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Title: Increasing adherence to digital mental health interventions delivered in the workplace
Author: Carolan, Stephany
ISNI:       0000 0004 7431 6155
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2018
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Background: Work related stress, depression and anxiety are common. Despite evidence that these problems can be successfully treated in the workplace, take-up of psychological treatments by workers is low, resulting in many going untreated. One way to address this may be through the use of digital mental health interventions (DMHIs) in the workplace, but there is a lack of information about their appeal and effectiveness. Research questions: 1. What is the evidence for delivering DMHIs in the workplace? 2. What are the advantages and disadvantages to delivering DMHIs in the workplace? 3. What features of DMHIs influence engagement and adherence? What can be done to improve these? 4. What are employers' priorities when selecting DMHIs for their workforce? Method of investigation: Mixed methods were used to answer the research questions. Summary of conclusions: There is evidence for the efficacy of workplace DMHIs, especially if they are delivered over a short timeframe, utilise secondary modalities to deliver the interventions (emails and text messages), and use elements of persuasive technology (self-monitoring and tailoring). Use of online-facilitated discussion groups may increase engagement. Both employees and employers identified convenience, flexibility, and anonymity as advantages of DMHIs. Employers also valued the potential of DMHIs to reach many employees. The main barrier to engagement for employees was lack of time. For employers, barriers to purchasing DMHIs were employees' lack of access to equipment, and their low interest and skills. Cost and effectiveness were priorities for decision makers when purchasing DMHIs. Further work needs to be done with workers and employers to design and deliver DMHIs that meet both their needs.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: RC0489.D35 Data processing. Including computer-assisted psychotherapy