Presentations


Presentation slides available upon request.

2021

Shifts in time: identifying reliable symptom changes of different duration in within-person time series

European Association for Behavioural and Cognitive Therapies (EABCT) | annual congress, Belfast, IE (online)

M. A. Helmich (presenter)
11 September
2021 | Presentation as part of a symposium

Click to view abstract.

Abstract

Routinely measuring (former) patients’ psychological complaints and collecting time series of repeated assessments within individuals has become common practice in the context of therapy and relapse prevention. Identifying relevant symptom shifts as they enfold can be of interest to psychopathology researchers and clinicians alike, but it is important to know whether the variability in a person’s measurements on a symptom questionnaire are more likely to be due to the instrument’s precision (standard error of measurement), or due to an actual important change.

While various methods exist to determine whether a relevant change in symptoms has occurred at the within-person level, these typically 1) make no particular assumption about the time it took for the symptoms to change, e.g., pre-post treatment changes, 2) require quite a few data points to model change, e.g., simple linear regression or change point analysis, and 3) even those that examine ‘sudden gains and losses’, do not provide solutions for relatively fast changes that extend over multiple time points. Thus, I propose an adaptation of the well-established Reliable Change Index (RCI) that allows researchers and clinicians to explore the presence of symptom changes of varying durations in individual patients’ time series: the Duration-adjusted RCI (DaRCI).

In essence, the DaRCI takes the RCI cut-off score for change between two points, and proportionally extends this over multiple observations. Reliability of the change is maintained for a given confidence level. Researchers choose the relevant time period between observations, and additional increments are added accordingly, e.g., change over one week can be extended over two, three, four weeks, etc. (as the measurement scale or research interest allows). We expect that the DaRCI may be particularly useful for identifying shifts in symptoms that occur relatively fast, indicating when a patient is showing significant improvement or deterioration and encouragement or intervention is necessary.

To illustrate the ability of this method to detect changes of various durations, we simulated depressive symptom time series with varying degrees of discontinuity and overall mean change in scores. I will present the first results of these simulations, as well as a few examples in empirical data, which reveal that the DaRCI is effective at identifying the simulated changes over multiple weeks.

The rocky road to recovery: do early warning signals precede transitions towards depressive symptom improvement?

Society for Ambulatory Assessment (SAA) | biennial conference, Zürich, CH (online)

M. A. Helmich (presenter), A. C. Smit, L. F. Bringmann, M. J. Schreuder, A. J. Oldehinkel, M. Wichers, & E. Snippe
1 July 2021 | Presentation as part of a symposium

Click to view abstract.

Abstract

The path to depressive symptom improvement during therapy is very personal and often complex. This complicates evaluating the effectiveness of the therapy based on depressive symptoms alone, as many individuals experience periods of instability and discontinuous symptom change. To gain a better understanding of the dynamics that precede clinically relevant symptom shifts in depression, researchers have begun intensive monitoring of symptoms and momentary affect over time. Although the process of improvement is particular to each individual and can be hard to monitor, Early Warning Signals (EWS) in the form of lag-1 autocorrelation and variance in EMA time series, have been suggested as potential generic indicators of imminent symptom shifts. If EWS can indeed be found consistently, this could be a useful tool for treatment as it may provide patients and therapists with feedback about the effectiveness of the current treatment, even when depressive symptoms have not yet improved at the mean-level or are strongly fluctuating.

In the current study, we gathered individual intensive longitudinal timeseries data from 41 individuals undergoing psychological treatment to be able to investigate whether EWS indeed consistently occur before clinically relevant symptom improvements. Specifically, we test whether lag-1 autocorrelation and variance in momentary affect rises before the 28 identified transitions. Affect was measured five-times daily for a period of four months (521 observations per individual on average), and depressive symptoms were assessed weekly over six months. In this symposium, I will present the results and answer whether EWS indeed precede depressive symptom improvements.

Presenting the TRANS-ID project
So you want to define transitions?

13th DynaNeT lab meeting | Organised by Laura Bringmann (online)

M. A. Helmich
Co-presenters: R.N. Groen, M.J. Schreuder, & A.C. Smit

9 Feb 2021 | Invited presentation, together with other TRANS-ID team members

Click to view topics.

Topics per presentation


First Robin Groen gave a short introduction to the project:


The TRANS-ID project (TRANSitions In Depression) started in 2016 and wrapped up data collection in 2020. Over four years, an abundance of self-report, heart rate and movement measurements were collected for 241 participants. In this meeting the TRANS-ID group will share their experiences concerning the data collection and discuss several insights related to studying transitions in empirical data.

Next, Marieke Helmich introduced the first discussion topic:

While a ‘critical transition’ in symptoms may sound like it would be an obvious event that should be readily captured in intensive longitudinal data, operationalizing it for detection in empirical data is challenging. Let’s discuss the theoretical unknowns, clinical best-guesses and practical issues with defining transitions in psychological data.


Then Marieke Schreuder continued on the EWS topic:

Our first results show that the presence, timing, and type of EWS differ considerably between individuals. This complicates drawing group-level inferences, and raises the question whether and how EWS can contribute to our understanding of psychopathology.

Finally, Arnout Smit ended with a discussion on EWS in clinical practice:

Several publications have expressed the hope that if transitions in psychopathology tend to be preceded by EWS, these EWS may be used to acquire personalized information about upcoming transitions in clinical practice. We discussed some of the challenges in bridging the gap between research findings and clinical applications.

2020

Could you be more specific?
Preregistering analysis choices for a preconceived set of hypotheses

Celebrating Openness | Open Research Award 2020, online event

M. A. Helmich
22 Oct 2020 | Invited lightning talk

The Open Research Award was set up by the University of Groningen Library and the Open Science Community Groningen, to celebrate the way academics are making their research more accessible, transparent and reproducible. Winners were selected via a random draw (with a bingo wheel!), and I was one of three lucky winners! I was then asked to give a lightning talk on my experiences with open science practices at the online Celebrating Openness event, and to talk candidly about the pitfalls, the challenges and the successes I experienced.

Click to view submission.

My submission for the Open Research Award

Preregistering analysis methods to examine the hypotheses for Transitions in Depression (TRANS-ID) Recovery

My experience with open research practices centres on the task of translating the ‘grand’ research questions and hypotheses from a grant proposal, to the ‘specific’, testable questions for an analysis plan. A large portion of my PhD trajectory has been dedicated to collecting data that was designed to answer a particular research question: Can we find early warning signals before symptom improvements in depression? Briefly: we collected intensive longitudinal data of mood and depressive symptoms from people seeking psychological treatment for depression, with the expectation that they were more likely to show large, discontinuous improvements. The hypothesis to be tested is that certain statistical patterns emerge in the daily measurements (e.g., variance and autocorrelation rise) that may signal that a symptom shift is imminent.

Although the research question and hypotheses were broadly specified when the project was designed, many particular decisions still had to be made about how we would define and analyse crucial components of the study. Particularly challenging was the fact that, although my project was based on an earlier study, that was only an n=1 case study of a patient that relapsed, rather than remitted from depression. This meant that I could not simply repeat the steps from that study, and the methodological details of my analysis still had to be adapted to work for a larger sample (42 repeated case studies), as well as for a different clinical process (depressive symptom improvement will look different over time than a depressive relapse). In short, the analysis choices I had to make could only be guided by the existing work and background theory to a certain extent.

Because our study is a somewhat complex hybrid between exploratory and confirmatory work, the preregistration was an important opportunity for us to show that we have taken care in devising our analysis steps. In the context of a preregistration, we could write down the hypotheses that will be tested with the method that we believe, a priori, to be theoretically most likely to work. Additionally, we have planned robustness checks and extensive descriptions of the data to provide further information about our sample, and the preregistration is a way to demonstrate that the additional tests and explorations are pre-designed and not a result of post hoc reasoning in response to the results. Essentially, the preregistration offered us a way to timestamp what we believed, to the best of our theoretical knowledge, to be an optimal analysis plan before seeing the data, while also serving as a testament of our good intent to give a thorough description of our data.

In the past few years (while data was being collected), we spent a lot of time making carefully weighed considerations and analysis choices, so it was not much extra work to write them down and publish them online. On the project OSF page, I have provided 1) a detailed description of the study methods, 2) a brief methods piece describing an adapted version of the Reliable Change Index for use when change can happen over multiple time points, 3a) the original (Dutch) experience sampling questionnaires and 3b) an English translation including the measured constructs, and finally, 4) a preregistration of our analysis plan. Numbers 1 and 2 are also available on ResearchGate and, to my great joy, the detailed study methods (1) have already been cited in a recent review. In conclusion, my experience with open research practices is only positive, it has brought extra clarity and thoroughness to my research work; a practice I hope to continue in the future!

References and further information:

2019

Daily dynamics of negative affect: an indicator for response to treatment and remission from depression?

Society for Ambulatory Assessment (SAA) | biennial conference, Syracuse, NY, USA

M. A. Helmich (presenter), M. Wichers, F. Peeters & E. Snippe
20 June 2019 | Presentation as part of a symposium

Click to view abstract.

Abstract

Background: As more instability (MSSD) and less variability (SD) of negative affect (NA) have been related to current and future depressive symptoms, these emotion dynamics may also be indicators of the likelihood of early treatment response and long-term presence of symptoms. We investigated whether MSSD and SD of NA were predictive of the rate of 1) depressive symptom reduction during treatment and 2) of time-to-remission over 18 months.

Methods: 41 participants with major depressive disorder completed six days of experience sampling, with 10 semi-random beeps per day before starting treatment. During and after treatment, depressive symptom severity was assessed monthly for 18 months with the Hamilton Depression Rating Scale (HDRS). Rate of depressive symptom reduction was modelled as a log-linear decrease in monthly HDRS in a multilevel model, controlled for baseline HDRS. Candidate predictors were individual SD, MSSD, and mean NA, and several patient characteristics. Predictors were first tested in univariate models, significant predictors were entered in a multivariate model. Regression analyses with the same predictor variables were performed to predict individual time-to-remission (N months to HDRS of <8).

Results: Preliminary results show that NA dynamics before treatment have no predictive value for the course of depressive symptoms over 5 months beyond baseline symptom severity. Analyses for time-to-remission are yet to be completed.

Conclusions: Preliminarily, our results suggest that instability and variability in NA may be not as indicative of an upcoming reduction of depressive symptoms as they are for the onset of depressive symptoms.


Keywords: depression, treatment response, negative affect dynamics

Capturing important periods of symptom transitions: a how-to

Society for Ambulatory Assessment (SAA) | biennial conference, Syracuse, NY, USA

M. A. Helmich, A. C. Smit (presenters) & M. Wichers
21 June 2019 | Presentation as part of a symposium

Click to view abstract.

Abstract

Experience sampling (ESM) has been extensively used to study psychopathology. However, most of these studies used very short periods of sampling (< 7 days). However, as technology progresses novel sampling opportunities have become available and feasible. This justifies the urge to explore and test cutting-edge applications of daily life monitoring to extend our current scientific boundaries. Urgent scientific aims include capturing the precise process of symptom change and identify what changes in mood, behavior and physiology take place over time precisely before symptom transitions occur. As this requires intensive sampling over periods of months, this opportunity has only recently become available. We will present the first results of the TRANS-ID study, in which we followed patients at several phases of their psychiatric symptoms over a period 4 months or longer with intensive ESM monitoring, actigraphy and heart rate monitoring. So far, we followed 50 patients who tapered their antidepressant medication, 36 patients who were currently depressed and started psychotherapy and 120 young adults that are familiar with psychiatric symptoms. Whereas drop-out depended on the study population, compliance appeared consistently high (around 80%). Furthermore, most participants indicated that it helped them with dealing with their symptoms. I will further discuss challenges that came with such intensive longterm data sampling based on the TRANS-ID data. Also, we will discuss to what extent we were indeed able to capture important symptom transitions during the intensive monitoring period. Feasibility of long-term intensive monitoring maybe crucial for novel and urgent insights into the process contributing to the development and the disappearance of psychiatric symptoms.

Abstract written by M. Wichers. Presented by M. A. Helmich and A. C. Smit.

2018

Kleine stapjes en grote sprongen: patronen van verandering leiden tot betere uitkomsten in depressie

Rob Giel Onderzoekscentrum studiemiddag, Zuidlaren, NL

M. A. Helmich (presenter), M. Wichers, M. Olthof, G. Strunk, B. Aas, W. Aichhorn, G. Schiepek, & E. Snippe
11 Dec 2018 | Invited talk for a clinical audience

Click to view abstract.

Abstract

Patronen van verandering zoals sudden gains en de vorm van het beloop van verbetering zijn in eerder onderzoek gekoppeld aan betere uitkomsten. Wij onderzochten hoe deze eerdere bevindingen zich verhouding in een rijkere, dagelijkse dataset van depressieve patiënten die tijdens hun behandeling de ervaren last van hun problemen hebben bijgehouden. Uit onze resultaten blijkt dat de helft van de mensen met kleine stapjes verbetert (lineair), dat het hebben van een klinisch relevante sprong (een sudden gain) betere uitkomsten voorspelt, en dat de vorm van het beloop voorspellend is voor betere uitkomsten als deze lineair is.

Change by the day: detailed patterns of improvement during therapy for depression

Society for Psychotherapy Research (SPR) | International annual meeting, Amsterdam, NL

M. A. Helmich (presenter), M. Wichers, M. Olthof, G. Strunk, B. Aas, W. Aichhorn, G. Schiepek, & E. Snippe
28 June 2018 | Presentation as part of a symposium

Click to view abstract.

Abstract

Aim: Group-level studies have mostly shown that symptom improvement occurs in a linear fashion. However, studies at the level of the individual showed that improvements in depressive symptoms during therapy can also occur suddenly, or in a log-linear fashion. This study examines how linear patterns of change relate to sudden gains, by using daily measurements of subjectively rated symptom burden over the course of treatment. We aim to elucidate per individual: 1) the overall change pattern, 2) how often sudden gains occur within various overall change patterns.

Methods: 160 depressed patients with a relevant improvement in daily symptom burden ratings during treatment were identified. The best-fitting overall pattern of change was examined for each individual by fitting regression models of linear, log-linear and one-step trajectories. Sudden gains were determined using change point analysis and previously used sudden gain criteria (Tang & DeRubeis, 1999).

Results: We found that half (52.5%) of all patients experienced a sudden gain in the course of treatment. Preliminary analyses indicate that sudden gains not only occurred in cases with a one-step mean shift, but also in about half the cases with overall linear and log-linear trajectories.

Discussion: Our preliminary results indicate that sudden decreases in experienced symptom burden may be more common than previously estimated with weekly symptom assessments and also occur when patients change in an overall linear fashion. This study showcases the importance of using fine-grained daily data to investigate the process of remission in depression in individuals.

Transitions toward recovery in depression: An intensive mood- and activity-monitoring design

Predicting Transitions in Complex Systems | International Workshop, Dresden, DE

M. A. Helmich (presenter), E. Snippe, Y. K. Kunkels, A. C. Smit, H. Riese, & M. Wichers
24 Apr 2018 | Poster presentation

Click to view abstract & poster.

Abstract

Background Sudden transitions are an established pattern of change toward recovery in depression research. However, it is unknown if these transitions are preceded by early-warning signals (EWS), and thus whether recovery from depression functions according to the principals of complex dynamic systems. This research project examines the use of EWS in detecting oncoming shifts in depressive symptoms within individuals that are expected to improve in the near future. We aim to map micro-level changes in symptom dynamics using frequent self-ratings as well as physiological measurements.

Methods/Design We recruit 45 people with depressive symptoms who are due to start psychological treatment. All participants will report on their mood, activities, and cognitions in a brief questionnaire five times a day, for a period of four months. They also wear an actigraph continuously, and measure their heart rate for 5 minutes, twice a day. For six months, they report on their depressive symptoms weekly, and monthly for six months thereafter. Personalized analyses will be conducted, testing the presence of EWS such as rising autocorrelation, rising variance and rising connection strength in the daily measures before transitions toward remission of depression.

Discussion With 600 observations per person, this study is the first to monitor the process of recovery in depression in this much detail. We expect that it will be possible to predict a transition in depressive symptoms using EWS within individuals. This study addresses a gap in our knowledge of change processes in depression, and could lead to the development of early interventions to promote remission of depression.


2017

Reality check: an experience sampling study of the relationship between theory of mind and social functioning of patients with schizophrenia

Society for Ambulatory Assessment (SAA) | biennial conference, Esch-zur-Alzette, LU

M. A. Helmich (presenter), M. Wichers, U. Reininghaus, & A.-K. Fett
Poster presentation

Click to view abstract & poster.

Abstract

Aim: Group-level studies have mostly shown that symptom improvement occurs in a linear fashion. However, studies at the level of the individual showed that improvements in depressive symptoms during therapy can also occur suddenly, or in a log-linear fashion. This study examines how linear patterns of change relate to sudden gains, by using daily measurements of subjectively rated symptom burden over the course of treatment. We aim to elucidate per individual: 1) the overall change pattern, 2) how often sudden gains occur within various overall change patterns.

Methods: 160 depressed patients with a relevant improvement in daily symptom burden ratings during treatment were identified. The best-fitting overall pattern of change was examined for each individual by fitting regression models of linear, log-linear and one-step trajectories. Sudden gains were determined using change point analysis and previously used sudden gain criteria (Tang & DeRubeis, 1999).

Results: We found that half (52.5%) of all patients experienced a sudden gain in the course of treatment. Preliminary analyses indicate that sudden gains not only occurred in cases with a one-step mean shift, but also in about half the cases with overall linear and log-linear trajectories.

Discussion: Our preliminary results indicate that sudden decreases in experienced symptom burden may be more common than previously estimated with weekly symptom assessments and also occur when patients change in an overall linear fashion. This study showcases the importance of using fine-grained daily data to investigate the process of remission in depression in individuals.