Objective: This study aimed to assess the association between patient satisfaction and socio-demographic characteristics, as well as the predictors for patient satisfaction.

Methods: This was a cross-sectional study conducted at the medical outpatient department in Hospital Port Dickson from January until October 2019. Convenience sampling method was used to recruit potential study participants. Patient satisfaction was measured using Validated Patient Satisfaction with Pharmacist Services Questionnaire (PSPSQ2.0), consisted of quality of care and interpersonal relationship between pharmacist and patient domains. Descriptive data were presented as mean and standard deviation or numbers and percentages, while Independent Sample t-test, ANOVA and post-hoc analysis, and multiple linear regression were used for inferential data analysis.

Results: There were 37 (25%) diabetes MTAC, 36 (24.3%) respiratory MTAC, and 75 (50.7%) warfarin MTAC patients recruited. On average, the mean overall satisfaction score was 3.30(SD=0.43). The mean satisfaction score in the interpersonal relationship domain [3.35(SD=0.44)] was higher than the quality of care domain [3.26(SD=0.45)]. There was a significant association between gender, education level, and patient satisfaction towards pharmaceutical care service (p<0.05). Gender and education level statistically predicted respondents' satisfaction with MTAC services (p<0.001).

Methods: Childhood cancer patients (6-17 years old) and their caregivers were recruited in a multi-centre, single-arm intervention in Malaysia. A total of 24 child-caregiver dyads have completed the study. This study used PMT-based surveys to collect quantitative data regarding children's motivation to adhere to treatment and perform daily self-care. Additionally, a 20-question multiple-choice quiz was used to determine children's knowledge levels. These surveys were conducted pre-test and post-test. Children's and caregivers' feedback were also gathered post-test as qualitative data.

Results: The results showed that overall, the children's intention to undergo cancer treatment had increased significantly. A significant increase in the intention to perform daily self-care was found among younger children, while older children showed significant improvement in their cancer knowledge levels. The post-test feedback suggested that the game was liked by both children and caregivers and it provided various benefits to children with cancer.

MATERIALS AND METHODS: A technology survey was completed by professionals (n = 36) attending O&M workshops in Malaysia. A revised survey was completed online by O&M specialists (n = 31) primarily in Australia. Qualitative data about technology use came from conferences, workshops and interviews with O&M professionals. Descriptive statistics were analysed together with free-text data.

RESULTS: Limited awareness of apps used by clients, unaffordability of devices, and inadequate technology training discouraged many O&M professionals from employing existing technologies in client programmes or for broader professional purposes. Professionals needed to learn smartphone accessibility features and travel-related apps, and ways to use technology during O&M client programmes, initial professional training, ongoing professional development and research.

METHODS AND ANALYSIS: This multiphase observational study will employ embedded mixed methods with a qualitative/quantitative priority: corating functional vision and O&M during social inquiry. Australian O&M agencies (n=15) provide the sampling frame. O&M specialists will use quota sampling to generate cross-sectional assessment data (n=400) before investigating selected cohorts in outcome studies. Cultural relevance of the VROOM and OMO tools will be investigated in Malaysia, where the tools will inform the design of assistive devices and evaluate prototypes. Exploratory and confirmatory factor analysis, Rasch modelling, cluster analysis and analysis of variance will be undertaken along with descriptive analysis of measurement data. Qualitative findings will be used to interpret VROOM and OMO scores, filter statistically significant results, warrant their generalisability and identify additional relevant constructs that could also be measured.