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Workload effects of online consultation implementation from a Job-Characteristics Model perspective: a qualitative
Cordet Smart1, Craig Newman2, Lisa Hartill2
1Department of Psychology, University of Exeter, Exeter, UK C.A.Smart2@exeter.ac.uk.
Background:
Online consultation (OC) was previously promoted by the NHS to solve primary care workload challenges. Its implementation was sped up during the COVID-19 pandemic. Workload effects are widely debated. Using a job design perspective may enhance understandings of workload effect.
Aim:
To qualitatively interrogate the workload experiences of primary care staff involved in OC implementation, using the Job Characteristics Model (JCM) to enable the following: a clearer understanding of the primary care staff psychological experiences; and recommendations informing the design of digital implementations and continued use.
Design & Setting:
A qualitative interview study of GP practices using OC within South West England.
Method:
Thirteen participants representing seven practices completed JCM-based semi-structured telephone interviews. An abductive theoretically driven thematic analysis was completed.
Results:
Participants experienced different tasks pre- and post-implementation of OC, and adapted differently to them. Differences included the following: contact modality change, some administrative staff felt removed from patient contact; and in perceived autonomy, some GPs valued increased workload control. Variation in workload experience was affected by job role and practice context, and the form of and rationale for implementation. Use of a psychological model (the JCM) allowed clearer consideration of the effects of change, as well as OC on workload.
Conclusion:
Psychological theory may be helpful in interpreting workload effects of technology implementation such as OC. Designing change to include consideration of technology effects, psychological experiences, differences across roles, and individual and practice contexts may be important for technology implementation and evaluation of its workload effects.
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