Factors affecting generation Z’s intention to use self-service technology (SST)

As the world moves towards a technological era, various innovations have been introduced across different industries in order to meet customers’ expectations and enhance service quality. Self-service Technology (SST) is one innovation that can be commonly found across industries, and has gained high popularity among users. The main objective of this study is to examine the factors that affect customer intention in using SST, specifically among Generation Z. It examines the relationship between the independent variables of perceived ease of use, perceived usefulness, need of interaction, and technology anxiety and the dependent variable of customer intention in using SST. A questionnaire survey adopted in this study secured the required information from 152 target respondents. Analyses of responses explained 65.5% variances in customer intention of using SST. The research findings established through data analysed with SPSS version 27 application, suggest that perceived ease of use and perceived usefulness have positive significant relationships towards customer intention of using SST, but no significant relationship was found on need of interaction and technology anxiety in customer intention of using SST. Therefore, in order to encourage and attract potential and future users to utilise the service of SST, the system and function of SST need to be upgraded consistently to ensure it brings benefits and usefulness to users. Besides, a company can also educate users on ways to operate the SST in order to enhance the level of ease of use, and to increase the awareness of the usefulness of SST among users. The limitations and recommendations of future study are discussed at the end of the paper

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society