Effects of SlowMo, a Blended Digital Therapy Targeting Reasoning, on Paranoia Among People With Psychosis

Ward, Thomas; Emsley, Richard; Greenwood, Kathryn; Freeman, Daniel; Fowler, David; Kuipers, Elizabeth; Bebbington, Paul; Rus-Calafell, Mar; McGourty, Alison; Sacadura, Catarina; Collett, Nicola; James, Kirsty; Hardy, Amy

doi:10.1001/jamapsychiatry.2021.0326

Cited by 55 publications

(61 citation statements)

References 47 publications

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“…Both of these reasoning biases were involved in causal pathways that increased paranoia and the perceived dangerousness of vaccines, thereby reducing vaccine intentions and encouraging conspiracist ideation. Given this potential pathway, future research should investigate whether existing intervention that target these biases and/or paranoia, such as SlowMo and Metacognitive Training [19] , [35] , might be adapted to encourage vaccination and reduce conspiracist ideation. The possibility that these interventions might have these effects is particularly exciting given that existing interventions on vaccine intentions are frequently ineffective [42] or backfire [40] .…”

Section: Discussionmentioning

confidence: 99%

“…Determining whether the aforementioned factors indirectly impact vaccine intentions could support more effective intervention on vaccine uptake. Many of these factors (e.g., paranoia, reasoning biases) are modifiable [19] ; Steffen [35] and are therefore potential novel targets for interventions aiming to increase vaccine uptake. Novel interventions that encourage vaccination would be invaluable because commonly-used strategies are frequently ineffective [42] or backfire.…”

Section: Introductionmentioning

confidence: 99%

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Willingness to vaccinate against SARS-CoV-2: The role of reasoning biases and conspiracist ideation

Bronstein

Kummerfeld

MacDonald

et al. 2022

Vaccine

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Background Widespread vaccine hesitancy and refusal complicate containment of the SARS-CoV-2 pandemic. Extant research indicates that biased reasoning and conspiracist ideation discourage vaccination. However, causal pathways from these constructs to vaccine hesitancy and refusal remain underspecified, impeding efforts to intervene and increase vaccine uptake. Method 554 participants who denied prior SARS-CoV-2 vaccination completed self-report measures of SARS-CoV-2 vaccine intentions, conspiracist ideation, and constructs from the Health Belief Model of medical decision-making (such as perceived vaccine dangerousness) along with tasks measuring reasoning biases (such as those concerning data gathering behavior). Cutting-edge machine learning algorithms (Greedy Fast Causal Inference) and psychometric network analysis were used to elucidate causal pathways to (and from) vaccine intentions. Results Results indicated that a bias toward reduced data gathering during reasoning may cause paranoia, increasing the perceived dangerousness of vaccines and thereby reducing willingness to vaccinate. Existing interventions that target data gathering and paranoia therefore hold promise for encouraging vaccination. Additionally, reduced willingness to vaccinate was identified as a likely cause of belief in conspiracy theories, subverting the common assumption that the opposite causal relation exists. Finally, perceived severity of SARS-CoV-2 infection and perceived vaccine dangerousness (but not effectiveness) were potential direct causes of willingness to vaccinate, providing partial support for the Health Belief Model’s applicability to SARS-CoV-2 vaccine decisions. Conclusions These insights significantly advance our understanding of the underpinnings of vaccine intentions and should scaffold efforts to prepare more effective interventions on hesitancy for deployment during future pandemics.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Willingness to vaccinate against SARS-CoV-2: The role of reasoning biases and conspiracist ideation

Bronstein

Kummerfeld

MacDonald

et al. 2022

Vaccine

View full text Add to dashboard Cite

show abstract

“…For example, the Actissist app targets negative symptoms (e.g., reduced socialization), general psychotic symptoms, mood, and cannabis misuse through offering tools to help with cognitive appraisals, belief conviction, emotions and associated behaviors 153 . Another app ( SlowMo ) targets paranoia through offering tools to help with jumping to conclusions and belief inflexibility as part of blended care 154 . A study of 361 patients with a diagnosis of schizophrenia, randomized to receive either SlowMo therapy or usual care, found no significant difference between groups on the primary outcomes related to paranoia at 24 weeks (the primary end‐point), though significant effects between groups were apparent post‐treatment 154 .…”

Section: Evidence For Digital Psychiatry Within Specific Contextsmentioning

confidence: 99%

“…Another app ( SlowMo ) targets paranoia through offering tools to help with jumping to conclusions and belief inflexibility as part of blended care 154 . A study of 361 patients with a diagnosis of schizophrenia, randomized to receive either SlowMo therapy or usual care, found no significant difference between groups on the primary outcomes related to paranoia at 24 weeks (the primary end‐point), though significant effects between groups were apparent post‐treatment 154 .…”

Section: Evidence For Digital Psychiatry Within Specific Contextsmentioning

confidence: 99%

The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality

et al. 2021

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As the COVID-19 pandemic has largely increased the utilization of telehealth, mobile mental health technologies -such as smartphone apps, virtual reality, chatbots, and social media -have also gained attention. These digital health technologies offer the potential of accessible and scalable interventions that can augment traditional care. In this paper, we provide a comprehensive update on the overall field of digital psychiatry, covering three areas. First, we outline the relevance of recent technological advances to mental health research and care, by detailing how smartphones, social media, artificial intelligence and virtual reality present new opportunities for "digital phenotyping" and remote intervention. Second, we review the current evidence for the use of these new technological approaches across different mental health contexts, covering their emerging efficacy in self-management of psychological well-being and early intervention, along with more nascent research supporting their use in clinical management of long-term psychiatric conditions -including major depression; anxiety, bipolar and psychotic disorders; and eating and substance use disorders -as well as in child and adolescent mental health care. Third, we discuss the most pressing challenges and opportunities towards real-world implementation, using the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework to explain how the innovations themselves, the recipients of these innovations, and the context surrounding innovations all must be considered to facilitate their adoption and use in mental health care systems. We conclude that the new technological capabilities of smartphones, artificial intelligence, social media and virtual reality are already changing mental health care in unforeseen and exciting ways, each accompanied by an early but promising evidence base. We point out that further efforts towards strengthening implementation are needed, and detail the key issues at the patient, provider and policy levels which must now be addressed for digital health technologies to truly improve mental health research and treatment in the future.

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“…Digital technologies also offer novel opportunities for individuals with paranoia: as a very broad generalisation, we might recognise that for some they might reduce anxieties about social engagements with clinicians, while equally appreciating that others might have concerns about the technology itself. Garety et al 2 tested ‘SloMo’, an eight-session digitally supported reasoning intervention, in 361 individuals with psychotic illness randomised to receive this or treatment as usual. The authors state that SloMo adopts an interventionalist-causal approach to enhancing CBT for psychosis by ‘targeting reasoning processes considered causal in psychosis’.…”

mentioning

confidence: 99%

Kaleidoscope

Tracy¹,

Joyce²,

Albertson³

et al. 2021

Br J Psychiatry

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Effects of SlowMo, a Blended Digital Therapy Targeting Reasoning, on Paranoia Among People With Psychosis

Cited by 55 publications

References 47 publications

Willingness to vaccinate against SARS-CoV-2: The role of reasoning biases and conspiracist ideation

Willingness to vaccinate against SARS-CoV-2: The role of reasoning biases and conspiracist ideation

The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality

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