Development and validation of a structured survey questionnaire on knowledge, attitude, preventive practice, and treatment-seeking behaviour regarding dengue among the resident population of Sabah, Malaysia: an exploratory factor analysis

Psychometric Properties and Assessment of Knowledge, Attitude, and Practice Towards ChatGPT in Pharmacy Practice and Education: a Study Protocol

ChatGPT represents an advanced conversational artificial intelligence (AI), providing a powerful tool for generating human-like responses that could change pharmacy prospects. This protocol aims to describe the development, validation, and utilization of a tool to assess the knowledge, attitude, and practice towards ChatGPT (KAP-C) in pharmacy practice and education. The development and validation process of the KAP-C tool will include a comprehensive literature search to identify relevant constructs, content validation by a panel of experts for items relevancy using content validity index (CVI) and face validation by sample participants for items clarity using face validity index (FVI), readability and difficulty index using the Flesch-Kincaid Readability Test, Gunning Fog Index, or Simple Measure of Gobbledygook (SMOG), assessment of reliability using internal consistency (Cronbach's alpha), and exploratory factor analysis (EFA) to determine the underlying factor structures (eigenvalues, scree plot analysis, factor loadings, and varimax). The second phase will utilize the validated KAP-C tool to conduct KAP surveys among pharmacists and pharmacy students in selected low- and middle-income countries (LMICs) (Nigeria, Pakistan, and Yemen). The final data will be analyzed descriptively using frequencies, percentages, mean (standard deviation) or median (interquartile range), and inferential statistics like Chi-square or regression analyses using IBM SPSS version 28. A p<0.05 will be considered statistically significant. ChatGPT holds the potential to revolutionize pharmacy practice and education. This study will highlight the psychometric properties of the KAP-C tool that assesses the knowledge, attitude, and practice towards ChatGPT in pharmacy practice and education. The findings will contribute to the potential ethical integration of ChatGPT into pharmacy practice and education in LMICs, serve as a reference to other economies, and provide valuable evidence for leveraging AI advancements in pharmacy.

Development and validation of a structured questionnaire for assessing risk factors of medication non-adherence among pulmonary tuberculosis patients in Indonesia

Background: Medication non-adherence is a significant concern in tuberculosis (TB) treatment, requiring a precise understanding of the associated risk factors. However, there is a lack of appropriate means to assess the risk factors among TB patients in Indonesia, leading to the development and validation of a structured questionnaire for this purpose. Method: This study unfolded in two distinct phases, namely, the first included questionnaire construction through framework development, item generation, item screening, and pretesting (in 50 patients). The second comprised questionnaire validation with 346 participants using confirmatory factor analysis (CFA) and structural equation modeling-partial least squares (SEM-PLS). Additionally, reliability testing was conducted using Cronbach's alpha and composite reliability statistical techniques. Results: In the development phase, 168 items were defined, consisting of sociodemographic characteristics (8 items) and risk factors for medication non-adherence (160 items). Expert evaluation reduced the number of items to 60, which decreased to 22 after performing a pilot study. Subsequent SEM-PLS modeling resulted in the identification of 14 valid items, representing five major risk factors, namely, socioeconomics (4 items), healthcare team (4 items), condition (3 items), therapy (2 items), and patient (1 item). Only condition-related factors were found to influence non-adherence, and all constructs showed good reliability based on Cronbach's alpha (>0.6) and composite reliability (0.7) values. Conclusion: The final 22 items that emerged from this rigorous process indicated a valid and robust questionnaire for assessing risk factors of medication non-adherence among pulmonary tuberculosis patients in Indonesia. The developed questionnaire was positioned to be a valuable tool for healthcare professionals, policymakers, and scientists in creating patient-centered strategies and interventions to address non-adherence.

Machine learning algorithms using national registry data to predict loss to follow- up during tuberculosis treatment

Background

Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in prediction models may be a useful tool to inform healthcare workers about risk of LTFU. Here we developed a score to predict the risk of LTFU during anti-TB treatment (ATT) in a nationwide cohort of cases using clinical data reported to the Brazilian Notifiable Disease Information System (SINAN).

Methods

We performed a retrospective study of all TB cases reported to SINAN between 2015-2022; excluding children (<18 years-old), vulnerable groups or drug-resistant TB. For the score, data before treatment initiation were used. We trained and internally validated three different prediction scoring systems, based on Logistic Regression, Random Forest, and Light Gradient Boosting. Before applying our models we split our data into train (~80% data) and test (~20%), and then we compare model metrics using a test data set.

Results

Of the 243,726 cases included, 41,373 experienced LTFU whereas 202,353 were successfully treated and cured. The groups were different with regards to several clinical and sociodemographic characteristics. The directly observed treatment (DOT) was unbalanced between the groups with lower prevalence in those who were LTFU. Three models were developed to predict LTFU using 8 features (prior TB, drug use, age, sex, HIV infection and schooling level) with different score composition approaches. Those prediction scoring system exhibited an area under the curve (AUC) ranging between 0.71 and 0.72. The Light Gradient Boosting technique resulted in the best prediction performance, weighting specificity, and sensibility. A user-friendly web calculator app was created (https://tbprediction.herokuapp.com/) to facilitate implementation.

Conclusions

Our nationwide risk score predicts the risk of LTFU during ATT in Brazilian adults prior to treatment commencement. This is a potential tool to assist in decision-making strategies to guide resource allocation, DOT indications, and improve TB treatment adherence.

Knowledge, attitude, and practice of healthcare workers regarding dengue fever in Mazandaran Province, northern Iran

Background

Dengue fever is a rapidly emerging infection worldwide with a high public health burden. Adequate training of healthcare workers is essential to warrant the timely provision of health services to improve the outcome of dengue management.

Methods

This is an analytical cross-sectional study, conducted to assess the knowledge, attitudes and practice (KAP) of healthcare workers regarding dengue from April 2021 to March 2022 in Mazandaran Province, northern Iran. Data was collected using a researcher-made structured questionnaire, prepared as Google Forms, and sent to target groups through social media and email. Data analysis was performed by SPSS 22 software using descriptive and inferential statistics (Chi-square) at a significant level of 5%.

Results

Most of the respondents had heard about dengue (83.8%); media (32.7%) and academic education (25%) were the main sources of information. Respondents had less knowledge associated with dengue symptoms (52%) than prevention and control (69%), transmission (72.2%) and clinical management (81%). Based on the 70% cut-off point, the majority of the participants had a good attitude (81%) and practice (73%). However, only 49.6% of the respondents showed good practice regarding dengue local transmission. A significant difference was observed between participants knowledge on clinical management with occupation; attitude with gender and occupation; and practice with gender (p < 0.05).

Conclusion

The results of this study revealed gaps in some dimensions of KAP in healthcare workers, therefore, a greater focus should be placed on future training programs to raise knowledge and attitude leading to sound practice and behavior for adequate management of dengue.

Psychometrics of the Persian version of the COVID-19-related health literacy in the Iranian population

Background

Since the occurrence of the COVID-19 pandemic, information dissemination has increased rapidly. Promoting health literacy is currently crucial to prepare people to respond quickly to situations, such as the COVID-19 pandemic. Due to the importance of health literacy in this critical situation, we are looking for a questionnaire to measure COVID-19 health literacy. The COVID-19 Germany Health Literacy Questionnaire (HLS-COVID-Q22) is an excellent tool, so the study aimed to create a cultural validity of this questionnaire for the Iranian population.

Methods

In this validation study, 880 samples were enrolled using a convenient sampling method. The questionnaire was translated through a backward forwarding procedure. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) were employed for Persian version validity. McDonald's omega (Ω), Cronbach's alpha, and average inter-item correlation (AIC) coefficients were assessed for reliability.

Results

Using EFA on the random half sample (n = 440), the EFA indicated that the scale had four factors: accessing, understanding, appraising, and applying health-related information in the COVID-19 pandemic context, which explained 59.3% of the total variance. CFA was used for the sample's second part (n = 440) to evaluate the goodness of fit of the four-factor solution. CFA showed the model fit. All indices RMSEA = 0.067, CFI = 0.934, IFI = 0.934, PCFI = 0.772, PNFI = 0.747, and CMIN/DF = 2.972 confirmed the model fit. The convergent validity of the HLS-COVID-Q22 was confirmed. McDonald's omega and Cronbach's alpha were very good (α and Ω >0.80).

Conclusion

The Persian version of the HLS-COVID-Q22 had acceptable psychometric properties and is applicable to measure COVID-19 health literacy.

The current status of lean manufacturing in small, medium and large scale manufacturing companies of Karachi, Pakistan

The major purpose of this study was to examine the current status of lean manufacturing in small, medium and large scale manufacturing companies situated in Karachi, Pakistan.The status of lean awareness, implementation, barriers and benefits in manufacturing companies were investigated through the questionnaire survey. The questionnaire was sent to 320 manufacturing companies and a response rate of 40.6% was received. SPSS 22.0 software was used to determine the average mean score for each factor and certain statistical analyses were performed to evaluate the results. It was observed that large organizations and SMEs both are fairly aware of the basic lean concepts but there is a sufficient difference in understanding of lean tools and techniques. Large organizations have a greater understanding and implementation of lean tools and techniques than SMEs. Some tools like 5S, Poka-yoke and TPM were found to have a similar status of implementation in various manufacturing companies irrespective of their size. The results of this study are applicable in Pakistani context, but could vary for other regions of the world, considering the awareness and challenges manufacturing enterprises are facing. To date there has been no research carried out in the context of large, small and medium manufacturing enterprises together in Pakistan, specifically in the Karachi region which investigate the status of lean awareness, implementation, benefits and barriers. Therefore, this study would serve as a foundation for conducting further in depth studies on lean manufacturing in Pakistani manufacturing companies.

Taylor-Robinson A, Wu YS, Aung YN, Low WY, Sim MS, Sekaran SD, Azizan N. Different domains of dengue research in the Philippines: A systematic review and meta-analysis of questionnaire-based studies

Background

Dengue is the most rapidly spreading mosquito-borne viral disease of humans worldwide, including southeast Asia region. This review provides a comprehensive overview of questionnaire-related dengue studies conducted in the Philippines and evaluates their reliability and validity in these surveys.

Methods

A review protocol constructed by a panel of experienced academic reviewers was used to formulate the methodology, research design, search strategy and selection criteria. An extensive literature search was conducted between March–June 2020 in various major electronic biomedical databases including PubMed, EMBASE, MEDLINE and ScienceDirect. A systematic review and meta-analysis (PRISMA) were selected as the preferred item reporting method.

Results

Out of a total of 34 peer-reviewed dengue-related KAP studies that were identified, 15 published from 2000 to April 2020 met the inclusion criteria. Based on the meta-analysis, a poor mean score was obtained for each of knowledge (68.89), attitude (49.86) and preventive practice (64.69). Most respondents were equipped with a good knowledge of the major clinical signs of dengue. Worryingly, 95% of respondents showed several negative attitudes towards dengue prevention, claiming that this was not possible and that enacting preventive practices was not their responsibility. Interestingly, television or radio was claimed as the main source of gaining dengue information (range 50–95%). Lastly, only five articles (33.3%) piloted or pretested their questionnaire before surveying, of which three reported Cronbach’s alpha coefficient (range 0.70 to 0.90).

Conclusion

This review indicates that to combat the growing public health threat of dengue to the Philippines, we need the active participation of resident communities, full engagement of healthcare personnel, promotion of awareness campaigns, and access to safe complementary and alternative medicines. Importantly, the psychometric properties of each questionnaire should be assessed rigorously.