Graduate Student Journal of Psychology

A Conceptual Model for Addressing Weight Stigma and Health: Guiding Practitioner Conversations for Weight Health

Colter Clayton — Tue, 16 Dec 2025 00:00:00 +0000

Practitioners working in a variety of healthcare settings increasingly face a dilemma when speaking with patients about weight health. On one hand, prescriptive weight-related health advice can exacerbate stigma, while on the other, ignoring insufficient health behavior engagement limits health and increases the risk of other adverse weight-related health conditions. Research has demonstrated that higher-than-optimal body weight is a correlate of morbidit and mortality, but has also demonstrated that weight stigma is pervasive, negatively impacting health, health behavior, and well-being. This article introduces a novel conceptual model to help practitioners initiate conversations about weight health by striving to support health behavior change in a way that deactivates and disempowers weight stigma. By advancing the acceptance principle from motivational interviewing and adapting its scope, the model focuses on destigmatizing attitudes and assumptions related to weight health to prevent or reduce generalized and internalized weight stigma. The model also focuses on limiting interpersonal stigma and its disruptive role in practitioner-patient communication by supporting personal autonomy for a lifestyle of health behavior. This article reports results from a rapid review and calls for research efforts to examine the potential causal role of active acceptance for reducing weight stigma. Overall, the conceptual model simultaneously promotes health behavior and reduces weight stigma for weight health.

The Pertinent Prenatal Period: A Secondary Analysis Examining the Relationship Between Prenatal Maternal Anxiety and Child Language Development at 18 Months

Melanie Esterine — Tue, 16 Dec 2025 00:00:00 +0000

Maternal mental health is thought to be an important factor that may shape child development as early as the prenatal period. Prenatal maternal mental health has been linked to both physiological and factors that are theorized to explain the links between mental health and child language development. Whereas some past research has examined the associations between prenatal mental health and child language development, most have examined broad measures that include both anxiety and depression. Given that there are distinct mechanisms by which these aspects of maternal mental health are hypothesized to impact development, this study aims to parse the association between anxiety and child language development specifically. This study utilized data from a longitudinal prospective study to examine the associations between prenatal anxiety and child language development at 18 months in 167 families. We conducted a series of three regression models beginning with a simple linear regression examining prenatal anxiety and language development, followed by two models, first adding demographic covariates, then including prenatal depression. We did not find associations between maternal anxiety and child language development; inadvertently raising the question of when and by which mechanisms maternal mental health may or may not impact aspects of child development, which are crucial answers to be discerned in order to determine the most effective way to support pregnant mothers and their children throughout the prenatal period.

Exploring the Mediating Role of Mentalization in the Relationship Between Attachment Styles and Suicidal Ideation in a Non-Clinical Pakistani Sample

Hamna Khan, Haya Naseem, Zara Sohail, Shabnam Arshi — Tue, 16 Dec 2025 00:00:00 +0000

The aim of the current study is to determine the relationship between attachment styles, mentalization, and suicidal ideation using a quantitative correlational survey design in a non-clinical Pakistani sample. A purposive-convenience sampling technique was employed to recruit N = 295 adults (males, n = 81; females, n = 214) from Pakistan, aged 18 to 55 years (M = 23.07, SD = 5.37), using a Google survey. It was hypothesized that there is a relationship between attachment styles, mentalization, and suicidal ideation. Moreover, it was also hypothesized that there is a relationship between anxious attachment style and self-mentalization. To test the hypotheses, data were collected through three questionnaires: the Mentalization Scale (MentS), the Revised Adult Attachment Scale (RAAS), and the Suicidal Ideation Attributes Scale (SIDAS). The study's results were analyzed using SPSS 29.0.1.0. The findings revealed that attachment styles have a relationship with mentalization, self-mentalization (MentS-S), and suicidal ideation, whereas no significant correlation was found between mentalization and suicidal ideation. Only self-mentalization was found to have a negative correlation with suicidal ideation (r = −0.14, p = .01). Anxious attachment style was found to have a negative correlation with self-mentalization (r = −0.42, p = .01) and a positive correlation with suicidal ideation (r = 0.26, p = .01). The current findings underscore the importance of integrating emotional regulation strategies in therapeutic work with individuals with anxious attachment styles to prevent the development of suicidal ideation.

Caution when Crowdsourcing: Prolific as a Superior Platform Compared with MTurk

Daniel OConnell, Ashley Bautista, Clint Johnson, Amanda Venta — Tue, 16 Dec 2025 00:00:00 +0000

Many researchers host surveys on online crowdsourcing platforms, such as Amazon’s Mechanical Turk (MTurk) and Prolific. Online platforms promise a convenient way to meet sample size needs while drawing on diverse pools that might not otherwise participate in science. Yet, the quality of data obtained from these platforms is often questionable, so the collection must be closely monitored and reviewed. This study aimed to independently determine which crowdsourcing pool best serves researchers who plan to recruit for online surveys. To achieve this aim, we analyzed data from a recently completed study that drew participants from both MTurk and Prolific. We screened the collected data for both cost and quality, focusing on measures of attention, duration, and internal consistency. We found that only 9.89% of MTurk participants (N = 354) and 43.34% of Prolific participants (N = 345) produced high-quality data; Prolific also proved to be the more affordable option. Researchers considering these platforms for recruitment may weigh the evidence to make decisions when developing their own recruitment strategies. Finally, we highlight best practices for social scientists conducting online research, including additional survey and screening techniques.

Response Time to Detect Careless Responding and Its Relationship with and Prediction of Emotional Distress

Kristen Zentner, Seyma Yildirim-Erbasli — Tue, 16 Dec 2025 00:00:00 +0000

People experiencing emotional distress struggle with cognitive and motivational decline, which has been correlated with patterns of careless responding. Although several methods have been used to detect careless responses in emotionally distressed respondents, the response time has not been widely explored. The current study conducted secondary data analyses on a sample (N = 37,819) who completed the Depression Anxiety Stress Scale (DASS-42) in an online survey between 2017 and 2019. First, a response-time-based approach––a normative threshold method––was used to identify careless responding and examine its association with emotional distress using the DASS-42. Second, four machine learning models––decision tree (DT), random forest (RF), support vector machine (SVM), and naive Bayes (NB)––were trained on DASS-42 item responses and response times to predict emotional distress severity level. A significant correlation was found between the number of careless responses and subscale scores of anxiety and stress. In addition, Mann-Whitney U tests showed statistically significant differences between careless and careful responders in depression, anxiety, and stress. Regarding the machine learning models, SVM was found to be the best predictive model for classifying distressed people with an accuracy, sensitivity, and specificity exceeding 90%. Our results suggest that, in addition to survey responses, response time can identify careless responders and predict distressed responders.

Pretty Privilege vs. Ingroup Bias in Decision Making

Vicky Zhu, Daniel White — Tue, 16 Dec 2025 00:00:00 +0000

In-group and attractiveness bias are well-established concepts in social psychology. This study examines the concurrent influence of these concepts on the decision-making process using the Minimal Group Paradigm. Confederates, individuals who appear to be participants, were used to simulate out-group members. Participants (n = 119, aged 20–30 years) answered a series of mathematics questions, followed by a response, agreeing or disagreeing with the participant’s answer, from a confederate. Participants were then asked to rate the attractiveness of the confederates. Results indicated that in-group bias significantly outweighed attractiveness bias. Participants changed answers more frequently when their group disagreed, regardless of the confederate's attractiveness. Results highlighted the robust effects of group membership on decision-making. Additional research is required to explore confounds within decision-making, such as individual differences and familiarity bias.