Search

Abstract Background In the field of implementation research, there is an increased interest in use of theory when designing implementation research studies involving behavior change. In 2003, we initiated a series of five studies to establish a scientific rationale for interventions to translate research findings into clinical practice by exploring the performance of a number of different, commonly used, overlapping behavioral theories and models. We reflect on the strengths and weaknesses of the methods, the performance of the theories, and consider where these methods sit alongside the range of methods for studying healthcare professional behavior change. Methods These were five studies of the theory-based cognitions and clinical behaviors (taking dental radiographs, performing dental restorations, placing fissure sealants, managing upper respiratory tract infections without prescribing antibiotics, managing low back pain without ordering lumbar spine x-rays) of random samples of primary care dentists and physicians. Measures were derived for the explanatory theoretical constructs in the Theory of Planned Behavior (TPB), Social Cognitive Theory (SCT), and Illness Representations specified by the Common Sense Self Regulation Model (CSSRM). We constructed self-report measures of two constructs from Learning Theory (LT), a measure of Implementation Intentions (II), and the Precaution Adoption Process. We collected data on theory-based cognitions (explanatory measures) and two interim outcome measures (stated behavioral intention and simulated behavior) by postal questionnaire survey during the 12-month period to which objective measures of behavior (collected from routine administrative sources) were related. Planned analyses explored the predictive value of theories in explaining variance in intention, behavioral simulation and behavior. Results Response rates across the five surveys ranged from 21% to 48%; we achieved the target sample size for three of the five surveys. For the predictor variables, the mean construct scores were above the mid-point on the scale with median values across the five behaviors generally being above four out of seven and the range being from 1.53 to 6.01. Across all of the theories, the highest proportion of the variance explained was always for intention and the lowest was for behavior. The Knowledge-Attitudes-Behavior Model performed poorly across all behaviors and dependent variables; CSSRM also performed poorly. For TPB, SCT, II, and LT across the five behaviors, we predicted median R2 of 25% to 42.6% for intention, 6.2% to 16% for behavioral simulation, and 2.4% to 6.3% for behavior. Conclusions We operationalized multiple theories measuring across five behaviors. Continuing challenges that emerge from our work are: better specification of behaviors, better operationalization of theories; how best to appropriately extend the range of theories; further assessment of the value of theories in different settings and groups; exploring the implications of these methods for the management of chronic diseases; and moving to experimental designs to allow an understanding of behavior change.

Abstract Background Psychological models predict behaviour in a wide range of settings. The aim of this study was to explore the usefulness of a range of psychological models to predict the health professional behaviour 'referral for lumbar spine x-ray in patients presenting with low back pain' by UK primary care physicians. Methods Psychological measures were collected by postal questionnaire survey from a random sample of primary care physicians in Scotland and north England. The outcome measures were clinical behaviour (referral rates for lumbar spine x-rays), behavioural simulation (lumbar spine x-ray referral decisions based upon scenarios), and behavioural intention (general intention to refer for lumbar spine x-rays in patients with low back pain). Explanatory variables were the constructs within the Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-Regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Weinstein's Stage Model termed the Precaution Adoption Process (PAP), and knowledge. For each of the outcome measures, a generalised linear model was used to examine the predictive value of each theory individually. Linear regression was used for the intention and simulation outcomes, and negative binomial regression was used for the behaviour outcome. Following this 'theory level' analysis, a 'cross-theoretical construct' analysis was conducted to investigate the combined predictive value of all individual constructs across theories. Results Constructs from TPB, SCT, CS-SRM, and OLT predicted behaviour; however, the theoretical models did not fit the data well. When predicting behavioural simulation, the proportion of variance explained by individual theories was TPB 11.6%, SCT 12.1%, OLT 8.1%, and II 1.5% of the variance, and in the cross-theory analysis constructs from TPB, CS-SRM and II explained 16.5% of the variance in simulated behaviours. When predicting intention, the proportion of variance explained by individual theories was TPB 25.0%, SCT 21.5%, CS-SRM 11.3%, OLT 26.3%, PAP 2.6%, and knowledge 2.3%, and in the cross-theory analysis constructs from TPB, SCT, CS-SRM, and OLT explained 33.5% variance in intention. Together these results suggest that physicians' beliefs about consequences and beliefs about capabilities are likely determinants of lumbar spine x-ray referrals. Conclusions The study provides evidence that 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.

Abstract Background Psychological 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. Methods Measures 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 Results Behavioural 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. Summary The 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.

Abstract Background There is growing interest in the use of cognitive, behavioural, and organisational theories in implementation research. However, the extent of use of theory in implementation research is uncertain. Methods We conducted a systematic review of use of theory in 235 rigorous evaluations of guideline dissemination and implementation studies published between 1966 and 1998. Use of theory was classified according to type of use (explicitly theory based, some conceptual basis, and theoretical construct used) and stage of use (choice/design of intervention, process/mediators/moderators, and post hoc/explanation). Results Fifty-three of 235 studies (22.5%) were judged to have employed theories, including 14 studies that explicitly used theory. The majority of studies (n = 42) used only one theory; the maximum number of theories employed by any study was three. Twenty-five different theories were used. A small number of theories accounted for the majority of theory use including PRECEDE (Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation), diffusion of innovations, information overload and social marketing (academic detailing). Conclusions There was poor justification of choice of intervention and use of theory in implementation research in the identified studies until at least 1998. Future research should explicitly identify the justification for the interventions. Greater use of explicit theory to understand barriers, design interventions, and explore mediating pathways and moderators is needed to advance the science of implementation research.

Abstract Background The results of randomised controlled trials can be usefully illuminated by studies of the processes by which they achieve their effects. The Theory of Planned Behaviour (TPB) offers a framework for conducting such studies. This study used TPB to explore the observed effects in a pragmatic cluster randomised controlled trial of a structured recall and prompting intervention to increase evidence-based diabetes care that was conducted in three Primary Care Trusts in England. Methods All general practitioners and nurses in practices involved in the trial were sent a postal questionnaire at the end of the intervention period, based on the TPB (predictor variables: attitude; subjective norm; perceived behavioural control, or PBC). It focussed on three clinical behaviours recommended in diabetes care: measuring blood pressure; inspecting feet; and prescribing statins. Multivariate analyses of variance and multiple regression analyses were used to explore changes in cognitions and thereby better understand trial effects. Results Fifty-nine general medical practitioners and 53 practice nurses (intervention: n = 55, 41.98% of trial participants; control: n = 57, 38.26% of trial participants) completed the questionnaire. There were no differences between groups in mean scores for attitudes, subjective norms, PBC or intentions. Control group clinicians had 'normatively-driven' intentions (i.e., related to subjective norm scores), whereas intervention group clinicians had 'attitudinally-driven' intentions (i.e., related to attitude scores) for foot inspection and statin prescription. After controlling for effects of the three predictor variables, this group difference was significant for foot inspection behaviour (trial group × attitude interaction, beta = 0.72, p < 0.05; trial group × subjective norm interaction, beta = -0.65, p < 0.05). Conclusion Attitudinally-driven intentions are proposed to be more consistently translated into action than normatively-driven intentions. This proposition was supported by the findings, thus offering an interpretation of the trial effects. This analytic approach demonstrates the potential of the TPB to explain trial effects in terms of different relationships between variables rather than differences in mean scores. This study illustrates the use of theory-based process evaluation to uncover processes underlying change in implementation trials.

Abstract Background Psychological 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. Methods Psychological 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. Results All 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. Conclusion The 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.

Abstract Background Biomedical research constantly produces new findings but these are not routinely translated into health care practice. One way to address this problem is to develop effective interventions to translate research findings into practice. Currently a range of empirical interventions are available and systematic reviews of these have demonstrated that there is no single best intervention. This evidence base is difficult to use in routine settings because it cannot identify which intervention is most likely to be effective (or cost effective) in a particular situation. We need to establish a scientific rationale for interventions. As clinical practice is a form of human behaviour, theories of human behaviour that have proved useful in other similar settings may provide a basis for developing a scientific rationale for the choice of interventions to translate research findings into clinical practice. The objectives of the study are: to amplify and populate scientifically validated theories of behaviour with evidence from the experience of health professionals; to use this as a basis for developing predictive questionnaires using replicable methods; to identify which elements of the questionnaire (i.e., which theoretical constructs) predict clinical practice and distinguish between evidence compliant and non-compliant practice; and on the basis of these results, to identify variables (based on theoretical constructs) that might be prime targets for behaviour change interventions. Methods We will develop postal questionnaires measuring two motivational, three action and one stage theory to explore five behaviours with 800 general medical and 600 general dental practitioners. We will collect data on performance for each of the behaviours. The relationships between predictor variables (theoretical constructs) and outcome measures (data on performance) in each survey will be assessed using multiple regression analysis and structural equation modelling. In the final phase of the project, the findings from all surveys will be analysed simultaneously adopting a random effects approach to investigate whether the relationships between predictor variables and outcome measures are modified by behaviour, professional group or geographical location.

Introduction: Advanced practice providers (APP), including physicians’ assistants and nurse practitioners, have been increasingly incorporated into emergency department (ED) staffing over the past decade. There is scant literature examining resource utilization and the cost benefit of having APPs in the ED. The objectives of this study were to compare resource utilization in EDs that use APPs in their staffing model with those that do not and to estimate costs associated with the utilized resources.Methods: In this five-year retrospective secondary data analysis of the Emergency Department Benchmarking Alliance (EDBA), we compared resource utilization rates in EDs with and without APPs in non-academic EDs. Primary outcomes were hospital admission and use of computed tomography (CT), radiography, ultrasound, and magnetic resonance imaging (MRI). Costs were estimated using the 2014 physician fee schedule and inpatient payments from the Centers for Medicare and Medicaid Services. We measured outcomes as rates per 100 visits. Data were analyzed using a mixed linear model with repeated measures, adjusted for annual volume, patient acuity, and attending hours. We used the adjusted net difference to project utilization costs between the two groups per 1000 visits.Results: Of the 1054 EDs included in this study, 79% employed APPs. Relative to EDs without APPs, EDs staffing APPs had higher resource utilization rates (use per 100 visits): 3.0 more admissions (95% confidence interval [CI], 2.0–4.1), 1.7 more CTs (95% CI, 0.2–3.1), 4.5 more radiographs (95% CI, 2.2–6.9), and 1.0 more ultrasound (95% CI, 0.3–1.7) but comparable MRI use 0.1 (95% CI, -0.2–0.3). Projected costs of these differences varied among the resource utilized. Compared to EDs without APPs, EDs with APPs were estimated to have 30.4 more admissions per 1000 visits, which could accrue $414,717 in utilization costs.Conclusion: EDs staffing APPs were associated with modest increases in resource utilization as measured by admissions and imaging studies.

The fungus Botrytis cinerea is a polyphagous pathogen that encompasses multiple host-specialized lineages. While several secreted proteins, secondary metabolites and retrotransposons-derived small RNAs have been characterized as virulence factors, their roles in host specialization remain unknown. The aim of this study was to identify the genomic correlates of host-specialization in populations of B. cinerea associated with grapevine and tomato. Using PacBio sequencing, we produced complete assemblies of the genomes of strains Sl3 and Vv3 that represent the French populations T and G1 of B. cinerea, specialized on tomato and grapevine, respectively. Both assemblies revealed 16 core chromosomes that were highly syntenic with chromosomes of the reference strain B05.10. The main sources of variation in gene content were the subtelomeric regions and the accessory chromosomes, especially the chromosome BCIN19 of Vv3 that was absent in Sl3 and B05.10. The repertoires and density of transposable elements were clearly different between the genomes of Sl3 and Vv3 with a larger number of subfamilies (26) and a greater genome coverage in Vv3 (7.7%) than in Sl3 (14 subfamilies, 4.5% coverage). An Helitron-like element was found in almost all subtelomeric regions of the Vv3 genome, in particular in the flanking regions of a highly duplicated gene encoding a Telomere-Linked Helicase, while both features were absent from the Sl3 and B05.10 genomes. Different retrotransposons in the Sl3 and the Vv3 strains resulted in the synthesis of distinct sets of small RNAs. Finally, extending the study to additional strains indicated that the accessory chromosome BCIN19 and the small RNAs producing retrotransposons Copia_4 and Gypsy_7 are common features of the G1 population that are scarcely if ever found in strains isolated from other populations. This research reveals that accessory chromosomes, repertoires of transposons and their derived small RNAs differ between populations of B. cinerea specialized on different hosts. The genomic data characterized in our study pave the way for further studies aiming at investigating the molecular mechanisms underpinning host specialization in a polyphagous pathogen.

The seasonal snowpack across the boreal forest is an important national resource in both Canada and Finland, contributing freshwater for agriculture, human consumption, and hydropower generation. In both countries, satellite passive microwave data are utilized to provide operational information on snow depth and snow water equivalent (SWE) throughout the snow cover season. Airborne passive microwave surveys conducted independently across Finland and western Canada during March and April 2005 and March 2006 provided the opportunity to assess the level of similarity in snowpack physical properties and brightness temperature response to snowpack qualities using two independent data sets. The primary objectives of these campaigns were to determine the influence of small-scale heterogeneity on satellite data, using relatively high resolution airborne measurements, and to assess the Helsinki University of Technology (HUT) snow emission model capability of predicting emitted brightness temperatures under varying snowpack and landscape conditions. Comparisons of brightness temperature emissions over different land cover types showed a clear distinction of wetlands and snow-covered ice from forested and open areas. This is reflected also as a strong relationship between 6.9-GHz measurements and fractional lake cover in both Canada and Finland, with relationships at 18 and 37 GHz being less consistent between data sets. Comparisons of experimental data versus HUT snow emission model predictions showed relatively good agreement between the simulations and airborne data, specifically for the Finnish data set. Index Terms--Radiometry, remote sensing, snow water equivalent (SWE).

Anticoagulant compounds, i.e., derivatives of either 4-hydroxycoumarin (e.g., warfarin, bromadiolone) or indane-l,3-dione (e.g., diphacinone, chlorophacinone), have been in worldwide use as rodenticides for >50 years. These compounds inhibit blood coagulation by repression of the vitamin K reductase reaction (VKOR). Anticoagulant-resistant rodent populations have been reported from many countries and pose a considerable problem for pest control. Resistance is transmitted as an autosomal dominant trait although, until recently, the basic genetic mutation was unknown. Here, we report on the identification of eight different mutations in the VKORC1 gene in resistant laboratory strains of brown rats and house mice and in wild-caught brown rats from various locations in Europe with five of these mutations affecting only two amino acids (Tyr139Cys, Tyr139Ser, Tyr139Phe and Leu128Gln, Leu128Ser). By recombinant expression of VKORC1 constructs in HEK293 cells we demonstrate that mutations at Tyr139 confer resistance to warfarin at variable degrees while the other mutations, in addition, dramatically reduce VKOR activity. Our data strongly argue for at least seven independent mutation events in brown rats and two in mice. They suggest that mutations in VKORC1 are the genetic basis of anticoagulant resistance in wild populations of rodents, although the mutations alone do not explain all aspects of resistance that have been reported. We hypothesize that these mutations, apart from generating structural changes in the VKORC1 protein, may induce compensatory mechanisms to maintain blood clotting. Our findings provide the basis for a DNA-based field monitoring of anticoagulant resistance in rodents.

New multiscale research datasets were acquired in central Saskatchewan, Canada during February 2003 to quantity the effect of spatially heterogeneous land cover and snowpack properties on passive microwave snow water equivalent (SWE) retrievals. Microwave brightness temperature data at various spatial resolutions were acquired from tower and airborne microwave radiometers, complemented by spaceborne Special Sensor Microwave/Imager (SSM/I) data for a 25 x 25 km study area centerd on the Old Jack Pine tower in the Boreal Ecosystem Research and Monitoring Sites (BERMS). To best address scaling issues, the airborne data were acquired over an intensively spaced grid of north-south and east-west oriented flight lines. A coincident ground sampling program characterized in situ snow cover for all representative land cover types found in the study area. A suite of micrometeorological data from seven sites within the study area was acquired to aid interpretation of the passive microwave brightness temperatures. The in situ data were used to determine variability in SWE, snow depth, and density within and between forest stands and land cover types within the 25 x 25 km SSM/I grid cell. Statistically significant subgrid scale SWE variability in this mixed forest environment was controlled by variations in snow depth, not density. Spaceborne passive microwave SWE retrievals derived using the Meteorological Service of Canada land cover sensitive algorithm suite were near the center of the normally distributed in situ measurements, providing a reasonable estimate of the mean grid cell SWE. A realistic level of SWE variability was captured by the high-resolution airborne data, showing that passive microwave retrievals are capable of capturing stand-to-stand SWE variability if the imaging footprint is sufficiently small. Index Terms--Microwave radiometry, scaling, snow water equivalent (SWE).

Snow water equivalent (SWE) is a critical parameter for climatological and hydrological studies over northern high-latitude areas. In this paper, we study the usability of the Helsinki University of Technology (HUT) snow emission model for the estimation of SWE in a Canadian boreal forest environment. The experimental data (airborne passive microwave and ground-based data) were acquired during the Boreal Ecosystem-Atmosphere Study winter field campaign held in February 1994 in Central Canada. Using the experimental dataset, surface brightness temperatures at 18 and 37 GHz (vertical polarization) were simulated with the HUT snow emission model and compared to those acquired by the airborne sensors. The results showed an important underestimation at 37 GHz (-27 K) and an overestimation at 18 GHz (10 K). In this paper, we demonstrate that the errors in the model simulations are due mainly to the extinction coefficient modeling, which is a function of snow grain size. Therefore, we propose a new semiempirical function for the extinction coefficient, based on an empirical correction to the Rayleigh scattering expression. Results presented in this paper show that the proposed function improves the HUT model accuracy to predict brightness temperature in the experimental context considered, with a mean error of [+ or -] 5 K and [+ or -] 9 K, respectively, at 18 and 37 GHz, and a negligible bias (less than 4 K) in both cases. These errors are comparable in magnitude to the accuracy of the radiometers used during the airborne flights. SWE was retrieved using the modified HUT snow emission model based on an iterative inversion technique. SWE was estimated with a mean error of [+ or -] 10 mm and a negligible bias. Only a rough knowledge of mean snow grain size [phi] was required in the inversion procedure. The effects of possible errors on mean snow grain size [phi] are presented and discussed. Index Terms--Boreal Ecosystem-Atmosphere Study (BOREAS), Boreal forest, microwave radiometry, snow emission model, snow water equivalent (SWE).

Vertically polarized 18-, 19-, and 37-GHz brightness temperatures from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) are examined for the August 2-20, 1987 period when data from both sensors are available in the Equal-Area Scalable Earth Grid (EASE-Grid) projection. Colocated measurements over terrestrial surfaces of central North America are compared because of a previously observed inconsistency in derived winter season snow water equivalent across the cross-platform passive microwave time series. The results of this comparison show that SSM/I brightness temperatures systematically exceed SMMR measurements, with the magnitude of this difference dependant on overpass time and brightness temperature magnitude. Regression relationships are determined for adjusting EASE-Grid SMMR data to an SSM/I F8 baseline and are compared to the results of a previous study that examined daily averaged data for the polar regions. These results suggest that adjustment factors are not globally applicable; rather the region and application must be considered. Index Terms--Brightness temperatures, passive microwave, Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave/Imager (SSM/I).