In recent years, cloud storage has become a viable option for businesses to store and retrieve information. This storage service allows its clients releasing from financial burden of hiring professionals to maintain l...
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In recent years, cloud storage has become a viable option for businesses to store and retrieve information. This storage service allows its clients releasing from financial burden of hiring professionals to maintain local databases. However, it comes at a cost of requiring the clients to relinquish control of their data to cloud service providers. There remains the possibility of malicious attacks to make the data no longer correct, fresh nor complete. This paper presents a novel database model called the integrity coded Database (ICDB), where the model allows the client to insert integrity codes (ICs), as well as fake tuples, to an outsourced database, run queries against the server, and verify that the queried data from the cloud is both correct, fresh and complete. We have benchmarked and evaluated six ICDB schemes with different combinations of three IC generation algorithms and two integrity verification modes.
Many randomized controlled trials in which motivational interviewing (MI) is a key intervention make no provision for the assessment of treatment fidelity. This methodological shortcoming makes it impossible to distin...
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Many randomized controlled trials in which motivational interviewing (MI) is a key intervention make no provision for the assessment of treatment fidelity. This methodological shortcoming makes it impossible to distinguish between high- and low-quality MI interventions, and, consequently, to know whether MI provision has contributed to any intervention effects. This article makes some practical recommendations for the collection, selection, coding and reporting of MI fidelity data, as measured using the Motivational Interviewing Treatment integrity code. We hope that researchers will consider these recommendations and include MI fidelity measures in future studies. (C) 2015 Elsevier Inc. All rights reserved.
Motivational Interviewing (MI) is an evidence-based behavior change intervention. The interactional change processes that make MI effective have been increasingly studied using observational coding schemes. We introdu...
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Motivational Interviewing (MI) is an evidence-based behavior change intervention. The interactional change processes that make MI effective have been increasingly studied using observational coding schemes. We introduce an implementation of a software-supported MI coding scheme the Motivational Interviewing Treatment integrity code (MITI) and discuss advantages for process researchers. Furthermore, we compared reliability of the software version with prior results of the paper version. A sample of 14 double-coded dyadic interactions showed good to excellent interrater reliabilities. We selected a second sample of 22 sessions to obtain convergent validity results of the software version: substantial correlations were obtained between the software instrument and the Rating Scales for the Assessment of Empathic Communication. Finally, we demonstrate how the software version can be used to test whether single code frequencies obtained by using intervals shorter than 20 min (i.e., 5 or 10 min) are accurate estimates of the respective code frequencies for the entire session (i.e., behavior slicing). Our results revealed that coding only a 10-min interval provides accurate estimates of the entire session. Our study demonstrates that the software implementation of the MITI is a reliable and valid instrument. We discuss advantages of the software version for process research in MI. (C) 2014 Elsevier Ltd. All rights reserved.
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