stochastic processes of receptor insertion and removal in dendritic spines. The model simulates long-term (>1?yr) persistence of groups of strong synapses. A unimodal weight distribution results. For stability of this distribution it proved essential to incorporate resource competition between synapses organized into small clusters. With competition, these clusters are stable for years. These simulations concur with recent data to support the "clustered plasticity hypothesis" which suggests clusters, rather than single synaptic contacts, may be a fundamental unit for storage of long-term memory. The model makes empirical predictions and may provide a framework to investigate mechanisms maintaining the balance between synaptic plasticity and stability of memory.
| S-EPMC4402204 | biostudies-literature
Project description:Transgender and gender nonconforming (TGNC) people are a highly-stigmatized population. For this reason, they might internalize society's normative gender attitudes and develop negative mental health outcomes. As an extension of the minority stress model, the psychological mediation framework sheds light on psychological processes through which anti-transgender discrimination might affect mental health. Within this framework, the current study aimed at assessing in 149 TGNC Italian individuals the role of internalized transphobia as a mediator between anti-transgender discrimination and mental health, considering resilience as the individual-level coping mechanism buffering this relationship. The results suggest that both indicators of internalized transphobia (i.e., shame and alienation) mediate the relationship between anti-transgender discrimination and depression, while only alienation mediates the relationship between anti-transgender discrimination and anxiety. Furthermore, the results suggest that the indirect relation between anti-transgender discrimination and anxiety through alienation is conditional on low and moderate levels of resilience. Findings have important implications for clinical practice and psycho-social interventions to reduce stigma and stress caused by interpersonal and individual stigma.
| S-EPMC5877053 | biostudies-other
Project description:Memory can last a lifetime, yet synaptic contacts that contribute to the storage of memory are composed of proteins that have much shorter lifetimes. A physiological model of memory formation, long-term potentiation (LTP), has a late protein-synthesis-dependent phase (L-LTP) that can last for many hours in slices or even for days in vivo. Could the activity-dependent synthesis of new proteins account for the persistence of L-LTP and memory? Here, we examine the proposal that a self-sustaining regulation of translation can form a bistable switch that can persistently regulate the on-site synthesis of plasticity-related proteins. We show that an alpha CaMKII-CPEB1 molecular pair can operate as a bistable switch. Our results imply that L-LTP should produce an increase in the total amount of alpha CaMKII at potentiated synapses. This study also proposes an explanation for why the application of protein synthesis and alphaCaMKII inhibitors at the induction and maintenance phases of L-LTP result in very different outcomes.
| S-EPMC2710869 | biostudies-other
Project description:Obesity and its impact on health is a multifaceted phenomenon encompassing many factors, including demographics, environment, lifestyle, and psychosocial functioning. A systems science approach, investigating these many influences, is needed to capture the complexity and multidimensionality of obesity prevention to improve health. Leveraging baseline data from a unique clinical cohort comprising 333 postmenopausal overweight or obese breast cancer survivors participating in a weight-loss trial, we applied Bayesian networks, a machine learning approach, to infer interrelationships between lifestyle factors (e.g., sleep, physical activity), body mass index (BMI), and health outcomes (biomarkers and self-reported quality of life metrics). We used bootstrap resampling to assess network stability and accuracy, and Bayesian information criteria (BIC) to compare networks. Our results identified important behavioral subnetworks. BMI was the primary pathway linking behavioral factors to glucose regulation and inflammatory markers; the BMI-biomarker link was reproduced in 100% of resampled networks. Sleep quality was a hub impacting mental quality of life and physical health with > 95% resampling reproducibility. Omission of the BMI or sleep links significantly degraded the fit of the networks. Our findings suggest potential mechanistic pathways and useful intervention targets for future trials. Using our models, we can make quantitative predictions about health impacts that would result from targeted, weight loss and/or sleep improvement interventions. Importantly, this work highlights the utility of Bayesian networks in health behaviors research.
| S-EPMC6122792 | biostudies-literature