Ensuring Survey Research Data Integrity in the Era of Internet Bots

We used an internet-based survey platform to conduct a cross-sectional survey regarding the impact of COVID-19 on the LGBTQ + population in the United States. While this method of data collection was quick and inexpensive, the data collected required extensive cleaning due to the infiltration of bots. Based on this experience, we provide recommendations for ensuring data integrity. Recruitment conducted between May 7 and 8, 2020 resulted in an initial sample of 1251 responses. The Qualtrics survey was disseminated via social media and professional association listservs. After noticing data discrepancies, research staff developed a rigorous data cleaning protocol. A second wave of recruitment was conducted on June 11–12, 2020 using the original recruitment methods. The five-step data cleaning protocol led to the removal of 773 (61.8%) surveys from the initial dataset, resulting in a sample of 478 participants in the first wave of data collection. The protocol led to the removal of 46 (31.9%) surveys from the second two-day wave of data collection, resulting in a sample of 98 participants in the second wave of data collection. After verifying the two-day pilot process was effective at screening for bots, the survey was reopened for a third wave of data collection resulting in a total of 709 responses, which were identified as an additional 514 (72.5%) valid participants and led to the removal of an additional 194 (27.4%) possible bots. The final analytic sample consists of 1090 participants. Although a useful and efficient research tool, especially among hard-to-reach populations, internet-based research is vulnerable to bots and mischievous responders, despite survey platforms’ built-in protections. Beyond the depletion of research funds, bot infiltration threatens data integrity and may disproportionately harm research with marginalized populations. Based on our experience, we recommend the use of strategies such as qualitative questions, duplicate demographic questions, and incentive raffles to reduce likelihood of mischievous respondents. These protections can be undertaken to ensure data integrity and facilitate research on vulnerable populations

Qualitative and quantitative evidence of motivation states for physical activity, exercise and being sedentary from university student focus groups

Motivation for physical activity and sedentary behaviors (e.g., desires, urges, wants, cravings) varies from moment to moment. According to the WANT model, these motivation states may be affectively-charged (e.g., felt as tension), particularly after periods of maximal exercise or extended rest. The purpose of this study was to examine postulates of the WANT model utilizing a mixed-methods approach. We hypothesized that: (1) qualitative evidence would emerge from interviews to support this model, and (2) motivation states would quantitatively change over the course of an interview period. Seventeen undergraduate students (mean age = 18.6y, 13 women) engaged in focus groups where 12 structured questions were presented. Participants completed the “right now” version of the CRAVE scale before and after interviews. Qualitative data were analyzed with content analysis. A total of 410 unique lower-order themes were classified and grouped into 43 higher order themes (HOTs). From HOTs, six super higher order themes (SHOTs) were designated: (1) wants and aversions, (2) change and stability, (3) autonomy and automaticity, (4) objectives and impulses, (5) restraining and propelling forces, and (6) stress and boredom. Participants stated that they experienced desires to move and rest, including during the interview, but these states changed rapidly and varied both randomly as well as systematically across periods of minutes to months. Some also described a total absence of desire or even aversion to move and rest. Of note, strong urges and cravings for movement, typically from conditions of deprivation (e.g., sudden withdrawal from exercise training) were associated with physical and mental manifestations, such as fidgeting and feeling restless. Urges were often consummated with behavior (e.g., exercise sessions, naps), which commonly resulted in satiation and subsequent drop in desire. Importantly, stress was frequently described as both an inhibitor and instigator of motivation states. CRAVE-Move increased pre-to-post interviews (p < .01). CRAVE-Rest demonstrated a trend to decline (p = .057). Overall, qualitative and quantitative data largely corroborated postulates of the WANT model, demonstrating that people experience wants and cravings to move and rest, and that these states appear to fluctuate significantly, especially in the context of stress, boredom, satiety, and deprivation

Urges to Move and Other Motivation States for Physical Activity in Clinical and Healthy Populations: A Scoping Review Protocol

[EN] Motivation for bodily movement, physical activity and exercise varies from moment to moment. These motivation states may be “affectively-charged,” ranging from instances of lower tension (e.g., desires, wants) to higher tension (e.g., cravings and urges). Currently, it is not known how often these states have been investigated in clinical populations (e.g., eating disorders, exercise dependence/addiction, Restless Legs Syndrome, diabetes, obesity) vs. healthy populations (e.g., in studies of motor control; groove in music psychology). The objective of this scoping review protocol is to quantify the literature on motivation states, to determine what topical areas are represented in investigations of clinical and healthy populations, and to discover pertinent details, such as instrumentation, terminology, theories, and conceptual models, correlates and mechanisms of action. Iterative searches of scholarly databases will take place to determine which combination of search terms (e.g., “motivation states” and “physical activity”; “desire to be physically active,” etc.) captures the greatest number of relevant results. Studies will be included if motivation states for movement (e.g., desires, urges) are specifically measured or addressed. Studies will be excluded if referring to motivation as a trait. A charting data form was developed to scan all relevant documents for later data extraction. The primary outcome is simply the extent of the literature on the topic. Results will be stratified by population/condition. This scoping review will unify a diverse literature, which may result in the creation of unique models or paradigms that can be utilized to better understand motivation for bodily movement and exercise.GA was supported by a fellowship from the Office of Academic Affiliations at the United States Veterans Health Administration, a Robert E. Leet and Clara Guthrie Patterson Trust Mentored Research Award, Bank of America, N.A., Trustee, and American Heart Association Grant #852679 (GA, 2021–2024).We would like to thank Melissa Eden, Ph.D. (Hanover College, IN) for her valuable assistance in refining aspects of the search strategy. Khristdman Cavalcanti helped with technical aspects of the study. Sunao Akashi Slayton, PharmD BCOP (Smilow Cancer Hospital, Yale – New Haven Hospital, CT) evaluated clinical information and provided nomenclatur

Strengths and Limitations of Internet-Based Cognitive-Behavioral Treatments for Anxiety Disorders

This commentary discusses the strengths and limitations of internet-based cognitive-behavioral treatments (ICBT) for anxiety disorders, as highlighted by the case studies described in Ciuca, Berger, and Miclea (2017), and in Schulz, Vincent, and Berger (2017). In comparing the course of treatment for patients with contrasting clinical outcomes, the authors offer insights into the many benefits and challenges of ICBT. Suggestions for improving ICBT interventions for anxiety disorders, implications for implementation and dissemination, and ethical considerations are discussed

Depression Severity among a Sample of LGBTQ+ Individuals during the COVID-19 Pandemic

Background: The global pandemic of coronavirus disease 2019 (COVID-19) has led to immense impacts on global community health, the public perception of healthcare, and attitudes surrounding mental health during widespread quarantine. Methods: This analysis examines the rates of depressive symptomology among a sample of LGBTQ+-identifying individuals in the United States (n = 1090). The variables examined included socio-demographic factors, the use of mental health medication, access to mental health medication, and experiences of depression symptomology. Results: The findings indicate that depressive symptoms were less severe for older adults, as they reported higher levels of minimal to moderately severe depressive symptoms. Participants who were not working and those who were using substances were less likely to report depressive symptoms. Participants who were employed full-time reported higher levels of depression compared to those who were unemployed. Conclusions: Understanding the mental health of marginalized populations such as the LGBTQ+ community is critical to providing more nuanced preventative healthcare for unique populations, as members of the LGBTQ+ community are non-monolithic and require more personalized approaches to their healthcare needs

Motivation states to move, be physically active and sedentary vary like circadian rhythms and are associated with affect and arousal

Introduction: Motivation to be physically active and sedentary is a transient state that varies in response to previous behavior. It is not known: (a) if motivational states vary from morning to evening, (b) if they are related to feeling states (arousal/hedonic tone), and (c) whether they predict current behavior and intentions. The primary purpose of this study was to determine if motivation states vary across the day and in what pattern. Thirty adults from the United States were recruited from Amazon MTurk. Methods: Participants completed 6 identical online surveys each day for 8 days beginning after waking and every 2–3 h thereafter until bedtime. Participants completed: (a) the CRAVE scale (Right now version) to measure motivation states for Move and Rest, (b) Feeling Scale, (c) Felt Arousal Scale, and (d) surveys about current movement behavior (e.g., currently sitting, standing, laying down) and intentions for exercise and sleep. Of these, 21 participants (mean age 37.7 y; 52.4% female) had complete and valid data. Results: Visual inspection of data determined that: a) motivation states varied widely across the day, and b) most participants had a single wave cycle each day. Hierarchical linear modelling revealed that there were significant linear and quadratic time trends for both Move and Rest. Move peaked near 1500 h when Rest was at its nadir. Cosinor analysis determined that the functional waveform was circadian for Move for 81% of participants and 62% for Rest. Pleasure/displeasure and arousal independently predicted motivation states (all p's <.001), but arousal had an association twice as large. Eating, exercise and sleep behaviors, especially those over 2 h before assessment, predicted current motivation states. Move-motivation predicted current body position (e.g., laying down, sitting, walking) and intentions for exercise and sleep more consistently than rest, with the strongest prediction of behaviors planned for the next 30 min. Discussion: While these data must be replicated with a larger sample, results suggest that motivation states to be active or sedentary have a circadian waveform for most people and influence future behavioral intentions. These novel results highlight the need to rethink the traditional approaches typically utilized to increase physical activity levels