Effect on smoking quit rate of telling patients their lung age: the Step2quit randomised controlled trial

Objective To evaluate the impact of telling patients their estimated spirometric lung age as an incentive to quit smoking.Design Randomised controlled trial.Setting Five general practices in Hertfordshire, England.Participants 561 current smokers aged over 35.Intervention All participants were offered spirometric assessment of lung function. Participants in intervention group received their results in terms of "lung age" (the age of the average healthy individual who would perform similar to them on spirometry). Those in the control group received a raw figure for forced expiratory volume at one second (FEV1). Both groups were advised to quit and offered referral to local NHS smoking cessation services.Main outcome measures The primary outcome measure was verified cessation of smoking by salivary cotinine testing 12 months after recruitment. Secondary outcomes were reported changes in daily consumption of cigarettes and identification of new diagnoses of chronic obstructive lung disease.Results Follow-up was 89%. Independently verified quit rates at 12 months in the intervention and control groups, respectively, were 13.6% and 6.4% (difference 7.2%, P=0.005, 95% confidence interval 2.2% to 12.1%; number needed to treat 14). People with worse spirometric lung age were no more likely to have quit than those with normal lung age in either group. Cost per successful quitter was estimated at 280 pound ((euro) 365, $556). A new diagnosis of obstructive lung disease was made in 17% in the intervention group and 14% in the control group; a total of 16% (89/561) of participants.Conclusion Telling smokers their lung age significantly improves the likelihood of them quitting smoking, but the mechanism by which this intervention achieves its effect is unclear.Trial registration National Research Register N0096173751

Help-Seeking among People with Symptoms of Lung or Colorectal Cancer: Experience and social context

The UK has some of the poorest cancer outcomes in Europe, commonly attributed to diagnostic delays. The patient interval appears to be a substantial contributor to these, with awareness raising campaigns a key strategy for encouraging earlier presentation. However, research has identified a number of barriers to help-seeking beyond awareness, such as fear, concerns about wasting the doctor’s time, personal commitments and access. This research sought to explore social context and help-seeking for people with symptoms of lung or colorectal cancer, comparing the experiences of prompt consulters with those who prolonged presentation. 164 people with symptoms of lung or colorectal cancer completed a questionnaire on symptom experience and social context and 26 of these took part in follow-up semi-structured interviews. People with symptoms of bleeding or pain had shorter patient intervals than those experiencing other symptoms. Those with symptoms which were perceived of as severe body state deviations decided to seek help much quicker than those with general or systemic symptoms, who instead reappraised symptoms over time. Symptom appraisal and help-seeking processes were informed by numerous contributory elements, which were drawn from four contextual domains of a person's life; individual experience, interpersonal relationships, health care system interactions and social and temporal context. They included micro-level elements, such as exposure to carcinogens as well as macro-level factors, like social discourses on morality, calling into question the centrality of awareness-raising campaigns to encourage earlier presentation among the symptomatic population. A novel model The Contextual Model of the Patient Interval, is presented to illustrate this part of the diagnostic pathway. The concept of risk is used to explain how people assess the necessity of help-seeking and the threshold of tolerability is introduced as a means of explaining the timing of help-seeking decision making, based on contextual contributory elements and symptom burden. The assessment of cancer risk is one contributory element which is explored in detail and its incorporation into calculations of the threshold of tolerability is considered. The idea of 'critical incidents' is used to explain the assessment of cancer risk among people who consulted quickly about symptoms, with 'cancer candidacy' being used to explain the cancer risk assessments undertaken by those with prolonged patient intervals. In line with a societal focus on risk generally, public health developments have now resulted in a shift away from contagion and treatment, towards prediction and prevention, under the 'new public health' approach. The focus on risk and prevention has created an environment in which discourses of 'early presentation' and the 'good patient' have emerged. These discourses place moral obligations on people in relation to acceptable responses to symptoms and the need to present oneself as a 'good patient', which are explored through the examples of 'time wasting', the Be Clear on Cancer campaign, and discrepant reports of patient interval length from this study

The Relationship Between Health Adherence Behaviors, Level of Acculturation, Frequency of Cognitive Distortions, and Psychological Distress in Filipino Americans

Nonadherence to medical recommendations is a prevalent concern within the U.S health care system, including among many ethnic minority groups, such as Filipino Americans. The purpose of this study was to investigate the relationship between health adherence behaviors, acculturation level, frequency of cognitive distortions, and psychological distress in Filipino Americans. Filipino American participants (N = 121) completed the following measures: the Health Adherence Behavior Inventory, A Short Acculturation Scale for Filipino Americans, the Patient Health Questionnaire-9th edition, the Generalized Anxiety Disorder 7-item scale, and the Inventory of Cognitive Distortions. Results indicated a significant negative relationship between anxiety symptoms and health adherence behaviors and a significant negative relationship between depression symptoms and health adherence behaviors. Further, psychological distress was found to significantly predict health adherence behaviors, with depression making a significant contribution. There was also a significant positive relationship between acculturation and anxiety, and a significant positive relationship between acculturation and frequency of cognitive distortions. Clinical implications for this population include that the more acculturated a Filipino American is to the host culture, the higher frequency of cognitive distortions. This suggests that acculturation is an important factor to consider within health care as it relates to cognitive distortions. Future recommendations would be to consider the concept of colonial mentality, protective factors, and the development of more acculturation assessment tools for Filipino Americans

An ontology for formal representation of medication adherence-related knowledge : case study in breast cancer

Indiana University-Purdue University Indianapolis (IUPUI)Medication non-adherence is a major healthcare problem that negatively impacts the health and productivity of individuals and society as a whole. Reasons for medication non-adherence are multi-faced, with no clear-cut solution. Adherence to medication remains a difficult area to study, due to inconsistencies in representing medicationadherence behavior data that poses a challenge to humans and today’s computer technology related to interpreting and synthesizing such complex information. Developing a consistent conceptual framework to medication adherence is needed to facilitate domain understanding, sharing, and communicating, as well as enabling researchers to formally compare the findings of studies in systematic reviews. The goal of this research is to create a common language that bridges human and computer technology by developing a controlled structured vocabulary of medication adherence behavior—“Medication Adherence Behavior Ontology” (MAB-Ontology) using breast cancer as a case study to inform and evaluate the proposed ontology and demonstrating its application to real-world situation. The intention is for MAB-Ontology to be developed against the background of a philosophical analysis of terms, such as belief, and desire to be human, computer-understandable, and interoperable with other systems that support scientific research. The design process for MAB-Ontology carried out using the METHONTOLOGY method incorporated with the Basic Formal Ontology (BFO) principles of best practice. This approach introduces a novel knowledge acquisition step that guides capturing medication-adherence-related data from different knowledge sources, including adherence assessment, adherence determinants, adherence theories, adherence taxonomies, and tacit knowledge source types. These sources were analyzed using a systematic approach that involved some questions applied to all source types to guide data extraction and inform domain conceptualization. A set of intermediate representations involving tables and graphs was used to allow for domain evaluation before implementation. The resulting ontology included 629 classes, 529 individuals, 51 object property, and 2 data property. The intermediate representation was formalized into OWL using Protégé. The MAB-Ontology was evaluated through competency questions, use-case scenario, face validity and was found to satisfy the requirement specification. This study provides a unified method for developing a computerized-based adherence model that can be applied among various disease groups and different drug categories

The selection, development, and objective evaluation of tobacco (smoking) concepts as an aid to curriculum construction

Thesis (Ed.D.)--Boston University

Factors affecting access to fruit and vegetables in Chester and the importance of eating healthily: A case study of Blacon and Hoole

The link between diet and the aetiology of chronic diseases such as cancer and coronary heart disease is widely accepted. Consumption of fruit and vegetables is known to have a protective effect on such health issues. Research shows that access to and availability of such foods are key to facilitating change and sustainable healthy behaviours. This study examines the access to fruit and vegetables at a community level using the Chester wards of Blacon and Hoole. A phenomenological perspective was adopted to explore the attitudes, perceptions and behaviours of a sample of Chester based female adults living in Blacon, a ward characteristic of multiple deprivation, or Hoole, a ward characteristic of only health deprivation. Qualitative data was collected using semi-standardised interviews and data was analysed using a framework approach. Few differences emerged between the two wards across all aspects of access. Intakes of fruit and vegetables were consistent with national averages. Access to healthy food in both wards was percived to be 'good'. Time and cost were the barriers most frequently stated to fruit and vegetable consumption. Participants were aware of the need to consume fruit and vegetables but the desire to include them in their diets was equally positive and negative. Information available and level of access was percieved to be good in both wards, however, a lack of follow-up initiatives has meant that a majority of participants were unaware of ways to integrate such information and behaviours into their busy lifestyles

The use of knowledge discovery databases in the identification of patients with colorectal cancer

Colorectal cancer is one of the most common forms of malignancy with 35,000 new patients diagnosed annually within the UK. Survival figures show that outcomes are less favourable within the UK when compared with the USA and Europe with 1 in 4 patients having incurable disease at presentation as of data from 2000.Epidemiologists have demonstrated that the incidence of colorectal cancer is highest on the industrialised western world with numerous contributory factors. These range from a genetic component to concurrent medical conditions and personal lifestyle. In addition, data also demonstrates that environmental changes play a significant role with immigrants rapidly reaching the incidence rates of the host country.Detection of colorectal cancer remains an important and evolving aspect of healthcare with the aim of improving outcomes by earlier diagnosis. This process was initially revolutionised within the UK in 2002 with the ACPGBI 2 week wait guidelines to facilitate referrals form primary care and has subsequently seen other schemes such as bowel cancer screening introduced to augment earlier detection rates. Whereas the national screening programme is dependent on FOBT the standard referral practice is dependent upon a number of trigger symptoms that qualify for an urgent referral to a specialist for further investigations. This process only identifies 25-30% of those with colorectal cancer and remains a labour intensive process with only 10% of those seen in the 2 week wait clinics having colorectal cancer.This thesis hypothesises whether using a patient symptom questionnaire in conjunction with knowledge discovery techniques such as data mining and artificial neural networks could identify patients at risk of colorectal cancer and therefore warrant urgent further assessment. Artificial neural networks and data mining methods are used widely in industry to detect consumer patterns by an inbuilt ability to learn from previous examples within a dataset and model often complex, non-linear patterns. Within medicine these methods have been utilised in a host of diagnostic techniques from myocardial infarcts to its use in the Papnet cervical smear programme for cervical cancer detection.A linkert based questionnaire of those attending the 2 week wait fast track colorectal clinic was used to produce a ‘symptoms’ database. This was then correlated with individual patient diagnoses upon completion of their clinical assessment. A total of 777 patients were included in the study and their diagnosis categorised into a dichotomous variable to create a selection of datasets for analysis. These data sets were then taken by the author and used to create a total of four primary databases based on all questions, 2 week wait trigger symptoms, Best knowledge questions and symptoms identified in Univariate analysis as significant. Each of these databases were entered into an artificial neural network programme, altering the number of hidden units and layers to obtain a selection of outcome models that could be further tested based on a selection of set dichotomous outcomes. Outcome models were compared for sensitivity, specificity and risk. Further experiments were carried out with data mining techniques and the WEKA package to identify the most accurate model. Both would then be compared with the accuracy of a colorectal specialist and GP.Analysis of the data identified that 24% of those referred on the 2 week wait referral pathway failed to meet referral criteria as set out by the ACPGBI. The incidence of those with colorectal cancer was 9.5% (74) which is in keeping with other studies and the main symptoms were rectal bleeding, change in bowel habit and abdominal pain. The optimal knowledge discovery database model was a back propagation ANN using all variables for outcomes cancer/not cancer with sensitivity of 0.9, specificity of 0.97 and LR 35.8. Artificial neural networks remained the more accurate modelling method for all the dichotomous outcomes.The comparison of GP’s and colorectal specialists at predicting outcome demonstrated that the colorectal specialists were the more accurate predictors of cancer/not cancer with sensitivity 0.27 and specificity 0.97, (95% CI 0.6-0.97, PPV 0.75, NPV 0.83) and LR 10.6. When compared to the KDD models for predicting the same outcome, once again the ANN models were more accurate with the optimal model having sensitivity 0.63, specificity 0.98 (95% CI 0.58-1, PPV 0.71, NPV 0.96) and LR 28.7.The results demonstrate that diagnosis colorectal cancer remains a challenging process, both for clinicians and also for computation models. KDD models have been shown to be consistently more accurate in the prediction of those with colorectal cancer than clinicians alone when used solely in conjunction with a questionnaire. It would be ill conceived to suggest that KDD models could be used as a replacement to clinician- patient interaction but they may aid in the acceleration of some patients for further investigations or ‘straight to test’ if used on those referred as routine patients