Eight Myths About Causality and Structural Equation Models

The path less traveled: Using structural equation modeling to investigate factors influencing bone functional morphology

OBJECTIVES

The relationship between an organism's mechanical environment and its bone strength has been long established by experimental research. Multiple intrinsic and extrinsic factors, including body mass, muscle strength, genetic background, and nutritional and/or hormonal status, are likely to influence bone deposition and resorption throughout the lifespan, complicating this relationship. Structural equation modeling (SEM) is uniquely positioned to parse this complex set of influences.

MATERIALS AND METHODS

Data from the Third National Health and Nutrition Examination Survey, including sex, total body mass, lean body mass, exercise frequency, peak body mass, and age, were analyzed using SEM to determine how they affect bone strength both individually and combined.

RESULTS

Body mass is typically the driver of cross-sectional area, but body mass and lean mass have similar effects on the polar moment of area (J). Peak body mass had a strong direct effect on J, despite decreasing strongly with increases in lean mass. Exercise also did not confer a large direct effect on cross-sectional area or J but did modify body mass and lean mass. In females, intentional weight loss was associated with decreased exercise levels.

DISCUSSION

SEM is a useful tool for parsing complex systems in bone functional morphology and has the potential to uncover causal links in the study of skeletal remodeling, including factors like weight loss or exercise that may have secondary effects.

Inadequate Coping Strategies of Men who Have Committed Sexual Aggression Against Women: A Study of Their Developmental Antecedents

Several researchers have found that men who have committed sexual aggression have inadequate coping strategies (e.g., paraphilic sexual fantasies, substance abuse). However, very few researchers have empirically examined the factors potentially associated with the development of these strategies. In 2011, Maniglio hypothesized that the inadequate coping strategies of men who have committed sexual aggression are the result of childhood victimization, mediated by internalized psychological problems. The present study therefore empirically tested this hypothesis in a Canadian sample of 205 men who had committed sexual aggression against women, of whom 37 committed sexual murder. Structural equation modeling (SEM) resulted in the identification of several direct and indirect trajectories leading from childhood victimization (psychological, physical, sexual) to the development of inadequate coping strategies (paraphilic sexual fantasies, alcohol and drug use) mediated by internalized psychological problems (e.g., anxiety, depression, social isolation). The theoretical and clinical implications of these developmental trajectories are discussed.

How to develop causal directed acyclic graphs for observational health research: a scoping review

Causal directed acyclic graphs (DAGs) serve as intuitive tools to visually represent causal relationships between variables. While they find widespread use in guiding study design, data collection and statistical analysis, their adoption remains relatively rare in the domain of psychology. In this paper we describe the relevance of DAGs for health psychology, review guidelines for developing causal DAGs, and offer recommendations for their development. A scoping review searching for papers and resources describing guidelines for DAG development was conducted. Information extracted from the eligible papers and resources (n = 11) was categorised, and results were used to formulate recommendations. Most records focused on DAG development for data analysis, with similar steps outlined. However, we found notable variations on how to implement confounding variables (i.e., sequential inclusion versus exclusion). Also, how domain knowledge should be integrated in the development process was scarcely addressed. Only one paper described how to perform a literature search for DAG development. Key recommendations for causal DAG development are provided and discussed using an illustrative example.

Long-term impacts of socioeconomic status and childhood trauma on depression in older adults: social work strategies

This study explores the impact of life course socioeconomic status (SES) and childhood trauma on depressive symptoms in Chinese middle-aged and older adults, while also examining the role of chronic diseases and implications for social work practice. Using data from 9,942 participants, structural equation was established to investigate these relationships. Results reveals that low childhood SES positively affects depressive symptoms through low SES in mid-to-late life (std. β = 0.168, p < .001), and domestic child abuse negatively impacts depressive symptoms through low SES in mid-to-late life (std. β=-0.020, p < .001). Additionally, experiencing peer bullying is directly associated with depressive symptoms (std. β = 0.145, p < .001). Exposure to domestic violence is directly related to depressive symptoms (std. β = 0.078, p < .001) and indirectly leads to more severe depressive symptoms through chronic disease (std. β = 0.023, p < .001). Social workers in healthcare settings can utilize these findings to better understand risk factors for depression and provide trauma-informed care and economic assistance across the life course. Additional training for social workers on the lasting impacts of childhood adversity is warranted. By intervening at both individual and policy levels, social work practitioners can help break cycles of poverty and poor health stemming from childhood.

Evaluation of a Computer-Aided Clinical Decision Support System for Point-of-Care Use in Low-Resource Primary Care Settings: Acceptability Evaluation Study

BACKGROUND

A clinical decision support system (CDSS) based on the logic and philosophy of clinical pathways is critical for managing the quality of health care and for standardizing care processes. Using such a system at a point-of-care setting is becoming more frequent these days. However, in a low-resource setting (LRS), such systems are frequently overlooked.

OBJECTIVE

The purpose of the study was to evaluate the user acceptance of a CDSS in LRSs.

METHODS

The CDSS evaluation was carried out at the Jimma Health Center and the Jimma Higher Two Health Center, Jimma, Ethiopia. The evaluation was based on 22 parameters organized into 6 categories: ease of use, system quality, information quality, decision changes, process changes, and user acceptance. A Mann-Whitney U test was used to investigate whether the difference between the 2 health centers was significant (2-tailed, 95% CI; α=.05). Pearson correlation and partial least squares structural equation modeling (PLS-SEM) was used to identify the relationship and factors influencing the overall acceptance of the CDSS in an LRS.

RESULTS

On the basis of 116 antenatal care, pregnant patient care, and postnatal care cases, 73 CDSS evaluation responses were recorded. We found that the 2 health centers did not differ significantly on 16 evaluation parameters. We did, however, detect a statistically significant difference in 6 parameters (P<.05). PLS-SEM results showed that the coefficient of determination, R2, of perceived user acceptance was 0.703. More precisely, the perceived ease of use (β=.015, P=.91) and information quality (β=.149, P=.25) had no positive effect on CDSS acceptance but, rather, on the system quality and perceived benefits of the CDSS, with P<.05 and β=.321 and β=.486, respectively. Furthermore, the perceived ease of use was influenced by information quality and system quality, with an R2 value of 0.479, indicating that the influence of information quality on the ease of use is significant but the influence of system quality on the ease of use is not, with β=.678 (P<.05) and β=.021(P=.89), respectively. Moreover, the influence of decision changes (β=.374, P<.05) and process changes (β=.749, P<.05) both was significant on perceived benefits (R2=0.983).

CONCLUSIONS

This study concludes that users are more likely to accept and use a CDSS at the point of care when it is easy to grasp the perceived benefits and system quality in terms of health care professionals' needs. We believe that the CDSS acceptance model developed in this study reveals specific factors and variables that constitute a step toward the effective adoption and deployment of a CDSS in LRSs.

Longitudinal Relationship between L2 Grit and Motivational Regulation Strategy in University Second Language Learning: An Autoregressive Cross-lagged Model Study

Despite the significance of grit and motivational regulation strategies (MRS) to language learning, limited research has been conducted on their longitudinal interplay. The present study explores the relationship between these two constructs in an English as a second language (L2) learning context through a longitudinal design. This study utilizes repeated measures of L2 grit and MRS at two time points (T1 and T2) to investigate the direction of influence between them and proposes and evaluates four models: an autoregressive model, two unidirectional models, and a bidirectional model. Using questionnaire data from 205 Chinese university students to evaluate the models, results from model assessment revealed that L2 grit at T1 positively predicted L2 grit at T2 and that MRS at T1 positively predicted MRS at T2. While L2 grit showed stability, MRS developed over time. The unidirectional model with L2 grit at T1 as a predictor of MRS at T2 was identified as the model of best fit, indicating that L2 grit at an earlier time unidirectionally influenced MRS at a later time. Based on these findings, we conclude that there is a unidirectional influence between L2 grit and MRS: the former plays an influential role in shaping MRS in L2 learning over time. Implications and recommendations for future research are discussed. This study contributes to a deeper understanding of the dynamics between the two constructs, which in turn impacts language learning persistence and success, offering valuable insights for educators, policymakers, and researchers striving to optimize language learning environments and interventions.

Childhood maltreatment influences adult brain structure through its effects on immune, metabolic, and psychosocial factors

Childhood maltreatment (CM) leads to a lifelong susceptibility to mental ill-health which might be reflected by its effects on adult brain structure, perhaps indirectly mediated by its effects on adult metabolic, immune, and psychosocial systems. Indexing these systemic factors via body mass index (BMI), C-reactive protein (CRP), and rates of adult trauma (AT), respectively, we tested three hypotheses: (H1) CM has direct or indirect effects on adult trauma, BMI, and CRP; (H2) adult trauma, BMI, and CRP are all independently related to adult brain structure; and (H3) childhood maltreatment has indirect effects on adult brain structure mediated in parallel by BMI, CRP, and AT. Using path analysis and data from N = 116,887 participants in UK Biobank, we find that CM is related to greater BMI and AT levels, and that these two variables mediate CM's effects on CRP [H1]. Regression analyses on the UKB MRI subsample (N = 21,738) revealed that greater CRP and BMI were both independently related to a spatially convergent pattern of cortical effects (Spearman's ρ = 0.87) characterized by fronto-occipital increases and temporo-parietal reductions in thickness. Subcortically, BMI was associated with greater volume, AT with lower volume and CPR with effects in both directions [H2]. Finally, path models indicated that CM has indirect effects in a subset of brain regions mediated through its direct effects on BMI and AT and indirect effects on CRP [H3]. Results provide evidence that childhood maltreatment can influence brain structure decades after exposure by increasing individual risk toward adult trauma, obesity, and inflammation.

Recognize the Value of the Sum Score, Psychometrics' Greatest Accomplishment

The sum score on a psychological test is, and should continue to be, a tool central in psychometric practice. This position runs counter to several psychometricians' belief that the sum score represents a pre-scientific conception that must be abandoned from psychometrics in favor of latent variables. First, we reiterate that the sum score stochastically orders the latent variable in a wide variety of much-used item response models. In fact, item response theory provides a mathematically based justification for the ordinal use of the sum score. Second, because discussions about the sum score often involve its reliability and estimation methods as well, we show that, based on very general assumptions, classical test theory provides a family of lower bounds several of which are close to the true reliability under reasonable conditions. Finally, we argue that eventually sum scores derive their value from the degree to which they enable predicting practically relevant events and behaviors. None of our discussion is meant to discredit modern measurement models; they have their own merits unattainable for classical test theory, but the latter model provides impressive contributions to psychometrics based on very few assumptions that seem to have become obscured in the past few decades. Their generality and practical usefulness add to the accomplishments of more recent approaches.

Using Directed Acyclic Graphs (DAGs) to Determine if the Total Causal Effect of an Individual Randomized Physical Activity-Promoting Intervention is Identifiable

Physical activity promotion is a best buy for public health because it has the potential to help individuals feel better, sleep better, and perform daily tasks more easily, in addition to providing disease prevention benefits. There is strong evidence that individual-level theory-based behavioral interventions are effective for increasing physical activity levels in adult populations but causal inference from these interventions often is unclearly articulated. A directed acyclic graph (DAG) can be, but rarely is, used to determine if the causal effect of an individual-level theory-based physical activity-promoting intervention is identifiable (e.g. stripped of any spurious association). The primary objective of the current study was to demonstrate how a DAG can be used to determine if the total causal effect of an individual randomized physical activity-promoting intervention is identifiable. The demonstration was based on the Well-Being and Physical Activity study (ClinicalTrials.gov, identifier: NCT03194854). Annotated files from DAGitty and Mplus are provided.

Drivers of men's use of intimate partner violence in conflict-affected settings: learnings from the Democratic Republic of Congo

BACKGROUND

Intimate partner violence against women (IPVAW) is prevalent in conflict-affected settings. Yet, there is limited knowledge about the risk factors that influence men's use of IPVAW in conflict-affected settings. This paper adopts a transdisciplinary perspective to understand how experiences hypothesized to increase men's use of IPVAW relate to each other and to men's use of IPVAW. The findings may help researchers and interventionists to better select and target interventions for IPVAW in conflict-affected settings.

METHODS

We used baseline data from the Tushinde Ujeuri project in the Democratic Republic of Congo. Men with at least partial data for the variables of interest were included in the analysis (n = 2080). We estimated a structural equation model that explored how five constructs - interpersonal violence, mental health, socioeconomic adversity, gender inequitable attitudes, and conflict violence - influenced men's self-reported past-year use of physical and/or sexual IPVAW.

RESULTS

The model had acceptable fit (χ2 = 1576.574, p = 0.000; RMSEA = 0.041; CLI = 0.882; SRMR = 0.055). There was a statistically significant path from interpersonal violence to IPVAW (β = 0.875; OR = 2.40). Interpersonal violence also was linked to gender inequitable attitudes (β = 0.364), which were linked to increased use of IPVAW (β = 0.180; OR = 1.20). Moreover, interpersonal violence was linked to trauma symptoms (β = 0.331), which were linked to increased use of IPVAW (β = 0.238; OR = 1.27). Use of IPVAW decreased as conflict exposures increased (β=-0.036; OR = 0.96), and there was no path from socioeconomic adversity to IPVAW.

CONCLUSIONS

Our findings suggest interpersonal violence exposures, trauma symptoms, and gender inequitable attitudes are all risk factors for the use of IPVAW in a conflict-affected setting. While continuing to focus on gender inequitable attitudes and norms, interventionists should also consider addressing men's experiences of victimization and mental wellbeing. Doing so can help to improve trauma symptoms and may hold promise to reduce IPVAW in conflict-affected settings.

The inside out model of emotion recognition: how the shape of one's internal emotional landscape influences the recognition of others' emotions

Some people are exceptional at reading emotional expressions, while others struggle. Here we ask whether the way we experience emotion "on the inside" influences the way we expect emotions to be expressed in the "outside world" and subsequently our ability to read others' emotional expressions. Across multiple experiments, incorporating discovery and replication samples, we develop EmoMap (N = 20; N = 271) and ExpressionMap (N = 98; replication N = 193) to map adults' experiences of emotions and visual representations of others' emotions. Some individuals have modular maps, wherein emotional experiences and visual representations are consistent and distinct-anger looks and feels different from happiness, which looks and feels different from sadness. In contrast, others have experiences and representations that are variable and overlapping-anger, happiness, and sadness look and feel similar and are easily confused for one another. Here we illustrate an association between these maps: those with consistent and distinct experiences of emotion also have consistent and distinct visual representations of emotion. Finally (N = 193), we construct the Inside Out Model of Emotion Recognition, which explains 60.8% of the variance in emotion recognition and illuminates multiple pathways to emotion recognition difficulties. These findings have important implications for understanding the emotion recognition difficulties documented in numerous clinical populations.

Exploring the Factors That Influence Stakeholder Participation in Decision-Making for the Moat System Restoration Project in Tianchang City, China

The driving factors have a critical effect on shaping stakeholder behavior toward participating in decision-making for river restoration initiatives. The participation of stakeholders is a vital determinant for increasing public confidence in the government and enhancing the acceptance of government decisions. Conversely, insufficient stakeholder participation in decision-making may lead to resistance to decisions on river restoration projects. Thus, the primary purpose of this investigation is to shed light on the complex interactions between the various drivers that underpin stakeholder participation in the context of the Moat System Restoration Project (MSRP). The extended Theory of Planned Behavior (TPB) describes the relationships between seven drivers that have positively influenced stakeholder participation behaviors: stakeholder attitude, priority, risk perception, trust in government decisions, motivation, intention, and knowledge. The empirical underpinning of this research was obtained through a questionnaire survey conducted in Tianchang, China, encompassing a sample size of 473. The empirical findings discern that stakeholder attitudes vis-à-vis the MSRP favorably influence stakeholder participation behaviors. Additionally, stakeholder motivation and intention have been discerned as catalysts for heightened stakeholder participation behavior. These findings promise to furnish invaluable insights, benefit forthcoming river restoration initiatives, and equip decision-makers with a profound understanding of strategies to enhance stakeholder participation.

Disentangling natural and anthropogenic effects on benthic macroinvertebrate assemblages in western US streams

Stream macroinvertebrate assemblages are shaped by natural and human-related factors that operate through complex hierarchical pathways. Quantifying these relationships can provide additional insights into stream ecological assessment. We applied a structural equation modeling framework to evaluate hypothesized pathways by which watershed, riparian, and in-stream factors affect benthic macroinvertebrate condition in the Western Mountains (WMT) and Xeric (XER) ecoregions in the United States. We developed a conceptual model grounded in theory, empirical evidence, and expert opinion to evaluate the following hypotheses: (1) macroinvertebrate assemblages are primarily driven by proximal, in-stream factors (e.g., water quality and physical habitat); (2) anthropogenic land uses affect macroinvertebrates indirectly by altering in-stream characteristics; and (3) riparian vegetation cover attenuates land use effects. We tested our model separately on three measures of benthic macroinvertebrate assemblage condition: ratio of observed-to-expected taxonomic richness (O/E); a multimetric index (MMI); and richness of Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT). In the WMT, site-level riparian cover, in-stream physical habitat (relative bed stability), and water chemistry (total nitrogen) were the top three predictors of macroinvertebrate assemblages, each having over two times the magnitude of effect on macroinvertebrates compared with watershed-level predictors. In the arid XER, annual precipitation and stream flow characteristics were top predictors of macroinvertebrate assemblages and had similar magnitudes of effect as in-stream water chemistry. Path analyses revealed that land use activities in the watershed and at the stream site degraded macroinvertebrate assemblages indirectly by altering relative bed stability, water quality, and riparian cover/complexity. Increased riparian cover was associated with greater macroinvertebrate condition by reducing land use impacts on stream flow, streambed substrate, and water quality, but the pathways differed among ecoregions. In the WMT, site-level riparian cover affected macroinvertebrate assemblages partly through indirect pathways associated with greater streambed stability and reduced total nitrogen concentrations. In contrast, in the XER, watershed-level riparian cover affected macroinvertebrate assemblages through greater specific stream power. Identifying the relative effects of and pathways by which natural and anthropogenic factors affect macroinvertebrates can serve as a framework for prioritizing management and conservation efforts.

"Why is this relevant for me?": increasing content relevance enhances student motivation and vitality

The notion that motivation is imperative for students' psychological well-being and academic functioning is central to Self-Determination Theory (SDT). According to SDT, different types of motivations can co-occur to a various degree with separate outcomes, depending on the extent of experienced degree of autonomy. In the current study, we investigate how making a learning exercise more relevant for higher education STEM students can affect aspects of student functioning mediated through motivation. In a randomized experiment, results indicate that the students who received a more "relevant" assignment (experimental group) experienced more autonomous forms of motivation relative to the students who received a "generic" or "traditional" exercise (control group). Further, the experimental group reported higher levels of vitality and effort relative to the control group. Using a pre- and post-test design measuring changes in emotional affect during the learning activity, we found that the control group reported an increase in negative affect and a decrease in positive affect. Finally, path analysis showed significant relationships between the type of assignment provided and motivation and student functioning.

Adjusting for Baseline Measurements of the Mediators and Outcome as a First Step Toward Eliminating Confounding Biases in Mediation Analysis

Mediation analysis prevails for researchers probing the etiological mechanisms through which treatment affects an outcome. A central challenge of mediation analysis is justifying sufficient baseline covariates that meet the causal assumption of no unmeasured confounding. But current practices routinely overlook this assumption. In this article, we suggest a relatively easy way to mitigate the risks of incorrect inferences resulting from unmeasured confounding: include pretreatment measurements of the mediator(s) and the outcome as baseline covariates. We explain why adjusting for pretreatment baseline measurements is a necessary first step toward eliminating confounding biases. We hope that such a practice can encourage explication, justification, and reflection of the causal assumptions underpinning mediation analysis toward improving the validity of causal inferences in psychology research.

How job demands and job resources contribute to our overall subjective well-being

Objectives

How the work environment contributes to employees' overall subjective well-being remains inadequately explored. Building upon the seminal Job Demands-Resources model, this study aims to test a complex model that combines leadership, job demands, and job resources, as factors contributing either indirectly (via job satisfaction) or directly to employees' subjective well-being (SWB).

Methods

The cross-sectional data (N = 1,859) of the Belgian National happiness study (2020) were used. Leadership (satisfaction with leadership; perceived supervisor support), job demands (role conflict; job insecurity; work-private conflict; perceived working conditions), job resources (autonomy; relatedness; competence; skill utilization; personal growth), job satisfaction and subjective well-being (life evaluation; positive affect; negative affect) were assessed via self-report questionnaires. The proposed model investigates the direct impact of job demands and resources on SWB, as well as the indirect impact with job satisfaction as mediating factor, and was tested using the Structural Equation Modeling technique.

Results

Findings supported the proposed model. Both job demands and job resources have a direct relationship with SWB. Job resources are positively related to overall SWB, whereas job demands negatively affected SWB. Moreover, job resources are more strongly related to SWB compared to job demands. The demands and resources also indirectly contribute to employee's SWB via job satisfaction as job satisfaction appeared to mediate these relationships.

Conclusion

The current study shows that both job demands and resources directly and indirectly contribute to employees' SWB. Creating a supportive and healthy work environment is thus of paramount importance in order to foster employees' SWB. In particular, investing in improving job resources may be a fruitful approach to promote employees' overall subjective well-being.

The role of universal health coverage and global health security nexus and interplay on SARS-CoV-2 infection and case-fatality rates in Africa : a structural equation modeling approach

BACKGROUND

The Coronavirus Disease (COVID-19) caused by SARS-CoV-2 infections remains a significant health challenge worldwide. There is paucity of evidence on the influence of the universal health coverage (UHC) and global health security (GHS) nexus on SARS-CoV-2 infection risk and outcomes. This study aimed to investigate the effects of UHC and GHS nexus and interplay on SARS-CoV-2 infection rate and case-fatality rates (CFR) in Africa.

METHODS

The study employed descriptive methods to analyze the data drawn from multiple sources as well used structural equation modeling (SEM) with maximum likelihood estimation to model and assess the relationships between independent and dependent variables by performing path analysis.

RESULTS

In Africa, 100% and 18% of the effects of GHS on SARS-CoV-2 infection and RT-PCR CFR, respectively were direct. Increased SARS-CoV-2 CFR was associated with median age of the national population (β = -0.1244, [95% CI: -0.24, -0.01], P = 0.031 ); COVID-19 infection rate (β = -0.370, [95% CI: -0.66, -0.08], P = 0.012 ); and prevalence of obesity among adults aged 18 + years (β = 0.128, [95% CI: 0.06,0.20], P = 0.0001) were statistically significant. SARS-CoV-2 infection rates were strongly linked to median age of the national population (β = 0.118, [95% CI: 0.02,0.22 ], P = 0.024); population density per square kilometer, (β = -0.003, [95% CI: -0.0058, -0.00059], P = 0.016 ) and UHC for service coverage index (β = 0.089, [95% CI: 0.04,0.14, P = 0.001 ) in which their relationship was statistically significant.

CONCLUSIONS

The study shade a light that UHC for service coverage, and median age of the national population, population density have significant effect on COVID-19 infection rate while COVID-19 infection rate, median age of the national population and prevalence of obesity among adults aged 18 + years were associated with COVID-19 case-fatality rate. Both, UHC and GHS do not emerge to protect against COVID-19-related case fatality rate.

The role of psychological distress, stigma and coping strategies on help-seeking intentions in a sample of Italian college students

BACKGROUND

Mental health issues are common among university students, but the latter are unlikely to seek professional help even when mental health services are available. Coping strategies, stigma and psychological distress are often considered as factors that can affect help-seeking intentions in university students.

METHODS

This study aimed to determine the role of coping strategies, stigma and psychological distress on the intentions to seek professional help for psychological problems. All students (N = 13,886) from an Italian medium-sized university were asked to participate in a multidimensional online survey and 3754 (27.1%) agreed to participate. A Structural Equation Modelling approach was applied to explore the simultaneous direct and indirect effects of distress, stigma and coping strategies on professional help-seeking intentions.

RESULTS

Results showed that students were not very likely to seek professional help and, through the Structural Equation Model, psychological distress was found to be positively correlated with coping strategies, which in turn was negatively associated with the stigma of seeking help. The latter was negatively associated with professional help-seeking intentions. These effects suggest that students with significant psychological distress use coping strategies to face the stigma of seeking help: the lower the stigma of seeking help, the higher the chance of developing intentions to seek professional help.

CONCLUSIONS

This study suggests the importance of implementing programs to encourage college students to seek help, including measures that foster a stigma-free environment, reduce psychological distress and promote the use of adaptive coping strategies. Interventions should be focused firstly on self-stigma and secondly on perceived stigma, taking into consideration the level of psychological distress and social stereotypes associated with mental disorders and help seeking behaviours. Programs about coping are also essential and should focus on promoting emotion-focused strategies and problem-focused strategies.

Examination of sleep in relation to dietary and lifestyle behaviors during Ramadan: A multi-national study using structural equation modeling among 24,500 adults amid COVID-19

Background

Of around 2 billion Muslims worldwide, approximately 1.5 billion observe Ramadan fasting (RF) month. Those that observe RF have diverse cultural, ethnic, social, and economic backgrounds and are distributed over a wide geographical area. Sleep is known to be significantly altered during the month of Ramadan, which has a profound impact on human health. Moreover, sleep is closely connected to dietary and lifestyle behaviors.

Methods

This cross-sectional study collected data using a structured, self-administered electronic questionnaire that was translated into 13 languages and disseminated to Muslim populations across 27 countries. The questionnaire assessed dietary and lifestyle factors as independent variables, and three sleep parameters (quality, duration, and disturbance) as dependent variables. We performed structural equation modeling (SEM) to examine how dietary and lifestyle factors affected these sleep parameters.

Results

In total, 24,541 adults were enrolled in this study. SEM analysis revealed that during RF, optimum sleep duration (7-9 h) was significantly associated with sufficient physical activity (PA) and consuming plant-based proteins. In addition, smoking was significantly associated with greater sleep disturbance and lower sleep quality. Participants that consumed vegetables, fruits, dates, and plant-based proteins reported better sleep quality. Infrequent consumption of delivered food and infrequent screen time were also associated with better sleep quality. Conflicting results were found regarding the impact of dining at home versus dining out on the three sleep parameters.

Conclusion

Increasing the intake of fruits, vegetables, and plant-based proteins are important factors that could help improve healthy sleep for those observing RF. In addition, regular PA and avoiding smoking may contribute to improving sleep during RF.

Do executive functions explain older adults' health-related quality of life beyond event-based prospective memory?

Previous work has shown that event-based prospective memory (EBPM) predicted health-related quality of life (HrQoL). In the present study, we aimed to examine whether the relationship between EBPM and HrQoL extended to life satisfaction, and whether it persisted after controlling for other cognitive functions related to EBPM, namely executive functions and retrospective memory. We tested two models using structural equation modeling with latent variables in a sample of older adults. In the first model, we assessed whether EBPM predicted life satisfaction and HrQoL; in the second model, we controlled for retrospective memory and executive functions. The first model indicated that EBPM was related to HrQoL. However, in the second model, this relationship was eliminated by executive functions; life satisfaction was not related to any of the cognitive variables. Findings corroborated the link between HrQoL and EBPM, suggesting that such relationship stems from executive functions rather than retrospective memory.

Mental and Physical Health, Psychosocial Maturity, and Desistance in Young Adulthood

Recent theoretical and empirical work has drawn increased attention to the role that mental and physical health can play in promoting life-course success and desistance from crime. This study integrates literature on youth development with the health-based desistance framework to investigate a key developmental pathway through which health influences desistance among system-involved youth. Using multiple waves of data from the Pathways to Desistance Study, the current study uses generalized structural equation modeling to examine whether and to what extent mental and physical health influence offending and substance use directly and indirectly through psychosocial maturity. Findings indicate that both depression and poor health stall the development of psychosocial maturity, and that those with higher psychosocial maturity are less likely to engage in offending and substance use. The model provides general support for the health-based desistance framework, finding an indirect process linking better health states to normative developmental desistance processes. Results hold important implications for the development of age-graded policies and programs geared toward promoting desistance among serious adolescent offenders both within correctional and community settings.

Developmental pathways from child maltreatment to adolescent pregnancy: A multiple mediational model

Adolescent pregnancy (AP) is a significant public health issue. Child maltreatment (CM) represents an established risk factor, yet little is known about the explanatory mechanisms linking the phenomena. Informed by developmental theory, this study prospectively tested seven multi-level, indirect pathways that could plausibly explain the relationship between CM and AP: (1) substance use (polysubstance use and frequency); (2) sexual risk behavior; (3) depressive symptoms; (4) posttraumatic stress disorder symptoms; (5) cognitive dysregulation; (6) pregnancy desire and difficulty expectancies; and (7) age at menarche. Data came from a prospective, longitudinal cohort study of 469 ethnically diverse, nulliparous adolescent females, designed to examine the impact of substantiated CM on reproductive outcomes such as pregnancy and childbirth (265 maltreated and 204 demographically matched comparison adolescents). A multiple-mediator structural equation model was conducted to simultaneously test multiple indirect effects while accounting for confounding variables. Maltreatment had an indirect effect on pregnancy via substance use and higher pregnancy desire/lower perceived difficulty. Findings represent a step towards elucidating pathways linking CM with AP. Recommendations are offered to prevent pregnancy by addressing the pregnancy-specific mechanisms that are part of the maltreatment sequelae.

"It's not you, it's me": identity disturbance as the main contributor to interpersonal problems in pathological narcissism

BACKGROUND

Core impairments in self and other functioning typify individuals with personality disorder. While interpersonal dysfunction is a known element of narcissistic disorders, empirical research investigating intrapersonal elements is lacking. The aim of this study was to investigate the internal representations of individuals with grandiose and vulnerable features, as manifested through their attachment styles, and the specific role of identity disturbance in explaining the relationship between pathological narcissism and maladaptive interpersonal functioning.

METHODS

A sample of 270 university students completed the Brief Pathological Narcissism Inventory (B-PNI), the Severity Indices of Personality Problems (SIPP), the Relationship Questionnaire (RQ), and the Inventory of Interpersonal Problems (IIP-32).

RESULTS

Both vulnerable and grandiose narcissism were positively associated with both fearful and preoccupied attachment, and negatively associated with secure attachment, whilst grandiose narcissism was also positively associated with dismissive attachment. Furthermore, unstable representations of self, poor self-reflective functioning, and low sense of purpose fully mediated the relationship between interpersonal problems and grandiose narcissism while partially mediating the relationship between interpersonal problems and vulnerable narcissism.

CONCLUSIONS

Overall, our findings suggest that for individuals presenting with narcissistic features, capacity for adaptive interpersonal functioning is grounded by deficits in identity integration. Implications of these findings are discussed.

A combined model of child malnutrition and morbidity in Ethiopia using structural equation models

Malnutrition and morbidity are substantial problems in Ethiopia and are still pervasive and persistent. Despite this, there has been scant research on the coexistence of malnutrition and morbidity indicators. Moreover, previous studies were based on all data records of measurements from manifest data. Thus, this study aims to identify the correlates and coexistence of child malnutrition and morbidity within this country. Cross-sectional data which is collected by Ethiopia Demographic and Health Survey were used. The generalized structural equation models were used to examine the association between child malnutrition, morbidity, and potential risk factors. The generalized structural equation models help to provide latent effects of child malnutrition and morbidity within a combined modeling framework. In addition, the generalized structural equation models make it possible to analyze malnutrition as a mediator of the association between selected risk factors and latent variable morbidity. The data analysis was done using SPSS AMOS and R software. The analysis indicated that children born to nourished mothers (AOR = 0.71, 95% CI 0.68-0.75), born to enough birth space between 24 and 47 months and (AOR = 0.93, 95% CI 0.88-0.99), 48 months and above (AOR = 0.71, 95% CI 0.65-0.76), being from middle-income households (AOR = 0.85, 95% CI 0.78-0.91), high-income households (AOR = 0.66, 95% CI 0.61-0.72), from mother with primary or secondary (AOR = 0.79, 95% CI 0.75-0.85) and higher education level (AOR = 0.57, 95% CI 0.41-0.78) were less affected by malnutrition. It also revealed that a child born second to third (AOR = 0.87, 95% CI 0.77-0.99), fourth and higher (AOR = 0.88, 95% CI 0.79-0.99) and children from a husband-educated higher level (AOR = 0.76, 95% CI 0.64-0.89) were less likely to be ill. Children who breastfeed (AOR = 0.98, 95% CI 0.80-0.99), from nourished mothers (AOR = 0.96, 95% CI 0.94-0.097), from middle income (AOR = 0.97, 95% CI 0.96-0.99), high-income households (AOR = 0.94, 95% CI 0.93-0.96), birth spacing 24-47 months (AOR = 0.99, 95% CI 0.98-1.00) and 48 months and above (AOR = 0.96, 95% CI 0.94-0.97) were indirectly affected by morbidity via malnutrition. This investigation has revealed that childhood malnutrition and morbidity remain major child health challenges in Ethiopia with demographic, socioeconomic, maternal, child, and geographic variables playing significant roles. Efforts to resolve these issues need to take these factors into account. Therefore, malnutrition and morbidity prevention should include encouraging birth spacing, mother education programs, and breastfeeding practices.

Vaping in a Time of Pandemics: Risk Perception and Motivations for Electronic Cigarette Use

INTRODUCTION

Prior studies on the association between the intensity of and motives for vaping e-cigarettes have highlighted the psychological dynamics of motivational changes, but less about how vaping motives may shift as a function of risk perceptions exacerbated by unanticipated events. This study frames the COVID-19 pandemic as an exacerbating threat to pulmonary health, and tests how e-cigarette users' risk perceptions of COVID-19 are related to different motives for vaping and ultimately the intensity of e-cigarette use.

AIMS AND METHODS

An online survey of e-cigarette users in the United States (n = 562) was conducted during April 2020 when much of the United States was under "lockdown" conditions. We distinguished three types of vaping motives (health, socialization, and dependence) and established the classification with confirmatory factor analysis. Structural equation modeling was conducted for path analyses and mediation tests.

RESULTS

All three vaping motives were significantly associated with greater use intensity. A heightened risk perception of e-cigarette users' vulnerability to COVID-19 was inversely associated with use intensity (-.18, p < .01) and health motives for vaping (-.27, p < .001), but not associated with socialization and dependence motivations. Health motives for vaping mediated 35% of the association between COVID-19 risk perceptions and use intensity.

CONCLUSIONS

Our findings indicate that risk perceptions of exacerbated threats may reduce e-cigarette use directly, and also indirectly through shifting certain types of motivations for vaping. Beyond elucidating the relational dynamics between vaping psychology and health risks, these results also indicate health professionals may leverage the pandemic to promote nicotine cessation or reduced use.

IMPLICATION

Little is known about how vaping motives shift after unanticipated events such as pandemics. This study contributes to knowledge of how the use of e-cigarettes is motivated by different dimensions of rationales and exogenous risks. Exploiting the emergence of the COVID-19 pandemic, we found risk perceptions are associated with the intensity of e-cigarette use indirectly specifically through health motivations. Risk perceptions are not associated with socialization and dependence motives for vaping.

Investigating speed-safety association: Considering the unobserved heterogeneity and human factors mediation effects

The relationship between mean speed and crash likelihood is unclear in the literature. The contradictory findings can be attributed to the masking effects of the confounding variables in this association. Moreover, the unobserved heterogeneity has almost been criticized as a reason behind the current inconclusive results. This research provides an effort to develop a model that analyzes the mean speed-crash frequency relationship by crash severity and type. Also, the confounding and mediation effects of the environment, driver, and traffic-related attributes have been considered. To this end, the loop detector and crash data were aggregated daily for rural multilane highways of Tehran province, Iran, covering two years, 2020-2021. The partial least squares path modeling (PLS-PM) was employed for crash causal analysis along with the finite mixture partial least squares (FIMIX-PLS) segmentation to account for potential unobserved heterogeneity between observations. The mean speed was negatively and positively associated with the frequency of property damage-only (PDO) and severe accidents, respectively. Moreover, driver-related variables, including tailgating, distracted driving, and speeding, played key mediation roles in associating traffic and environmental factors with the crash risk. The higher the mean speed and the lower the traffic volume, the higher odds of distracted driving. Distracted driving was, in turn, associated with the higher vulnerable road users (VRU) accidents and single-vehicle accidents, triggering a higher frequency of severe accidents. Moreover, lower mean speed and higher traffic volume were positively correlated with the percentage of tailgating violations, which, in turn, predicted multi-vehicle accidents as the main predictor of PDO crash frequency. In conclusion, the mean speed effects on the crash risk are entirely different for each crash type through distinct crash mechanisms. Hence, the distinct distribution of crash types in different datasets might have led to current inconsistent results in the literature.

Physical attractiveness and women's intra-household bargaining power

This paper explores the role of physical attractiveness in affecting women's intra-household bargaining power. The empirical analysis based on the China Family Panel Studies finds that physical attractiveness significantly increases women's intra-household bargaining power. To solve the endogenous problem of physical attractiveness, we employ an instrument-variable-based regression to corroborate the conclusion. Using generalized structural equation model, we show that income, self-esteem, and interpersonal relationship are three possible transmission channels (or mediators) between physical attractiveness and women's intra-household bargaining power.

Methodologies to Advance a "Science of How": Identifying and Engaging Intervention Targets and Outcomes

OBJECTIVE

Although implementation science has taken hold in many areas of psychiatric services research, a need remains for developing effective, low-cost interventions for specific subpopulations with mental health conditions. The experimental therapeutics approach has gained momentum as a framework for developing effective interventions. However, few studies have taken steps to rigorously apply experimental therapeutics. This article provides a blueprint for applying this approach.

METHODS

A focused literature review was conducted to document the frequency of the application of experimental therapeutics among articles published between 2011 and 2021 in some of the American Psychiatric Association's journals. Independently of the review, the authors delineated a four-component approach for applying experimental therapeutics in research and present practical, innovative strategies to advance psychiatric services research.

RESULTS

The four-component approach includes outlining prerequisites, identifying target mechanisms, proposing intervention strategies to address target mechanisms, and using advanced analytic methods. The strategies described for each component are not exhaustive; rather, they suggest promising avenues for research that can lead to more effective interventions and deeper understanding of how, and for whom, an intervention works.

CONCLUSIONS

The application of experimental therapeutics in psychiatric services research can lead to increased development, refinement, and implementation of effective interventions for specific populations or conditions.

TRUE Dads: The impact of a couples-based fatherhood intervention on family relationships, child outcomes, and economic self-sufficiency

TRUE Dads, a federally funded Responsible Fatherhood intervention, aims to strengthen three of men's key roles in the family: (1) as fathers, building and maintaining positive engagement with their child; (2) as partners, maintaining a positive relationship with their co-parent; and (3) as providers, through fostering employment and economic self-sufficiency. A feature of the program is that low-income fathers and their co-parenting partners participate together in 6 3-hour group workshops, followed by optional participation in an additional 6 3-hour workshops. Fathers in the intervention condition were offered a chance to participate in a 2-week employment program. 1,042 co-parenting teams were recruited and randomly assigned to TRUE Dads' group intervention (60%) or a no-treatment control group (40%). In analyses of single measures, one year after study entry, compared with no-treatment controls, TRUE Dads program participants reported fewer depressive symptoms, less destructive couple communication and domestic violence, and increased employment for fathers. Using expanded latent variable measures of core constructs, Structural Equation Modeling revealed indirect effects of the intervention, in which reductions in both parents' negative symptoms and destructive couple communication were associated with (a) reductions in negative parenting qualities and children's behavior problems and (b) increases in fathers' economic self-sufficiency. Reducing parents' personal distress and improving relationship quality between co-parents appears to be important to enhancing fathers' positive family engagement. From a family policy perspective, the results suggest that integration rather than separation of healthy marriage, responsible fatherhood, and employment programs could provide synergistic power to programs designed to strengthen low-income families.

Beyond the Mean: A Flexible Framework for Studying Causal Effects Using Linear Models

Graph-based causal models are a flexible tool for causal inference from observational data. In this paper, we develop a comprehensive framework to define, identify, and estimate a broad class of causal quantities in linearly parametrized graph-based models. The proposed method extends the literature, which mainly focuses on causal effects on the mean level and the variance of an outcome variable. For example, we show how to compute the probability that an outcome variable realizes within a target range of values given an intervention, a causal quantity we refer to as the probability of treatment success. We link graph-based causal quantities defined via the do-operator to parameters of the model implied distribution of the observed variables using so-called causal effect functions. Based on these causal effect functions, we propose estimators for causal quantities and show that these estimators are consistent and converge at a rate of [Formula: see text] under standard assumptions. Thus, causal quantities can be estimated based on sample sizes that are typically available in the social and behavioral sciences. In case of maximum likelihood estimation, the estimators are asymptotically efficient. We illustrate the proposed method with an example based on empirical data, placing special emphasis on the difference between the interventional and conditional distribution.

Structural Relationships Among Mental Boundaries, Childhood Imaginary Companions, Creative Experiences, and Entity Encounters

This study investigated relationships between thin mental boundary functioning, creativity, imaginary companions (ICs), and anomalous '(entity) encounter experiences.' A convenience sample of 389 respondents completed the Revised Transliminality Scale, Oxford-Liverpool Inventory of Feelings and Experiences, Creative Experiences Questionnaire, Survey of Strange Events, and a measure of Childhood Imaginary Companions. Competing testing with path analysis found that the best-fitting model was consistent with the causal chain of 'Thin Boundaries (transliminality and schizotypy) → Creative Experiences → ICs → (Entity) Encounter Experiences.' These results suggest that deep-types of ICs (i.e., showing apparent independent agency) are perhaps most accurately characterized as syncretic cognitions versus hallucination-like experiences. The authors examine these findings relative to study limitations, as well as discussing the need for future research that approaches ICs as a special mental state that can facilitate allied altered-anomalous experiences. In this context, this study furthered understanding of relationships between conscious states related to mental boundaries, childhood imaginary companions, creative experiences, and entity encounters.

Incorporating causality in energy consumption forecasting using deep neural networks

Forecasting energy demand has been a critical process in various decision support systems regarding consumption planning, distribution strategies, and energy policies. Traditionally, forecasting energy consumption or demand methods included trend analyses, regression, and auto-regression. With advancements in machine learning methods, algorithms such as support vector machines, artificial neural networks, and random forests became prevalent. In recent times, with an unprecedented improvement in computing capabilities, deep learning algorithms are increasingly used to forecast energy consumption/demand. In this contribution, a relatively novel approach is employed to use long-term memory. Weather data was used to forecast the energy consumption from three datasets, with an additional piece of information in the deep learning architecture. This additional information carries the causal relationships between the weather indicators and energy consumption. This architecture with the causal information is termed as entangled long short term memory. The results show that the entangled long short term memory outperforms the state-of-the-art deep learning architecture (bidirectional long short term memory). The theoretical and practical implications of these results are discussed in terms of decision-making and energy management systems.

Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach

The ubiquitous nature of smartphone ownership, its broad application and usage, along with its interactive delivery of timely feedback are appealing for health-related behavior change interventions via mobile apps. However, users' perspectives about such apps are vital in better bridging the gap between their design intention and effective practical usage. In this vein, a modified technology acceptance model (mTAM) is proposed here, to explain the relationship between users' perspectives when using an AI-based smartphone app for personalized nutrition and healthy living, namely, PROTEIN, and the mTAM constructs toward behavior change in their nutrition and physical activity habits. In particular, online survey data from 85 users of the PROTEIN app within a period of 2 months were subjected to confirmatory factor analysis (CFA) and regression analysis (RA) to reveal the relationship of the mTAM constructs, i.e., perceived usefulness (PU), perceived ease of use (PEoU), perceived novelty (PN), perceived personalization (PP), usage attitude (UA), and usage intention (UI) with the users' behavior change (BC), as expressed via the acceptance/rejection of six related hypotheses (H1-H6), respectively. The resulted CFA-related parameters, i.e., factor loading (FL) with the related p-value, average variance extracted (AVE), and composite reliability (CR), along with the RA results, have shown that all hypotheses H1-H6 can be accepted (p < 0.001). In particular, it was found that, in all cases, FL > 0.5, CR > 0.7, AVE > 0.5, indicating that the items/constructs within the mTAM framework have good convergent validity. Moreover, the adjusted coefficient of determination (R 2) was found within the range of 0.224-0.732, justifying the positive effect of PU, PEoU, PN, and PP on the UA, that in turn positively affects the UI, leading to the BC. Additionally, using a hierarchical RA, a significant change in the prediction of BC from UA when the UI is used as a mediating variable was identified. The explored mTAM framework provides the means for explaining the role of each construct in the functionality of the PROTEIN app as a supportive tool for the users to improve their healthy living by adopting behavior change in their dietary and physical activity habits. The findings herein offer insights and references for formulating new strategies and policies to improve the collaboration among app designers, developers, behavior scientists, nutritionists, physical activity/exercise physiology experts, and marketing experts for app design/development toward behavior change.

Online listening responses and e-learning performance

Purpose

This research investigates the impact of learners' non-substantive responses in online course forums, referred to as online listening responses, on e-learning performance. A common type of response in online course forums, online listening responses consist of brief, non-substantive replies/comments (e.g. “agree,” “I see,” “thank you,” “me too”) and non-textual inputs (e.g. post-voting, emoticons) in online discussions. Extant literature on online forum participation focuses on learners' active participation with substantive inputs and overlooks online listening responses. This research, by contrast, stresses the value of online listening responses in e-learning and their heterogeneous effects across learner characteristics. It calls for recognition and encouragement from online instructors and online forum designers to support this activity.

Design/methodology/approach

The large-scale proprietary dataset comes from a leading MOOC (massive open online courses) platform in China. The dataset includes 68,126 records of learners in five MOOCs during 2014–2018. An ordinary least squares model is used to analyze the data and test the hypotheses.

Findings

Online listening responses in course forums, along with learners' substantive inputs, positively influence learner performance in online courses. The effects are heterogeneous across learner characteristics, being more prominent for early course registrants, learners with full-time jobs and learners with more e-learning experience, but weaker for female learners.

Originality/value

This research distinguishes learners' brief, non-substantive responses (online listening responses) and substantive inputs (online speaking) as two types of active participation in online forums and provides empirical evidence for the importance of online listening responses in e-learning. It contributes to online forum research by advancing the active-passive dichotomy of online forum participation to a nuanced classification of learner behaviors. It also adds to e-learning research by generating insights into the positive and heterogeneous value of learners' online listening responses to e-learning outcomes. Finally, it enriches online listening research by introducing and examining online listening responses, thereby providing a new avenue to probe online discussions and e-learning performance.

Causal Inference in Radiomics: Framework, Mechanisms, and Algorithms

The widespread use of machine learning algorithms in radiomics has led to a proliferation of flexible prognostic models for clinical outcomes. However, a limitation of these techniques is their black-box nature, which prevents the ability for increased mechanistic phenomenological understanding. In this article, we develop an inferential framework for estimating causal effects with radiomics data. A new challenge is that the exposure of interest is latent so that new estimation procedures are needed. We leverage a multivariate version of partial least squares for causal effect estimation. The methodology is illustrated with applications to two radiomics datasets, one in osteosarcoma and one in glioblastoma.

Partisanship, Policy, and Americans' Evaluations of State-Level COVID-19 Policies Prior to the 2020 Election

The COVID-19 pandemic was a key policy issue during the 2020 election in the United States. As such, it is important to analyze how voters evaluated government responses to the pandemic. To this end, in this article, we examine factors that influenced Americans' evaluations of state-level COVID-19 policy responses. We find that during the pandemic onset period, Americans typically rated their state governments' responses more favorably if their governor was a co-partisan. In contrast, during the re-opening period, we find that Democrats relied on both partisanship and policy to evaluate their state-level responses, while Republicans continued to rely solely on partisanship. We contend that given the complex policy environment surrounding COVID-19, Americans may have not been fully aware of the policies their state governments adopted, so they relied on partisan cues to help them evaluate their state-level policy responses. But by the re-opening period, Americans likely had enough time to better understand state-level policy responses; this allowed Democrats to also evaluate their state-level responses based on policy. These findings shed light on how Americans evaluated COVID-19 responses just prior to the 2020 election.

Impact of working from home on activity-travel behavior during the COVID-19 Pandemic: An aggregate structural analysis

The ongoing COVID-19 pandemic has created significant public health concerns that led the public and private sectors to impose stay-at-home and work-from-home policies. Although working from home has been a conventional albeit infrequent behavior, the prevalence of this option was significantly and rapidly accelerated during the pandemic. This study explored the impacts of working from home on activity-travel behavior during the pandemic. Both work and non-work activity participation declined during the pandemic but to what extent was this due to working from home? How did working from home affect other measures of travel such as person-miles traveled? We approached these questions by developing a Structural Regression model and using cross-sectional data for the early phase of the pandemic when the infection curve was flattened and activity-travel behavior became relatively stable following the drastic changes observed during the pandemic's initial shock. Combining U.S. county-level data from the Maryland Transportation Institute and Google Mobility Reports, we concluded that the proportion of people working from home directly depended on pandemic severity and associated public health policies as well as on a range of socio-economic characteristics. Working from home contributed to a reduction in workplace visits. It also reduced non-work activities but only via a reduction in non-work activities linked to work. Finally, a higher working from home proportion in a county corresponded to a reduction in average person-miles traveled. A higher degree of state government responses to containment and closure policies contributed to an increase in working from home, and decreases in workplace and non-workplace visits and person-miles traveled in a county. The results of this study provide important insights into changes in activity-travel behavior associated with working from home as a response strategy to major disruptions such as those imposed by a pandemic.

A systematic review of the associations, mediators and moderators of life satisfaction, positive affect and happiness in near-centenarians and centenarians

OBJECTIVE

Results from studies investigating life satisfaction, positive affect and happiness of near-centenarians (95+) and centenarians are inconsistent. This is the first systematic review to summarise the extant literature on the subjective well-being of this unique age group.

METHOD

Seven electronic databases (PubMed, MEDLINE, EMBASE, PsycINFO, CINAHL, Web of Science and the Cochrane database for systematic reviews) were systematically searched. Subjective well-being was defined as life satisfaction, positive affect and happiness. A narrative synthesis of relevant articles was undertaken.

RESULTS

Of 28 studies eligible for inclusion in this review, 20 predominantly examined life satisfaction, 11 positive affect and 4 happiness. Sex and other demographic variables were not significant predictors of subjective well-being. In contrast, greater perceived health was significantly associated with higher levels of life satisfaction and positive affect. Fatigue and visual impairment were significantly correlated with lower levels of life satisfaction and positive affect. However, there was considerable heterogeneity in the findings on physical, cognitive and social associations, mediators and moderators.

CONCLUSION

The large discrepancy of results in the literature may be explained by methodological differences between studies. Centenarian research needs a clearer definition of life satisfaction, positive affect and happiness as their operationalisation is inconsistent. An international consortium of centenarian studies could facilitate cross-cultural comparisons on subjective well-being. Future research should be directed towards interventions that promote subjective well-being in the oldest-old.

Impact of institutional voids on the performance of small and medium-sized enterprises

Purpose

There is a critical gap in assessing how institutional voids affect SMEs' growth, investment commitment and reputation. The purpose of this paper is to explain how institutional void affects these three dimensions of SME performance; and to develop an institutional void-SME performance framework that can be applied for strategising, resourcing and competency acquisition for better performance.

Design/methodology/approach

The study used the Enterprise Survey Data of the World Bank, consisting of 118,763 firms from 140 countries. The structural equation modelling (SEM) is used to analyse the data, validate our analytical model and investigate the imposed theoretical claims of causality as indicated by specific research questions through correlation/covariation between the constructs of institutional void and SME performance.

Findings

Evidence suggests that there is a strong positive correlation between formal institutional infrastructure (independent variable) and SMEs' reputation (dependent variable). Among the institutional sub-constructs, tax administration, business licensing and permits, access to a bigger market and skilled labour and informal competition are significant for the SME performance constructs. We find similar results while comparing SMEs with large businesses.

Practical implications

The institutional void-SME performance framework developed from our findings will allow SMEs to manage institutional voids affecting their performance. The analytical framework can also be the foundation for future empirical research.

Originality/value

The originality of the study is embedded in its investigation of SMEs' investment commitment and reputation in relation to institutional voids. The latent relationship between the sub-constructs of institutional voids and SME performance adds new knowledge to the dynamic relationship between institutions and firm performance.

Plant Diversity Increased Arthropod Diversity and Crop Yield in Traditional Agroforestry Systems but Has No Effect on Herbivory

Improving agricultural production in response to the increasing food demand remains a major challenge in agroecology. The world has made significant efforts to meet this issue by developing several cultivation techniques, such as the use of chemical fertilizers and arable land conversion into agricultural land. However, most of these techniques have caused a significant loss of biodiversity and ecosystems services. Recent data suggest that biological conservation within and around agroforestry systems are potential solutions that can both reduce biodiversity loss and guarantee crop production. This logic is based on the hypothesis that increasing plant diversity in and around agricultural systems can limit the pest attack rate and increase crop yield. We tested this hypothesis using structural equation modeling on empirical data collected in agroforestry systems around the Pendjari biosphere reserve in West Africa. We measured crop diversity, crop yield, arthropod pest diversity, abundance, the rate of crop herbivory, and the diversity of plants in surrounding natural vegetation in 32 permanent plots. We estimated arthropod diversity and abundance using pitfall traps. We found a direct positive effect for plant diversity and a direct negative effect of arthropod herbivory on crop yield. The diversity of plants in surrounding natural vegetation had a direct positive effect on arthropod pest diversity but a marginal negative direct effect on the rate of crop herbivory. We found no significant direct or indirect effect for crop diversity. Our findings underline the important role of biodiversity conservation in agricultural production improvement. We suggest that the conservation of plant diversity around agroforestry systems may be an effective option to control herbivory damage. Its combination with other pest control techniques may further limit crop depredation and ensure the long-term conservation of wildlife.

Material Hardships, Perceived Stress, and Health among Low-Wage Hospital Workers

Many service, clerical, and technical hospital workers deemed essential during the pandemic have wages that do not reflect the essential nature of their work and do not earn enough income to cover basic expenses. Thus, many experience material hardships related to food, housing, and medical care. Previous studies have shown strong relationships between material hardships and health; however, they do not fully explain the role of stress as an intervening mechanism. This cross-sectional study analyzes an online survey with 257 lower-wage hospital workers to examine the relationships between hardships and health, and how perceived stress mediates these relationships. Path analysis revealed that financial and food hardships were related to mental health through perceived stress, while medical hardship was directly associated with physical health. These findings add to the evidence that workers' hardships either directly or indirectly contribute to negative mental and physical health outcomes through perceived stress. Future investigations should further examine relationships among material hardships, stress, and health, and advocacy efforts should focus on raising wages for essential hospital workers.

Sustainable Supply Chain and Business Performance: The Impact of Strategy, Network Design, Information Systems, and Organizational Structure

Technological advancement and the highly competitive nature of business have forced organizations to use multiple strategies to streamline their business operations. Current research investigates the relationship between sustainable supply chain management (SSCM) and business performance, focusing on operational and financial performance. It provides insights into the operational structure, resource utilization, and the identification of strategic tools needed to strengthen organizational performance. The researchers conducted unstructured interviews with 41 industrialists and analyzed them via open-source coding and deducing reasoning. A questionnaire was developed by analyzing critical scientific literature and unstructured interviews. Empirical responses were taken from 202 industrial corporations. The structural analyses indicate that the effective execution of SSCM significantly improves firms’ operational and financial performance. The findings also provide detailed information about different components of SSCM, namely supply chain strategy (SCS), supply chain network design (SCND), organizational structure, and information system, and explain how it relates to the previous literature review by using a multivariate statistical analysis, followed by structural equation modeling (SEM). The findings of current research highlight the significant role of SSC in accelerating firms’ operational and financial performance and suggest that SSCM should be taken as a secondary strategy and must be integrated with the overall business strategy.

Testing the moderating role of trade openness on the environmental Kuznets curve hypothesis: a novel approach

We explore the moderating role of trade openness (TO) by gauging its main and interaction effects on the economic growth and environmental quality nexus. In this direction, we implement a novel approach by using three different measures of pollution emissions (CO2-CH4-PM2.5) in the environmental Kuznets curve hypothesis and applying a structural equation modelling methodology to 115 countries, grouped into low-, middle- and high-income countries, spanning the period 1992-2018. The evidence suggests that energy consumption has a positive impact on CO2 emissions for all income panels whilst the moderating effect of TO appears to be a key degrading factor of environmental quality in low- and middle-income countries. In addition, TO's interaction with GDP growth is found to negatively affect environmental quality across all income groups. Given that global economies are on the verge of returning to pre-pandemic levels of industrial operations along with emissions in the wake of the failure of COP26 and that COVID-19 has reminded the world the urgency of developing sustainable approaches in fostering 'green economic growth' models; a host of policy measures are proposed in support of this whilst their likely implications are discussed with reference to different income level countries.