Objectives: The main aim of this study was to use text mining on social media to analyze information and gain insight into the health-related concerns of thalassemia patients, thalassemia carriers, and their caregivers. Methods: Posts from two Facebook groups whose members consisted of thalassemia patients, thalassemia carriers, and caregivers in Malaysia were extracted using the Data Miner tool. In this study, a new framework known as Malay-English social media text pre-processing was proposed for performing the steps of pre-processing the noisy mixed language (Malay-English language) of social media posts. Topic modeling was used to identify hidden topics within posts shared among members. Three different topic models—latent Dirichlet allocation (LDA) in GenSim, LDA in MALLET, and latent semantic analysis—were applied to the dataset with and without stemming using Python. Results: LDA in MALLET without stemming was found to be the best topic model for this dataset. Eight topics were identified within the posts shared by members. Of those eight topics, four were newly discovered by this study, and four others corresponded to the findings of previous studies that used an interview approach. Conclusions Topic 2 (the challenges faced by thalassemia patients) was found to be the topic with the highest attention and engagement. Healthcare practitioners and other concerned parties should make an effort to build a stronger support system related to this issue for those affected by thalassemia.

Objectives: The main aim of this study was to use text mining on social media to analyze information and gain insight into the health-related concerns of thalassemia patients, thalassemia carriers, and their caregivers. Methods: Posts from two Facebook groups whose members consisted of thalassemia patients, thalassemia carriers, and caregivers in Malaysia were extracted using the Data Miner tool. In this study, a new framework known as Malay-English social media text pre-processing was proposed for performing the steps of pre-processing the noisy mixed language (Malay-English language) of social media posts. Topic modeling was used to identify hidden topics within posts shared among members. Three different topic models—latent Dirichlet allocation (LDA) in GenSim, LDA in MALLET, and latent semantic analysis—were applied to the dataset with and without stemming using Python. Results: LDA in MALLET without stemming was found to be the best topic model for this dataset. Eight topics were identified within the posts shared by members. Of those eight topics, four were newly discovered by this study, and four others corresponded to the findings of previous studies that used an interview approach. Conclusions Topic 2 (the challenges faced by thalassemia patients) was found to be the topic with the highest attention and engagement. Healthcare practitioners and other concerned parties should make an effort to build a stronger support system related to this issue for those affected by thalassemia.

Introduction: Unsafe blood products cause transfusion-transmissible infections. A good knowledge and perception about blood safety issues is crucial to ensure safe blood supply. The objective is to develop and validate a questionnaire about the knowledge and perception among blood donors on blood safety issues. Method: A cross-sectional study was conducted among 130 blood donors who attended the National Blood Centre, Kuala Lumpur in April and May 2018. The questionnaire was developed in the Malay language after extensive literature search. The self-administrated questionnaire consisted 39 items which required around 20 minutes to complete. The validation involved content validity, construct validity using exploratory factor analysis and reliability using test-retest analysis in IBM SPSS statistics. The same group of respondents was retested after two weeks using the same questionnaire. Results: Content validity was established through multidisciplinary expert meeting and two content reviewers. The factors loadings of all questionnaires were more than 0.40. Knowledge questions were divided into three domains; perception questions were divided into four domains. The intraclass correlation (ICC) values of the test-retest were more than 0.80 for the three knowledge domains and more than 0.60 for the four perception domains. The third domain of the perception section which consisted two questions had the lowest ICC value of 0.686 (95% CI 0.583-0.767). One of the questions was restructured to improve clarity. Conclusions: The questionnaire on knowledge and perception on blood safety issues has good validity and reliability, with appropriate items which warranted its utilization among blood donors.

Introduction: Good knowledge and perception regarding iron supplementation are crucial to ensure adherence to iron therapy. This study aims to develop and validate a questionnaire on the knowledge and perception among pregnant women about oral iron consumption. Method: A self-administrated questionnaire was developed in Malay language through extensive literature search and a face and content validation process. The questionnaire validation involved two parts; Validation Study 1 included item response theory (IRT) and exploratory factor analysis (EFA) for the knowledge and perception items, respectively. Validation Study 2 comprised a repeat IRT analysis for the knowledge items and confirmatory factor analysis (CFA) for the perception items. Results: For the knowledge section, the initial 22 items in Validation Study 1 were reduced to 19 items after the repeat IRT analysis. The remaining 19 items had difficulty and discrimination parameters close to or within the acceptable values. For the perception section, the original 16 items were reduced to 14 in the EFA as two items had a factor loading ≤0.3. The CFA model showed poor fit of items (chi-square p-value <0.05; CFIrobust=0.73; TLIrobust=0.68; RMSEArobust=0.20; and SRMR=0.12). The Cronbach’s alpha for both sections were >0.7, and the intra-class correlation coefficient value in the knowledge and perception sections were 0.74 and 0.87, respectively. Conclusion: The results illustrate good psychometric properties for the knowledge items. However, further confirmatory validation is needed for the perception items. This questionnaire can be a valid and reliable assessment tool for assessing the knowledge of pregnant women regarding oral iron consumption.

Introduction: Cord blood (CB) is rich in hematopoietic stem cells. There has been significant growth in cord blood banks (CBBs) throughout the world. In Malaysia, the CB units cryopreserved in public CBB is below its optimal level. Lack of knowledge about CB banking among mothers in other countries influenced their decision to donate CB, however, there is no local data to support this in Malaysia. Moreover, no validated and reliable tool is available for measuring local women’s knowledge about CB banking. In this study, a questionnaire to assess pregnant women’s knowledge about CB banking was developed and validated. Method: Several steps were taken to develop the knowledge items in the questionnaire which includes comprehensive literature review, content validity by a panel of experts, and face validity by a group of pregnant women. The questionnaire was developed in Malay language and contained 18 items. After modifications, the self-administered questionnaire was distributed to 121 pregnant women to assess its psychometric properties using two-parameter logistic item response theory analysis and internal consistency reliability analysis. Results: The majority of the knowledge items showed acceptable difficulty and discriminatory values. The Cronbach’s alpha and ICC values were 0.831 and 0.887, respectively, indicating good reliability. All 18 knowledge items were retained for the final version of the questionnaire. Conclusion: The newly developed questionnaire demonstrated acceptable psychometric properties and can be used as a reliable tool to assess knowledge about CB banking among pregnant women in the local population.