Explaining the variation in the management of lifestyle risk factors in primary health care: a multilevel cross sectional study

BackgroundDespite evidence for the effectiveness of interventions to modify lifestyle behaviours in the primary health care (PHC) setting, assessment and intervention for these behaviours remains low in routine practice. Little is known about the relative importance of various determinants of practice.This study aimed to examine the relative importance of provider characteristics and attitudes, patient characteristics and consultation factors in determining the rate of assessment and intervention for lifestyle risk factors in PHC.MethodsA prospective audit of assessment and intervention for lifestyle risk factors was undertaken by PHC nurses and allied health providers (n = 57) for all patients seen (n = 732) over a two week period. Providers completed a survey to assess key attitudes related to addressing lifestyle issues. Multi-level logistic regression analysis of patient audit records was undertaken. Associations between variables from both data sources were examined, together with the variance explained by patient and consultation (level 1) and provider (level 2) factors.ResultsThere was significant variance between providers in the assessment and intervention for lifestyle risk factors. The consultation type and reason for the visit were the most important in explaining the variation in assessment practices, however these factors along with patient and provider variables accounted for less than 20% of the variance. In contrast, multi-level models showed that provider factors were most important in explaining the variance in intervention practices, in particular, the location of the team in which providers worked (urban or rural) and provider perceptions of their effectiveness and accessibility of support services. After controlling for provider variables, patients\u27 socio-economic status, the reason for the visit and providers\u27 perceptions of the \u27appropriateness\u27 of addressing risk factors in the consultation were all significantly associated with providing optimal intervention. Together, measured patient consultation and provider variables accounted for most (80%) of the variation in intervention practices between providers.ConclusionThe findings highlight the importance of provider factors such as beliefs and attitudes, team location and work context in understanding variations in the provision of lifestyle intervention in PHC. Further studies of this type are required to identify variables that improve the proportion of variance explained in assessment practices

An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study

BackgroundDespite the effectiveness of brief lifestyle intervention delivered in primary healthcare (PHC), implementation in routine practice remains suboptimal. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about the process by which clinicians\u27 perceptions shape implementation. This study aims to describe a theoretical model to understand how clinicians\u27 perceptions shape the implementation of lifestyle risk factor management in routine practice. The implications of the model for enhancing practices will also be discussed.MethodsThe study analysed data collected as part of a larger feasibility project of risk factor management in three community health teams in New South Wales (NSW), Australia. This included journal notes kept through the implementation of the project, and interviews with 48 participants comprising 23 clinicians (including community nurses, allied health practitioners and an Aboriginal health worker), five managers, and two project officers. Data were analysed using grounded theory principles of open, focused, and theoretical coding and constant comparative techniques to construct a model grounded in the data.ResultsThe model suggests that implementation reflects both clinician beliefs about whether they should (commitment) and can (capacity) address lifestyle issues. Commitment represents the priority placed on risk factor management and reflects beliefs about role responsibility congruence, client receptiveness, and the likely impact of intervening. Clinician beliefs about their capacity for risk factor management reflect their views about self-efficacy, role support, and the fit between risk factor management ways of working. The model suggests that clinicians formulate different expectations and intentions about how they will intervene based on these beliefs about commitment and capacity and their philosophical views about appropriate ways to intervene. These expectations then provide a cognitive framework guiding their risk factor management practices. Finally, clinicians\u27 appraisal of the overall benefits versus costs of addressing lifestyle issues acts to positively or negatively reinforce their commitment to implementing these practices.ConclusionThe model extends previous research by outlining a process by which clinicians\u27 perceptions shape implementation of lifestyle risk factor management in routine practice. This provides new insights to inform the development of effective strategies to improve such practices

Factors influencing participation in a vascular disease prevention lifestyle program among participants in a cluster randomized trial

BackgroundPrevious research suggests that lifestyle intervention for the prevention of diabetes and cardiovascular disease (CVD) are effective, however little is known about factors affecting participation in such programs. This study aims to explore factors influencing levels of participation in a lifestyle modification program conducted as part of a cluster randomized controlled trial of CVD prevention in primary care.MethodsThis concurrent mixed methods study used data from the intervention arm of a cluster RCT which recruited 30 practices through two rural and three urban primary care organizations. Practices were randomly allocated to intervention (n = 16) and control (n = 14) groups. In each practice up to 160 eligible patients aged between 40 and 64 years old, were invited to participate. Intervention practice staff were trained in lifestyle assessment and counseling and referred high risk patients to a lifestyle modification program (LMP) consisting of two individual and six group sessions over a nine month period. Data included a patient survey, clinical audit, practice survey on capacity for preventive care, referral and attendance records at the LMP and qualitative interviews with Intervention Officers facilitating the LMP. Multi-level logistic regression modelling was used to examine independent predictors of attendance at the LMP, supplemented with qualitative data from interviews with Intervention Officers facilitating the program.ResultsA total of 197 individuals were referred to the LMP (63% of those eligible). Over a third of patients (36.5%) referred to the LMP did not attend any sessions, with 59.4% attending at least half of the planned sessions. The only independent predictors of attendance at the program were employment status - not working (OR: 2.39 95% CI 1.15-4.94) and having high psychological distress (OR: 2.17 95% CI: 1.10-4.30). Qualitative data revealed that physical access to the program was a barrier, while GP/practice endorsement of the program and flexibility in program delivery facilitated attendance.ConclusionBarriers to attendance at a LMP for CVD prevention related mainly to external factors including work commitments and poor physical access to the programs rather than an individuals’ health risk profile or readiness to change. Improving physical access and offering flexibility in program delivery may enhance future attendance. Finally, associations between psychological distress and attendance rates warrant further investigation

Should I and Can I?: a mixed methods study of clinician beliefs and attitudes in the management of lifestyle risk factors in primary health care

BackgroundPrimary health care (PHC) clinicians have an important role to play in addressing lifestyle risk factors for chronic diseases. However they intervene only rarely, despite the opportunities that arise within their routine clinical practice. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about this for PHC clinicians working outside general practice. The aim of this study was to explore the beliefs and attitudes of PHC clinicians about incorporating lifestyle risk factor management into their routine care and to examine whether these varied according to their self reported level of risk factor management.MethodsA cross sectional survey was undertaken with PHC clinicians (n = 59) in three community health teams. Clinicians\u27 beliefs and attitudes were also explored through qualitative interviews with a purposeful sample of 22 clinicians from the teams. Mixed methods analysis was used to compare beliefs and attitudes for those with high and low levels of self reported risk factor management.ResultsRole congruence, perceived client acceptability, beliefs about capabilities, perceived effectiveness and clinicians\u27 own lifestyle were key themes related to risk factor management practices. Those reporting high levels of risk factor screening and intervention had different beliefs and attitudes to those PHC clinicians who reported lower levels.ConclusionPHC clinicians\u27 level of involvement in risk factor management reflects their beliefs and attitudes about it. This provides insights into ways of intervening to improve the integration of behavioural risk factor management into routine practice

Biotic interactions influence sediment erodibility on wave exposed sandflats

Biological activities in marine soft-sediments can modify the sedimentary environment through processes that change erosion rates. In low-energy environments, bioturbating macrofauna destabilizes sediments while microbes bind sediments and stabilize them. The degree to which these counter-acting processes influence sediment movement in a physically dynamic environment has not been well quantified. In a field experiment, we established 56 (1 m(2)) plots on an exposed intertidal sandflat. We used shade cloth and manipulated grazing pressure exerted by the deposit-feeding bivalve Macomona liliana (0-200 ind. m(-2)) to alter the microphytobenthic community. Three months post-manipulation, initiation of sediment transport (T-c) and change in sediment erosion rate with increasing bed shear stress (m(e)) were measured. Mean grain size, density of the spionid polychaete Aonides trifida, density of adult M. liliana, and bulk carbohydrate concentration could account for 54% of the variation in T-c (0.3-1.1 N m(-2) s(-1)). Mean grain size was the only significant predictor (p <= 0.01) of me explaining 22% of the variability (6-20 g N-1 s(-1)). T-c was negatively correlated with density of several abundant shallow- dwelling bioturbators (indicating sediment destabilization), but we did not observe the expected increase in T-c with microbial biomass. Furthermore, there was a positive correlation between adult M. liliana and T-c as well as evidence for several positive feedbacks between abundant shallow- dwelling macrofauna and microbial biomass. These study results demonstrate that despite frequent reworking by tidal currents and waves, bioturbating macrofauna are important to initiating sediment transport regardless of their effects on microbial biomass

Single base mutations in the nucleocapsid gene of SARS-CoV-2 affects amplification efficiency of sequence variants and may lead to assay failure

Reverse transcriptase quantitative PCR (RT-qPCR) is the main diagnostic assay used to detect SARS-CoV-2 RNA in respiratory samples. RT-qPCR is performed by specifically targeting the viral genome using complementary oligonucleotides called primers and probes. This approach relies on prior knowledge of the genetic sequence of the target. Viral genetic variants with changes to the primer/probe binding region may reduce the performance of PCR assays and have the potential to cause assay failure. In this work we demonstrate how two single nucleotide variants (SNVs) altered the amplification curve of a diagnostic PCR targeting the Nucleocapsid (N) gene and illustrate how threshold setting can lead to false-negative results even where the variant sequence is amplified. We also describe how in silico analysis of SARS-CoV-2 genome sequences available in the COVID-19 Genomics UK Consortium (COG-UK) and GISAID databases was performed to predict the impact of sequence variation on the performance of 22 published PCR assays. The vast majority of published primer and probe sequences contain sequence mismatches with at least one SARS-CoV-2 lineage. We recommend that visual observation of amplification curves is included as part of laboratory quality procedures, even in high throughput settings where thresholds are set automatically and that in silico analysis is used to monitor the potential impact of new variants on established assays. Ideally comprehensive in silico analysis should be applied to guide selection of highly conserved genomic regions to target with future SARS-CoV-2 PCR assays

Computerised speechreading training for deaf children: A randomised controlled trial

Purpose: We developed and evaluated in a randomised controlled triala computerised speechreading training programme to determine a) whether it is possible to train speechreading in deaf children and b) whether speechreading training results in improvements in phonological and reading skills.Previous studies indicate a relationship between speechreading and reading skill and further suggest this relationshipmay be mediated by improved phonological representations. This is important since many deaf children find learning to read to be very challenging. Method: Sixty-six deaf 5-7 year olds were randomised into speechreading and maths training arms. Each training programme was comprised of10 minutesessionsa day, 4 days a week for 12 weeks. Children were assessed on a battery of language and literacy measures before training, immediately after training, 3 months and 10 months after training. Results: We found no significant benefits for participants who completed the speechreading training, compared to those who completed the maths training, on the speechreading primary outcome measure. However, significantly greater gains were observed in the speechreading training group on one of the secondary measures of speechreading. There was also some evidence of beneficial effects of the speechreading training on phonological representations, however these effects were weaker. No benefits were seen toword reading. Conclusions: Speechreading skill is trainable in deaf children. However, to support early reading, training may need to be longer or embedded in a broader literacy programme. Nevertheless, a training tool that can improve speechreading is likely to be of great interest to professionals working with deaf children

Severity Index for Suspected Arbovirus (SISA) : machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection

Funding: This study was supported, in part, by the Department of Defense Global Emerging Infection Surveillance (https://health.mil/Military-Health-Topics/Combat-Support/Armed-Forces-Health-Surveillance-Branch/Global-Emerging-Infections-Surveillance-and-Response) grant (P0220_13_OT) and the Department of Medicine of SUNY Upstate Medical University (http://www.upstate.edu/medicine/). D.F., M.H. and P.H. were supported by the Ben Kean Fellowship from the American Society for Tropical Medicine and Hygeine (https://www.astmh.org/awards-fellowships-medals/benjamin-h-keen-travel-fellowship-in-tropical-medi). S.J.R and A.M.S-I were supported by NSF DEB EEID 1518681, NSF DEB RAPID 1641145 (https://www.nsf.gov/), A.M.S-I was additionally supported by the Prometeo program of the National Secretary of Higher Education, Science, Technology, and Innovation of Ecuador (http://prometeo.educacionsuperior.gob.ec/).Background: Dengue, chikungunya, and Zika are arboviruses of major global health concern. Decisions regarding the clinical management of suspected arboviral infection are challenging in resource-limited settings, particularly when deciding on patient hospitalization. The objective of this study was to determine if hospitalization of individuals with suspected arboviral infections could be predicted using subject intake data. Methodology/Principal findings: Two prediction models were developed using data from a surveillance study in Machala, a city in southern coastal Ecuador with a high burden of arboviral infections. Data were obtained from subjects who presented at sentinel medical centers with suspected arboviral infection (November 2013 to September 2017). The first prediction model-called the Severity Index for Suspected Arbovirus (SISA)-used only demographic and symptom data. The second prediction model-called the Severity Index for Suspected Arbovirus with Laboratory (SISAL)-incorporated laboratory data. These models were selected by comparing the prediction ability of seven machine learning algorithms; the area under the receiver operating characteristic curve from the prediction of a test dataset was used to select the final algorithm for each model. After eliminating those with missing data, the SISA dataset had 534 subjects, and the SISAL dataset had 98 subjects. For SISA, the best prediction algorithm was the generalized boosting model, with an AUC of 0.91. For SISAL, the best prediction algorithm was the elastic net with an AUC of 0.94. A sensitivity analysis revealed that SISA and SISAL are not directly comparable to one another. Conclusions/Significance: Both SISA and SISAL were able to predict arbovirus hospitalization with a high degree of accuracy in our dataset. These algorithms will need to be tested and validated on new data from future patients. Machine learning is a powerful prediction tool and provides an excellent option for new management tools and clinical assessment of arboviral infection.Publisher PDFPeer reviewe

Pain outcomes in patients with bone metastases from advanced cancer: assessment and management with bone-targeting agents

Bone metastases in advanced cancer frequently cause painful complications that impair patient physical activity and negatively affect quality of life. Pain is often underreported and poorly managed in these patients. The most commonly used pain assessment instruments are visual analogue scales, a single-item measure, and the Brief Pain Inventory Questionnaire-Short Form. The World Health Organization analgesic ladder and the Analgesic Quantification Algorithm are used to evaluate analgesic use. Bone-targeting agents, such as denosumab or bisphosphonates, prevent skeletal complications (i.e., radiation to bone, pathologic fractures, surgery to bone, and spinal cord compression) and can also improve pain outcomes in patients with metastatic bone disease. We have reviewed pain outcomes and analgesic use and reported pain data from an integrated analysis of randomized controlled studies of denosumab versus the bisphosphonate zoledronic acid (ZA) in patients with bone metastases from advanced solid tumors. Intravenous bisphosphonates improved pain outcomes in patients with bone metastases from solid tumors. Compared with ZA, denosumab further prevented pain worsening and delayed the need for treatment with strong opioids. In patients with no or mild pain at baseline, denosumab reduced the risk of increasing pain severity and delayed pain worsening along with the time to increased pain interference compared with ZA, suggesting that use of denosumab (with appropriate calcium and vitamin D supplementation) before patients develop bone pain may improve outcomes. These data also support the use of validated pain assessments to optimize treatment and reduce the burden of pain associated with metastatic bone disease