Behavioral Tech

Abstract Online panels have become an important resource for research in political science, but the compensation offered to panelists incentivizes them to become “survey professionals,” raising concerns about data quality. We provide evidence on survey professionalism exploring three US samples of subjects who donated their browsing data, recruited via Lucid, YouGov, and Facebook (total $n = 3,886$ ). Survey professionalism is common, but varies across samples: by our most conservative estimate, we find 1.7% of respondents on Facebook, 7. $\color {black}6$ % on YouGov, and 34 $\color {black}.7$ % on Lucid to be professionals (under the assumption that professionals are as likely as non-professionals to donate data after conditioning on observable demographics available from all online survey takers). However, evidence that professionals lower data quality is limited: they do not systematically differ demographically or politically from non-professionals and do not exhibit more response instability. They are, however, somewhat more likely to speed, straightline, and attempt to take questionnaires repeatedly. To address potential selection issues in donating of browsing data, we present sensitivity analyses with lower bounds for survey professionalism. While concerns about professionalism are warranted, we conclude that survey professionals do not, by and large, distort inferences of research based on online panels.

This study examines associations between patient demographics, clinical status, and linguistic features of text messages with engagement in a message-based intervention for serious mental illness. Data from a randomized controlled trial of a message-based mental health intervention were analyzed. Engagement was operationalized as total texts sent per day and total number of disengaged days. Linguistic Inquiry and Word Count identified expressions of affect, social processes, thinking styles, health, and time orientation. Generalized estimating equations assessed associations between demographic, clinical, and Linguistic Inquiry and Word Count variables with engagement across three different time intervals. Among 39 participants, most were male (n = 23, 59%), with diagnoses of schizophrenia (n = 16, 41%), schizoaffective disorder (n = 9, 23%), bipolar disorder (n = 9, 23%), and major depressive disorder (n = 5, 13%). Participants sent approximately two messages per day, with 48% of days disengaged. Race, education, and diagnosis were associated with engagement. Black participants and those with at least some college education sent more texts while individuals with schizophrenia had more disengaged days. Messages containing language about anxiety, friendship, cognitive processes, and common verbs were associated with engagement. Significant relationships between message content and future engagement were observed, particularly in the first 2 weeks, as well as in messages sent the day and week before a disengaged day. Demographic, clinical, and linguistic features are related to engagement in message-based interventions for serious mental illness. Identifying these characteristics can help tailor interventions, enhancing engagement, and reducing dropout rates in digital mental health interventions. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Seasonal and weather changes can significantly impact depression severity, yet findings remain inconsistent across populations. This study explored depression variations across the seasons and the interplays between weather changes, physical activity, and depression severity among 428 participants in a real-world longitudinal mobile health study. Clustering analysis identified four participant subgroups with distinct patterns of depression severity variations in 1 year. While one subgroup showed stable depression levels throughout the year, others peaked at various seasons. The subgroup with stable depression had older participants with lower baseline depression severity. Mediation analysis revealed temperature and day length significantly influenced depression severity, which in turn impacted physical activity levels indirectly. Notably, these indirect influences manifested differently or even oppositely across participants with varying responses to weather. These findings support the hypothesis of heterogeneity in individuals’ seasonal depression variations and responses to weather, underscoring the necessity for personalized approaches in depression management and treatment.

PurposeIndividuals with obesity and binge eating face weight stigma, which can lead to internalized weight bias (IWB), reinforce eating disorder (ED) pathology, and promote unrealistic weight loss expectations (WLE). Greater understanding of pathways between IWB, ED pathology, and WLE could inform interventions to promote healthy WLE and reduce IWB. This study explored pathways through which IWB directly and indirectly relates to eating pathology and WLE in treatment-seeking adults with obesity and recurrent binge eating.MethodsParticipants (N = 199, Mage = 40.3, SD = 14.3) completed the Eating Disorder Examination interview (EDE) and questionnaire (EDE-Q), Modified Weight Bias Internalization Scale, and Positive and Negative Affect Scale. WLE were calculated based on participants’ expected weight loss divided by current weight. We hypothesized that greater IWB would be associated with greater eating pathology and higher WLE. Pearson correlations were examined to identify possible pathways, followed by exploring direct and indirect associations for pathways with significant correlations.ResultsIWB was positively correlated with Eating and Shape Concerns, as well as negative affect (p < 0.05), but not with WLE. Negative affect was positively correlated with WLE. In the pathway model, IWB was directly, negatively associated with WLE (b = − 0.02, p < 0.05). Negative affect was a significant indirect pathway between IWB and WLE (b = 0.01).ConclusionsOur results align with previous literature showing that IWB reinforces eating pathology. Interventions targeting negative affect might promote more reasonable WLE.Level of evidence: Level V, cross-sectional descriptive study

Individuals with multiple chronic conditions (MCCs) and mental health challenges such as depression or anxiety have complex health needs and experience significant challenges with care coordination. Approaches to enhance care for patients with MCCs typically focus on eliciting patients' values to identify and align treatment priorities across patients and providers. However, these efforts are often hindered by both systems- and patient-level barriers, which are exacerbated for patients with co-occurring mental health symptoms. Technology-enabled services (TES) offer a promising avenue to facilitate values elicitation and promote patient-centered care for these patients, though TES have not yet been tailored to their unique needs. This study aimed to identify design and implementation considerations for TES that facilitate values elicitation among patients with MCCs and depression or anxiety. We sought to understand the preferences of both clinicians and patients for TES that could bridge the gap between mental and physical health care. Using human-centered design methods, we conducted 7 co-design workshops with 18 participants, including primary care clinicians, mental health clinicians, and patients with MCCs and depression or anxiety. Participants were introduced to TES prototypes that used various formats (eg, worksheets and artificial intelligence chatbots) to elicit and communicate patients' values. Prototypes were iteratively refined based on participant feedback. Data from these sessions were analyzed using reflexive thematic analysis to uncover themes related to service, technology, and implementation considerations. Three primary themes were identified. (1) Service considerations: TES should help patients translate elicited values into actionable treatment plans and include low-burden, flexible activities to accommodate fluctuations in their mental health symptoms. Both patients and clinicians indicated that TES could be valuable for improving appointment preparation and patient-provider communication through interpersonal skill-building. (2) Technology considerations: Patients expressed openness to TES prototypes that used artificial intelligence, particularly those that provided concise summaries of appointment priorities. Visual aids and simplified language were highlighted as essential features to support accessibility for neurodiverse patients. (3) Implementation considerations: Clinicians and patients favored situating values elicitation in mental health care settings over primary care and preferred self-guided TES that patients could complete independently before appointments. Findings indicate that TES can address the unique needs of patients with MCCs and mental health challenges by facilitating values-based care. Key design considerations include ensuring TES flexibility to account for fluctuating mental health symptoms, facilitating skill-building for effective communication, and creating user-friendly technology interfaces. Future research should explore how TES can be integrated into health care settings to enhance care coordination and support patient-centered treatment planning. By aligning TES design with patient and clinician preferences, there is potential to bridge gaps in care for this complex patient population.

This study aimed to determine whether the second-generation cannabinoid receptor subtype 1 (CB 1 ) antagonist, monlunabant - designed to treat obesity by targeting peripheral receptors - might actually exert its effects through CB 1 receptors in the central nervous system. In adult male mice, both monlunabant and rimonabant reduced appetite and antagonized CB 1 agonist-induced hypothermia. Monlunabant was consistently less potent than rimonabant in both appetite suppression and blocking hypothermia. The cannabinoid agonist HU-210 produced profound hypothermia, which was significantly attenuated by 10 mg/kg of either drug and by 3 mg/kg of rimonabant. Similarly, both drugs reduced appetite in food-deprived mice with limited access to preferred food at the same doses that were effective in the hypothermia assay. Lower doses of monlunabant, which likely saturated peripheral receptors, had no effect on appetite. These findings suggest that monlunabant suppresses appetite mainly through antagonism of central CB 1 receptors. Consequently, monlunabant and other second-generation CB 1 antagonists being developed for obesity may carry a similar risk of adverse psychiatric effects, as previously observed with rimonabant.