Reporting ethics committee approval and patient consent by study design in five general medical journals.

BACKGROUND: Authors are required to describe in their manuscripts ethical approval from an appropriate committee and how consent was obtained from participants when research involves human participants. OBJECTIVE: To assess the reporting of these protections for several study designs in general medical journals. DESIGN: A consecutive series of research papers published in the Annals of Internal Medicine, BMJ, JAMA, Lancet and The New England Journal of Medicine between February and May 2003 were reviewed for the reporting of ethical approval and patient consent. Ethical approval, name of approving committee, type of consent, data source and whether the study used data collected as part of a study reported elsewhere were recorded. Differences in failure to report approval and consent by study design, journal and vulnerable study population were evaluated using multivariable logistic regression. RESULTS: Ethical approval and consent were not mentioned in 31% and 47% of manuscripts, respectively. 88 (27%) papers failed to report both approval and consent. Failure to mention ethical approval or consent was significantly more likely in all study designs (except case-control and qualitative studies) than in randomised controlled trials (RCTs). Failure to mention approval was most common in the BMJ and was significantly more likely than in The New England Journal of Medicine. Failure to mention consent was most common in the BMJ and was significantly more likely than in all other journals. No significant differences in approval or consent were found when comparing studies of vulnerable and non-vulnerable participants. CONCLUSION: The reporting of ethical approval and consent in RCTs has improved, but journals are less good at reporting this information for other study designs. Journals should publish this information for all research on human participants

Just picking it up? Young children learning with technology at home

We describe a two-year empirical investigation of three- and four-year-old children's uses of technology at home, based on a survey of 346 families and 24 case studies. Using a sociocultural approach, we discuss the range of technologies children encounter in the home, the different forms their learning takes, the roles of adults and other children, and how family practices support this learning. Many parents believed that they do not teach children how to use technology. We discuss parents' beliefs that their children 'pick up' their competences with technology and identify trial and error, copying and demonstration as typical modes of learning. Parents tend to consider that their children are mainly self-taught and underestimate their own role in supporting learning and the extent to which learning with technology is culturally transmitted within the family

The big picture? Video and the representation of interaction

Researchers who use video to record interactions usually need to translate the video data into another medium at some stage in order to facilitate its analysis and dissemination. This article considers some methodological issues that arise in this process by examining transcripts, diagrams and pictures as examples of different techniques for representing interaction. These examples are used to identify some general principles for the representation of data where video is the source material. The article presents an outline of guided interaction and this is used as a case for illustrating these principles in the context of young children, technology and adults in pre-school settings. Although the article focuses on a specific study and solution, the principles are applicable in all cases where video is used as a source of data for the representation of interaction, whether or not it is technologically mediated

The cleaning of burned and contaminated archaeological maize prior to 87Sr/86Sr analysis

Accurate trace-metal and strontium-isotope analyses of archaeological corn cobs require that metal contaminants be removed prior to chemical analysis. Archaeological cobs are often coated with construction debris, dust, or soilwhich contains mineral particles. In addition, most archaeological cobs are partially or completely burned and the burned parts incorporate mineral debris in their hardened residual structures. Unburned cobs are weak ion exchangers and most metals within a cob are not firmly bound to cob organic matter; therefore, immersing cobs in acids and rinsing them in deionized water to remove mineral contaminants may result in the undesirable loss of metals, including strontium, from the cob. In this paper we show that some cob metal-pair ratios are not substantially changed when the cob is ‘‘cleaned’’ with deionized water, if the water-cob contact time does not exceed five minutes. Additionally, we introduce a method for eliminating mineral contaminants in both burned and unburned cobs, thus rendering them acceptable for strontium-isotope analysis. However, the decontamination procedure results in the rapid non-stoichiometric leaching of trace metals from the unburned cobs and it is possible that most metals will be extracted from the cobs during the lengthy decontamination process. Trace metals, in particular Al and Ca, should be analyzed in order to determine the presence and level of mineral contamination after cleaning

Constraining properties of the black hole population using LISA

LISA should detect gravitational waves from tens to hundreds of systems containing black holes with mass in the range from 10 thousand to 10 million solar masses. Black holes in this mass range are not well constrained by current electromagnetic observations, so LISA could significantly enhance our understanding of the astrophysics of such systems. In this paper, we describe a framework for combining LISA observations to make statements about massive black hole populations. We summarise the constraints that LISA observations of extreme-mass-ratio inspirals might be able to place on the mass function of black holes in the LISA range. We also describe how LISA observations can be used to choose between different models for the hierarchical growth of structure in the early Universe. We consider four models that differ in their prescription for the initial mass distribution of black hole seeds, and in the efficiency of accretion onto the black holes. We show that with as little as 3 months of LISA data we can clearly distinguish between these models, even under relatively pessimistic assumptions about the performance of the detector and our knowledge of the gravitational waveforms.Comment: 12 pages, 3 figures, submitted to Class. Quantum Grav. for proceedings of 8th LISA Symposium; v2 minor changes for consistency with accepted versio

Participation in Decision Making as a Property of Complex Adaptive Systems: Developing and Testing a Measure

Objectives. To (1) describe participation in decision-making as a systems-level property of complex adaptive systems and (2) present empirical evidence of reliability and validity of a corresponding measure. Method. Study 1 was a mail survey of a single respondent (administrators or directors of nursing) in each of 197 nursing homes. Study 2 was a field study using random, proportionally stratified sampling procedure that included 195 organizations with 3,968 respondents. Analysis. In Study 1, we analyzed the data to reduce the number of scale items and establish initial reliability and validity. In Study 2, we strengthened the psychometric test using a large sample. Results. Results demonstrated validity and reliability of the participation in decision-making instrument (PDMI) while measuring participation of workers in two distinct job categories (RNs and CNAs). We established reliability at the organizational level aggregated items scores.We established validity of the multidimensional properties using convergent and discriminant validity and confirmatory factor analysis. Conclusions. Participation in decision making, when modeled as a systems level property of organization, has multiple dimensions and is more complex than is being traditionally measured. Managers can use this model to form decision teams that maximize the depth and breadth of expertise needed and to foster connection among them