Trauma exposure among young children in rural Pakistan: Associations with gender, mental health, and cognitive skills.

BACKGROUND: The burden of childhood trauma (violence, injury/illness, loss) in low-resource settings is high, although the effect of trauma on children's mental and cognitive health is under-researched. Child gender may moderate the association between trauma and outcomes; boys are more likely to experience trauma, but girls are more likely to show distress following trauma. METHODS: We draw on data from the Bachpan cohort (n = 888), a sample of mother-child dyads in rural Pakistan, to investigate these associations among 6-year-old children in a South Asian, low-resource setting. Mothers reported on children's lifetime exposure to 15 possible traumas and their current mental health. In addition, children were assessed for their verbal skills, working memory, and inhibitory control. We estimated trauma prevalence and used generalized estimating equations to test the association between number of traumatic events and child mental health and cognitive skills in the overall sample and by gender. RESULTS: 90.5% of children experienced at least one trauma. The most common traumas were death of a loved one (47%) and hearing about war/terrorism on the TV/radio (48%). On average, boys experienced more traumas (M = 3.00) than girls (M = 2.67). Specifically, boys were more likely than girls to experience an injury or hospitalization (30% vs. 21%, p < .05) and to hear about war/terrorism on the TV/radio (52% vs. 43%, p < .05). Trauma was associated with increased mental health difficulties and increased anxiety scores. There was little evidence that trauma exposure was associated with child cognitive skills. The strength of association between trauma and outcomes was similar for boys and girls. CONCLUSIONS: Findings show that childhood trauma exposure is common in this setting and associated with worse mental health problems among young boys and girls. Results suggest that trauma-informed interventions are important for supporting child mental health in South Asia.

Assessing relinquishment of positivity as a central symptom bridging anxiety and depression.

Anxiety and depression are often comorbid and chronic disorders. Previous research indicates that positivity relinquishment is a moderator of anxiety and depression, such that only anxious individuals who endorsed relinquishing positivity were also depressed. We sought to extend those findings by conducting three network analyses with self-report measures of anxiety, depression, activity avoidance, and perceived positivity of avoided activities (N = 104). We pre-registered our hypothesis for the first two networks that relinquishment of positivity would emerge as a central bridge symptom between anxiety and depressive symptoms. After combining redundant nodes, we estimated three networks and investigated the bridge symptoms in each network. Relinquishment of positivity bridged the symptom clusters in the first network, and avoidance of positivity was found to bridge the two symptom clusters of anxiety and depression in networks two and three. Additionally, an anhedonia circuit was uncovered in all three networks in which loss of interest/worthlessness, loss of energy, and loss of pleasure/pessimism connected to anxiety through relinquishment or avoidance. Our findings suggest that both relinquishment of positivity as well as avoidance of positivity could be potential pathways explaining the development and maintenance of anxiety and depression and should be properly targeted in treatment.

MoodCapture: Depression Detection Using In-the-Wild Smartphone Images.

MoodCapture presents a novel approach that assesses depression based on images automatically captured from the front-facing camera of smartphones as people go about their daily lives. We collect over 125,000 photos in the wild from N=177 participants diagnosed with major depressive disorder for 90 days. Images are captured naturalistically while participants respond to the PHQ-8 depression survey question: "I have felt down, depressed, or hopeless". Our analysis explores important image attributes, such as angle, dominant colors, location, objects, and lighting. We show that a random forest trained with face landmarks can classify samples as depressed or non-depressed and predict raw PHQ-8 scores effectively. Our post-hoc analysis provides several insights through an ablation study, feature importance analysis, and bias assessment. Importantly, we evaluate user concerns about using MoodCapture to detect depression based on sharing photos, providing critical insights into privacy concerns that inform the future design of in-the-wild image-based mental health assessment tools.

Disability severity and risk of new or recurrent intimate partner violence - Evidence from a cohort study in rural Pakistan.

BACKGROUND: People with disabilities are more likely to experience intimate partner violence (IPV) than those without. Most research examining the relationship between disability and IPV, however, is cross-sectional and approaches disability as a binary variable. This relationship is also important to consider in a South Asian context, where it may be affected by cultural norms surrounding IPV, and resources for people with disabilities. OBJECTIVE: To estimate the degree to which disability severity increases the risk of subsequent IPV among a cohort of mothers living in rural Pakistan. METHODS: Mothers from the Bachpan study (N = 869) with data for at least two consecutive waves between 1-, 2-, 3-, and 6-years postpartum were included in this study. Modified Poisson regression models were used to estimate the relationship between disability level in the preceding wave and psychological, physical, and sexual IPV in the following wave. RESULTS: For psychological IPV, the risk ratio (RR) for medium severity was 1.27 (95 % CI: 1.10, 1.46) and the RR for high severity was 1.23 (95 % CI: 1.02, 1.48), relative to low severity. Physical IPV had a medium severity RR of 1.44 (95 % CI: 1.00, 2.06) and high severity RR of 1.60 (95 % CI: 1.02, 2.53). For sexual IPV, the medium severity RR was 1.35 (95 % CI: 1.05, 1.75) and the high severity RR was 1.53 (95 % CI: 1.11, 2.10). CONCLUSIONS: This study supports that, in a low-income, rural South Asian context, mothers with disabilities are particularly susceptible to future psychological, physical, and sexual IPV.

The role of borderline personality disorder traits in predicting longitudinal variability of major depressive symptoms among a sample of depressed adults.

BACKGROUND: Major depressive disorder (MDD) and borderline personality disorder (BPD) often co-occur, with 20 % of adults with MDD meeting criteria for BPD. While MDD is typically diagnosed by symptoms persisting for several weeks, research suggests a dynamic pattern of symptom changes occurring over shorter durations. Given the diagnostic focus on affective states in MDD and BPD, with BPD characterized by instability, we expected heightened instability of MDD symptoms among depressed adults with BPD traits. The current study examined whether BPD symptoms predicted instability in depression symptoms, measured by ecological momentary assessments (EMAs). METHODS: The sample included 207 adults with MDD (76 % White, 82 % women) recruited from across the United States. At the start of the study, participants completed a battery of mental health screens including BPD severity and neuroticism. Participants completed EMAs tracking their depression symptoms three times a day over a 90-day period. RESULTS: Using self-report scores assessing borderline personality disorder (BPD) traits along with neuroticism scores and sociodemographic data, Bayesian and frequentist linear regression models consistently indicated that BPD severity was not associated with depression symptom change through time. LIMITATIONS: Diagnostic sensitivity and specificity may be restricted by use of a self-report screening tool for capturing BPD severity. Additionally, this clinical sample of depressed adults lacks a comparison group to determine whether subclinical depressive symptoms present differently among individuals with BPD only. CONCLUSIONS: The unexpected findings shed light on the interplay between these disorders, emphasizing the need for further research to understand their association.

From mood to use: Using ecological momentary assessments to examine how anhedonia and depressed mood impact cannabis use in a depressed sample.

Anhedonia and depressed mood are two cardinal symptoms of major depressive disorder (MDD). Prior work has demonstrated that cannabis consumers often endorse anhedonia and depressed mood, which may contribute to greater cannabis use (CU) over time. However, it is unclear (1) how the unique influence of anhedonia and depressed mood affect CU and (2) how these symptoms predict CU over more proximal periods of time, including the next day or week (rather than proceeding weeks or months). The current study used data collected from ecological momentary assessment (EMA) in a sample with MDD (N = 55) and employed mixed effects models to detect and predict weekly and daily CU from anhedonia and depressed mood over 90 days. Results indicated that anhedonia and depressed mood were significantly associated with CU, yet varied at daily and weekly scales. Moreover, these associations varied in both strength and directionality. In weekly models, less anhedonia and greater depressed mood were associated with greater CU, and directionality of associations were reversed in the models looking at any CU (compared to none). Findings provide evidence that anhedonia and depressed mood demonstrate complex associations with CU and emphasize leveraging EMA-based studies to understand these associations with more fine-grained detail.

Predicting Individual Response to a Web-Based Positive Psychology Intervention: A Machine Learning Approach.

Positive psychology interventions (PPIs) are effective at increasing happiness and decreasing depressive symptoms. PPIs are often administered as self-guided web-based interventions, but not all persons benefit from web-based interventions. Therefore, it is important to identify whether someone is likely to benefit from web-based PPIs, in order to triage persons who may not benefit from other interventions. In the current study, we used machine learning to predict individual response to a web-based PPI, in order to investigate baseline prognostic indicators of likelihood of response (N = 120). Our models demonstrated moderate correlations (happiness: r Test = 0.30 ± 0.09; depressive symptoms: r Test = 0.39 ± 0.06), indicating that baseline features can predict changes in happiness and depressive symptoms at a 6-month follow-up. Thus, machine learning can be used to predict outcome changes from a web-based PPI and has important clinical implications for matching individuals to PPIs based on their individual characteristics.

How etiological beliefs contribute to the structure of depression symptom networks.

OBJECTIVES: Each person possesses a unique view surrounding depressive symptomology and etiology that is shaped by idiosyncratic experiences. However, the influence that subjective etiological beliefs regarding a person's depressive symptoms have on actual symptom presentation and organization is seldom considered. METHODS: The current study employed network analytic techniques to examine how subjective views surrounding the cause of depressive symptoms altered actual symptom presentation networks. Additionally, the interaction between depressive symptoms and various etiological beliefs was examined. RESULTS: The results revealed that characterological beliefs, representing the idea that depression is caused by an internal sense of self, are strongly connected to a negative view of self, as well as a saddened mood. Additionally, the characterological beliefs node exhibited the greatest node predictability in its respective network, as well as in an omnibus network consisting of all depression symptoms and potential etiological beliefs. Whereas an achievement-based view of depression has a strong connection with concentration difficulties, a physical view of depression tends to form strong connections with physically based depressive symptoms. CONCLUSION: Subjective views regarding the cause of depression have the potential to influence symptom presentation and organization within a network, which may influence a person's willingness to engage in treatment or specific treatment preferences.

Depressive symptoms as a heterogeneous and constantly evolving dynamical system: Idiographic depressive symptom networks of rapid symptom changes among persons with major depressive disorder.

Major depressive disorder (MDD) is conceptualized by individual symptoms occurring most of the day for at least two weeks. Despite this operationalization, MDD is highly variable with persons showing greater variation within and across days. Moreover, MDD is highly heterogeneous, varying considerably across people in both function and form. Recent efforts have examined MDD heterogeneity byinvestigating how symptoms influence one another over time across individuals in a system; however, these efforts have assumed that symptom dynamics are static and do not dynamically change over time. Nevertheless, it is possible that individual MDD system dynamics change continuously across time. Participants (N = 105) completed ratings of MDD symptoms three times a day for 90 days, and we conducted time varying vector autoregressive models to investigate the idiographic symptom networks. We then illustrated this finding with a case series of five persons with MDD. Supporting prior research, results indicate there is high heterogeneity across persons as individual network composition is unique from person to person. In addition, for most persons, individual symptom networks change dramatically across the 90 days, as evidenced by 86% of individuals experiencing at least one change in their most influential symptom and the median number of shifts being 3 over the 90 days. Additionally, most individuals had at least one symptom that acted as both the most and least influential symptom at any given point over the 90-day period. Our findings offer further insight into short-term symptom dynamics, suggesting that MDD is heterogeneous both across and within persons over time. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Detecting major depressive disorder presence using passively-collected wearable movement data in a nationally-representative sample.

Major Depressive Disorder (MDD) is a heterogeneous disorder, resulting in challenges with early detection. However, changes in sleep and movement patterns may help improve detection. Thus, this study aimed to explore the utility of wrist-worn actigraphy data in combination with machine learning (ML) and deep learning techniques to detect MDD using a commonly used screening method: Patient Health Questionnaire-9 (PHQ-9). Participants (N = 8,378; MDD Screening = 766 participants) completed the and wore Actigraph GT3X+ for one week as part of the National Health and Nutrition Examination Survey (NHANES). Leveraging minute-level, actigraphy data, we evaluated the efficacy of two commonly used ML approaches and identified actigraphy-derived biomarkers indicative of MDD. We employed two ML modeling strategies: (1) a traditional ML approach with theory-driven feature derivation, and (2) a deep learning Convolutional Neural Network (CNN) approach, coupled with gramian angular field transformation. Findings revealed movement-related features to be the most influential in the traditional ML approach and nighttime movement to be the most influential in the CNN approach for detecting MDD. Using a large, nationally-representative sample, this study highlights the potential of using passively-collected, actigraphy data for understanding MDD to better improve diagnosing and treating MDD.

Does grit protect against the adverse effects of depression on academic achievement?

Depressive symptoms have been shown to be negatively related to academic achievement, as measured by grade point average (GPA). Grit, or the passion for and the ability to persevere toward a goal despite adversity, has been linked to GPA. Thus, grit may potentially buffer against the negative effects of depressive symptoms in relation to academic achievement. However, social desirability may might impact the validity of grit when assessed by self-report measures, so how these constructs are all related is unknown. The current study explored the relationship between depressive symptoms, grit, social desirability, and GPA among University students (N = 520) in the United States using a cross-sectional design. We conducted a moderated-moderation model to examine how social desirability moderated the relationship between depressive symptoms, grit, and GPA. Findings replicated prior work and indicated negative relationships between depressive symptoms and social desirability with GPA and a positive relationship, albeit non-significant, between grit and GPA. However, results suggest that grit did not moderate the relationship between depressive symptoms and GPA when including social desirability in the model. Future research should investigate this relationship in a longitudinal setting to further examine how grit and depressive symptoms influence one another in academic domains.

Longitudinal and experimental investigations of implicit happiness and explicit fear of happiness.

ABSTRACTSome individuals devalue positivity previously associated with negativity (Winer & Salem, 2016). Positive emotions (e.g. happiness) may be seen as threatening and result in active avoidance of future situations involving positivity. Although some self-report measures can capture emotions of happiness-averse individuals, they are not always capable of capturing automatic processing. Thus, we examined the association between implicitly-assessed happiness and explicit (i.e. self-reported) fear of happiness in three studies. In Study 1, participants completed the Fear of Happiness Scale (FHS) and an implicit measure of emotions at four-time points over approximately one year. The implicit measure required participants to choose which emotion (i.e. anger, fear, happiness, sadness, or none) best corresponded to 20 individual Chinese characters. In Studies 2 and 3, we utilized an experimental design, implementing a mood induction to emphasise the relationship between explicit fear of happiness and implicitly-assessed happiness. Participants completed the FHS and chose which emotion they believed the artist tried to convey in 20 abstract images. Results indicated that greater self-reported fear of happiness was related to reduced implicit happiness. Findings from these studies provide compound evidence that individuals who hold negative views of positivity may process implicit happiness in a devaluative manner.

A network analytic investigation of avoidance, dampening, and devaluation of positivity.

BACKGROUND AND OBJECTIVES: Reward Devaluation Theory suggests that devaluation of positivity may be integral in understanding depression (Winer & Salem, 2016). Specifically, the anticipatory (e.g., fear of happiness) and responsive (e.g., dampening) behaviors related to the processing of positivity may play a role in the development and maintenance of depression. METHODS: The goal of this study was to examine the potential overlap between measures that operationalize positivity avoidance, two Fear of Happiness Scales (Gilbert et al., 2012; Joshanloo, 2013), as well as positivity dampening, measured via the dampening subscale of the Responses to Positive Affect Questionnaire (Feldman et al., 2008). Network and community analyses were employed to examine the extent to which the items of these measures clustered into their parent measures and investigate the dynamic interactions between items. RESULTS: The results of the community analysis revealed that the three self-report measures overall clustered into their parent measures, except for the Gilbert et al. (2012) Fear of Happiness Scale, which clustered into two separate communities. The most influential nodes represented the concept that good feelings are often followed by negative outcomes. Additionally, nodes related to the theme of fear of letting oneself become happy emerged as the strongest bridge nodes. LIMITATIONS: One limitation of this study is the use of a cross-sectional design; thus, causality cannot be inferred, but the results can guide future longitudinal network designs. CONCLUSIONS: These findings demonstrate how anticipatory avoidance and responsive dampening may influence depression, thus providing evidence for unique targets for treatment.

Canine detection of chronic wasting disease (CWD) in laboratory and field settings.

Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy that affects both free-ranging and farmed cervid species, including mule deer, white-tailed deer, and elk (Odocoileus hemionus, Odocoileus virginianus, and Cervus canadensis). Due to the long incubation period and variability of clinical signs, CWD can expand and spread to new areas before they reach diagnostically detectable levels. Antemortem testing methods currently available can be difficult to obtain and to be applied to the large numbers required for adequate surveillance. However, key volatile biomarkers could be harnessed for non-invasive antemortem surveillance. Detection dogs are the most effective tool currently available for volatile detection; dogs can effectively complete wildlife surveys at rates surpassing that of humans. This study is the first to demonstrate that trained detection dogs can be used as an antemortem test for CWD. First, we trained three dogs to differentiate between CWD-positive and CWD-negative white-tailed deer faeces in a laboratory setting. Dogs spent significantly more time at the positive sample than the negative samples, suggesting that they differentiated between the positive and negative volatile signatures. We then trained the same dogs to search for CWD-positive faecal samples in a more naturalistic field setting. In the field, dogs found 8/11 CWD-positive samples and had an average false detection rate of 13%. These results suggest that dogs can be trained to differentiate CWD-positive faeces from CWD-negative faeces in both laboratory and field settings. Future studies will compare canine accuracy to other antemortem methods, as well as improved canine training methods.

Individuals fearing positivity do not perceive positive affect treatments as strong fits: A novel experimental finding and replication.

BACKGROUND AND OBJECTIVES: Positive affect treatments, which hold great promise to connect with those who are otherwise resistant to depression treatments, attempt to upregulate positive emotions. These treatments have potential advantages over standard therapies because they target cross-diagnostic core symptoms (e.g., anhedonia) that may respond better to interventions aimed at increased positivity. However, the extent to which these treatments are a perceived fit by individuals for whom they were developed (i.e., individuals who are afraid of, avoid, or experience less positivity) is unclear. METHODS: We conducted two independent studies utilizing a cross-sectional, experimental design to examine perceived treatment fit. Participants (Study 1: N = 416; Study 2: N = 321) read counterbalanced treatment descriptions of (1) positive affect treatment and (2) psychodynamic psychotherapy and answered questions regarding perceived treatment fit, effectiveness, and preference of the two treatments. RESULTS: Our findings suggest that individuals fearful of happiness perceived a prospective depression treatment specifically targeting positivity as a poorer fit, demonstrating an opposite pattern to the overall samples' treatment preference in both studies. Thus, as predicted by Reward Devaluation Theory, those fearing positivity exhibited avoidance behaviors for treatments that are to an extent designed, and might otherwise be most effective, for them. LIMITATIONS: The current study utilized a college student sample. CONCLUSION: These empirical findings may ultimately inform psychoeducation of why positive affect treatments, which are in direct contrast with clients' preferences, may be the very treatments they need the most.

The Use of Biological Sensors and Instrumental Analysis to Discriminate COVID-19 Odor Signatures.

The spread of SARS-CoV-2, which causes the disease COVID-19, is difficult to control as some positive individuals, capable of transmitting the disease, can be asymptomatic. Thus, it remains critical to generate noninvasive, inexpensive COVID-19 screening systems. Two such methods include detection canines and analytical instrumentation, both of which detect volatile organic compounds associated with SARS-CoV-2. In this study, the performance of trained detection dogs is compared to a noninvasive headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) approach to identifying COVID-19 positive individuals. Five dogs were trained to detect the odor signature associated with COVID-19. They varied in performance, with the two highest-performing dogs averaging 88% sensitivity and 95% specificity over five double-blind tests. The three lowest-performing dogs averaged 46% sensitivity and 87% specificity. The optimized linear discriminant analysis (LDA) model, developed using HS-SPME-GC-MS, displayed a 100% true positive rate and a 100% true negative rate using leave-one-out cross-validation. However, the non-optimized LDA model displayed difficulty in categorizing animal hair-contaminated samples, while animal hair did not impact the dogs' performance. In conclusion, the HS-SPME-GC-MS approach for noninvasive COVID-19 detection more accurately discriminated between COVID-19 positive and COVID-19 negative samples; however, dogs performed better than the computational model when non-ideal samples were presented.

Effects of Intranasal and Oral Bordetella bronchiseptica Vaccination on the Behavioral and Olfactory Capabilities of Detection Dogs.

The bacterium Bordetella bronchiseptica is responsible for serious respiratory disease in dogs, most often associated with 'kennel cough' (canine infectious tracheobronchitis). It is recommended that dogs are vaccinated against the bacterium every 6-12 months, either by oral or intranasal administration. Any impairment of dogs' olfactory capabilities due to medical treatments may impact their efficiency and accuracy in their jobs. This study examined (1) the effect of intranasal and oral vaccines on the olfactory capabilities of detection dogs; as well as (1) effects of the vaccines on canine behavior. Dogs that were vaccinated initially with the oral and 28 days later with intranasal B. bronchiseptica were generally slower to find the target odor than the dogs that were assigned intranasal then oral vaccine. This result prompted a second between-subjects study to further investigate any impact of intranasal administration of the B. bronchiseptica vaccine on the olfactory capabilities of dogs. The intranasal vaccine was of particular interest due to its prevalent use and potential for nasal inflammation leading to decreased olfactory capabilities. Neither odor threshold nor time spent searching for odor were affected by the intranasal vaccine. Behavioral analyses showed that behaviors associated with the dogs' positive and negative motivation affected their time spent finding the target odor; this suggests that behavior should be considered in future studies of olfactory performance.

Paired 18F-Fluorodeoxyglucose (18F-FDG), and 64Cu-Copper(II)-diacetyl-bis(N(4)-methylthiosemicarbazone) (64Cu-ATSM) PET Scans in Dogs with Spontaneous Tumors and Evaluation for Hypoxia-Directed Therapy.

Hypoxia is associated with neoplastic tissue, protecting cancer cells from death by irradiation and chemotherapy. Identification of hypoxic volume of tumors could optimize patient selection for hypoxia-directed medical, immunological, and radiation therapies. Clostridium novyi-NT (CNV-NT) is an oncolytic bacterium derived from attenuated wild-type Clostridium novyi spores, which germinates exclusively in the anaerobic core of tumors with low-oxygen content. The hypothesis was that 64Cu-ATSM would localize to regions of hypoxia, and that greater hypoxic volume would result in greater germination of Clostridium novyi-NT (CNV-NT). Tumor-bearing companion dogs were recruited to a veterinary clinical trial. Dogs received a CT scan, 18F-FDG PET scan (74 MBq) and 64Cu-ATSM PET scan (74 MBq). Scan regions of interest were defined as the highest 20% of counts/voxel for each PET scan, and regions with voxels overlapping between the two scans. Maximum standardized uptake value (MaxSUV) and threshold volume were calculated. Direct oximetry was performed in select tumors. Tumor types evaluated included nerve sheath tumor (10), apocrine carcinoma (1), melanoma (3) and oral sarcoma (6). MaxSUVATSM ranged from 0.3-6.6. Measured oxygen tension ranged from 0.05-89.9 mmHg. Inverse of MaxSUVATSM had a linear relationship with oxygen tension (R2 = 0.53, P = 0.0048). Hypoxia <8 mmHg was associated with an SUVATSM > 1.0. Hypoxic volume ranged from 0 to 100% of gross tumor volume (GTV) and MaxSUVATSM was positively correlated with hypoxic volume (R = 0.674; P = 0.0001), but not GTV (P = 0.182). Tumor hypoxic volume was heterogeneous in location and distribution. 64Cu-ATSM-avid regions were associated with differential CT attenuation. Hypoxic volume did not predict CNV-NT germination. 64Cu-ATSM PET scanning predicts hypoxia patterns within spontaneously occurring tumors of dogs as measured by direct oxymetry. Total tumor volume does not accurately predict degree or proportion of tumor hypoxia.

Examining rumination, devaluation of positivity, and depressive symptoms via community-based network analysis.

OBJECTIVE: Components of rumination, including brooding and reflection, as well as devaluating prospective positivity, may help maintain depressive symptoms. We examined these components together for the first time using network analysis. METHODS: We examined the robustness of rumination communities of closely related items in one network and then examined the interrelationships between rumination communities, devaluation of positivity, and depression, in a second network. RESULTS: Three rumination communities emerged, replicating findings of Bernstein et al. (2019). Within a dense network, nodes representing brooding, reflective pondering, and difficulty trusting positive feelings were most influential. In addition, the node representing the depressive symptom negative self-views shared strong edges with nodes representing devaluation of positivity and brooding. CONCLUSION: Brooding, reflective pondering, and elements of devaluing positivity are influential to depressive symptoms and may be important future experimental and therapeutic targets. Depressed individuals with negative self-views may engage in brooding and devalue their experience of positivity.

Egg masses as training aids for spotted lanternfly Lycorma delicatula detection dogs.

The spotted lanternfly (Lycorma delicatula) is an invasive species first detected in 2014. The insect feeds on plants causing severe damage in vineyards such as the occurrence of sooty mold fungus that impairs leaf photosynthesis. Currently, there is extensive research on how to track and ultimately prevent the spread of this species. It lays eggs that persist through the winter, while the adults die out, which presents a unique opportunity to enter infested or suspected infested areas to begin quarantine and management of the spread while the species is dormant. Detection dogs may be a tool that can be used to search out the spotted lanternfly egg masses during this overwintering period, however it is not known whether dogs can detect any specific odor from the spotted lanternfly eggs. Moreover, as the eggs are only available during certain times of the year, and hatch based on temperature, finding training aids for the dogs could prove difficult. In this study, we investigated whether three detection dogs could learn the odor from dead spotted lanternfly egg masses and if so, whether that would allow them to recognize live spotted lanternfly egg masses. We found that dogs could be trained to find dead spotted lanternfly egg masses, and could learn to ignore relevant controls, with high levels of sensitivity and specificity (up to 94.6% and 92.8%, respectively). Further, we found that after the training, dogs could find live spotted lanternfly egg masses without additional training and returned to previous levels of sensitivity and specificity within a few sessions. Coded videos of training and testing sessions showed that dogs spent more time at the egg masses than at controls, as expected from training. These results suggest that dead spotted lanternfly egg masses could be a useful training aid for spotted lanternfly detection dogs.