PACT Appendix D - HM Baseline Q-by-Q Justification - 2-4-13

Parents and Children Together (PACT) Evaluation

APPENDIX d

question-by-question justification,

KEY OUTCOME domains AND SUBGROUPS,

AND SURVEYS REFERENCED FOR

THE PACT HEALTHY MARRIAGE Baseline survey

Table C.1. Baseline HM Survey: Question-by-Question Justification

Question	Source	How Question Will be Used						Rationale
		Descriptor		Covariate	Subgroup	Predictor of Participation	Outcome
Introduction
Introduction (i1–i7)								Obtaining consent
Screening Questions
Date of birth (A2)	PACT- developed		X	X	X	X		The date of birth will be used to calculate the person’s age. It is asked early in the instrument so that respondents who are under 18 and not eligible for the study do not answer the rest of the instrument.
Children (A11-A11b)	PACT-developed		X	X	X	X		Questions about the existence of children are asked early in the instrument to screen out from the study respondents who have no biological or adopted children living with him or her, no biological or adopted children living with his or her partner, and is not expecting a child with his or her partner.
Demographic and Socioeconomic Characteristics
Race and ethnicity (B1–B2)	OMB	X		X	X			Program impacts may be moderated by these variables and thus they are important for use as covariates and subgroups. In addition, they will be used to describe the characteristics of the population served by PACT and to predict participation.
Country of birth (B3)	BSF	X		X	X	X
Age arrived in US (B4)	BSF	X		X
Highest level of education (B5)	CBRA tailored for PACT	X		X	X	X
Education completed in US (B5a)	PACT-developed	X		X
Primary language (B6)	BSF	X		X	X	X
Relationship Status
Marital status of HM couple (C1)	BSF	X		X	X	X	X	A central goal of HM programs is to encourage healthy relationships and marriage among participants. Measuring relationship status at baseline will increase the precision of the estimates of the impact of HM programs on relationships. Relationship status might also be a key predictor of other outcomes, such as parental engagement, making it an important covariate in estimating impacts. Finally, program impacts might differ by relationship status and relationship status might predict program participation.
Marriage start and end dates (C2-C4)	BSF	X					X
Relationship status of HM couple (C5)	BSF	X		X	X	X	X
Duration of romantic involvement with HM partner (C6)	BSF	X		X
Plans for and likelihood of marriage with HM partner (C7-C9)	BSF	X		X			X	Like relationships status, these key indicators of movement toward marriage could be used to improve the precision of estimates of impacts on other outcomes or on these same measures (at follow-up).
Whether living with HM partner (C10)	BSF	X		X	X		X	Whether the HM couple is sharing a residence is an important element of the status of their romantic relationship and is therefore an important measure for the HM impact analysis. Residential status might also be predictive of other outcomes, making it an important covariate. Finally, program impacts might differ by residential status.
Frequency of contact with HM partner (C11)	BSF	X		X		X	X	Frequency of contact with the HM partner is another important element of the couple’s relationship status (an outcome), a predictor of other outcomes, and a predictor of program participation; therefore it is an important measure for the HM impact analysis.
Prior marriages (C12-C13)	BSF	X		X	X			A complete marital history will allow us to construct baseline variables for subgroup analysis based on whether respondents were married at the time of random assignment. Marital history will also be used as a covariate in the impact analysis.
Whether expecting a baby with HM partner (C14-C14a)	PACT-developed	X		X		X		Number of children will be used to establish how many children to collect information on in the subsequent child-specific questions, to predict outcomes like parental engagement, and to predict participation. Finally, program impacts might differ by whether or not HM couples have children with other partners.
Number of children with HM partner (C15)	BSF tailored for PACT	X		X		X
Number of children with other partners (C16-C16a)	BSF tailored for PACT	X		X	X
Number of children partner has with other partners (C17-C17a)	BSF tailored for PACT	X		X	X
Number of adopted children (C18-C18a)	BSF tailored for PACT	X		X
Parenting
Child’s name (D1-D3)	BSF							This information will be used to identify the child for subsequent follow-ups and to fill in the child’s name in later survey questions.
Child’s gender (D4)	PACT-developed	X		X				Child’s gender may be an important predictor of parental engagement, economic stability, and the relationship status of HM couples. In general, fathers’ investments in children appear to be larger for sons than daughters. The birth of a son increases fathers’ labor supply and wages more than the birth of a daughter (Lundberg and Rose 2002). For never-married mothers, the birth of a son increases the speed of marriages to the child’s father more than the birth of a daughter (Lundberg and Rose 2003), and among parents married at the time of the child’s birth, fathers are more likely to live with sons than daughters at the child’s first birthday (Lundberg, McLanahan, and Rose 2007). Some studies suggest that adolescent girls receive less attention from fathers than do sons (Harris and Morgan 1991) and that nonresident fathers’ involvement with girls is more likely to decline over time (Manning and Smock 1999), although others find the opposite or no association between child gender and father involvement (Seltzer 1991).
Child’s date of birth or age (D5-D6)	PACT-developed	X		X				This demographic information can be used to confirm the child’s identity at follow-up and to determine which children are eligible for questions about behavior problems and parental engagement. There is also mixed evidence that father involvement can vary with the child’s age (Hofferth et al. 2002, Seltzer 1991, Veum 1993), suggesting that child age will be a useful covariate.
Was the birth of the child expected and wanted (C14b-c, D6a-b)	BSF	X		X	X	X		Whether the pregnancy was intended is an important baseline measure because it may affect a couple’s relationship, as well as child outcomes. There are two dimensions of whether a pregnancy is intended – whether the pregnancy was wanted at all, and whether it was wanted at that time. Using the question on the baseline, the sample can be divided into three groups: wanted pregnancies, wanted but mistimed pregnancies, and unwanted pregnancies.
Whether living with child (D7)	FFCWS tailored for PACT							Residential status will be used to determine which children are eligible to be the subject of questions about behavior problems and parental engagement.
Relationship to child (D8-D9)	RWTW tailored for PACT							Relationship to child will be used to determine which children are eligible to be the subject of questions about behavior problems and parental engagement.
Additional children (D10)	PACT-developed							This item will be used to identify children for the child roster.
Quality of co-parenting relationship (D11)	PAM, BSF	X		X		X	X	Because a goal of HM programs is to improve the quality of the HM couple’s co-parenting relationship, the impact analysis aims to measure impacts on co-parenting. Measuring the quality the co-parenting relationship at baseline will improve the statistical precision of our impact estimates. The quality of the co-parenting relationship is also predictive of subsequent father involvement (Carlson, McLanahan, and Brooks-Gunn 2008; Sobolewski and King 2005), and so may be an important covariate in models of parental engagement and child behavior. Finally, the quality of the co-parenting relationship might predict program participation.
Attitudes towards marriage and parenting (D12)	BSF, SHM, FFCWS tailored for PACT	X		X		X	X	HM programs aim to improve attitudes towards marriage and parenting, making attitudes an outcome of interest. Measuring attitudes at baseline will improve the precision of our impact estimates. Attitudes towards marriage and parenting may also be predictive other important outcomes. For example, attitudes toward marriage have been shown to be highly predictive of whether low-income, unwed parents marry (Carlson, McLanahan, and England 2004). Finally, attitudes may also influence program participation.
Relationship Quality
Happiness with relationship with HM partner (E1)	BSF	X		X	X		X	Relationship happiness and satisfaction is one of the most frequently used measures of relationship quality. It is highly correlated with the likelihood of later breakup (Karney and Bradbury 1995). In addition, interventions with married couples similar to the HM program have been shown to improve relationship happiness and satisfaction in the short run (Carroll and Doherty 2003; Markman et al. 1988; Wampler 1990). Therefore, relationship happiness will be an important outcome measure. By measuring relationship happiness at baseline, we will improve the precision of our impact estimates for this and other outcomes. Commitment is another aspect of relationship quality that is predictive of the stability of relationships (Stanley 2003). Finally, program impacts may differ by initial relationship quality.
Commitment to partner (E1a and 1b)	Suggested by Professor Scott Stanley	X		X	X		X
Whether marriage is in trouble (E2)	SHM	X		X	X		X
Trust, intimacy, and respect (E3)	BSF	X		X	X		X	HM programs may influence trust, intimacy, and respect. Positive aspects of relationships—such as intimacy and supportiveness—have been shown to counteract some of the negative effects of high conflict on romantic relationships (Huston and Chorost 1994). These positive aspects of relationships are also highly predictive of whether couples remain together (Carlson, McLanahan, and England 2004). Program impacts may differ by initial relationship quality.
Conflict and conflict management (E4)	BSF, SHM	X		X	X		X	The HM curriculum focuses largely on conflict management, making this an important outcome to examine in the impact analysis. By measuring conflict and conflict management at baseline, we will improve the precision of our impact estimates. Poorly managed conflict is highly correlated with relationship dissolution (Stanley 2003). In addition, high conflict between parents has been shown to have adverse consequences for child well-being (Stanley 2003; Cummings and Davies 1994; Cummings et al. 1991). Therefore, conflict and conflict management will also be used as a covariate. Finally, program impacts may differ by initial relationship quality.
Psychological abuse (E5)	SHM tailored for PACT	X		X	X		X	HM programs provide training on healthy relationship skills, aiming to reduce abuse. Recent research suggests that participation in similar programs decreases rates of psychological abuse between spouses (Hsueh et al. 2012). Therefore, abuse is an important outcome measure; measuring abuse at baseline will improve the precision of our impact estimates. Abuse may also be predictive of other outcomes, including relationship happiness. Finally, program impacts may differ by initial relationship quality.
Physical abuse (E6)	SHM modified for PACT	X		X	X		X
Infidelity and cheating (E7-E8)	BSF	X		X				Infidelity has been found to be a major obstacle to marriage for unwed parents (Edin and Kefalas 2005; Smock and Manning 2003), therefore, it is an important covariate in models of relationship outcomes.
Economic Stability
Paid work in last month (F1)	WFNJ tailored for PACT	X		X	X	X	X	A key goal of HM programs is to improve economic self-sufficiency. Current employment status and earnings are expected to be key predictors of similar economic outcomes at follow-up. It is also possible that the effects of PACT on economic outcomes will vary according to baseline labor market experience. For example, Parents’ Fair Share increased earnings only among men with the least labor market experience (Miller and Knox 2001). Employment and earnings might also be related to program participation.
Date of last employment (F2)	WFNJ tailored for PACT	X		X
Earnings in last month (F3–F5)	WFNJ tailored for PACT, RWTW tailored for PACT	X		X		X	X
Rent or own home (F6)	WFNJ	X		X		X		Understanding the housing circumstances of the PACT sample will help capture the extent of their disadvantage. Housing instability has also been cited as a barrier to employment (Miller and Knox 2001), and so may be an important covariate in models of PACT’s impact on couples’ economic well-being. Finally, housing instability might predict program participation.
Material hardship (F7)	BSF	X		X			X	Measures of material hardship are a useful addition to earnings because they reflect a broader concept of economic well-being that is not captured by earnings and that takes into consideration other factors that affect economic well-being, such as wealth, debt, and access to credit (Ouelette et al. 2004). If HM programs’ succeed in improving relationship and employment stability, they may reduce material hardship and participants’ reliance on public assistance. Measuring these variables at baseline will improve the statistical precision of our impact estimates.
Receipt of public assistance (F8-F9)	BSF	X		X			X
Background and Well-Being
Structure of family of origin (G1-G3)	BSF	X		X				Research suggests that whether individuals lived with both their biological parents while growing up is highly predictive of their likelihood of marriage (Carlson, McLanahan, and England 2004; Wood, Rangarajan, and Deke 2003).
Depressive symptoms (G4)	PHQ-8	X		X		X	X	Parental depression has been shown to have adverse consequences for child outcomes (Downey and Coyne 1990, Gelfand and Teti 1990). To measure depressive symptoms, we will use eight items from the Patient Health Questionnaire (PHQ-9), which was designed as a diagnostic instrument for depression but can also be used to measure subthreshold depressive disorder in the general population (Martin et al. 2006). The PHQ-9 has been shown to be reliable and valid in diverse populations and has been used in clinical settings to measure symptom improvement and monitor treatment outcomes (Kroenke, Spitzer, and Williams 2001; Löwe et al. 2004). Findings from telephone administrations of the instrument have been shown to be similar to in-person assessments (Pinto-Meza et al. 2005). The PHQ-8 includes eight of the nine items from the PHQ-9; it has been shown to be a useful measure of depression in population-based studies (Kroenke et al. 2009).
Smoking behavior (G5-G5b)	MIHOPE	X		X			X	One HM program is incorporating into their curriculum information about the dangers of smoking to unborn children and children in the household. We will collect this information to estimate the impact of the program on smoking cessation.
Ever arrested (G6)	BSF	X		X				Recent research suggests that a history of incarceration and involvement with the criminal justice system may be fairly common among fathers in the PACT target population (Pettit and Western 2004). Parental incarceration has major negative effects on child and family well-being, reducing the financial support and other types of support parents can provide to their children and families. Previously-incarcerated men also face unique challenges in securing work and housing (Geller and Curtis 2011, Pager 2003). Criminal history information can be used to improve the precision of our impact estimates. Finally, parole or probation status might predict program participation. Each respondent will also be asked to report on his or her partner’s criminal history, as partner reports may differ from self-reports (Western 2002).
Number of times arrested (G7)	SVORI, SVORI tailored for PACT	X		X
Ever convicted of a crime (G8)	SVORI	X		X
Current parole or probation (G9)	SVORI	X		X		X
Partner ever convicted of a crime (G10)	PACT-developed	X		X
Partner currently on parole or probation (G11)	SVORI tailored for PACT	X		X		X
Motivation to Participate in Program
Reasons for applying to HM program (H1)	PACT-developed	X				X		Participation is a common challenge in programs serving low-income couples (Avellar et al. 2011; Dion, Avellar, and Clary 2010). Past research has shown that factors such as motivation to change and perceived benefits of services are associated with subsequent participation (Dumas, Nissley-Tsiopinis, and Moreland 2007, Eisner and Meidert 2011, Nock and Photos 2006, Nock, Ferriter, and Holmberg 2007). We will collect this information to estimate the impact on those who receive services as well as the impact of being offered services.
Importance of making time to participate (H2a-H2b)	PACT-developed	X				X
Contact Information
A1–A10 I1–I8					X			Contact information is necessary to locate the respondent for the follow-up data collection 12 months later. Date of birth will also be used to calculate age for the subgroup analysis.

Sources: Building Strong Families Study (BSF), American Recovery and Reinvestment Act COBRA Subsidy Study (CBRA), Fragile Families and Child Well-Being Study (FFCWS), Work First New Jersey (WFNJ), Parenting Alliance Measure (PAM), Rural Welfare-to-Work Demonstration Evaluation (RWTW), Patient Health Questionnaire (PHQ-9), Serious Violent Offender Reentry Initiative Evaluation (SVORI), Supporting Healthy Marriage (SHM), Mother and Infant Home Visiting Program Evaluation (MIHOPE).

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KEY OUTCOME DOMAINS

Relationship status (marriage, romantic involvement)

Relationship quality

Attitudes towards marriage and parenting

Parental employment

Co-parenting

Father involvement (father presence, father engagement, financial support)

Parental well-being (includes mental health)

Child well-being (includes family and economic stability, socio-emotional well-being)

Service receipt

KEY SUBGROUPS

Initial relationship status

Initial relationship quality

Father’s employment status at baseline

Race/ethnicity

Parents’ educational attainment

Parents’ ages

Whether any children with other partners

SURVEYS REFERENCED

The list below contains brief descriptions of the eight surveys referenced in the PACT HM baseline survey, as well as locations of the surveys referenced. Descriptions were compiled from websites about the surveys and descriptions of Mathematica studies were gathered from project summaries. When necessary, we modified questions drawn from these surveys to make them easier to understand or to have the questions align more closely with the baseline survey’s goals.

1. Building Strong Families Study (BSF)

The United States Department of Health and Human Services/Administration for Children and Families (ACF) initiated the Building Strong Families (BSF) project to help interested and romantically involved low-income, unwed parents build stronger relationships and thus enhance their child’s well being and their own future. The BSF evaluation being conducted by Mathematica is designed to test the effectiveness of these programs for couples and children. BSF data collection included a baseline information form to collect demographic and socioeconomic data along with two follow-up surveys. The follow-up surveys included questions related to mother-father relationships, family structure, fathers’ involvement in child rearing, parent-child relationships and the home environment, family functioning, child well-being and development, and parental well-being.

Surveys are available from Mathematica upon request.

2. American Recovery and Reinvestment Act COBRA Subsidy Study (CBRA)

Sponsored by the U.S. Department of Labor, Mathematica’s American Recovery and Reinvestment Act (ARRA) COBRA Subsidy study examines the effect of the availability of an ARRA COBRA premium subsidy on the take-up of COBRA coverage and other health and employment outcomes. As part of the study, Mathematica will conduct a survey of COBRA-eligible individuals drawn from state Unemployment Insurance recipients. The CBRA survey asks questions related to respondents’ demographic characteristics, employment history, receipt of social services, and health insurance.

Surveys are available from Mathematica upon request.

3. Fragile Families and Child Well-Being Study (FFCWS)

The Fragile Families and Child Well-Being Study is a longitudinal study of a cohort of nearly 5,000 children born between 1998 and 2000 from birth through age five. Approximately one-third of the children were born to unmarried parents. Interviews were conducted with both mothers and fathers covering a range of topics including attitudes, relationships, and parenting behavior.

Study protocols and codebooks can be found here: http://www.fragilefamilies.princeton.edu/documentation.asp

4. Work First New Jersey (WFNJ)

Mathematica evaluated the effects of New Jersey’s initiative to help welfare recipients transition from welfare to work. WFNJ interviewed sample members annually for five years documenting changes in household composition, income, employment, and other indicators of well-being.

Surveys are available from Mathematica upon request.

5. Rural Welfare-to-Work Demonstration Evaluation (RWTW)

Mathematica’s Rural Welfare-to-Work Strategies Demonstration Evaluation used random assignment to assess innovative approaches to helping welfare-dependent and other low-income families in rural areas to enter, maintain, and advance in employment and to secure family well-being. Data collection included a baseline information form to collect demographic and socioeconomic data on sample members and two follow-up surveys to collect detailed employment history data as well as information on various outcomes related to individual and family well-being.

Surveys are available from Mathematica upon request.

6. Evaluation of the Serious Violent Offender Reentry Initiative (SVORI)

The Evaluation of the Serious Violent Offender Reentry Initiative (SVORI) was a multi-year, multi-site evaluation funded by National Institute of Justice. The impact evaluation was designed to measure the impact of enhanced reentry programming on post-release outcomes. As part of the evaluation, interviews were conducted at four points in time.

Surveys are available from the National Archive of Criminal Justice Data.

7. Supporting Healthy Marriage (SHM)

ACF sponsors the Supporting Healthy Marriage project (SHM). SHM is a multi-year, multi-site evaluation of marriage education programs for low-income married couples. Data collection includes baseline information forms to determine eligibility and collect demographic information, a 12-month follow-up survey to measure short-term impacts of the marriage education program, and a 30-month follow-up survey to measure longer-term impacts.

Surveys are available from MDRC.

8. The Mother and Infant Home Visiting Program Evaluation (MIHOPE)

ACF and the Health Resources and Services Administration jointly administer the Maternal, Infant, and Early Childhood Home Visiting Evaluation. MIHOPE is a multi-year, multi-site evaluation of the Home Visiting program designed to prevent child maltreatment, improve maternal and child health outcomes, and increase school readiness. Data collection includes a baseline survey and a 15-month follow up survey.

Surveys are available from MDRC.

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Hsueh, J., D.P. Alderson, E. Lundquist, C. Michalopoulos, D. Gubits, D. Fein, and V. Knox. “The Supporting Healthy Marriage Evaluation: Early Impacts on Low-Income Families.” Washington DC: OPRE Report 2012-11, 2012.

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