title: Applying Generalisability Theory to examine the distinction between state and trait in the State and Trait Anxiety Inventory (STAI)

authors: Forrest, Sarah Jane

subjects: Generalisability Theory

abstract: Accurate distinction between state and trait anxiety is necessary for monitoring of individual anxiety levels over time and developing effective interventions to reduce anxiety, which is especially important in the current COVID-19 pandemic situation increasing anxiety of the world population. The widely used State and Trait Anxiety Inventory (STAI) with 78,600 Google scholar citations to date, was specifically designed to measure both state and trait anxiety. However, ability of the STAI to accurately distinguish between the two and the overall reliability and generalisability of its assessment scores were not rigorously investigated using appropriate methodology. Generalisability theory (G-theory) is increasingly used as the most robust method to distinguish between state and trait and establish the overall reliability while accounting for specific error sources in the assessment of psychological conditions.

G-theory was applied to the 40-item STAI completed by 139 participants on three occasions separated by two-week intervals. Both subscales of the STAI demonstrated excellent reliability in measuring trait anxiety with high generalizability of scores across occasions (G=0.84-0.92) but fail to distinguish state from trait. This means that the state subscale of the STAI is not suitable to detect changes over time and reliably measure state anxiety. A minor amount of error variance identified in the STAI subscales were mainly attributed to interaction between person and occasion, which reflected state anxiety, and interaction between person, item and occasion. Dynamic aspects of anxiety were identified in both subscales including feelings of satisfaction, nervousness, feeling pleasant, restlessness, perceived failure, lack of calmness, feeling insecure, feeling inadequate and sensitivity to disappointments. This study derived a sensitive state anxiety scale using G-theory that includes items the most sensitive to state changes. State anxiety can be measured with higher accuracy by using the proposed short state scale without modifications of the original STAI format. Dynamic aspects of anxiety identified using G-theory, are more amendable, and proposed as the primary target of interventions aiming at effectively reducing anxiety. Further enhancement of state anxiety measurement informed by G- theory is warranted. Overall, this study contributed to enhanced assessment of state and trait anxiety and informs psychological interventions aiming at more effective reduction of
anxiety.

text: Applying Generalisability Theory to examine the distinction between state and trait in the State and Trait Anxiety Inventory (STAI) Accurate distinction between state and trait anxiety is necessary for monitoring of individual anxiety levels over time and developing effective interventions to reduce anxiety, which is especially important in the current COVID-19 pandemic situation increasing anxiety of the world population. The widely used State and Trait Anxiety Inventory (STAI) with 78,600 Google scholar citations to date, was specifically designed to measure both state and trait anxiety. However, ability of the STAI to accurately distinguish between the two and the overall reliability and generalisability of its assessment scores were not rigorously investigated using appropriate methodology. Generalisability theory (G-theory) is increasingly used as the most robust method to distinguish between state and trait and establish the overall reliability while accounting for specific error sources in the assessment of psychological conditions.

G-theory was applied to the 40-item STAI completed by 139 participants on three occasions separated by two-week intervals. Both subscales of the STAI demonstrated excellent reliability in measuring trait anxiety with high generalizability of scores across occasions (G=0.84-0.92) but fail to distinguish state from trait. This means that the state subscale of the STAI is not suitable to detect changes over time and reliably measure state anxiety. A minor amount of error variance identified in the STAI subscales were mainly attributed to interaction between person and occasion, which reflected state anxiety, and interaction between person, item and occasion. Dynamic aspects of anxiety were identified in both subscales including feelings of satisfaction, nervousness, feeling pleasant, restlessness, perceived failure, lack of calmness, feeling insecure, feeling inadequate and sensitivity to disappointments. This study derived a sensitive state anxiety scale using G-theory that includes items the most sensitive to state changes. State anxiety can be measured with higher accuracy by using the proposed short state scale without modifications of the original STAI format. Dynamic aspects of anxiety identified using G-theory, are more amendable, and proposed as the primary target of interventions aiming at effectively reducing anxiety. Further enhancement of state anxiety measurement informed by G- theory is warranted. Overall, this study contributed to enhanced assessment of state and trait anxiety and informs psychological interventions aiming at more effective reduction of
anxiety.

year: 2020

title: Effect of iron on grain refinement of high-purity Mg–Al alloys

authors: Cao, Peng

subjects: Magnesium alloys

abstract: The effect of iron on the grain refinement of high-purity Mg–3%Al and Mg–9%Al alloys has been investigated using anhydrous FeCl3 as an iron additive at 750 °C in carbon-free aluminium titanite crucibles. It was shown that grain refinement was readily achievable for both alloys. Fe- and Al-rich intermetallic particles were observed in many magnesium grains.

text: Effect of iron on grain refinement of high-purity Mg–Al alloys The effect of iron on the grain refinement of high-purity Mg–3%Al and Mg–9%Al alloys has been investigated using anhydrous FeCl3 as an iron additive at 750 °C in carbon-free aluminium titanite crucibles. It was shown that grain refinement was readily achievable for both alloys. Fe- and Al-rich intermetallic particles were observed in many magnesium grains.

year: 2004-07

title: Understanding Māori rights and interests in intellectual property arising from research and innovation

authors: Sterling, Rogena

abstract: In the era of big data, the significance of data as a raw material for production and a source of societal and economic value has grown immensely. Advances in data mining, analytics, computing power, and storage capacity have facilitated broader access and utilization of big data for corporate and governmental purposes. This surge aligns with the knowledge economy, emphasizing knowledge-intensive activities to drive economic growth, a focus underscored in the latest Government Strategy.

However, as the knowledge economy expands, concerns arise about equity, Treaty partnerships, and the need to address issues of Māori data sovereignty and Indigenous data sovereignty. Discussions around Māori data sovereignty emphasize the importance of Māori control over various forms of Māori data, such as Mātauranga Māori, taonga species, and administrative data. Organizations like Te Mana Raraunga have been instrumental in developing principles and audit tools to support Māori data sovereignty.

Amidst these developments, questions have surfaced about the protection of Māori intellectual property (IP) within Aotearoa New Zealand, particularly outlined in the WAI262 report. This report, funded by Genomics Aotearoa and the National Science Challenge Science for Technological Innovation, aims to address these concerns. The project includes a literature review examining national legislation and international agreements constituting New Zealand's Intellectual Property Rights regime. This review explores how these frameworks safeguard Māori IP rights concerning Māori data, genomic data, and Mātauranga Māori. The second component involves a survey targeting research institutions to assess the presence of IP policies protecting Māori data in research and innovation processes.

The report provides a concise summary of the literature review and survey findings, with the overarching goal of assisting institutions in developing policies that safeguard Māori rights over their knowledge and data. The objective is to ensure equitable benefit-sharing throughout the innovation processes and address the evolving landscape of data sovereignty.

text: Understanding Māori rights and interests in intellectual property arising from research and innovation In the era of big data, the significance of data as a raw material for production and a source of societal and economic value has grown immensely. Advances in data mining, analytics, computing power, and storage capacity have facilitated broader access and utilization of big data for corporate and governmental purposes. This surge aligns with the knowledge economy, emphasizing knowledge-intensive activities to drive economic growth, a focus underscored in the latest Government Strategy.

However, as the knowledge economy expands, concerns arise about equity, Treaty partnerships, and the need to address issues of Māori data sovereignty and Indigenous data sovereignty. Discussions around Māori data sovereignty emphasize the importance of Māori control over various forms of Māori data, such as Mātauranga Māori, taonga species, and administrative data. Organizations like Te Mana Raraunga have been instrumental in developing principles and audit tools to support Māori data sovereignty.

Amidst these developments, questions have surfaced about the protection of Māori intellectual property (IP) within Aotearoa New Zealand, particularly outlined in the WAI262 report. This report, funded by Genomics Aotearoa and the National Science Challenge Science for Technological Innovation, aims to address these concerns. The project includes a literature review examining national legislation and international agreements constituting New Zealand's Intellectual Property Rights regime. This review explores how these frameworks safeguard Māori IP rights concerning Māori data, genomic data, and Mātauranga Māori. The second component involves a survey targeting research institutions to assess the presence of IP policies protecting Māori data in research and innovation processes.

The report provides a concise summary of the literature review and survey findings, with the overarching goal of assisting institutions in developing policies that safeguard Māori rights over their knowledge and data. The objective is to ensure equitable benefit-sharing throughout the innovation processes and address the evolving landscape of data sovereignty.

year: 2021-05