III. Detecting Treatment Effects in Clinical Trials With Different Indices of Pain Intensity Derived From Ecological Momentary Assessment

A major problem in mental health clinical trials, such as depression, is low assay sensitivity in primary outcome measures. This has contributed to clinical trial failures, resulting in the exodus of the pharmaceutical industry from the Central Nervous System space. This reduced assay sensitivity in psychiatry outcome measures stems from inappropriately broad measures, recall bias, and poor interrater reliability. Limitations in the ability of traditional measures to differentiate between the trait versus state-like nature of individual depressive symptoms also contributes to measurement error in clinical trials. In this viewpoint, we argue that ecological momentary assessment (EMA)—frequent, real time, in-the-moment assessments of outcomes, delivered via smartphone—can both overcome these psychometric challenges and reduce clinical trial failures by increasing assay sensitivity and minimizing recall and rater bias. Used in this manner, EMA has the potential to further our understanding of treatment response by allowing for the assessment of dynamic interactions between treatment and distinct symptom response.

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An electronic diary software for ecological momentary assessment (EMA) in clinical trials

Proceedings. 17th IEEE Symposium on Computer-Based Medical Systems ◽

10.1109/cbms.2004.1311709 ◽

2004 ◽

Cited By ~ 12

Author(s):

M. Vahabzadeh ◽

D. Epstein ◽

M. Mezghanni ◽

Jia-Ling Lin ◽

K. Preston

Keyword(s):

Clinical Trials ◽

Ecological Momentary Assessment ◽

Electronic Diary ◽

Ecological Momentary ◽

Momentary Assessment

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Ecological momentary assessment of the relationship between headache pain intensity and pain interference in women with migraine and obesity

Cephalalgia ◽

10.1177/0333102415625613 ◽

2016 ◽

Vol 36 (13) ◽

pp. 1228-1237 ◽

Cited By ~ 9

Author(s):

J Graham Thomas ◽

Jelena Pavlovic ◽

Richard B Lipton ◽

Julie Roth ◽

Lucille Rathier ◽

...

Keyword(s):

Pain Intensity ◽

Ecological Momentary Assessment ◽

Migraine Headache ◽

Behavioral Treatment ◽

Pain Catastrophizing ◽

Brief Pain Inventory ◽

Pain Interference ◽

Headache Diary ◽

Ecological Momentary ◽

Momentary Assessment

Background While pain intensity during migraine headache attacks is known to be a determinant of interference with daily activities, no study has evaluated: (a) the pain intensity-interference association in real-time on a per-headache basis, (b) multiple interference domains, and (c) factors that modify the association. Methods Participants were 116 women with overweight/obesity and migraine seeking behavioral treatment to lose weight and decrease headaches in the Women’s Health and Migraine trial. Ecological momentary assessment, via smartphone-based 28-day headache diary, and linear mixed-effects models were used to study associations between pain intensity and total- and domain-specific interference scores using the Brief Pain Inventory. Multiple factors (e.g. pain catastrophizing (PC) and headache management self-efficacy (HMSE)) were evaluated either as independent predictors or moderators of the pain intensity-interference relationship. Results Pain intensity predicted degree of pain interference across all domains either as a main effect (coeff = 0.61–0.78, p < 0.001) or interaction with PC, allodynia, and HMSE ( p < 0.05). Older age and greater allodynia consistently predicted higher interference, regardless of pain intensity (coeff = 0.04–0.19, p < 0.05). Conclusions Pain intensity is a consistent predictor of pain interference on migraine headache days. Allodynia, PC, and HMSE moderated the pain intensity-interference relationship, and may be promising targets for interventions to reduce pain interference.

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Emotionsregulation bei Depression

Psychologische Rundschau ◽

10.1026/0033-3042/a000172 ◽

2013 ◽

Vol 64 (4) ◽

pp. 235-243 ◽

Cited By ~ 14

Author(s):

Sven Barnow ◽

Maren Aldinger ◽

Ines Ulrich ◽

Malte Stopsack

Keyword(s):

Ecological Momentary Assessment ◽

Ecological Momentary ◽

Momentary Assessment

Die Anzahl der Studien, die sich mit dem Zusammenhang zwischen Emotionsregulation (ER) und depressiven Störungen befassen, steigt. In diesem Review werden Studien zusammengefasst und metaanalytisch ausgewertet, die den Zusammenhang zwischen ER und Depression mittels Fragebögen bzw. Ecological Momentary Assessment (EMA) erfassen. Dabei zeigt sich ein ER-Profil welches durch die vermehrte Nutzung von Rumination, Suppression und Vermeidung bei gleichzeitig seltenerem Einsatz von Neubewertung und Problemlösen gekennzeichnet ist. Mit mittleren bis großen Effekten, ist der Zusammenhang zwischen Depression und maladaptiven Strategien besser belegt als bei den adaptiven Formen, wo die Effekte eher moderat ausfielen. EMA-Messungen bestätigen dieses Profil. Da EMA-Studien neben der Häufigkeit des Strategieeinsatzes auch die Erfassung anderer ER-Parameter wie Effektivität und Flexibilität ermöglichen, sollten solche Designs in der ER-Forschung zukünftig vermehrt Einsatz finden.

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Using Personal Cell Phones for Ecological Momentary Assessment

European Psychologist ◽

10.1027/1016-9040/a000127 ◽

2013 ◽

Vol 18 (1) ◽

pp. 3-11 ◽

Cited By ~ 42

Author(s):

Emmanuel Kuntsche ◽

Florian Labhart

Keyword(s):

Data Collection ◽

Ecological Momentary Assessment ◽

Communication Systems ◽

Cell Phones ◽

Personal Digital Assistants ◽

Natural Environments ◽

Mobility Patterns ◽

Standard Data ◽

Ecological Momentary ◽

Momentary Assessment

Ecological Momentary Assessment (EMA) is a way of collecting data in people’s natural environments in real time and has become very popular in social and health sciences. The emergence of personal digital assistants has led to more complex and sophisticated EMA protocols but has also highlighted some important drawbacks. Modern cell phones combine the functionalities of advanced communication systems with those of a handheld computer and offer various additional features to capture and record sound, pictures, locations, and movements. Moreover, most people own a cell phone, are familiar with the different functions, and always carry it with them. This paper describes ways in which cell phones have been used for data collection purposes in the field of social sciences. This includes automated data capture techniques, for example, geolocation for the study of mobility patterns and the use of external sensors for remote health-monitoring research. The paper also describes cell phones as efficient and user-friendly tools for prompt manual data collection, that is, by asking participants to produce or to provide data. This can either be done by means of dedicated applications or by simply using the web browser. We conclude that cell phones offer a variety of advantages and have a great deal of potential for innovative research designs, suggesting they will be among the standard data collection devices for EMA in the coming years.

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