Katherine van Stolk-Cooke

All Publications

• Crowdsourcing Trauma: Psychopathology in a Trauma-Exposed Sample Recruited via Mechanical Turk JOURNAL OF TRAUMATIC STRESS van Stolk-Cooke, K., Brown, A., Maheux, A., Parent, J., Forehand, R., Price, M. 2018; 31 (4): 549-557

  Abstract

  Although crowdsourcing websites like Amazon's Mechanical Turk (MTurk) allow researchers to conduct research efficiently, it is unclear if MTurk and traditionally recruited samples are comparable when assessing the sequela of traumatic events. We compared the responses to validated self-report measures of posttraumatic stress disorder (PTSD) and related constructs that were given by 822 participants recruited via MTurk and had experienced a DSM-5 Criterion A traumatic event to responses obtained in recent samples of participants recruited via traditional methods. Results suggested that the rate of PTSD in the present sample (19.8%) was statistically higher than that found in a recent systematic review of studies that used only traditional recruitment methods. The severity of PTSD reported in the MTurk sample was significantly greater than that reported in a college sample, d = 0.24, and significantly less than that reported in a veteran sample, d = 0.90. The factor structure of PTSD found in the MTurk sample was consistent with prevailing models of PTSD. Findings indicate that crowdsourcing may improve access to this hard-to-reach population.

  View details for DOI 10.1002/jts.22303

  View details for Web of Science ID 000442495900009

  View details for PubMedID 30025175

  View details for PubMedCentralID PMC6107385

• mHealth solutions for early interventions after trauma: improvements and considerations for assessment and intervention throughout the acute post-trauma period. mHealth Price, M., van Stolk-Cooke, K., Brier, Z. M., Legrand, A. C. 2018; 4: 22

  Abstract

  Interventions administered shortly after a traumatic event have the potential to prevent posttraumatic stress disorder (PTSD) and related mental health conditions. A key challenge in delivering such interventions is understanding how PTSD symptoms develop in the acute post-trauma period, defined as the first 30 days after a trauma. Mobile devices have the potential to transform the way symptoms are assessed and how treatment is delivered in that they can capture the dynamic and nuanced nature of symptom progression after trauma. Symptoms can be assessed through active strategies that require user input, such as self-report, or through passive strategies, such as location information. Adaptive mobile interventions can be tailored to target PTSD symptoms as they appear and ultimately prevent more chronic courses of illness. Considerations for how such mobile strategies should be implemented are discussed.

  View details for DOI 10.21037/mhealth.2018.06.03

  View details for PubMedID 30148137

  View details for PubMedCentralID PMC6087875

• A Randomized Controlled Pilot Trial of Different Mobile Messaging Interventions for Problem Drinking Compared to Weekly Drink Tracking PLOS ONE Muench, F., van Stolk-Cooke, K., Kuerbis, A., Stadler, G., Baumel, A., Shao, S., McKay, J. R., Morgenstern, J. 2017; 12 (2): e0167900

  Abstract

  Recent evidence suggests that text messaging may help to reduce problem drinking as an extension to in-person services, but very little is known about the effectiveness of remote messaging on problem drinking as a stand-alone intervention, or how different types of messages may improve drinking outcomes in those seeking to moderate their alcohol consumption.We conducted an exploratory, single-blind randomized controlled pilot study comparing four different types of alcohol reduction-themed text messages sent daily to weekly drink self-tracking texts in order to determine their impact on drinking outcomes over a 12-week period in 152 participants (≈ 30 per group) seeking to reduce their drinking on the internet. Messaging interventions included: weekly drink self-tracking mobile assessment texts (MA), loss-framed texts (LF), gain-framed texts (GF), static tailored texts (ST), and adaptive tailored texts (TA). Poisson and least squares regressions were used to compare differences between each active messaging group and the MA control.When adjusting for baseline drinking, participants in all messaging groups except GF significantly reduced the number of drinks consumed per week and the number of heavy drinking days compared to MA. Only the TA and GF groups were significantly different from MA in reducing the number of drinking days. While the TA group yielded the largest effect sizes on all outcome measures, there were no significant differences between active messaging groups on any outcome measure. 79.6% of individuals enrolled in the study wanted to continue receiving messages for an additional 12 weeks at the end of the study.Results of this pilot study indicate that remote automated text messages delivered daily can help adult problem drinkers reduce drinking frequency and quantity significantly more than once-a-week self-tracking messages only, and that tailored adaptive texts yield the largest effect sizes across outcomes compared to MA. Larger samples are needed to understand differences between messaging interventions and to target their mechanisms of efficacy.

  View details for DOI 10.1371/journal.pone.0167900

  View details for Web of Science ID 000396131700001

  View details for PubMedID 28146560

  View details for PubMedCentralID PMC5287456

• Understanding Messaging Preferences to Inform Development of Mobile Goal-Directed Behavioral Interventions JOURNAL OF MEDICAL INTERNET RESEARCH Muench, F., van Stolk-Cooke, K., Morgenstern, J., Kuerbis, A. N., Markle, K. 2014; 16 (2): e14

  Abstract

  Mobile messaging interventions have been shown to improve outcomes across a number of mental health and health-related conditions, but there are still significant gaps in our knowledge of how to construct and deliver the most effective brief messaging interventions. Little is known about the ways in which subtle linguistic variations in message content can affect user receptivity and preferences.The aim of this study was to determine whether any global messaging preferences existed for different types of language content, and how certain characteristics moderate those preferences, in an effort to inform the development of mobile messaging interventions.This study examined user preferences for messages within 22 content groupings. Groupings were presented online in dyads of short messages that were identical in their subject matter, but structurally or linguistically varied. Participants were 277 individuals residing in the United States who were recruited and compensated through Amazon's Mechanical Turk (MTurk) system. Participants were instructed to select the message in each dyad that they would prefer to receive to help them achieve a personal goal of their choosing.Results indicate global preferences of more than 75% of subjects for certain types of messages, such as those that were grammatically correct, free of textese, benefit-oriented, polite, nonaggressive, and directive as opposed to passive, among others. For several classes of messages, few or no clear global preferences were found. There were few personality- and trait-based moderators of message preferences, but subtle manipulations of message structure, such as changing "Try to…" to "You might want to try to…" affected message choice.The results indicate that individuals are sensitive to variations in the linguistic content of text messages designed to help them achieve a personal goal and, in some cases, have clear preferences for one type of message over another. Global preferences were indicated for messages that contained accurate spelling and grammar, as well as messages that emphasize the positive over the negative. Research implications and a guide for developing short messages for goal-directed behaviors are presented in this paper.

  View details for DOI 10.2196/jmir.2945

  View details for Web of Science ID 000332397500038

  View details for PubMedID 24500775

  View details for PubMedCentralID PMC3936297