Towards an Implementation-STakeholder Engagement Model (I-STEM) for improving health and social care services.

BACKGROUND: The implementation science literature acknowledges a need for engagement of key stakeholders when designing, delivering and evaluating implementation work. To date, the literature reports minimal or focused stakeholder engagement, where stakeholders are engaged in either barrier identification and/or barrier prioritisation. This paper begins to answer calls from the literature for the development of tools and guidance to support comprehensive stakeholder engagement in implementation research and practice. The paper describes the systematic development of the Implementation-STakeholder Engagement Model (I-STEM) in the context of an international, large-scale empirical implementation study (ImpleMentAll) aimed at evaluating the effectiveness of a tailored implementation toolkit. The I-STEM is a sensitising tool that defines key considerations and activities for undertaking stakeholder engagement activities across an implementation process. METHODS: In-depth, semistructured interviews and observations were conducted with implementers who were tailoring implementation strategies to integrate and embed internet-based cognitive behavioural therapy (iCBT) services in 12 routine mental health care organisations in nine countries in Europe and Australia. The analytical process was informed by principles of first- and third-generation Grounded Theory, including constant comparative method. RESULTS: We conducted 55 interviews and observed 19 implementation-related activities (e.g., team meetings and technical support calls). The final outcome of our analysis is expressed in an initial version of the I-STEM, consisting of five interrelated concepts: engagement objectives, stakeholder mapping, engagement approaches, engagement qualities and engagement outcomes. Engagement objectives are goals that implementers plan to achieve by working with stakeholders in the implementation process. Stakeholder mapping involves identifying a range of organisations, groups or people who may be instrumental in achieving the engagement objectives. Engagement approaches define the type of work that is undertaken with stakeholders to achieve the engagement objectives. Engagement qualities define the logistics of the engagement approach. Lastly, every engagement activity may result in a range of engagement outcomes. CONCLUSION: The I-STEM represents potential avenues for substantial stakeholder engagement activity across key phases of an implementation process. It provides a conceptual model for the planning, delivery, evaluation and reporting of stakeholder engagement activities. The I-STEM is nonprescriptive and highlights the importance of a flexible, iterative approach to stakeholder engagement. It is developmental and will require application and validation across a range of implementation activities. PATIENT OR PUBLIC CONTRIBUTION: Patient contribution to ImpleMentAll trial was facilitated by GAMIAN-Europe at all stages-from grant development to dissemination. GAMIAN-Europe brings together a wide variety of patient representation organisations (local, regional and national) from almost all European countries. GAMIAN-Europe was involved in pilot testing the ItFits-toolkit and provided their views on the various aspects, including stakeholder engagement. Patients were also represented in the external advisory board providing support and advice on the design, conduct and interpretation of the wider project, including the development of the ItFits-toolkit. TRIAL REGISTRATION: ClinicalTrials.gov NCT03652883. Retrospectively registered on 29 August 2018.

A Data-Driven Clustering Method for Discovering Profiles in the Dynamics of Major Depressive Disorder Using a Smartphone-Based Ecological Momentary Assessment of Mood.

Background: Although major depressive disorder (MDD) is characterized by a pervasive negative mood, research indicates that the mood of depressed patients is rarely entirely stagnant. It is often dynamic, distinguished by highs and lows, and it is highly responsive to external and internal regulatory processes. Mood dynamics can be defined as a combination of mood variability (the magnitude of the mood changes) and emotional inertia (the speed of mood shifts). The purpose of this study is to explore various distinctive profiles in real-time monitored mood dynamics among MDD patients in routine mental healthcare. Methods: Ecological momentary assessment (EMA) data were collected as part of the cross-European E-COMPARED trial, in which approximately half of the patients were randomly assigned to receive the blended Cognitive Behavioral Therapy (bCBT). In this study a subsample of the bCBT group was included (n = 287). As part of bCBT, patients were prompted to rate their current mood (on a 1-10 scale) using a smartphone-based EMA application. During the first week of treatment, the patients were prompted to rate their mood on three separate occasions during the day. Latent profile analyses were subsequently applied to identify distinct profiles based on average mood, mood variability, and emotional inertia across the monitoring period. Results: Overall, four profiles were identified, which we labeled as: (1) "very negative and least variable mood" (n = 14) (2) "negative and moderate variable mood" (n = 204), (3) "positive and moderate variable mood" (n = 41), and (4) "negative and highest variable mood" (n = 28). The degree of emotional inertia was virtually identical across the profiles. Conclusions: The real-time monitoring conducted in the present study provides some preliminary indications of different patterns of both average mood and mood variability among MDD patients in treatment in mental health settings. Such varying patterns were not found for emotional inertia.

Discovering different profiles in the dynamics of depression based on real-time monitoring of mood: a first exploration.

BACKGROUND: Although depression is typically characterized by a persistent depressed mood, mood dynamics do seem to vary across a depressed population. Heterogeneity of mood variability (magnitude of changes) and emotional inertia (speed at which mood shifts) is seen in clinical practice. However, studies investigating the heterogeneity of these mood dynamics are still scarce. The aim of the present study is to explore different distinctive profiles in real-time monitored mood dynamics among depressed persons. METHODS: After completing baseline measures, mildly-to-moderately depressed persons (n = 37) were prompted to rate their current mood (1-10 scale) on their smartphones, 3 times a day for 7 consecutive days. Latent profile analyses were applied to identify profiles based on average mood, variability of mood and emotional inertia as reported by the participants. RESULTS: Two profiles were identified in this sample. The overwhelming majority of the sample belonged to profile 1 (n = 31). Persons in profile 1 were characterized by a mood just above the cutoff for positive mood (M = 6.27), with smaller mood shifts (lower variability [SD = 1.05]) than those in profile 2 (n = 6), who displayed an overall negative mood (M = 4.72) and larger mood shifts (higher variability [SD = 1.95]) but at similar speed (emotional inertia) (AC = 0.19, AC = 0.26, respectively). CONCLUSIONS: The present study provides preliminary indications for patterns of average mood and mood variability, but not emotional inertia, among mildly-to-moderately depressed persons.

Experienced Burden of and Adherence to Smartphone-Based Ecological Momentary Assessment in Persons with Affective Disorders.

(1) Background: The use of smartphone-based ecological momentary assessment (EMA) questionnaires in affective disorder research has rapidly increased. Though, a thorough understanding of experienced burden of and adherence to EMA is crucial in determining the usefulness of EMA. (2) Methods: Persons with current affective disorders (n = 100), remitted persons (n = 190), and healthy controls (n = 94) participated in a smartphone-based EMA two-week monitoring period. Our primary outcomes were (momentary) perceived burden of and adherence to EMA. (3) Results: In the whole sample, lower positive and higher negative affect were associated with slightly higher levels of perceived momentary burden (B = -0.23 [95%CI = -0.27-0.19], B = 0.30 [95%CI = 0.24-0.37], respectively). The persons with current affective disorders reported slightly higher levels of experienced momentary burden (Mdn = 1.98 [IQR = 1.28-2.57]), than the remitted persons (Mdn = 1.64 [IQR = 1.11-2.24]) and healthy controls (Mdn = 1.28 [IQR = 1.04-1.92]). Nevertheless, the persons with current affective disorders still showed very high adherence rates (Mdn = 94.3% [IQR = 87.9-97.1]), at rates on a par with the remitted persons (Mdn = 94.3% [IQR = 90.0-97.1]) and healthy controls (Mdn = 94.3% [IQR = 90.0-98.6]). (4) Discussion: Frequent momentary questionnaires of mental well-being are slightly more burdensome to the persons with current affective disorders, but this does not seem to have a negative impact on adherence. Their high rate of adherence to EMA-which was similar to that in remitted persons and healthy controls -suggests that it is feasible to apply (short-duration) EMA.