Accuracy of responses from postal surveys about continuing medical education and information behavior: experiences from a survey among German diabetologists

BACKGROUND: Postal surveys are a popular instrument for studies about continuing medical education habits. But little is known about the accuracy of responses in such surveys. The objective of this study was to quantify the magnitude of inaccurate responses in a postal survey among physicians. METHODS: A sub-analysis of a questionnaire about continuing medical education habits and information management was performed. The five variables used for the quantitative analysis are based on a question about the knowledge of a fictitious technical term and on inconsistencies in contingency tables of answers to logically connected questions. RESULTS: Response rate was 52%. Non-response bias is possible but seems not very likely since an association between demographic variables and inconsistent responses could not be found. About 10% of responses were inaccurate according to the definition. CONCLUSION: It was shown that a sub-analysis of a questionnaire makes a quantification of inaccurate responses in postal surveys possible. This sub-analysis revealed that a notable portion of responses in a postal survey about continuing medical education habits and information management was inaccurate

The potential for research-based information in public health: Identifying unrecognised information needs

OBJECTIVE: To explore whether there is a potential for greater use of research-based information in public health practice in a local setting. Secondly, if research-based information is relevant, to explore the extent to which this generates questioning behaviour. DESIGN: Qualitative study using focus group discussions, observation and interviews. SETTING: Public health practices in Norway. PARTICIPANTS: 52 public health practitioners. RESULTS: In general, the public health practitioners had a positive attitude towards research-based information, but believed that they had few cases requiring this type of information. They did say, however, that there might be a potential for greater use. During five focus groups and six observation days we identified 28 questions/cases where it would have been appropriate to seek out research evidence according to our definition. Three of the public health practitioners identified three of these 28 cases as questions for which research-based information could have been relevant. This gap is interpreted as representing unrecognised information needs. CONCLUSIONS: There is an unrealised potential in public health practice for more frequent and extensive use of research-based information. The practitioners did not appear to reflect on the need for scientific information when faced with new cases and few questions of this type were generated

Are decision trees a feasible knowledge representation to guide extraction of critical information from randomized controlled trial reports?

<p>Abstract</p> <p>Background</p> <p>This paper proposes the use of decision trees as the basis for automatically extracting information from published randomized controlled trial (RCT) reports. An exploratory analysis of RCT abstracts is undertaken to investigate the feasibility of using decision trees as a semantic structure. Quality-of-paper measures are also examined.</p> <p>Methods</p> <p>A subset of 455 abstracts (randomly selected from a set of 7620 retrieved from Medline from 1998 – 2006) are examined for the quality of RCT reporting, the identifiability of RCTs from abstracts, and the completeness and complexity of RCT abstracts with respect to key decision tree elements. Abstracts were manually assigned to 6 sub-groups distinguishing whether they were primary RCTs versus other design types. For primary RCT studies, we analyzed and annotated the reporting of intervention comparison, population assignment and outcome values. To measure completeness, the frequencies by which complete intervention, population and outcome information are reported in abstracts were measured. A qualitative examination of the reporting language was conducted.</p> <p>Results</p> <p>Decision tree elements are manually identifiable in the majority of primary RCT abstracts. 73.8% of a random subset was primary studies with a single population assigned to two or more interventions. 68% of these primary RCT abstracts were structured. 63% contained pharmaceutical interventions. 84% reported the total number of study subjects. In a subset of 21 abstracts examined, 71% reported numerical outcome values.</p> <p>Conclusion</p> <p>The manual identifiability of decision tree elements in the abstract suggests that decision trees could be a suitable construct to guide machine summarisation of RCTs. The presence of decision tree elements could also act as an indicator for RCT report quality in terms of completeness and uniformity.</p

Evaluation of molecular descriptors for antitumor drugs with respect to noncovalent binding to DNA and antiproliferative activity

34 pages, 6 additional files, 5 tables, 4 figures.[Background ] Small molecules that bind reversibly to DNA are among the antitumor drugs currently used in chemotherapy. In the pursuit of a more rational approach to cancer chemotherapy based upon these molecules, it is necessary to exploit the interdependency between DNA-binding affinity, sequence selectivity and cytotoxicity. For drugs binding noncovalently to DNA, it is worth exploring whether molecular descriptors, such as their molecular weight or the number of potential hydrogen acceptors/donors, can account for their DNA-binding affinity and cytotoxicity.[Results] Fifteen antitumor agents, which are in clinical use or being evaluated as part of the National Cancer Institute’s drug screening effort, were analyzed in silico to assess the contribution of various molecular descriptors to their DNA-binding affinity, and the capacity of the descriptors and DNA-binding constants for predicting cell cytotoxicity. Equations to predict drug-DNA binding constants and growth-inhibitory concentrations were obtained by multiple regression following rigorous statistical procedures.[Conclusions] For drugs binding reversibly to DNA, both their strength of binding and their cytoxicity are fairly predicted from molecular descriptors by using multiple regression methods. The equations derived may be useful for rational drug design. The results obtained agree with that compounds more active across the National Cancer Institute’s 60-cell line data set tend to have common structural features.Supported by a grant from the former Spanish Ministry of Education and Science (BFU2007-60998) and the FEDER program of the European Community.Peer reviewe

Bicyclic triterpenoid Iripallidal induces apoptosis and inhibits Akt/mTOR pathway in glioma cells

<p>Abstract</p> <p>Background</p> <p>The highly resistant nature of glioblastoma multiforme (GBM) to chemotherapy prompted us to evaluate the efficacy of bicyclic triterpenoid Iripallidal against GBM in vitro.</p> <p>Methods</p> <p>The effect of Iripallidal on proliferation and apoptosis in glioma cell lines was evaluated by MTS, colony formation and caspase-3 activity. The effect of iripallidal to regulate (i) Akt/mTOR and STAT3 signaling (ii) molecules associated with cell cycle and DNA damage was evaluated by Western blot analysis. The effect of Iripallidal on telomerase activity was also determined.</p> <p>Results</p> <p>Iripallidal (i) induced apoptosis, (ii) inhibited Akt/mTOR and STAT3 signaling, (iii) altered molecules associated with cell cycle and DNA damage, (iv) inhibited telomerase activity and colony forming efficiency of glioma cells. In addition, Iripallidal displayed anti-proliferative activity against non-glioma cancer cell lines of diverse origin.</p> <p>Conclusion</p> <p>The ability of Iripallidal to serve as a dual-inhibitor of Akt/mTOR and STAT3 signaling warrants further investigation into its role as a therapeutic strategy against GBM.</p

Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable

<p>Abstract</p> <p>Background</p> <p>By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Naïve Bayes and other machine learning algorithms we are able to distinguish between two classes of protein sequences: those folding to highly-designable conformations, or those folding to poorly- or non-designable conformations.</p> <p>Results</p> <p>First, we generate all possible compact lattice conformations for the specified shape (a hexagon or a triangle) on the 2D triangular lattice. Then we generate all possible binary hydrophobic/polar (H/P) sequences and by using a specified energy function, thread them through all of these compact conformations. If for a given sequence the lowest energy is obtained for a particular lattice conformation we assume that this sequence folds to that conformation. Highly-designable conformations have many H/P sequences folding to them, while poorly-designable conformations have few or no H/P sequences. We classify sequences as folding to either highly – or poorly-designable conformations. We have randomly selected subsets of the sequences belonging to highly-designable and poorly-designable conformations and used them to train several different standard machine learning algorithms.</p> <p>Conclusion</p> <p>By using these machine learning algorithms with ten-fold cross-validation we are able to classify the two classes of sequences with high accuracy – in some cases exceeding 95%.</p

Evaluating the impact of MEDLINE filters on evidence retrieval: study protocol

<p>Abstract</p> <p>Background</p> <p>Rather than searching the entire MEDLINE database, clinicians can perform searches on a filtered set of articles where relevant information is more likely to be found. Members of our team previously developed two types of MEDLINE filters. The 'methods' filters help identify clinical research of high methodological merit. The 'content' filters help identify articles in the discipline of renal medicine. We will now test the utility of these filters for physician MEDLINE searching.</p> <p>Hypothesis</p> <p>When a physician searches MEDLINE, we hypothesize the use of filters will increase the number of relevant articles retrieved (increase 'recall,' also called sensitivity) and decrease the number of non-relevant articles retrieved (increase 'precision,' also called positive predictive value), compared to the performance of a physician's search unaided by filters.</p> <p>Methods</p> <p>We will survey a random sample of 100 nephrologists in Canada to obtain the MEDLINE search that they would first perform themselves for a focused clinical question. Each question we provide to a nephrologist will be based on the topic of a recently published, well-conducted systematic review. We will examine the performance of a physician's unaided MEDLINE search. We will then apply a total of eight filter combinations to the search (filters used in isolation or in combination). We will calculate the recall and precision of each search. The filter combinations that most improve on unaided physician searches will be identified and characterized.</p> <p>Discussion</p> <p>If these filters improve search performance, physicians will be able to search MEDLINE for renal evidence more effectively, in less time, and with less frustration. Additionally, our methodology can be used as a proof of concept for the evaluation of search filters in other disciplines.</p

Challenges in multidisciplinary cancer care among general surgeons in Canada

<p>Abstract</p> <p>Background</p> <p>While many factors can influence the way that cancer care is delivered, including the way that evidence is packaged and disseminated, little research has evaluated how health care professionals who manage cancer patients seek and use this information to identify whether and how this could be supported. Through interviews we identified that general surgeons experience challenges in coordinating care for complex cancer patients whose management is not easily addressed by guidelines, and conducted a population-based survey of general surgeon information needs and information seeking practices to extend these findings.</p> <p>Methods</p> <p>General surgeons with privileges at acute care hospitals in Ontario, Canada were mailed a questionnaire to solicit information needs (task, importance), information seeking (source, frequency of and reasons for use), key challenges and suggested solutions. Non-responders received up to three reminder packages. Significant differences among sub-groups (age, setting) were examined statistically (Kruskal Wallis, Mann Whitney, Chi Square). Standard qualitative methods were used to thematically analyze open-ended responses.</p> <p>Results</p> <p>The response rate was 44.2% (170/385) representing all 14 health regions. System resource constraints (60.4%), comorbidities (56.4%) and physiologic factors (51.8%) were top-ranked issues creating information needs. Local surgical colleagues (84.6%), other local colleagues (82.2%) and the Internet (81.1%) were top-ranked sources of information, primarily due to familiarity and speed of access. No resources were considered to be highly applicable to patient care. Challenges were related to limitations in diagnostics and staging, operative resources, and systems to support multidisciplinary care, together accounting for 76.0% of all reported issues. Findings did not differ significantly by surgeon age or setting of care.</p> <p>Conclusion</p> <p>General surgeons appear to use a wide range of information resources but they may not address the complex needs of many cancer patients. Decision-making is challenged by informational and logistical issues related to the coordination of multidisciplinary care. This suggests that limitations in system capacity may, in part, contribute to variable guideline compliance. Further research is required to evaluate the appropriateness of information seeking, and both concurrent and consecutive mechanisms by which to achieve multidisciplinary care.</p