Prenatal testosterone synchrony in first-time parents predicts fathers' postpartum relationship quality.

There is evidence that men's testosterone levels decline across the transition to fatherhood and that this decline may reflect fathers' investment in the new family. There is also emerging evidence that cohabiting couples show synchrony or within-couple associations in testosterone levels during the perinatal period. Hormonal synchrony may act as a mechanism that supports fathers' biological preparation for parenthood, perhaps by facilitating perinatal declines in paternal testosterone. However, few studies have examined testosterone synchrony and change within couples. A sample of 97 U.S. couples expecting their first child provided testosterone samples during pregnancy, and of those couples, 78 couples also provided testosterone at seven months postpartum. Couples reported on relationship satisfaction both at prenatal and postpartum visits. Bayesian multilevel modeling revealed within-couple testosterone synchrony both during pregnancy and postpartum. Testosterone synchrony during pregnancy predicted a greater drop in fathers' testosterone levels from prenatal to postpartum and higher paternal postpartum relationship quality. Fathers' lower prenatal testosterone levels also subsequently predicted higher self-reported postpartum relationship quality for both parents. In sum, this study finds that couples' testosterone levels show synchrony across the transition to parenthood in ways that are associated with couple relationship quality and men's neuroendocrine preparation for fatherhood.

Does strict invariance matter? Valid group mean comparisons with ordered-categorical items.

Measurement invariance (MI) of a psychometric scale is a prerequisite for valid group comparisons of the measured construct. While the invariance of loadings and intercepts (i.e., scalar invariance) supports comparisons of factor means and observed means with continuous items, a general belief is that the same holds with ordered-categorical (i.e., ordered-polytomous and dichotomous) items. However, as this paper shows, this belief is only partially true-factor mean comparison is permissible in the correctly specified scalar invariance model with ordered-polytomous items but not with dichotomous items. Furthermore, rather than scalar invariance, full strict invariance-invariance of loadings, thresholds, intercepts, and unique factor variances in all items-is needed when comparing observed means with both ordered-polytomous and dichotomous items. In a Monte Carlo simulation study, we found that unique factor noninvariance led to biased estimations and inferences (e.g., with inflated type I error rates of 19.52%) of (a) the observed mean difference for both ordered-polytomous and dichotomous items and (b) the factor mean difference for dichotomous items in the scalar invariance model. We provide a tutorial on invariance testing with ordered-categorical items as well as suggestions on mean comparisons when strict invariance is violated. In general, we recommend testing strict invariance prior to comparing observed means with ordered-categorical items and adjusting for partial invariance to compare factor means if strict invariance fails.

Adjusting for partial invariance in latent parameter estimation: Comparing forward specification search and approximate invariance methods.

Measurement invariance is the condition that an instrument measures a target construct in the same way across subgroups, settings, and time. In psychological measurement, usually only partial, but not full, invariance is achieved, which potentially biases subsequent parameter estimations and statistical inferences. Although existing literature shows that a correctly specified partial invariance model can remove such biases, it ignores the model uncertainty in the specification search step: flagging the wrong items may lead to additional bias and variability in subsequent inferences. On the other hand, several new approaches, including Bayesian approximate invariance and alignment optimization methods, have been proposed; these methods use an approximate invariance model to adjust for partial measurement invariance without the need to directly identify noninvariant items. However, there has been limited research on these methods in situations with a small number of groups. In this paper, we conducted three systematic simulation studies to compare five methods for adjusting partial invariance. While specification search performed reasonably well when the proportion of noninvariant parameters was no more than one-third, alignment optimization overall performed best across conditions in terms of efficiency of parameter estimates, confidence interval coverage, and type I error rates. In addition, the Bayesian version of alignment optimization performed best for estimating latent means and variances in small-sample and low-reliability conditions. We thus recommend the use of the alignment optimization methods for adjusting partial invariance when comparing latent constructs across a few groups.

Mechanosensory interactions drive collective behaviour in Drosophila.

Collective behaviour enhances environmental sensing and decision-making in groups of animals. Experimental and theoretical investigations of schooling fish, flocking birds and human crowds have demonstrated that simple interactions between individuals can explain emergent group dynamics. These findings indicate the existence of neural circuits that support distributed behaviours, but the molecular and cellular identities of relevant sensory pathways are unknown. Here we show that Drosophila melanogaster exhibits collective responses to an aversive odour: individual flies weakly avoid the stimulus, but groups show enhanced escape reactions. Using high-resolution behavioural tracking, computational simulations, genetic perturbations, neural silencing and optogenetic activation we demonstrate that this collective odour avoidance arises from cascades of appendage touch interactions between pairs of flies. Inter-fly touch sensing and collective behaviour require the activity of distal leg mechanosensory sensilla neurons and the mechanosensory channel NOMPC. Remarkably, through these inter-fly encounters, wild-type flies can elicit avoidance behaviour in mutant animals that cannot sense the odour--a basic form of communication. Our data highlight the unexpected importance of social context in the sensory responses of a solitary species and open the door to a neural-circuit-level understanding of collective behaviour in animal groups.

Increasing Colorectal Cancer Screening at Community-Based Primary Care Clinics in San Francisco.

CONTEXT: Adult colorectal cancer screening (CRCS) can lower disease incidence and mortality. However, widespread implementation is inconsistent, especially in the public sector. While specific interventions to increase CRCS have been identified, firsthand accounts of CRCS improvement efforts using multiple techniques in public sector settings are lacking. OBJECTIVE: A program evaluation was conducted to assess the effect of implementing a culture of continuous quality improvement (QI) on CRCS practices and prevalence. A multipronged incremental effort over more than a decade to increase CRCS at the San Francisco Department of Public Health is described. SETTING: Community-based primary care clinics. PARTICIPANTS: Departmental activities and 5 clinics providing full-scope primary care to CRCS-eligible adults who participated in departmental activities and outreach interventions were assessed. MAIN OUTCOME MEASURES: Departmental and clinic-specific CRCS activities and prevalence. RESULTS: Efforts included departmental prioritization; data-driven QI incorporating routine data sharing (monthly reports and data walls); departmental and clinic-specific QI committees; panel management (a team approach to generation of eligibility lists prior to scheduled visits, routinely offering screening during appointments or mailing test kits for patients without appointments); and departmental mail and phone outreach events. Screening ranged from 36.6% to 54.4% in 2010; in 2013, it ranged from 43.6% to 70.2%. Increases occurred consistently over that time in 3 of the 5 clinics and ranged from 1.1% to 14.5%; decreases occurred during 2 intervals in 2 clinics and ranged from 2.3% to 4.3%. CONCLUSION: CRCS prevalence can be markedly improved in the public sector with a data-driven panel management approach supported by departmental and clinic-specific QI committees and group outreach events. Continued prioritization of and focus on CRCS is required to ensure long-term success. Even small increases will result in avoidable morbidity and mortality associated with this highly preventable disease.

Are factor scores measurement invariant?

There has been increased interest in practical methods for integrative analysis of data from multiple studies or samples, and using factor scores to represent constructs has become a popular and practical alternative to latent variable models with all individual items. Although researchers are aware that scores representing the same construct should be on a similar metric across samples-namely they should be measurement invariant-for integrative data analysis, the methodological literature is unclear whether factor scores would satisfy such a requirement. In this note, we show that even when researchers successfully calibrate the latent factors to the same metric across samples, factor scores-which are estimates of the latent factors but not the factors themselves-may not be measurement invariant. Specifically, we prove that factor scores computed based on the popular regression method are generally not measurement invariant. Surprisingly, such scores can be noninvariant even when the items are invariant. We also demonstrate that our conclusions generalize to similar shrinkage scores in item response models for discrete items, namely the expected a posteriori scores and the maximum a posteriori scores. Researchers should be cautious in directly using factor scores for cross-sample analyses, even when such scores are obtained from measurement models that account for noninvariance. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Assessing and increasing patient panel size in the public sector.

CONTEXT: Panel management is a central component of the primary care medical home, but faces numerous challenges in the safety net setting. In the San Francisco Department of Public Health, many of our community-based primary care clinics have difficulty accommodating all patients seeking care. OBJECTIVE: We evaluated patient panel size in our 7 clinics providing cradle-to-grave primary care services to more than 25,000 active patients. DESIGN: We adjusted panel size for age, gender, diagnoses, homelessness, and substance abuse; set related policies; and assessed the effects on our clinics. On the basis of our previous data and targets set by other safety net providers, we established a minimum of 1125 patients per full-time paid primary care provider (ie, full-time equivalent [FTE]) in April 2009. We calculated the target panel size each clinic would have if all their providers reached the minimum panel size goal and compared it with the panel size attained by the clinic. RESULTS: Nine months after establishing panel size policy, providers reached 82% of the aggregate target panel size. Five of the 7 clinics increased their adjusted panel size per FTE in the range of 2% to 23%. Two data-oriented and innovative clinics with some of the highest adjusted panel sizes per FTE largely maintained their panel size. Two clinics that had the lowest adjusted panel size per FTE realized a 23% and 8% respective gain; both clinics reduced barriers to new patient appointments. Two clinics acquired new providers and experienced a concomitant drop in panel size per FTE while the new clinicians expanded their panels. One of these clinics had difficulty managing high no-show rates and creating effective appointment templates. CONCLUSIONS: Routine data generation, review of data with administrators and providers, data-driven policies and panel size standards, and interventions to bolster team-based care are important tools for increasing capacity at our primary care clinics.

Improved Properties of the Big Five Inventory and the Rosenberg Self-Esteem Scale in the Expanded Format Relative to the Likert Format.

Previous research by Zhang and Savalei (2015) proposed an alternative scale format to the Likert scale format: the Expanded format. Scale items in the Expanded format present both positively worded and negatively worded sentences as response options for each scale item; therefore, they were less affected by the acquiescence bias and method effects that often occur in the Likert scale items. The major goal of the current study is to further demonstrate the superiority of the Expanded format to the Likert format across different psychological scales. Specifically, we aim to replicate the findings of Zhang and Savalei and to determine whether order effect exists in the Expanded format scales. Six psychological scales were examined in the study, including the five subscales of the big five inventory (BFI) and the Rosenberg self-esteem (RSE) scale. Four versions were created for each psychological scale. One version was the original scale in the Likert format. The other three versions were in different Expanded formats that varied in the order of the response options. For each scale, the participant was randomly assigned to complete one scale version. Across the different versions of each scale, we compared the factor structures and the distributions of the response options. Our results successfully replicated the findings of Zhang and Savalei, and also showed that order effect was generally absent in the Expanded format scales. Based on these promising findings, we encourage researchers to use the Expanded format for these and other scales in their substantive research.

Consensus statement on iodine deficiency disorders in Hong Kong.

This article reviews the available data on the study of iodine deficiency disorders in Hong Kong and to discuss the approach towards preventing such disorders in Hong Kong. The importance of iodine and iodine deficiency disorders is described, and the available data on the dietary iodine intake and urinary iodine concentration in different populations of Hong Kong are summarised and discussed. Dietary iodine insufficiency among pregnant women in Hong Kong is associated with maternal goitrogenesis and hypothyroxinaemia as well as neonatal hypothyroidism. Borderline iodine deficiency exists in the expectant mothers in Hong Kong. Women of reproductive age, and pregnant and lactating women should be made aware and educated to have an adequate iodine intake, such as iodised salt, as an interim measure. A steering group involving all stakeholders should be formed to advise on the strategy of ensuring adequate iodine intake, including universal iodisation of salt in Hong Kong. Continuous surveillance of iodine status in the Hong Kong population is necessary.