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Using smart-messaging to enhance mindfulness-based cognitive therapy for cancer patients: A mixed methods proof of concept evaluation.

ABSTRACT: OBJECTIVE:Depression and anxiety lead to reduced treatment adherence, poorer quality of life, and increased care costs amongst cancer patients. Mindfulness-based cognitive therapy (MBCT) is an effective treatment, but dropout reduces potential benefits. Smart-message reminders can prevent dropout and improve effectiveness. However, smart-messaging is untested for MBCT in cancer. This study evaluates smart-messaging to reduce dropout and improve effectiveness in MBCT for cancer patients with depression or anxiety. METHODS:Fifty-one cancer patients attending MBCT in a psycho-oncology service were offered a smart-messaging intervention, which reminded them of prescribed between-session activities. Thirty patients accepted smart-messaging and 21 did not. Assessments of depression and anxiety were taken at baseline, session-by-session, and one-month follow-up. Logistic regression and multilevel modelling compared the groups on treatment completion and clinical effectiveness. Fifteen post-treatment patient interviews explored smart-messaging use. RESULTS:The odds of programme completion were eight times greater for patients using smart-messaging compared with non-users, controlling for age, gender, baseline depression, and baseline anxiety (OR = 7.79, 95% CI 1.75 to 34.58, p = .007). Smart-messaging users also reported greater improvement in depression over the programme (B = -2.33, SEB = .78, p = .004) when controlling for baseline severity, change over time, age, and number of sessions attended. There was no difference between groups in anxiety improvement (B = -1.46, SEB = .86, p = .097). In interviews, smart-messaging was described as a motivating reminder and source of personal connection. CONCLUSIONS:Smart-messaging may be an easily integrated telehealth intervention to improve MBCT for cancer patients.

SUBMITTER: Wells C

PROVIDER: S-EPMC7004102 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Using smart-messaging to enhance mindfulness-based cognitive therapy for cancer patients: A mixed methods proof of concept evaluation.

Wells Chloe C Malins Sam S Clarke Simon S Skorodzien Iwona I Biswas Sanchia S Sweeney Tim T Moghaddam Nima N Levene Jo J

Psycho-oncology 20191125 1

<h4>Objective</h4>Depression and anxiety lead to reduced treatment adherence, poorer quality of life, and increased care costs amongst cancer patients. Mindfulness-based cognitive therapy (MBCT) is an effective treatment, but dropout reduces potential benefits. Smart-message reminders can prevent dropout and improve effectiveness. However, smart-messaging is untested for MBCT in cancer. This study evaluates smart-messaging to reduce dropout and improve effectiveness in MBCT for cancer patients w ...[more]

PMID: 31654533

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Project description:OBJECTIVES:Cognitive behavioural therapy (CBT) can improve symptoms of anxiety and depression, but also reduces the risk of future relapse after therapy completion. However, current CBT relapse prevention methods are resource-intensive and can be limited in clinical practice. This paper investigates a personalized means of reducing relapse using smart-messaging in two settings: research and routine care. DESIGN:Study 1 presents a cohort study comparing a cohort of smart-messaging users versus non-users. Study 2 presents time series follow-up data from a case series of smart-messaging users from clinical practice. METHODS:Fifteen of 56 CBT completers who participated in a trial for the treatment of health anxiety wrote advice they would want if in future they were doing well, experiencing early warning signs of relapse, or experiencing full relapse. Following CBT, participants received weekly text-message requests to rate their well-being. Dependent upon their response, participants received tailored advice they had written, appropriate to the well-being level reported after recovery from health anxiety. Smart-messaging was also trialled in a routine practice sample of 14 CBT completers with anxiety and depression. RESULTS:Across a 12-month follow-up, participants receiving smart-messaging showed greater health improvements than those who did not. Well-being scores showed stability between CBT completion and 6-month follow-up among routine care patients. CONCLUSIONS:These findings suggest that a low-intensity, personalized relapse prevention method can have a clinical benefit following CBT for common mental health problems. PRACTITIONER POINTS:Post-treatment outcomes may be improved using personalized smart-messaging to prevent relapse following cognitive behavioural therapy (CBT) for health anxiety. In clinical practice, post-treatment smart-messaging can be well-used by patients and may help maintain stable well-being in the 6 months after CBT ends. This evidence supports the clinical utility of a brief tailored digital intervention, which can be integrated within routine clinical practice with minimal therapist input. Overall, longer-term post-CBT outcomes may be improved by integrating a smart-messaging intervention at the end of therapy.

Project description:BackgroundThe protection of private data is a key responsibility for research studies that collect identifiable information from study participants. Limiting the scope of data collection and preventing secondary use of the data are effective strategies for managing these risks. An ideal framework for data collection would incorporate feature engineering, a process where secondary features are derived from sensitive raw data in a secure environment without a trusted third party.ObjectiveThis study aimed to compare current approaches based on how they maintain data privacy and the practicality of their implementations. These approaches include traditional approaches that rely on trusted third parties, and cryptographic, secure hardware, and blockchain-based techniques.MethodsA set of properties were defined for evaluating each approach. A qualitative comparison was presented based on these properties. The evaluation of each approach was framed with a use case of sharing geolocation data for biomedical research.ResultsWe found that approaches that rely on a trusted third party for preserving participant privacy do not provide sufficiently strong guarantees that sensitive data will not be exposed in modern data ecosystems. Cryptographic techniques incorporate strong privacy-preserving paradigms but are appropriate only for select use cases or are currently limited because of computational complexity. Blockchain smart contracts alone are insufficient to provide data privacy because transactional data are public. Trusted execution environments (TEEs) may have hardware vulnerabilities and lack visibility into how data are processed. Hybrid approaches combining blockchain and cryptographic techniques or blockchain and TEEs provide promising frameworks for privacy preservation. For reference, we provide a software implementation where users can privately share features of their geolocation data using the hybrid approach combining blockchain with TEEs as a supplement.ConclusionsBlockchain technology and smart contracts enable the development of new privacy-preserving feature engineering methods by obviating dependence on trusted parties and providing immutable, auditable data processing workflows. The overlap between blockchain and cryptographic techniques or blockchain and secure hardware technologies are promising fields for addressing important data privacy needs. Hybrid blockchain and TEE frameworks currently provide practical tools for implementing experimental privacy-preserving applications.

Project description:IntroductionMild cognitive impairment (MCI) not only negatively impacts upon a person's life, but it is also seen as an intermediate stage on the progression to Alzheimer's Disease (AD), and therefore warrants early intervention. However, there is currently no effective pharmacological treatment approved for MCI. There is a paucity of evidence that non-pharmacological interventions such as cognitive training could result in improvements in the daily activities functioning of persons with MCI. Growing evidence has shown that mindfulness meditation increases gray matter volume and concentration in brain regions such as the hippocampus and prefrontal cortex, strengthens brain functional connectivity, and enhances psychological well-being which could be beneficial to counteract the memory and cognitive decline of MCI.AimsWe aim to quantitatively investigate whether mindfulness practice can improve the cognitive function, psychological health, mindfulness and functional abilities in activities of daily living of the MCI participants over time; the relationship between the amount of mindfulness practice and degree of improvement in these health outcomes; and the differential effects and interactions of both formal and informal mindfulness practices. We will also qualitatively address the issues about the MCI participants' and familiar support persons' engagement with the program, the nature of group interactions, their program experience, their perceived effects and expectations of mindfulness practice, and the challenges encountered in practicing mindfulness.MethodsOur study is one of the first mixed-methods longitudinal studies with a 1-year follow-up using a pre- and post-intervention design. It involves the MCI participants and their familiar support person in a customized 8-week group-based mindfulness training program. The outcome measures will use the Montreal Cognitive Assessment, Depression Anxiety Stress Scales, Freiburg Mindfulness Inventory and Bayer Activities of Daily Living Scale. The qualitative methods will include participant observation during the program and semi-structured interviews at post-intervention and 1-year follow-up.SignificanceThis customized MCI group mindfulness training program presents as a promising and feasible non-pharmacological therapeutic intervention option for MCI and a possible preventive strategy for Alzheimer's disease. This study has been registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) (URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366695) and allocated theActrnACTRN12614000820606.

Project description:BackgroundPerinatal mental health symptoms commonly remain underdiagnosed and undertreated in maternity care settings in the United Kingdom, with outbreaks of disease, like the COVID-19 pandemic, further disrupting access to adequate mental health support. Digital technologies may offer an innovative way to support the mental health needs of women and their families throughout the perinatal period, as well as assist midwives in the recognition of perinatal mental health concerns. However, little is known about the acceptability and perceived benefits and barriers to using such technologies.ObjectiveThe aim of this study was to conduct a mixed methods evaluation of the current state of perinatal mental health care provision in the United Kingdom, as well as users' (women and partners) and midwives' interest in using a digital mental health assessment throughout the perinatal period.MethodsWomen, partners, and midwives were recruited to participate in the study, which entailed completing an online survey. Quantitative data were explored using descriptive statistics. Open-ended response data were first investigated using thematic analysis. Resultant themes were then mapped onto the components of the Capability, Opportunity, and Motivation Behavior model and summarized using descriptive statistics.ResultsA total of 829 women, 103 partners, and 90 midwives participated in the study. The provision of adequate perinatal mental health care support was limited, with experiences varying significantly across respondents. There was a strong interest in using a digital mental health assessment to screen, diagnose, and triage perinatal mental health concerns, particularly among women and midwives. The majority of respondents (n=781, 76.42%) expressed that they would feel comfortable or very comfortable using or recommending a digital mental health assessment. The majority of women and partners showed a preference for in-person consultations (n=417, 44.74%), followed by a blended care approach (ie, both in-person and online consultations) (n=362, 38.84%), with fewer participants preferring online-only consultations (n=120, 12.88%). Identified benefits and barriers mainly related to physical opportunity (eg, accessibility), psychological capability (eg, cognitive skills), and automatic motivation (eg, emotions).ConclusionsThis study provides proof-of-concept support for the development and implementation of a digital mental health assessment to inform clinical decision making in the assessment of perinatal mental health concerns in the United Kingdom.

Project description:OBJECTIVES:This study compared the impact of two different 8-week mindfulness based courses (.b Foundations and Mindfulness-Based Stress Reduction (MBSR)), delivered to school teachers, on quantitative (stress, anxiety and depression) and qualitative (experience, acceptability and implementation) outcomes. DESIGN:A mixed-methods design was employed. Matched-paired t-tests were used to examine change from baseline, with imputation conducted to account for those lost to follow-up. Qualitative methods involved 1:1 semistructured interviews (n=10). Thematic analysis was used to explore differences in experience between courses. SETTING:Courses took place in UK primary schools or nearby leisure centres, 1:1 interviews took place via telephone. PARTICIPANTS:44/69 teachers from schools in the UK were recruited from their attendance at mindfulness courses (.b and MBSR). INTERVENTIONS:Participants attended either an MBSR (experiential style learning, 2 hours per week) or .b Foundations (more classroom focused learning, 1.5 hours per week) 8-week mindfulness course. OUTCOME MEASURES:Stress (Perceived Stress Scale), anxiety and depression (Hospital Anxiety and Depression Scale) were evaluated in both groups at baseline (n=44), end of intervention (n=32) and 3-month follow-up (n=19). RESULTS:Both courses were associated with significant reductions in stress (.b 6.38; 95% CI 1.74 to 11.02; MBSR 9.69; 95% CI 4.9 to 14.5) and anxiety (.b 3.36; 95% CI 1.69 to 5.0; MBSR 4.06; 95% CI 2.6 to 5.5). MBSR was associated with improved depression outcomes (4.3; 95% CI 2.5 to 6.11). No differences were found in terms of experience and acceptability. Four main themes were identified including preconceptions, factors influencing delivery, perceived impact and training desires/practical application. CONCLUSION:.b Foundations appears as beneficial as MBSR in anxiety and stress reduction but MBSR may be more appropriate for depression. Consideration over implementation factors may largely improve the acceptability of mindfulness courses for teachers. Further research with larger samples is needed.

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Project description:BackgroundIn the home care industry, the assignment and tracking of care services are controlled by care centers that are centralized in nature and prone to inefficient information transmission. A lack of trust among the involved parties, information opaqueness, and large manual manipulation result in lower process efficiency.ObjectiveThis study aimed to explore and demonstrate the application of blockchain and smart contract technologies to innovate/renovate home care services for harvesting the desired blockchain benefits of process transparency, traceability, and interoperability.MethodsAn object-oriented analysis/design combined with a unified modeling language tool was used to construct the architecture of the proposed home care service system. System feasibility was evaluated via an implementation test, and a questionnaire survey was performed to collect opinions from home care service respondents knowledgeable about blockchain and smart contracts.ResultsAccording to the comparative analysis results, the proposed design outperformed the existing system in terms of traceability, system efficiency, and process automation. Moreover, for the questionnaire survey, the quantitative analysis results showed that the proposed blockchain-based system had significantly (P<.001) higher mean scores (when compared with the existing system) in terms of important factors, including timeliness, workflow efficiency, automatic notifications, insurance functionality, and auditable traceability. In summary, blockchain-based home care service participants will be able to enjoy improved efficiency, better transparency, and higher levels of process automation.ConclusionsBlockchain and smart contracts can provide valuable benefits to the home care service industry via distributed data management and process automation. The proposed system enhances user experiences by mitigating human intervention and improving service interoperability, transparency/traceability, and real-time response to home care service events. Efforts in exploring and integrating blockchain-based home care services with emerging technologies, such as the internet of things and artificial intelligence, are expected to provide further benefits and therefore are subject to future research.

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Using smart-messaging to enhance mindfulness-based cognitive therapy for cancer patients: A mixed methods proof of concept evaluation.

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Using smart-messaging to enhance mindfulness-based cognitive therapy for cancer patients: A mixed methods proof of concept evaluation.

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