Getting to More Effective Weight Management in Antipsychotic-Treated Youth: A Survey of Barriers and Preferences

Nicol, Ginger E.; Worsham, Elizabeth; Haire‐Joshu, Debra; Duncan, Alexis E.; Schweiger, Julia; Yingling, Michael; Lenze, Eric J.

doi:10.1089/chi.2015.0076

Cited by 16 publications

(8 citation statements)

References 30 publications

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“…Our results suggest adaptations to traditional health coaching delivery models, where existing clinical staff are trained and responsible for implementation, may benefit from the introduction of technology. These results are consistent with previous reports in SMI populations suggesting openness to the use of technology for delivering health behavior change interventions, which have been shown to boost treatment engagement in non-mentally ill obese adults ( 1 , 35 , 36 ).…”

Section: Discussionsupporting

confidence: 92%

“…Obesity is two to three times more prevalent in people with severe mental illness (SMI), contributing to higher rates of obesity-related conditions like type 2 diabetes and cardiovascular disease (CVD) compared to the general population ( 1 ). This burden of cardiometabolic risk contributes to a 10–15 year mortality gap between those with SMI and the general population ( 2 ).…”

Section: Introductionmentioning

confidence: 99%

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Using Innovation-Corps (I-Corps™) Methods to Adapt a Mobile Health (mHealth) Obesity Treatment for Community Mental Health Settings

Haddad

D’Andrea

Ricchio

et al. 2022

Front. Digit. Health

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BackgroundWe employed Innovation Corps (I-Corps™) methods to adaptation of a mobile health (mHealth) short-message-system (SMS) -based interactive obesity treatment approach (iOTA) for adults with severe mentall illness receiving care in community settings.MethodsWe hypothesized “jobs to be done” in three broad stakeholder groups: “decision makers” (DM = state and community clinic administrators), “clinician consumers” (CC = case managers, peer supports, nurses, prescribers) and “service consumers” (SC = patients, peers and family members). Semistructured interviews (N = 29) were recorded and transcribed ver batim and coded based on pragmatic-variant grounded theory methods.ResultsFour themes emerged across groups: education, inertia, resources and ownership. Sub-themes in education and ownership differed between DM and CC groups on implementation ownership, intersecting with professional development, suggesting the importance of training and supervision in scalability. Sub-themes in resources and intertia differed between CC and SC groups, suggesting illness severity and access to healthy food as major barriers to engagement, whereas the SC group identified the need for enhanced emotional support, in addition to pragmatic skills like menu planning and cooking, to promote health behavior change. Although SMS was percieved as a viable education and support tool, CC and DM groups had limited familiarity with use in clinical care delivery.ConclusionsBased on customer discovery, the characteristics of a minimum viable iOTA for implementation, scalability and sustainability include population- and context-specific adaptations to treatment content, interventionist training and delivery mechanism. Successful implementation of an SMS-based intervention will likely require micro-adaptations to fit specific clinical settings.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Using Innovation-Corps (I-Corps™) Methods to Adapt a Mobile Health (mHealth) Obesity Treatment for Community Mental Health Settings

Haddad

D’Andrea

Ricchio

et al. 2022

Front. Digit. Health

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“…Subsequent visits followed the same format, with the 30-minute discussion including session-specific content (session 2: meal planning and nutrition, session 3: physical activity, and session 4: skills for long-term health behavior change). The order of the content delivered in the sessions was determined based on prior behavioral weight loss treatment development experience in youth and adults with SMI treated in community settings, where qualitative efforts identified the greatest health behavior knowledge and skill deficits in this population were understanding nutrition and healthy meal planning [ 46 , 53 ].…”

Section: Methodsmentioning

confidence: 99%

Use of an Interactive Obesity Treatment Approach in Individuals With Severe Mental Illness: Feasibility, Acceptability, and Proposed Engagement Criteria

Nicol¹,

Jansen²,

Haddad³

et al. 2022

JMIR Form Res

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Background Digital and mobile health interventions are increasingly being used to support healthy lifestyle change, including in certain high-risk populations such as those with severe mental illnesses (SMIs). Life expectancy in this population lags 15 years behind counterparts in the general population, primarily due to obesity-related health conditions. Objective We tested the feasibility and usability of a 12-week interactive obesity treatment approach (iOTA) to adults with chronic SMIs (depression, bipolar disorder and schizophrenia spectrum disorder) receiving treatment in community settings. The iOTA incorporates short message service (SMS) text messages to supplement monthly in-person health coaching. Methods Factors hypothesized to be associated with weight change were illness severity and treatment engagement. Severe psychiatric symptoms were defined as baseline Clinical Global Impression severity score of >5. Criterion engagement was defined as a text messaging response rate >80% during the first 4 weeks of treatment. Disordered eating, assessed with the Loss of Control Over Eating Scores, was also evaluated. Participants provided qualitative data, further informing assessment of intervention feasibility, usability, and acceptability. Results A total of 26 participants were enrolled. The mean age was 48.5 (SD 15.67) years; 40% (10/26) were Black and 60% (15/26) female. Participants with lower symptom severity and adequate engagement demonstrated significantly decreased weight (F1,16=22.54, P<.001). Conversely, high symptom severity and lower text message response rates were associated with trend-level increases in weight (F1,7=4.33, P=.08). Loss-of-control eating was not observed to impact treatment outcome. Participants voiced preference for combination of live health coaching and text messaging, expressing desire for personalized message content. Conclusions These results demonstrate the feasibility of delivering an adapted iOTA to SMI patients receiving care in community settings and suggest testable criteria for defining sufficient treatment engagement and psychiatric symptom severity, two factors known to impact weight loss outcomes. These important findings suggest specific adaptations may be needed for optimal treatment outcomes in individuals with SMI.

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“…These individuals expressed preferences for digital self-monitoring and support delivered via a mobile device over in-person treatment. Moreover, participants indicated that needs and barriers varied from day to day, and that an intervention adaptive to their dynamically changing needs was important [ 13 ]. As the availability of mobile devices among mentally ill youth increases [ 14 ], this mode of treatment becomes a feasible way to increase access and engagement [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment

Nicol

Ricchio

Metts

et al. 2020

JMIR Mhealth Uhealth

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Background Mobile health apps are promising vehicles for delivering scalable health behavior change interventions to populations that are otherwise difficult to reach and engage, such as young adults with psychiatric conditions. To improve uptake and sustain consumer engagement, mobile health interventions need to be responsive to individuals’ needs and preferences, which may change over time. We previously created an ecological daily needs assessment to capture microprocesses influencing user needs and preferences for mobile health treatment adaptation. Objective The objective of our study was to test the utility of a needs assessment anchored within a mobile app to capture individualized, contextually relevant user needs and preferences within the framework of a weight management mobile health app. Methods Participants with an iOS device could download the study app via the study website or links from social media. In this fully remote study, we screened, obtained informed consent from, and enrolled participants through the mobile app. The mobile health framework included daily health goal setting and self-monitoring, with up to 6 daily prompts to determine in-the-moment needs and preferences for mobile health–assisted health behavior change. Results A total of 24 participants downloaded the app and provided e-consent (22 female; 2 male), with 23 participants responding to at least one prompt over 2 weeks. The mean length of engagement was 5.6 (SD 4.7) days, with a mean of 2.8 (1.1) responses per day. We observed individually dynamic needs and preferences, illustrating daily variability within and between individuals. Qualitative feedback indicated preferences for self-adapting features, simplified self-monitoring, and the ability to personalize app-generated message timing and content. Conclusions The technique provided an individually dynamic and contextually relevant alternative and complement to traditional needs assessment for assessing individually dynamic user needs and preferences during treatment development or adaptation. The results of this utility study suggest the importance of personalization and learning algorithms for sustaining app engagement in young adults with psychiatric conditions. Further study in broader user populations is needed.

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Getting to More Effective Weight Management in Antipsychotic-Treated Youth: A Survey of Barriers and Preferences

Cited by 16 publications

References 30 publications

Using Innovation-Corps (I-Corps™) Methods to Adapt a Mobile Health (mHealth) Obesity Treatment for Community Mental Health Settings

Using Innovation-Corps (I-Corps™) Methods to Adapt a Mobile Health (mHealth) Obesity Treatment for Community Mental Health Settings

Use of an Interactive Obesity Treatment Approach in Individuals With Severe Mental Illness: Feasibility, Acceptability, and Proposed Engagement Criteria

A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment

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