Economic distress and mental health: The role of family coping resources and behaviors

Relationships among economic distress, family coping resources and behaviors, and mental health are examined among a sample of 203 married men and 207 married women. Economic distress is negatively associated with mental health. Although family coping resources are lower among those experiencing economic distress and are generally positively related to mental health, their role as mediators of relationships between economic distress and mental health is limited. Economic distress is positively related to family coping behaviors. However, these behaviors do not have positive relationships with mental health and do not counteract the effects of economic distress on mental health. Some coping resources and behaviors have buffering effects on relationships between economic distress and mental health while others have exacerbating effects.This article is a revision of a paper presented at the annual meeting of the American Sociological Association, August, 1986. The research was supported by grant 84–164 from the Office of Program Evaluation and Research, Ohio Department of Mental Health. Additional support was provided by the Office of Computing Activities, University of Dayton.Patricia Voydanoff is Director of the Center for the Study of Family Development, University of Dayton. Dr. Voydanoff holds a Ph.D. in Sociology from Wayne State University. Her research interests include work and family life and coping with economic distress.Brenda W. Donnelly is a Research Associate at the Center for the Study of Family Development, University of Dayton. Dr. Donnelly received her Ph.D. from the University of Delaware. She is currently conducting research on adolescent childbearing and religion and family life.     

Exploring Adoptive Motherhood: Adoption-Seeking Among Hispanic and Non-Hispanic White Women

Predictors of ever having sought adoption are evaluated for Hispanic and non-Hispanic White women. Analysis of the 2002 National Survey of Family Growth, a nationally representative study of reproductive health of 7,643 women aged 15 to 44 years, is employed. These include Hispanic and non-Hispanic White women aged 18 to 44 who are currently married and cohabiting (n = 3,118) and Hispanic and non-Hispanic White women aged 18 to 44 of all marital statuses (n = 5,236). Being married, older, and attending religious services are significantly associated with having sought adoption among non-Hispanic White women. Nativity status, language spoken, and resources are significantly associated with having sought adoption among Hispanic women.     

Participation and level of play in the UK National Lottery and correlation with spending on other modes of gambling

The paper analyses UK data, collected from the Family Expenditure Survey, for over 6000 households. The focus is on participation in, and level of expenditure on, the national lotto game. Controlling for standard demographic, socio-economic and income variables, and some non-standard lifestyle indicators, it examines correlation between lotto play and expenditure on six other forms of gambling as well as on alcohol and tobacco. Correlations with lotto participation and expenditure are found to be positive and strong in most cases. Implications for the regulation of the gambling sector and for taxation policy are outlined and discussed.     

EDITORIAL

ABSTRACT

Data from Cycle 5 of the National Survey of Family Growth (NSFG) (1995) were analyzed to identify factors that could predict whether a woman 18-44 years of age would ever have sought to adopt a child. Of the 10,019 women in the specified age group overall, 508 (5.1 percent) had ever sought to adopt, including 5.4 percent of white women and 5.2 percent of black women. Multiple logistic regression analyses were conducted for all women and for white women and black women separately. Among women who were white, the likelihood of having ever sought to adopt increased under conditions of childlessness, a history of treatment for infertility and surgical sterility for non-contraceptive reasons, non-surgical sterility, or physical difficulty in becoming pregnant (subfecundity), and if the woman was married, older, had some amount of college education, and considered religion very important. Having received assisted reproductive technology treatment also increased the likelihood that women in this group had sought to adopt. The likelihood of having ever sought to adopt increased among black women who were childless, older, and surgically sterile for non-contraceptive reasons, non-surgically sterile, or subfe-cund. However, having been treated for infertility and the presence of “resource” variables (other than age) did not predict that black women would have sought adoption. Among women of all races, having been a foster parent to a child increased the likelihood that the woman had sought to adopt the child when the woman was also childless, had been treated for infertility, was non-surgically sterile or subfecund, and older. Having been a foster parent was a significant predictor among white women who were childless and had ever been treated for infertility. Results are discussed in terms of benefits and limitations of all analyses and in terms of their implications for practice, policy, and research.     

Spacing Between Births in Odisha,India

Birth spacing is of considerable importance to study the tempo and quantum of fertility. Using data from the National Family Health Survey III, this study explored the birth interval dynamics in Odisha, an eastern state of India. The life table analysis of spacing between births clearly suggests that birth spacing in the recent past has increased and the proportion of women moving to the second, third, and fourth parity has declined, leading to the decline in fertility in Odisha. From the proportional hazards model, educational level of women, age of women at previous birth, sex and survival status of the previous child, and the period effect are found to be important determinants of birth spacing at higher parities. Socioeconomic differences do not show a large effect at lower order births. This highlights the fact that most women in Odisha, regardless of their background characteristics, tend to have second births.     

Economic versus psychological forecasting. Evidence from consumer confidence surveys

Permanent and widespread psychological biases affect both the subjective probability of future economic events and their retrospective interpretation. They may give rise to a systematic gap between (over-critical) judgments and (over-optimistic) expectations – the “forecast” error. When things go bad, then, psychology suggests that people tend to become particularly bullish, amplifying the forecast error. Also, psychology argues that personal/future conditions are systematically perceived to be better than the aggregate/past ones. All this sharply contrasts with standard economic assumptions. Evidence from a unique dataset covering 10 European countries over 22 years confirms the presence of structural psychologically driven distortions in people’s judgments and expectations formation.     

Comparing the effectiveness of respondent-driven sampling and quota sampling in migration research

We evaluate the effectiveness in empirical migration research of the respondent-driven sampling (RDS) and the quota sampling with regard to four criteria: quality of the data; sociometric diversity of the sample; geographic coverage of the sample; and cost-effectiveness. We review two surveys of ex-USSR migrants, conducted simultaneously in the Warsaw metropolitan area, each undertaken with the use of one of the two sampling methods. We find that although the RDS was considerably costlier, it enabled faster data collection and posed a lower risk of underestimating the cost of the survey. We also find that the RDS generated higher-quality data, and that it was more successful in surveying short-term circular migrants. This comparative evaluation contributes to the literature on social research methods in that it links the sampling methods with the quality and character of the data, and helps assess the usefulness and applicability of RDS in empirical migration studies.     

Narratives of fathering young children in Britain: linking quantitative and qualitative analyses

The paper examines how in Britain the time fathers and couples spend in employment shifts in the first years of children’s lives, the conditions under which this happens and how fathers feel about and experience time with their families and time in paid work. In order to achieve these aims new longitudinal analysis of the UK Millennium Cohort Study (MCS) is carried out together with secondary analysis of narrative case studies drawn from a qualitative study of Fatherhood across the Generations. By linking these datasets the paper examines the potential for corroboration and complementarity between different types of data. Further, it seeks to show how qualitative cases corroborate, elaborate and expand on the main employment trajectories in the MCS population of fathers and how these extend understandings of fathers’ experience of time within families.     

The Importance of Household Management for the Business-Owning Family

The household managerial behavior of 673 business-owning families from the 1997 National Family Business Survey was examined using a scale adapted from Heck, Winter, and Stafford (1992). The scale was reliable and used to compare the managerial behavior of solo- and dual-role holders in the sample. Although t-tests revealed few significant differences between solo- and dual-role holders, factor analyses showed that the two groups differed noticeably in management style. The differences were not in the frequency of use of managerial activities but in which activities were viewed as related by the two groups.     

Structural effects of network sampling coverage I: Nodes missing at random

Network measures assume a census of a well-bounded population. This level of coverage is rarely achieved in practice, however, and we have only limited information on the robustness of network measures to incomplete coverage. This paper examines the effect of node-level missingness on 4 classes of network measures: centrality, centralization, topology and homophily across a diverse sample of 12 empirical networks. We use a Monte Carlo simulation process to generate data with known levels of missingness and compare the resulting network scores to their known starting values. As with past studies (0035 and 0135), we find that measurement bias generally increases with more missing data. The exact rate and nature of this increase, however, varies systematically across network measures. For example, betweenness and Bonacich centralization are quite sensitive to missing data while closeness and in-degree are robust. Similarly, while the tau statistic and distance are difficult to capture with missing data, transitivity shows little bias even with very high levels of missingness. The results are also clearly dependent on the features of the network. Larger, more centralized networks are generally more robust to missing data, but this is especially true for centrality and centralization measures. More cohesive networks are robust to missing data when measuring topological features but not when measuring centralization. Overall, the results suggest that missing data may have quite large or quite small effects on network measurement, depending on the type of network and the question being posed.     

Network sampling coverage II: The effect of non-random missing data on network measurement

Missing data is an important, but often ignored, aspect of a network study. Measurement validity is affected by missing data, but the level of bias can be difficult to gauge. Here, we describe the effect of missing data on network measurement across widely different circumstances. In Part I of this study (Smith and Moody, 2013), we explored the effect of measurement bias due to randomly missing nodes. Here, we drop the assumption that data are missing at random: what happens to estimates of key network statistics when central nodes are more/less likely to be missing? We answer this question using a wide range of empirical networks and network measures. We find that bias is worse when more central nodes are missing. With respect to network measures, Bonacich centrality is highly sensitive to the loss of central nodes, while closeness centrality is not; distance and bicomponent size are more affected than triad summary measures and behavioral homophily is more robust than degree-homophily. With respect to types of networks, larger, directed networks tend to be more robust, but the relation is weak. We end the paper with a practical application, showing how researchers can use our results (translated into a publically available java application) to gauge the bias in their own data.     

Can we trust parental reports of child care subsidy receipt?

In recent years, research examining determinants and consequences of the means-tested child care subsidy program (the Child Care and Development Fund [CCDF]) has grown dramatically. To measure subsidy utilization, existing studies typically rely on parent-reported measures of subsidy receipt drawn from large surveys. As the research literature on child care subsidies has grown, however, so have concerns about the trustworthiness of parent-reported subsidy use. One way to assess the quality of parent-reported subsidy use is to examine its overlap with another subsidy receipt measure, drawn from a different source. The current paper uses the Fragile Families and Child Well-Being Study (FFCWS), the only existing survey data source that contains an alternate measure of subsidy receipt — based on child care provider report — which permits a comparison to parent-reported measures. We find evidence that increases our confidence in the trustworthiness of parents as accurate reporters of subsidy receipt. In recognition that neither data source reflects “true” subsidy receipt, however, we conclude with a discussion of limitations and steps for future research.     

Counting people in the data revolution era: challenges and opportunities for population censuses*

Changes in technology, society and individual behaviours are having impressive effects on data production and use. Social networks, sensors and data infrastructure are generating a massive amount of new data (big data, big corpora, linked data, open data, etc.) that are readily available for the analysis of societies. Official statistics too is starting to pay attention to these unofficial data sources, to the aim of using them within the production processes. Despite the potentials of new data for statistical production, so far we can depict two main effects on official statistics, and especially on population censuses. First of all, there is the digitalization of data construction through both new instruments (e.g. web questionnaires) and new means of collection (e.g. tablets). Furthermore, the integration and the scaling-up of data archives is ongoing. This transition from the traditional ‘door-to-door’ census to new census methods, which make an higher use of technology, is not only a technical result, but it reflects the extent to which digital data are changing the routines of production of statistics and their use to gain social knowledge.     

Obtaining data linkage consent for children: factors influencing outcomes and potential biases

Understanding factors associated with consent for data linkage has largely focussed on adults, but parents or guardians can also be asked to consent on behalf of children for whom they are responsible. A framework for consent decision is presented, and is tested using a large nationally representative survey asking mothers to consent for both themselves and their children for two sets of records. Nearly all mothers give the same consent outcome for all their children. Consent rates are higher for education records than for health records and higher for mothers than children. Multivariate analyses suggest that minorities are generally less likely to consent, while more trust increases chances of consent. Several survey environment factors are important, with harder-to-contact respondents less likely to consent, while the presence of others and higher interviewer-respondent rapport lead to a higher chance of consent. These findings suggest potential methodologies to improve consent rates and possibly minimise bias. This is important given significant demographic differences between children across consent outcomes. However, data from a survey of 10–15 year olds in the study shows fewer differences for several important behaviours and attitudes across consent outcomes.     

Toward a valid approach to nonprofit efficiency measurement

Past literature in nonprofit management uses the overhead ratio of nonprofits as a measure of efficiency. Although the overhead ratio might measure top‐heaviness, we argue that it does not measure nonprofit efficiency. To investigate this, we use financial and operational data to rank the efficiency of Habitat for Humanity affiliates with the overhead and administrative ratio, as well as data envelopment analysis (DEA) and stochastic frontier analysis (SFA), two of the most popular efficiency measures. While the DEA and SFA rankings are statistically correlated, overhead ratio rankings are negatively correlated with both SFA and DEA rankings. We argue that nonprofit scholars, managers, and donors should move away from concepts and measures of efficiency based on financial ratios, and toward ones that embrace maximizing what nonprofits are able to make and do.     

Use of online crowdsourcing platforms for gambling research

Crowdsourcing platforms like Amazon’s Mechnical Turk and Crowdflower have been touted to be a cost-effective way to collect large amounts of behavioural data. Across four large-n studies, gambling-related behaviours, tendencies and traits among participants in these labour markets were examined. In Studies 1 and 2, both conducted on Crowdflower, problem gamblers (as measured by the benchmark Problem Gambling Severity Index) comprised 24.5% and 21.9% of participants, respectively. In Study 3, conducted on Mechanical Turk, problem gamblers comprised 9.0% of participants. In Study 4, a two-wave longitudinal study conducted on Crowdflower, problem gamblers comprised 13.5% of participants in wave one and 14.8% of participants in wave two. In Studies 2 and 3, strong convergent associations were demonstrated across various measures of problem gambling tendencies and general gambling involvement. Furthermore, it was demonstrated that gambling was associated with personality traits (impulsivity, sensation-seeking, self-control), risk attitudes, affect, and behavioural risk-taking consistent with previous research. In Study 4, it was demonstrated that measures of problem gambling have acceptable test-retest reliability. Online crowdsourcing platforms appear to offer access to samples with remarkably high proportions of problem gamblers. However, this characteristic means that such samples are not necessarily representative of gambling tendencies among more general populations.     

Modeling Participant Flows in Human Service Programs

ABSTRACT

Participants flow into, through, and out of human service programs in complex ways: into a program's screening process and out again without receiving services (ineligibility); from one internal state of receiving services to another (advances and setbacks); and out of and back into the program (repeating). Drawing on the traditions of the information systems field, we propose a methodology for defining and graphically modeling participant flows. The methodology, Status-Transition-Cycle (STC) mapping, assists in systems analysis and simultaneously suggests a data model convention for client-tracking systems.     

Toward Best Practices in Analyzing Datasets with Missing Data: Comparisons and Recommendations

Although several methods have been developed to allow for the analysis of data in the presence of missing values, no clear guide exists to help family researchers in choosing among the many options and procedures available. We delineate these options and examine the sensitivity of the findings in a regression model estimated in three random samples from the National Survey of Families and Households (n = 250–2,000). These results, combined with findings from simulation studies, are used to guide answers to a set of 10 common questions asked by researchers when selecting a missing data approach. Modern missing data techniques were found to perform better than traditional ones, but differences between the types of modern approaches had minor effects on the estimates and substantive conclusions. Our findings suggest that the researcher has considerable flexibility in selecting among modern options for handling missing data.     

The social economics of ethical consumption: Theoretical considerations and empirical evidence

Recent years have seen rising discussion of ethical consumption as a means of stemming global warming, challenging unsavory business practices, and promoting other pro-social goals. This paper first lays out a conceptual framework for understanding the spread of ethical consumption, in which heterogeneous preferences and sensitivity to social norms feature centrally. It then presents empirical evidence from a well-known nationally representative survey on factors associated with tendencies to ‘buy ethically’. It is found that, ceteris paribus, people are more likely to buy ethically when others around them do too, consistent with a role of social norms in promoting ethical-consumption behaviors.