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Data compatibility in the addiction sciences: an examination of measure commonality.

ABSTRACT: The need for comprehensive analysis to compare and combine data across multiple studies in order to validate and extend results is widely recognized. This paper aims to assess the extent of data compatibility in the substance abuse and addiction (SAA) sciences through an examination of measure commonality, defined as the use of similar measures, across grants funded by the National Institute on Drug Abuse (NIDA) and the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Data were extracted from applications of funded, active grants involving human-subjects research in four scientific areas (epidemiology, prevention, services, and treatment) and six frequently assessed scientific domains. A total of 548 distinct measures were cited across 141 randomly sampled applications. Commonality, as assessed by density (range of 0-1) of shared measurement, was examined. Results showed that commonality was low and varied by domain/area. Commonality was most prominent for (1) diagnostic interviews (structured and semi-structured) for substance use disorders and psychopathology (density of 0.88), followed by (2) scales to assess dimensions of substance use problems and disorders (0.70), (3) scales to assess dimensions of affect and psychopathology (0.69), (4) measures of substance use quantity and frequency (0.62), (5) measures of personality traits (0.40), and (6) assessments of cognitive/neurologic ability (0.22). The areas of prevention (density of 0.41) and treatment (0.42) had greater commonality than epidemiology (0.36) and services (0.32). To address the lack of measure commonality, NIDA and its scientific partners recommend and provide common measures for SAA researchers within the PhenX Toolkit.

SUBMITTER: Conway KP

PROVIDER: S-EPMC4096981 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Data compatibility in the addiction sciences: an examination of measure commonality.

Conway Kevin P KP Vullo Genevieve C GC Kennedy Ashley P AP Finger Matthew S MS Agrawal Arpana A Bjork James M JM Farrer Lindsay A LA Hancock Dana B DB Hussong Andrea A Wakim Paul P Huggins Wayne W Hendershot Tabitha T Nettles Destiney S DS Pratt Joseph J Maiese Deborah D Junkins Heather A HA Ramos Erin M EM Strader Lisa C LC Hamilton Carol M CM Sher Kenneth J KJ

Drug and alcohol dependence 20140520

The need for comprehensive analysis to compare and combine data across multiple studies in order to validate and extend results is widely recognized. This paper aims to assess the extent of data compatibility in the substance abuse and addiction (SAA) sciences through an examination of measure commonality, defined as the use of similar measures, across grants funded by the National Institute on Drug Abuse (NIDA) and the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Data were extrac ...[more]

PMID: 24954640

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Project description:ObjectivesThe objective of this review is to identify all preprint platforms with biomedical and medical scope and to compare and contrast the key characteristics and policies of these platforms.Study design and settingPreprint platforms that were launched up to 25 June 2019 and have a biomedical and medical scope according to MEDLINE's journal selection criteria were identified using existing lists, web-based searches and the expertise of both academic and non-academic publication scientists. A data extraction form was developed, pilot tested and used to collect data from each preprint platform's webpage(s).ResultsA total of 44 preprint platforms were identified as having biomedical and medical scope, 17 (39%) were hosted by the Open Science Framework preprint infrastructure, 6 (14%) were provided by F1000 Research (the Open Research Central infrastructure) and 21 (48%) were other independent preprint platforms. Preprint platforms were either owned by non-profit academic groups, scientific societies or funding organisations (n=28; 64%), owned/partly owned by for-profit publishers or companies (n=14; 32%) or owned by individuals/small communities (n=2; 5%). Twenty-four (55%) preprint platforms accepted content from all scientific fields although some of these had restrictions relating to funding source, geographical region or an affiliated journal's remit. Thirty-three (75%) preprint platforms provided details about article screening (basic checks) and 14 (32%) of these actively involved researchers with context expertise in the screening process. Almost all preprint platforms allow submission to any peer-reviewed journal following publication, have a preservation plan for read access and most have a policy regarding reasons for retraction and the sustainability of the service.ConclusionA large number of preprint platforms exist for use in biomedical and medical sciences, all of which offer researchers an opportunity to rapidly disseminate their research findings onto an open-access public server, subject to scope and eligibility.

Project description:The Autism Impact Measure (AIM) was designed specifically for treatment-outcome assessment in children with ASD, focusing on treatment-relevant aspects of symptom presentation and efficient detection of short-term improvement. The AIM demonstrated strong reliability and validity in initial psychometric studies. The current study evaluated the AIM's sensitivity to change across well-established treatments. The sample included 471 children with ASD (ages 2-14) participating in one of six treatments. The AIM was administered at baseline and 6-week intervals and a battery of domain-specific concurrent measures was also administered. A longitudinal repeated measures design examined the degree to which: (a) AIM domain scores changed over time in response to treatment and (b) change in AIM domains was associated with change in measures of similar constructs. Results across growth curve models indicated that AIM domains are sensitive to change in symptoms across treatment. Across all models, symptoms decreased over time, with some deceleration in rate of improvement. For all AIM domains except Repetitive Behavior, symptoms improved as a function of treatment group. Correlations of change between AIM and other measures varied across domains (from 0.01-0.43 across measures). This was the first large-scale study to systematically evaluate sensitivity to change in a measure of core ASD symptoms. The results provide support for the AIM's ability to detect short-term improvement across symptom domains and indicate that AIM domains are sensitive to change overall and as a function of different treatment conditions. The brief repeated assessment window also highlights the AIM's utility for detecting improvements across short-term treatments. Autism Res 2020, 13: 1867-1879. © 2020 International Society for Autism Research and Wiley Periodicals LLC LAY SUMMARY: Good measures are important for assessing outcomes in children with autism. However, there are few tools for tracking short-term changes in autism symptoms. This study tested a new measure, the Autism Impact Measure (AIM), in a large group of children with autism. The results showed that the AIM appears to be a valid and accurate tool for measuring autism symptoms. The AIM may be a helpful tool for researchers and clinicians interested in tracking short-term improvements in autism symptoms.

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Data compatibility in the addiction sciences: an examination of measure commonality.

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Data compatibility in the addiction sciences: an examination of measure commonality.

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