Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.Iqbal NStart date: 2020

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    Cross-Cultural Adaptation and Application of the One-Parameter Item Response Model to the Santa Clara Brief Compassion Scale (SCBCS)
    (Springer Science+Business Media, LLC, part of Springer Nature, 2025-09-22) Adu P; Popoola T; Iqbal N; Roemer A; Collings S; Aspin C; Medvedev ON; Simpson CR; Medvedev ON; Krägeloh CU
    Objectives International research has consistently demonstrated the positive impact of compassion towards others on both physical and mental well-being, with significant implications for mindfulness practice. Based on this evidence, we aimed to adapt the Santa Clara Brief Compassion Scale (SCBCS) into German while simultaneously conducting a cross-cultural validation and enhancing its measurement precision using Rasch methodology across samples from Germany, Ghana, India, and New Zealand. Method We applied the unrestricted Partial Credit Model to analyze data from a randomly selected subsample of 500 participants, drawn from a total convenience sample of 1822 individuals recruited from the general populations of Germany, Ghana, India, and New Zealand. Results Our initial analysis of the SCBCS showed significant misfit to the Rasch model (χ2(30) = 58.48, p < 0.001), which was successfully addressed by testlet creation resulting in satisfactory model fit (χ2(24) = 24.80, p = 0.09). This included strict unidimensionality, strong reliability (Person Separation Index = 0.81), and invariance across personal factors, such as country, educational levels, sex, and age. We then developed an algorithm for transforming ordinal scores to interval-level data to enhance the accuracy of the SCBCS. The scale demonstrated sound divergent and convergent validity. Conclusions Our study has validated both the German and English versions of the SCBCS using Rasch methodology. The precision of measuring compassion towards others using the two versions of the SCBCS can be further enhanced by applying the ordinal-to-interval transformation tables developed in this paper.
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    A cross-country network analysis of disease infodemics: Looking through the lens of the COVID-19 pandemic
    (Elsevier Ltd, 2025-02-27) Adu P; Popoola T; Iqbal N; Roemer A; Medvedev ON; Simpson CR
    Infodemics surrounding pandemics and epidemics have persisted for centuries and continue to impede efforts to promote high vaccination coverage. We explored the complex interplay between COVID-19 vaccination attitudes and COVID-19-related infodemics across Germany, Ghana, India, and New Zealand using the novel network analysis. We conducted an online cross-sectional survey and recruited 1822 participants from the general populations of India (n = 411), New Zealand (n = 413), Ghana (n = 523), and Germany (n = 413) to complete COVID-19 infodemic measures and demographics questions. Predictors of less favourable COVID-19 vaccination attitudes included the apocalypse-related infodemic in India, compared to all countries, as well as the not harmful belief of COVID-19 in New Zealand, compared to India and Germany, and in Ghana compared to India. COVID-19 origin-related infodemics were found to positively impact COVID-19 vaccination attitudes in Ghana and New Zealand only. The most influential infodemics in each of the countries studied-Ghana, New Zealand, Germany, and India-were the beliefs in bioweapons, 5G technology, apocalypse, and bat consumption, respectively. Across all countries, there were consistent strong positive connections between the infodemics. Our results suggest that country-specific infodemics significantly impact COVID-19 vaccination attitudes, with variations observed between nations. While the infodemics can reinforce each other and complicate public health efforts during pandemics, understanding the interactions between the central infodemic in each country and others can aid in developing more effective strategies to counter their influences. This highlights the importance of targeted public health interventions that address the unique dynamics of local infodemics during pandemics, epidemics, and Pathogen X outbreaks.
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    Enhancing the Precision of the Self-Compassion Scale Short Form (SCS-SF) with Rasch Methodology
    (Springer Science+Business Media, LLC, part of Springer Nature, 2024-10-28) Adu P; Popoola T; Bartholomew E; Iqbal N; Roemer A; Jurcik T; Collings S; Aspin C; Medvedev ON; Simpson CR
    Objectives: Precise measurement of self-compassion is essential for informing well-being–related policies. Traditional assessment methods have led to inconsistencies in the factor structure of self-compassion scales. We used Rasch methodology to enhance measurement precision and assess the psychometric properties of the Self-Compassion Scale Short Form (SCS-SF), including its invariance across Ghana, Germany, India, and New Zealand. Method: We employed the Partial Credit Rasch model to analyse responses obtained from 1000 individuals randomly selected (i.e. 250 from each country) from a total convenience sample of 1822 recruited from the general populations of Germany, Ghana, India, and New Zealand. Results: The initial identification of local dependency among certain items led to a significant misfitting of the SCS-SF to the Rasch model (χ2 (108) = 260.26, p < 0.001). We addressed this issue by merging locally dependent items, using testlets. The solution with three testlets resulted in optimal fit of the SCS-SF to the Rasch model (χ2 (27) = 23.84, p = 0.64), showing evidence of unidimensionality, strong sample targeting (M = 0.20; SD = 0.72), and good reliability (Person Separation Index = 0.71), including invariance across sociodemographic factors. We then developed ordinal-to-interval conversion tables based on the Rasch model’s person estimates. The SCS-SF showed positive correlations with measures of compassion towards others, optimism, and positive affect, alongside negative associations with psychological distress and negative affect. Conclusions: The current study supports the reliability, as well as the structural, convergent, and external validity of the SCS-SF. By employing the ordinal-to-interval conversion tables published here, the precision of the measure is significantly enhanced, offering a robust tool for investigating self-compassion across different cultures.
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    Color Image Encryption Algorithm Based on Hyper-Chaos and DNA Computing
    (IEEE, 2020-04-24) Malik MGA; Bashir Z; Iqbal N; Imtiaz MA; Gambino O
    In this study, a novel technique using a hyper chaotic dynamical system and DNA computing has been designed with high plaintext sensitivity. In order to reduce cost, a selection procedure using tent map has been employed for generating different key streams from the same chaotic data obtained from the iterations of chaotic dynamical system. After separating the three channels from the input color image, they are both confused and diffused. First of all, these channels are diffused on a decimal level. Then they are permuted. Further, DNA encoding is performed upon these channels. Moreover, DNA level diffusion is performed to further increase the degree of randomness in the image. Lastly, the DNA encoded image is converted into decimal to get the final cipher image. Both the experimental results and security analysis strongly demonstrate the robustness of the proposed scheme. A comparison of the proposed scheme has also been made with other recently developed schemes to show that this scheme outperforms the others in terms of computational cost, time and memory efficiency. Additionally, with the large key space, the proposed scheme can resist any brute force, plaintext and statistical attacks, therefore it is a good fit for the real world applications of the image security.