Ethics of digital technology for mental health

The potential of digital technology to make the lives of people with mental health difficulties better has never been greater | The Mental Elf

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The advent of the smartphone and mobile internet access has created the conditions for an ever-expanding range of opportunities for the use of technology to influence outcomes in health. However, ethical considerations remain for professionals in suggesting the use of such technologies.

Bauer et al.’s (2017) open access paper Ethical perspectives on recommending digital technology for patients with mental illness reviews some of the major ethical concerns presented to medical professionals by this explosion of technological possibilities and explores some of the ways in which new technologies challenge the boundaries between health, commerce and the private and public uses of data.

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E-therapies in England for stress, anxiety or depression: what is being used in the NHS?

Bennion, M.R. et al. (2017) BMJ Open. 7:e014844.

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Objective: To document the range of web and smartphone apps used and recommended for stress, anxiety or depression by the National Health Service (NHS) in England.

Results: A total of 61 (54.95%) out of the then 111 IAPT service providers responded, accounting for 191 IAPT services, and all 51 of the then NHS Mental Health Trusts responded. The results were that 13 different web apps and 35 different smartphone apps for depression, anxiety or stress were available through either referral services or the online NHS Apps Libraries. The apps used and recommended vary by area and by point of access (online library/IAPT/trust).

Conclusions: Future research is required to establish the evidence base for the apps that are being used in the NHS in England. There is a need for service provision to be based on evidence and established guidelines.

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Gamification for health promotion: systematic review of behaviour change techniques in smartphone apps

Edwards, E.A. et al. BMJ Open. 2016(6) e012447. Published online: 4 October 2016

phone-1537916_960_720Objective: Smartphone games that aim to alter health behaviours are common, but there is uncertainty about how to achieve this. We systematically reviewed health apps containing gaming elements analysing their embedded behaviour change techniques.

Methods: Two trained researchers independently coded apps for behaviour change techniques using a standard taxonomy. We explored associations with user ratings and price.

Data sources: We screened the National Health Service (NHS) Health Apps Library and all top-rated medical, health and wellness and health and fitness apps (defined by Apple and Google Play stores based on revenue and downloads). We included free and paid English language apps using ‘gamification’ (rewards, prizes, avatars, badges, leaderboards, competitions, levelling-up or health-related challenges). We excluded apps targeting health professionals.

Results: 64 of 1680 (4%) health apps included gamification and met inclusion criteria; only 3 of these were in the NHS Library. Behaviour change categories used were: feedback and monitoring (n=60, 94% of apps), reward and threat (n=52, 81%), and goals and planning (n=52, 81%). Individual techniques were: self-monitoring of behaviour (n=55, 86%), non-specific reward (n=49, 82%), social support unspecified (n=48, 75%), non-specific incentive (n=49, 82%) and focus on past success (n=47, 73%). Median number of techniques per app was 14 (range: 5–22). Common combinations were: goal setting, self-monitoring, non-specific reward and non-specific incentive (n=35, 55%); goal setting, self-monitoring and focus on past success (n=33, 52%). There was no correlation between number of techniques and user ratings (p=0.07; rs=0.23) or price (p=0.45; rs=0.10).

Conclusions: Few health apps currently employ gamification and there is a wide variation in the use of behaviour change techniques, which may limit potential to improve health outcomes. We found no correlation between user rating (a possible proxy for health benefits) and game content or price. Further research is required to evaluate effective behaviour change techniques and to assess clinical outcomes.

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iCBT may be an effective treatment for PTSD

Tomlin, A. The Mental Elf Blog. Published online: 29 September 2016

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Image source: Neil Webb – Wellcome Images // CC BY-NC-ND 4.0

NICE recommends a range of psychological and drug treatments for PTSD such as trauma-focused cognitive behavioural therapy, but does not recommend computer-based psychotherapies. A recent systematic review and meta-analysis from the Netherlands may persuade the guideline developers to think again.

The aim of this meta-analysis was to evaluate the effectiveness of Internet-delivered Cognitive Behavioural Therapy (iCBT) compared to inactive (waitlist control or treatment-as-usual) and active other interventions in reducing PTSD symptoms.

Overall, the results show that iCBT is superior to waitlist, with a trend suggesting that iCBT is more effective than active controls (e.g. psychoeducation and supportive counselling).

  • iCBT compared to waitlist or treatment as usual (11 comparisons from 10 studies of 1,139 participants) found a moderate pooled effect size (g = 0.71, 95% CI 0.49 to 0.93, P < .001) with moderate heterogeneity
  • iCBT compared to other interventions (3 comparisons from 3 studies) found a small pooled effect size (g = 0.28, 95% CI -0.00 to 0.56, P = .05) with low heterogeneity

The effects were strongest when iCBT interventions were therapist-assisted and longer than eight sessions. This echoes what we know from other web-based psychotherapy evidence.

When comparing iCBT to waitlist, visual inspection of the funnel plot and Egger’s test (P = .34) did not indicate the presence of publication bias.

Read the full overview here

Read the original research here

Mental health provider views about digital technologies in day-to-day practice

Betton, V. The Mental Elf Blog. Published online: 27 September 2016

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The use of digital technologies such as Internet sites and mobile applications, have received much hype in recent years, both in mental health and the NHS more widely. Opinions on these technologies vary; and those with extreme viewpoints see them as either a panacea to overstretched services or as undermining the primacy of the face-to-face patient/clinician relationship.

A recent open access study endeavoured to dig beneath the hype by seeking to understand the opportunities and challenges posed by the use of digital technologies from the perspective of mental health providers. As someone who runs an NHS digital innovation programme, I see how practitioners are often overlooked in the development process. This is a big problem because those same practitioners are often critical in influencing the take-up and use of digital technologies by patients. So understanding digital technologies from a practitioner perspective is a welcome addition to research in this field.

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Exercise and internet-based cognitive–behavioural therapy for depression

Hallgren, M. et al. (2016) The British Journal of Psychiatry. 209(3)

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Background: Evidence-based treatment of depression continues to grow, but successful treatment and maintenance of treatment response remains limited.

Aims: To compare the effectiveness of exercise, internet-based cognitive–behavioural therapy (ICBT) and usual care for depression.

Method: A multicentre, three-group parallel, randomised controlled trial was conducted with assessment at 3 months (post-treatment) and 12 months (primary end-point). Outcome assessors were masked to group allocation. Computer-generated allocation was performed externally in blocks of 36 and the ratio of participants per group was 1:1:1. In total, 945 adults with mild to moderate depression aged 18–71 years were recruited from primary healthcare centres located throughout Sweden. Participants were randomly assigned to one of three 12-week interventions: supervised group exercise, clinician-supported ICBT or usual care by a physician. The primary outcome was depression severity assessed by the Montgomery–Åsberg Depression Rating Scale (MADRS).

Results: The response rate at 12-month follow-up was 84%. Depression severity reduced significantly in all three treatment groups in a quadratic trend over time. Mean differences in MADRS score at 12 months were 12.1 (ICBT), 11.4 (exercise) and 9.7 (usual care). At the primary end-point the group × time interaction was significant for both exercise and ICBT. Effect sizes for both interventions were small to moderate.

Conclusions: The long-term treatment effects reported here suggest that prescribed exercise and clinician-supported ICBT should be considered for the treatment of mild to moderate depression in adults.

Read the abstract here

Systematic review of patients’ participation in and experiences of technology-based monitoring of mental health symptoms in the community

Walsh, S. et al. BMJ Open. 2016. 6:e008362

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Objectives: To review systematically the literature on patients’ experiences of, and participation in, technology-based monitoring of mental health symptoms. This practice was defined as patients monitoring their mental health symptoms, emotions or behaviours outside of routine clinical appointments by submitting symptom data using technology, with feedback arising from the data (for example, supportive messages or symptom summaries, being sent to the patient, clinician or carer).

Design: Systematic review following PRISMA guidelines of studies evaluating technology-based symptom monitoring. Tools from narrative synthesis were used to analyse quantitative findings on participation rates and qualitative findings on patient views.

Data sources: PubMed, EMBASE, PsycINFO, BNI, CINAHL, Cochrane Registers and Web of Science electronic databases were searched using a combination of ‘psychiatry’, ‘symptom monitoring’ and ‘technology’ descriptors. A secondary hand search was performed in grey literature and references.

Results: 57 papers representing 42 studies met the inclusion criteria for the review. Technology-based symptom monitoring was used for a range of mental health conditions, either independently of a specific therapeutic intervention or as an integrated component of therapeutic interventions. The majority of studies reported moderate-to-strong rates of participation, though a third reported lower rates. Qualitative feedback suggests that acceptability of monitoring is related to perceived validity, ease of practice, convenient technology, appropriate frequency and helpfulness of feedback, as well as the impact of monitoring on participants’ ability to manage health and personal relationships.

Conclusions: Such symptom monitoring practices appear to be well accepted and may be a feasible complement to clinical practice. However, there is limited availability of data and heterogeneity of studies. Future research should examine robustly patients’ role in the development and evaluation of technology-based symptom monitoring in order to maximise its clinical utility.

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