effects of home visitation on maternal competencies, family environment, and child development: a...

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Prevention Science ISSN 1389-4986 Prev SciDOI 10.1007/s11121-015-0573-8

Effects of Home Visitation on MaternalCompetencies, Family Environment,and Child Development: a RandomizedControlled Trial

Susan Sierau, Verena Dähne, TilmanBrand, Vivien Kurtz, Kai von Klitzing &Tanja Jungmann

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Effects of Home Visitation on Maternal Competencies, FamilyEnvironment, and Child Development: a RandomizedControlled Trial

Susan Sierau1& Verena Dähne1 & Tilman Brand2

& Vivien Kurtz3 & Kai von Klitzing1 &

Tanja Jungmann4

# Society for Prevention Research 2015

Abstract Based on the US Nurse-Family Partnership(NFP) program, the German home visiting program BProKind^ offered support for socially and financially disad-vantaged first-time mothers from pregnancy until the chil-dren’s second birthday. A multi-centered, longitudinal ran-domized controlled trial (RCT) was conducted to assess itseffectiveness on mothers and children. A total of 755women with multiple risk factors were recruited, 394 re-ceived regular home visits (treatment group), while 361only had access to standard community services (controlgroup). Program influences on family environment (e.g.,quality of home, social support), maternal competencies(e.g., maternal self-efficacy, empathy, parenting style),and child development (e.g., cognitive and motor develop-ment) were assessed from mothers’ program intake inpregnancy to children’s second birthday based on self-reports in regular interviews and developmental tests. Gen-eralized estimating equations (GEE) models showed small,

but significant positive treatment effects on parental self-efficacy, and marginally significant effects on social sup-port, and knowledge on child rearing. Maternal stress, self-efficacy, and feelings of attachment in the TG tend toshow a more positive development over time. Subgroupeffects were found for high-risk mothers in the TG, whoreported more social support over time and, generally, hadchildren with higher developmental scores compared totheir CG counterparts. Post hoc analyses of implementa-tion variables revealed the quality of the helping relation-ship as a significant indicator of treatment effects. Resultsare discussed in terms of implementation and public policydifferences between NFP and Pro Kind.

Keywords Socially disadvantaged families . Earlyintervention . Program implementation . Nurse-familypartnership

Home visiting is a prominent approach to support psycho-socially and financially disadvantaged families. Meta-analyses and systematic reviews have revealed significant,but small positive program effects on parenting competen-cies and children’s development (e.g., Peacock et al.2013). According to criteria established by the Health Re-sources and Services Administration of the United States(US) government (2010), few early childhood home visit-ing programs meet their standards for high-quality imple-mentation and effectiveness. One of the most importantprojects is the Nurse-Family Partnership (NFP) program(Olds 2006), whose positive effects were shown in threeexperimental trials with different samples (Elmira trial:Eckenrode et al. 2010; Memphis trial: Kitzman et al.1997; Denver trial: Olds et al. 2002). Most frequent andpersistent effects on family environment were found for

* Susan [email protected]

1 Department of Child and Adolescent Psychiatry, Psychotherapy, andPsychosomatics, University of Leipzig, Liebigstrasse 20a,04103 Leipzig, Germany

2 Department Prevention and Evaluation, Leibniz-Institute forPrevention Research and Epidemiology – BIPS, Achterstrasse 30,28359 Bremen, Germany

3 Department Youth and Family, Capital City of Hannover,Sutelstrasse 18, 30659 Hannover, Germany

4 Faculty of Humanities, Institute for Special Educational Interventionand Rehabilitation, University of Rostock, August-Bebel-Strasse 28,18051 Rostock, Germany

Prev SciDOI 10.1007/s11121-015-0573-8

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maternal life course, e.g., a more thoughtful family plan-ning with a longer interval between pregnancies, as wellas small effects on maternal mental health (Kitzman et al.1997; Olds et al. 2002, 2010). Research on the NFP pro-gram in the USA has also shown consistent positive ef-fects on parenting attitudes and behavior to prevent childabuse and neglect with regard to maternal competencies(Kitzman et al. 1997; Olds et al. 2002). Program effectson parenting characteristics and family environment can beidentified more easily, because they are in direct focus ofthe intervention. Indirect program impact on child devel-opment is harder to detect and effect sizes are expected tobe smaller (Howard and Brooks-Gunn 2009). However,short- and long-term effects of the NFP program on chil-dren’s mental and socio-emotional development (Oldset al. 2002), as well as on school achievement were found(Kitzman et al. 2010; Olds et al. 2007).

The current study aimed at analyzing effects of an adaptedversion of the NFP program in Germany. The BPro Kind^program was run from 2006 to 2012 in three federal states,two in Western and one in Eastern Germany. It focused onimproving maternal prenatal health, family functioning, par-enting competencies, and economic self-sufficiency to en-hance children’s development and to reduce child abuse andneglect (Jungmann et al. 2009; Olds 2006). Because of differ-ences between the US and German welfare systems (e.g.,more liberal and high-quality public health care services inGermany), we assumed program effects to be smaller but inthe same domains as indicated by the NFP results. Thus, wehypothesized positive influences on variables of family envi-ronment, particularly family planning and maternal stress, inwomen who receive BPro Kind^ home visitation. We alsoexpected program effects on maternal competencies and childdevelopment, i.e., improved mental, psychomotor, language,and behavioral development. As stronger NFP program ef-fects were evident in the subgroup of mothers with low psy-chological resources, we tested for subgroup effects in low-and high-risk mothers.

In a comprehensive study on intervention effects, pro-cess variables of the intervention program as well as par-ticipants’ environmental and personal variables should beconsidered (Korfmacher et al. 1998). An analysis of im-plementation variables helps to identify active programcomponents and to provide information how to refine theprogram model further. Quantity and quality of parentalinvolvement have been proposed as important contributorsto program success (Korfmacher et al. 2008). Quantitativeindicators typically include the number of home visits re-ceived. The relationship between home visitor and client isa sign for quality of parental involvement (helping rela-tionship; Korfmacher et al. 2007). In additional analyses,we investigated influences of these implementation vari-ables on program effects.

Methods

Randomization

From November 2006 until December 2009, BPro Kind^ reg-istered N=755 volunteering low-income first-time mothersbetween their 12th and 28th week of pregnancy. Inclusioncriteria were economic risk factors (e.g., unemployment,over-indebtedness >5.000 €) and at least one social risk factor(e.g., poor education, experiences of violence, or neglect).Project partners such as gynecologists, job centers, and youthwelfare offices referred 85% of the participants, 15%were self-referrals. Women were randomly assigned either to the treat-ment or to the control group (Efron’s biased coin design;Efron 1971). Strata were implementation site, being underage (<18 years) and maternal nationality. Members of bothgroups were provided with information about existing healthor social services, repayment for travel expenses to preven-tive medical check-ups, reimbursement for regular researchattendance, and feedback about the children’s developmentalstatus. However, only women in the treatment group re-ceived home visits. All participants gave written informedconsent. The ethical board of the Germany Society for Psy-chology approved the study design and procedures.

Participants

Table 1 presents demographic characteristics, risk factorsfor child abuse and neglect, and referral sources of partic-ipants at baseline assessment (on average at the 20th weekof pregnancy) in the treatment and control group. All par-ticipating women had at least one socio-economic risk fac-tor and an additional psychosocial risk factor, with no sig-nificant differences between the two groups. Participants inthe treatment and control group were comparable, exceptfor the higher likelihood of a psychiatric disorder in thecontrol group (χ2

1;755=9.430; p=.003). The influence ofthis variable was statistically controlled in further analyses.

Procedure

The NFP core components including target group criteria,prescribed average visit frequency and duration, structuredapproach, intensity of background support for home visitors,and program duration were not changed. NFP guidelines andparts of the PIPE curriculum (Perkins et al. 2002), an integrat-ed program module to enhance the quality of parent-child-interaction, were translated into German. Work sheets andinformation material available in Germany were added if theyfitted the NFP model. Major replacements of the original ma-terial (e.g., using a German developmental screening instru-ment instead of a US instrument) were done after consultationwith NFP program planners. Minor additions, such as

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information material on well-child check-ups, were donewithout consultation. The six German supervisors held a uni-versity degree in social work or psychology and had addition-al qualifications in coaching techniques. They received 5 daysof training on the basic program principles at the NFP Nation-al Office in the USA. In addition, they attended Btrain thetrainer^ lessons of the PIPE program. They judged model fitof additional German material. One major change concernsthe profession of home visitors. Whereas home visitors inthe NFP program were registered nurses, in the German ad-aptation they either held a university or college degree insocial work or were state-certified midwives (requirements:3-year school- and clinic-based apprenticeship). Generally,midwives and social workers are already engaged in home

visiting services in the German health and social service sys-tems (pre- and antenatal care; social support services), where-as nurses are primarily employed in hospitals. A pediatricnurse was employed only in one implementation site (seeBrand and Jungmann 2014 for further details).

A total of 62 home visitors (37 midwives, 24 social educa-tion workers, one pediatric nurse) who were on average40 years old (range 22–53), were employed in the program.They commonly had substantial work experience (M [mean]=15 years, range 0–31), especially in dealing with socially dis-advantaged families (M=11 years, range 0–30). Thirteenhome visitors left the program. Reasons were moving to an-other city, own pregnancies, health problems, and team con-flicts. Each home visitor received approximately 16 days of

Table 1 Demographiccharacteristics, risk factors, andreferral sources of participants atbaseline assessment

Demographic characteristics Treatment group Control group

Age 21.27 (4.2; 14–40) 21.53 (4.4; 14–40)

Not married 85.5 % 89.2 %

Born in Germany 89.1 % 84.2 %

Less than high school diploma 54.5 % 49.5 %

Over-indebtedness 47.8 % 53.5 %

Risk factors for child abuse and neglect

Being under age 21.1 % 17.7 %

Low educational status 78.2 % 74.8 %

Low income 82.0 % 80.9 %

Low occupational status 82.0 % 85.6 %

Unwanted pregnancy 18.0 % 16.6 %

Alcohol misuse 0 % 0.6 %

Drug misuse 1.8 % 2.5 %

Being a single mother 29.2 % 28.3 %

Social isolation 6.1 % 8.0 %

Experienced custodial care 23.4 % 19.7 %

Neglect or maltreatment during childhood 37.6 % 38.8 %

Lost attachment figure during childhood 50.8 % 54.6 %

Violence during pregnancy 7.9 % 9.1 %

Life-time violence 55.3 % 55.1 %

Psychiatric disordera 10.9 % 18.8 %

Depression DASS 10.2 % 13.3 %

Anxiety DASS 17.0 % 17.7 %

Stress DASS 31.5 % 28.8 %

Potential for aggression 14.5 % 18.6 %

Referral sources

Self-referral 14.4 % 15.3 %

Gynecologists 22.6 % 22.2 %

Child and youth welfare office 13.8 % 15.3 %

Job centers 15.9 % 13.6 %

Psychosocial counselling service 16.7 % 18.9 %

Others 16.7 % 14.7 %

Age is reported in average years (SD; range)a Significant

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in-service training during the research period. The training wasadapted from the NFP curriculum and comprised eight work-shops. The home visitors started their work at different timesduring the recruitment period but all of them attended the work-shops in the first 2 to 3 years of their Pro Kind employment.The curriculum included an introduction to the underlying pro-gram theories and their implications for the practical work withthe guidelines, as well as specific program modules. Further-more, all home visitors received an hour of clinical supervisionper week and had regular team meetings. The frequency ofhome visits as recommended by the NFP program varied be-tween weekly (first 4 weeks after program intake and 4 weeksafter birth), bi-weekly, andmonthly (last half year of treatment).Visit-to-visit guidelines structure the work of home visitorsgrounded in human ecology theory (Bronfenbrenner 1979),attachment theory (Bowlby 1969/1982), and the concept ofself-efficacy (Bandura 1977). They reflect challenges par-ents are likely to be confronted with during specific stagesof pregnancy and the first 2 years of children’s life. Inaccordance with the NFP model, practitioners were allowedto react flexibly to familial demands (e.g., by favoring cur-rent individual topics of the family).

Data Collection

Researchers who were blind to the treatment condition col-lected data via face-to-face interviews and developmental testsin families’ homes. In addition, participants of the treatmentgroup received telephone interviews. Figure 1 gives an over-view of participants’ numbers in both groups at the differentphases of the randomized trial, amount of completed inter-views, and dropout rates. From 755 participants recruited,346 (178 in the treatment and 168 in the control group)remained in the study. Attrition rate rose constantly up to50 %, which is similar to other studies dealing with high-risk families (O’Brien et al. 2012). The most important rea-sons were refusal of program service, loss of contact with thefamily, or relocation. Logistic regressions of participation sta-tus on baseline mother and family characteristics revealed ayounger age (OR=.897; p=.000), a lower income (OR=1.734; p=.007), and experienced foster care placement(OR=1.651; p=.012) as significant predictors for droppingout, χ2

8;755=88.564; p=.000; R2=.15. Further analyses of at-

trition reported elsewhere (Sandner 2012) found similar ratesfor treatment and control group as well as no significant dif-ferences in maternal and familial characteristics between treat-ment and control group for the baseline and follow-upsurveys.

Measures

Outcome Measures Table 2 gives an overview of outcomemeasures in the three main domains of interest Bfamily

environment^, Bmaternal competencies^, and Bchilddevelopment^, as well as the time of their first and last assess-ments. Nearly all measures were self-report scales frommothers. Mother-child affectivity and responsiveness aswell as child behavior was coded via video ratings.Raters were blind to any details of the rated families.Reliability was maintained through weekly checks, withone fifth of the video observations being double coded.Child’s mental, psychomotor, and language developmentwere assessed via standardized developmental tests. Allmeasures showed satisfactory to good reliabilities. Nodifferences between treatment and control group werefound in any of the outcome variables at baselineassessment.

Implementation Measures The quantity of parental in-volvement was operationalized as number of homevisits from baseline (t0) to 24 months after birth (t4)(M=32.7, SD=18.6, Min=0, Max=94, N=394). Homevisitors documented their work using encounter forms.The extreme range in the number of home visits re-ceived is partly due to the fact that descriptive statisticsinclude all cases randomized to the treatment group att0. There were participants in our study who dropped

Referrals: n=1157

Excluded: n=402

(263 not meeting inclusion criteria,

139 declined to participate)

Randomized: n=755

Allocated to Treatment Group (TG)

t0 (Baseline Interview): n=394

Allocated to Control Group (CG)

t0 (Baseline Interview): n=361

t1 (36th weeks of gestation)

Interviews completed: n=276 (70.0%)

Drop outs: 30.0%

t1 (36th weeks of gestation)


Drop outs: 31.6%

t2 (6 months after birth)


Drop outs: 32.8%



Drop outs: 33.5%



Drop outs: 43.2%



Drop outs: 42.4%



Final drop outs: 54.8%



Final drop outs: 53.5%

Fig. 1 CONSORT flowchart of the participants’ progress through thephases of the randomized trial

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out after completing the baseline interview—the caseswith zero home visits. At the other end of the range,there was one outlier who received 94 instead of 59expected visits because of severe problems includingdrug abuse, domestic violence, and a low prenatal at-tachment to the child.

The quality of parental involvement was assessed duringtelephone interviews with participants using an adapted ver-sion of the bonds-subscale from the Working Alliance Inven-tory (Horvath and Greenberg 1989) at children’s first birthday.This scale comprises seven items with a four-point scale. In-ternal consistency was α=.85.

Table 2 Outcome variables of the different domains

Domain First-lasttime ofassessment

Instrument Scale Authors Items Reliability first-lastassessment(Cronbach’s alpha)

Family environment

Maternal stress t1–t4 General level of stress scale 4-point Likert (1=neverstressed, 4=very strongstressed)

Bodenmann(2000)

10 .70–.71

Partnership satisfaction t1–t4 Life satisfaction questionnaire,subscale

4-point Likert: 1=veryunsatisfied, 4=verysatisfied

Fahrenberg et al.(2000)

7 .88–.89

Social support t0–t4 Perceived social support 4-point Likert: 1=not at alltrue, 4=absolutely true

Hosser (2000) 15 .91–.93

Further children t3–t4 Birth of another child Dichotomous: yes, no Self-constructed 1 –

Educationalachievement

t1–t4 Completed school orapprenticeship

Dichotomous: yes, no Self-constructed 1 –

Maternal competencies

Parental self-efficacy t0–t3 Parental expectations survey 4-point Likert: 1=veryunsure, 4=absolutelysure

Reece andHarkless(1998)

25 .90–.84

Knowledge on childrearing

t0–t2 Experiences and knowledgeabout children

4-point Likert: 1=very bad,4=very good

Porter and Hsu(2003)

6 .77–.74

Feelings of attachment t0–t3 Maternal antenatal/postnatalattachment questionnaire

4-point Likert: 1=not at alltrue, 4=absolutely true

Condon andCorkindale(1998)

19 .73–.79

Parenting style t3–t4 Parenting scale, short version 4-point Likert: 1=not at alltrue, 4=absolutely true

Arnold et al.(1993)

13 .69–.71

Mother-child affectivity t2–t4 Maternal behavior rating scale-revised, subscale

5-point Likert: 1=very low,5=very high

Mahoney (1999) 4 ICC: .62–.67

Mother-childresponsiveness

t2–t4 Maternal behavior rating scale-revised, subscale

5-point Likert: 1=very low,5=very high

Mahoney (1999) 3 ICC: .62–.67

Maternal empathy t1–t4 Interpersonal reactivity index,subscale

4-point Likert: 1=not at alltrue, 4=absolutely true

Davis (1980) 4 .69–.71

Belief of control t1–t4 Perceived stress scale, shortversion

4-point Likert: 1=never,4=very often

Cohen andWilliamson(1988)

4 .66–.72

Child development

Mental development t2–t4 Bayley Scales of InfantDevelopment (BSID-II), MDI

IQ scores Reuner et al.(2007)

* ICC: .83–.88

Psychomotor development t2–t4 Bayley Scales of InfantDevelopment (BSID-II), PDI

IQ scores Reuner et al.(2007)

* ICC: .83–.88

Rating of children’sbehavior

t2–t4 Behavior rating scale, BSID-II Percentiles Reuner et al.(2007)

30 ICC: .62–.67

Language development,mothers’ rating

t3–t4 Parent questionnaire ELFRA 1and 2, word production

Raw scores Grimm andDoil (2006)

260 .91–.99

Language development,children’s test

Language development test for2-year-old children, SETK-2

Mean length of utterances Grimm et al.(2000)

63 .95

Socio-emotionaldevelopment

t4 Child behavior checklist, CBCL1½–5 years, subscales internaland external symptoms

T scores Achenbach &Rescorla(2000)

99 >.86

*Adaptive tests with different item numbers

ICC intraclass correlation coefficient, inter-rater consistency

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Statistical Analyses

Generalized estimating equations (GEE) models wereused to assess program impact on the three main out-come areas (family environment, maternal competencies,and child development). GEE is an iterative procedurefor the analysis of longitudinal outcome data using aquasi-likelihood approach (Twisk 2003). In GEE, aworking correlation structure is chosen to correct fordependency of observation, i.e., within-subject correla-tions. A further advantage of GEE is that all availabledata are included in the analysis (no listwise deletion ofcases). In the main outcome analysis, time specific com-parisons, group effects (treatment group (TG) versuscontrol group (CG)) and time by group interactionswere estimated, controlling for baseline values of theoutcome variable (t0, if available), time, and presenceof psychiatric disorder, as TG and CG differed at base-line regarding the presence of a psychiatric disorder.Time was modeled as categorical variable as we didnot assume a linear relationship with time. The follow-ing equation summarizes the model for the main out-come analysis:

Y it ¼ β0 þ β1GROUPþ β2…4TIME� GROUPþ β5Y t0 þ β6…8TIMEþ β9PSYCH þ εit

Where Yit are observations for subject i at time t, β0 isthe intercept, β1 is the regression coefficient for TG versusCG, β2…4 are the regression coefficients for time bygroup interaction, β5 is the regression coefficient for thebaseline value of Y, β6…8 are the regression coefficientsfor time as a categorical variable, β9 is the regressioncoefficient for presence of a psychiatric disorder, and εitis the error term for subject i at time t. For the analysis ofchild development, children’s gender was entered into themodel as another controlling factor.

An exchangeable working correlation structure was chosenfor the GEE modeling, i.e., correlations of subsequent mea-surements were assumed to be the same. This did not perfectlyreflect the observed correlation structures, but was the work-ing correlation structure closest to the data. Anyway, it isgenerally assumed that GEE analysis is quite robustagainst wrong choice of correlation structures (Twisk2003). For continuous outcome variables, a linear GEEmodel was applied reporting unstandardized regression co-efficients. For the two count data outcome variables (edu-cational achievement and further children), a Poisson GEEmodel was chosen reporting rate ratios. In a second run,subgroup effects in low- and high-risk mothers wereassessed by adding risk status (<6 risk factors = low, ≥6risk factors = high) as factor to the main model as well asinteraction terms for risk status by group interaction andrisk status by time by group interaction.

Furthermore, we conducted a post hoc analysis of im-plementation factors contributing to program effects foroutcome variables with positive treatment effects overtime. For this purpose, we considered the influence ofimplementation factors in linear GEE models adjustingfor baseline values in the outcome variable, time as acategorical variable, maternal age, and number of risk fac-tors. For inspection of cluster effects on the home visitorand implementation site level, variance component modelswere used. As we did not find significant intra-class cor-relation on these levels, clustering effects were notdisplayed. For all analyses, p values for two-tailed testsare reported. Significance level was set to .05. All p valuesclose to significance were also addressed in the BResults^section.

Results

First, results of GEEmodels are reported for all three outcomedomains. Group effects and time by group interactions wereprimarily conducted, taking into account possible group dif-ferences at specific assessment times. Additionally, the influ-ence of risk status on group effects and on time by groupinteractions was calculated.

Treatment Effects on Family Environment

Table 3 shows the results for family environment. Onlyone marginally significant group effect for social sup-port was observed (p=.050), with women in the TGgenerally reporting more social support compared towomen in the CG. This effect is turning significantwhen adding risk status in the model (see Fig. 2). Whilesocial support developed in a similar way in low-riskwomen from both groups, a significant group differenceappeared over time for high-risk women (p=.006). Atboth groups, high-risk women started at a lower base-line level than low-risk women, but increased to thelevel of low-risk women at 36 weeks of gestation. How-ever, 24 months after birth, the level of perceived socialsupport of high-risk CG women declined under thebaseline level, while high-risk TG women could nearlymaintain their high level of perceived social support.Moreover, one marginally significant time by group in-teraction effect was detected for maternal stress(p=.074). Over time, women in the TG tend to reporta constant level of stress compared to women in the CGwhere the level of perceived stress increased at 12 and24 months after birth. Time-specific comparisons alsoshowed a significant group difference for partnershipsatisfaction at 6 months after birth, with women in theTG reporting higher scores on partnership satisfaction

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than the CG women. However, this difference did notpersist over time. No significant effects were found foreducational achievement and birth of further children.Between baseline assessment and children’s secondbirthday, 20 % of mothers in the TG completed schoolor an apprenticeship compared to 26 % in the CG.Twenty-four months after birth of the first child, 17women in the TG gave birth to a further child com-pared to 7 women in the CG.

Treatment Effects on Maternal Competencies

Results for effects on maternal competencies are report-ed in Table 4. One significant group difference for pa-rental self-efficacy (p=.044) and one marginally signifi-cant group difference for knowledge on child rearing(p=.064) were found. Women in the TG generally ratedthemselves as more self-efficient in parenting, and re-ported a slightly higher knowledge on child rearingcompared to CG women. Concerning parental self-effi-cacy, this group difference tends to increase over time(time by group interaction: p=.063), with a significanttime specific difference at 12 months after birth. In ad-dition, a marginally significant time by group interactionwas found for maternal feelings of attachment (p=.062),with a significant decline in the CG over time and aquite constant level in the TG. At 6 months after birth,self-reported maternal feelings of attachment were sig-nificantly higher in the TG compared to the CG. Nei-ther significant group differences nor a significantchange over time occurred for parenting style, observedmother-child affectivity and responsiveness, maternalempathy, and belief of control.

Treatment Effects on Child Development

We primarily did not find any significant treatment effectson child development in the analyses (see Table 5). Yet,when adding risk status to the model, a significant groupby risk interaction could be detected (see Fig. 3). Childrenfrom low-risk families showed similar levels of cognitivedevelopment on average. In high-risk families, childrenfrom the CG had a lower mental developmental score,whereas children from the TG revealed higher levels ofmental development which even slightly exceed those ofthe low-risk children.

Influences of Implementation VariablesWithin the Treatment Group

Furthermore, we conducted post hoc analyses of quantity(number of home visits) and quality of home visiting (qualityof helping relationship) contributing to program effects forT

able3

Treatmenteffectson

family

environm

ent(generalized

estim

atingequatio

nsmodel)

Outcome

Group

Estim

ated

marginalm

eans

(SE)

Group

effect

Tim

e×groupinteraction

t 0t 1

t 2t 3

t 4β(95%

CI)

Maternalstress

TG

–1.76

(.03)

1.73

(.03)

1.72

(.02)*

1.76

(.03)*

−.05

(−.10–.01)

Wald=2.564,df=1,p=.110

Wald=6.926,df=3,p=.074

CG

–1.75

(.03)

1.76

(.03)

1.80

(.03)

1.86

(.03)

Partnership

satisfaction

TG

–3.34

(.04)

3.24

(.04)*

3.21

(.05)

3.14

(.06)

.02(−.07–.12)

Wald=.262,df=1,p=.609

Wald=6.153,df=3,p=.101

CG

–3.39

(.04)

3.15

(.04)

3.12

(.05)

3.18

(.06)

Socialsupport

TG

3.39

(.04)

3.49

(.04)

––

3.45

(.05)

.04(.00–.09)

Wald=3.849,df=1,p=.050

Wald=3.251,df=2,p=.197

CG

3.38

(.04)

3.47

(.04)

––

3.34

(.05)

Educatio

nalachievementa

TG

–.08(.02)

.05(.01)

.03(.01)

.06(.02)

.80(.55–1.15)

Wald=1.458,df=1,p=.227

Wald=2.418,df=3,p=.490

CG

–.11(.02)

.06(.01)

.04(.01)

.08(.02)

Furtherchild

rena

TG

––

–.03(.01)

.12(.03)

1.67

(.83–3.36)

Wald=1.906,df=1,p=.167

Wald=.036,df=1,p=.850

CG

––

–.02(.01)

.07(.02)

Adjustedfortim

e,presence

ofapsychiatricdisorder,and

t 0measurement(ifavailable)

*p<.05fortim

especificcomparisons

aPo

issondistributio

nselected

fortheresponse

variable;p

aram

eter

estim

ateforthegroupeffectisarateratio

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outcome variables with significant time by treatment interac-tions. Linear GEE models adjusting for time, baseline valuesin the outcome variable, maternal age, and number of riskfactors were estimated (see Table 6). Quality of the helpingrelationship was a positive predictor for parental self-efficacyby trend (p=.093), with no influence of other variables in themodel. Moreover, a higher quality of the helping relationship(p=.002), a younger age (p=.049), and a lower number of riskfactors (p=.022) significantly contributed to maternal feelingsof attachment. Numbers of home visits showed a negativeeffect by trend (p=.095). For maternal stress, only maternalage (p=.001) and number of risk factors (p=.007) were sig-nificant positive predictors in the tested model.

Discussion

The present investigation is one of the few studies thatoffer comprehensive insights in the effectiveness of homevisiting programs in Northern Europe. We assessed mul-tiple longitudinal program effects of the BPro Kind^ pro-gram on family environment, maternal competencies, andchild development, as well as influences of risk status andimplementation variables on treatment effects in a RCT.In comparison to other rigorously evaluated programswith a home visiting component (Kahn and Moore2010), BPro Kind^ is among those 50 % with an impacton at least one outcome domain. In line with previous

Table 4 Treatment effects on maternal competencies (generalized estimating equations model)

Outcome Group Estimated marginal means (SE) Group effect Time × group interaction

t0 t1 t2 t3 t4 β (95 % CI)

Parentalself-efficacy

TG 3.41 (.03) 3.42 (.03) 3.65 (.03) 3.71 (.03) * – .03 (.00–.05)Wald=4.047, df=1, p=.044

Wald=7.311, df=3, p=.063CG 3.40 (.03) 3.43 (.03) 3.62 (.03) 3.63 (.03) –

Knowledge onchild rearing

TG 2.94 (.03) 3.15 (.03) 3.41 (.03) – – .03 (.00–.06)Wald=3.426, df=1, p=.064

Wald=3.751, df=2, p=.153CG 2.95 (.03) 3.12 (.03) 3.34 (.03) – –

Feelings ofattachment

TG 3.45 (.03) 3.60 (.03) 3.49 (.03) 3.45 (.03)* – .02 (−.01–.05)Wald=1.852, df=1, p=.174

Wald=7.331, df=3, p=.062CG 3.46 (.03) 3.59 (.03) 3.48 (.03) 3.38 (.03) –

Parenting style TG – – – 1.65 (.03) 1.71 (.03) −.04 (−.11–.02)Wald=1.552, df=1, p=.213

Wald=1.812, df=1, p=.178CG – – – 1.72 (.03) 1.73 (.03)

Mother-childaffectivity

TG – – 3.11 (.05) 3.17 (.05) 3.15 (.05) −.06 (−.16–.05)Wald=1.147, df=1, p=.284

Wald=3.913, df=2, p=.141CG – – 3.15 (.05) 3.16 (.05) 3.30 (.05)

Mother-childresponsiveness

TG – – 3.11 (.05) 3.37 (.05) 3.38 (.06) −.05 (−.15–.06)Wald=.853, df=1, p=.356

Wald=2.495, df=2, p=.287CG – – 3.15 (.05) 3.35 (.05) 3.51 (.06)

Maternal empathy TG – 3.22 (.03) – – 3.25 (.03) .01 (−.07–.09)Wald=.076, df=1, p=.782

Wald=.002, df=1, p=.967CG – 3.21 (.03) – – 3.24 (.03)

Belief of control TG – 2.91 (.03) 3.01 (.03) 2.98 (.04) 3.00 (.04) .04 (−.03–.11)Wald=1.359, df=1, p=.244

Wald=.578, df=3, p=.967CG – 2.88 (.03) 2.98 (.03) 2.94 (.04) 2.92 (.04)

Adjusted for time, presence of a psychiatric disorder, and t0 measurement (if available)

*p<.05 for time specific comparisons

3.00

3.10

3.20

3.30

3.40

3.50

3.60

t0 t1 t4)s

nae

ml

ani

gr

am

det

am it s

e (tr

op

pus

la i

cos

devi

ecre

P

TG high risk

CG high risk

TG low risk

CG low risk

Fig. 2 Development of perceivedsocial support by treatmentgroups and risk status (time ×group × risk status interaction:Wald=14.277, df=4, p=.006)

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studies (e.g., Peacock et al. 2013), our program effectswere few and small in magnitude.

Concerning family environment, women who received thehome visiting program reported lower stress levels at 12 and24 months after birth, whereas women without a treatmentperceived an increased level of postpartum stress. Taking intoaccount intervention effects over time, the time by group in-teraction for perceived stress was marginally significant. Thus,results may point to a protecting effect of the intervention onthe maternal perception of stress between the first and thesecond year after child’s birth. As this period of time has beenshown to be particularly demanding for young mothers withmultiple risks (O’hara and Swain 1996), support by a homevisiting intervention seems to be a resource to cope better withthese stressful conditions. Regarding social support, women in

the TG, particularly in the high-risk group, rated themselves toget more support compared to their CG counterparts who re-ported a decline of support after birth. Again, the home visit-ing intervention seems to have some kind of buffering effectunder stressful conditions. Results indicate improvements inperceived family functioning by the home visiting program,especially in terms of maintaining a social network after birth.Yet, these positive intervention effects were not found forpartnership satisfaction, number of further children or educa-tional achievement, although maternal life-course planning isone of the domains in which NFP has reported consistentprogram effects. With regard to subsequent births, generaldifferences in the fertility behavior between Germany andthe USA could be a reason why program effects were notachieved. For example, in the Denver trial 12 % of women

Table 5 Treatment effects on child development treatment (generalized estimating equations model) adjusted for time (if available), child’s sex, andpresence of a psychiatric disorder

Outcome Group Estimated marginal means (SE) Group effect Time × group interaction

t2 t3 t4 β (95 % CI)

Mental development TG 92.88 (.51) 95.13 (.80) 87.27 (1.08) 1.29 (−.42–3.00)Wald=2.179, df=1, p=.140

Wald=3.019, df=2, p=.221CG 91.77 (.54) 92.42 (.90) 87.14 (1.11)

Psychomotor development TG 82.74 (.77) 92.68 (1.06) 92.62 (1.11) .65 (−1.27–2.57)Wald=.437, df=1, p=.509

Wald=.507, df=2, p=.776CG 81.55 (.81) 91.89 (1.08) 92.65 (1.08)

Child behavior rating TG 45.83 (1.70) 52.00 (1.64) 52.42 (2.15) .66 (−2.78–4.09)Wald=.140, df=1, p=.708

Wald=3.906, df=2, p=.142CG 42.37 (1.78) 49.81 (1.74) 56.10 (2.29)

Language development, mothers’rating

TG – 14.40 (.78) 102.77 (4.98) −2.37 (−9.80–5.06)Wald=.391, df=1, p=.532

Wald=.532, df=1, p=.470CG – 14.27 (.80) 107.64 (5.22)

Language development, children’stest

TG – – .79 (.05) −.01 (−.15–.14)Wald=.014, df=1, p=.905

–CG – – .80 (.05)

Socio-emotional development(internal)

TG – – 9.63 (.48) −.19 (−1.46–1.07)Wald=.088, df=1, p=.767

–CG – – 9.82 (.45)

Socio-emotional development(external)

TG – – 16.04 (.59) .82 (−.78–2.42)Wald=1.010, df=1, p=.315

–CG – – 15.22 (.57)

Adjusted for time (if available), child’s sex, and presence of a psychiatric disorder

87.00

88.00

89.00

90.00

91.00

92.00

93.00

high risk group low risk group

Men

tal D

evel

opm

ent I

ndex

(est

imat

ed m

arig

nal m

eans

)

TG

CG

Fig. 3 Children’s mentaldevelopment by treatment groupsand risk status (group × risk statusinteraction: Wald=4.861, df=1,p=.028)

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in the nurse-visited group, and 19 % in the control group gavebirth to another child in the 24 months postpartum period(Olds et al. 2002). In our study, 12 % of the women in theTG and only 7% of the women in the CG gave birth to anotherchild. Likewise, TG and CG showed similar rates in educa-tional achievement (20 and 26 %, respectively) which can beexplained by the fact that all women received regular supportby the local employment agencies.

In the maternal competencies domain, we found positiveprogram effects for parental self-efficacy (a significant groupeffect as well as a marginally significant time by group inter-action), knowledge on child rearing (a marginally significantgroup effect), and a marginally significant time by group in-teraction for maternal feelings of attachment. These variablesrepresent more cognitive aspects of parenting competencies,which seem to be strengthened by our home visiting interven-tion. Previous studies also found program effects on parentingcharacteristics as the major aim ofmost interventions (Howardand Brooks-Gunn 2009). Yet, effects on other characteristicssuch as parenting style, mother-child interaction, maternal em-pathy, and belief of control that can broadly be described ascharacteristics of the mother-child relationship, could not bedetected. These variables are especially in the focus of pre-ventive interventions using video feedback that have beenshown to successfully change mother-child interaction factors(Bakermans-Kranenburg et al. 2003). The absence of thesespecific components within Pro Kind may explain the lackingresults. Yet, the maternal competency domain was the onlydomain in our study where significant effects of implementa-tion variables were evident. In support of the results byKorfmacher et al. (1998), a good quality of the relationshipbetween mother and home visitor was related to the improve-ment of maternal feelings of attachment and, by trend, to pa-rental self-efficacy. This underlines that a trusting and

satisfying working alliance to the home visitor can enhanceeffects of the intervention like strengthening parenting com-petencies and skills.

In the domain of child development, only children of high-risk mothers showed a superior mental development com-pared to their CG counterparts. Thus, our home visiting inter-vention may have encouraged high-risk mothers to show abetter stimulation of their children’s cognitive skills, whichcould have improved their mental development. No effectson child behavior, language, or social-emotional developmentwere evident. One could assume that effects of early interven-tion on children’s development become more visible at laterstages of their lives, for example, at school entry. Some of thefindings from the NFP trials support this assumption (e.g.,Eckenrode et al. 2010; Olds et al. 2007).

In general, the low frequency of home visits may havecontributed to small or even absent effects. According toNievar et al. (2010), programs with more than three visitsper month were twice as effective. Second, less time thanintended was spent on parenting issues during the visits inthe infancy and toddler phase of intervention. Anecdotal casereports revealed that home visitors often felt that they had tofix a current crisis before they could turn to the topics theyplanned to present to the families, such as quality of mother-child interaction and child development (Brand and Jungmann2012). Third, in contrast to NFP, Pro Kind was implementedby midwives and social workers rather than registered nurses,which may have contributed, in part, to the different resultscompared to that in the USA.

Limitations

The high drop-out rate of families with the most severe socio-economical disadvantages is an important limitation of the

Table 6 Effects of implementation variables and risk factors on change in maternal stress, parental self-efficacy, and maternal feelings of attachment(generalized estimating equations model)

Outcome Predictors Unstandardized regression coefficient (95 % CI) p

Maternal stress Number of home visits .000 (−.002–.002) .839

Quality of helping relationship .004 (−.005–.014) .365

Maternal age .009 (.003–.014) .001

Number of risk factors .018 (.005–.030) .007

Parental self-efficacy Number of home visits −.001 (−.003–.002) .610

Quality of helping relationship .004 (−.001–.009) .093

Maternal age −.003 (−.009–.003) .298

Number of risk factors .000 (−.009–.009) .948

Feelings of attachment Number of home visits −.002 (−.005–.000) .095

Quality of helping relationship .007 (.002–.011) .002

Maternal age −.004 (−.009–.000) .049

Number of risk factors −.010 (−.009–.000) .022

Adjusted for time and baseline values of the outcome variable

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study, in particular, as these families appear to benefit mostfrom early intervention programs (Gaylor and Spiker 2012).In line with our results, Gomby et al. (1999) found a dropoutrate between 20 and 67 % in their review of home visitationprograms. Consequently, retaining high-risk families is themost difficult challenge for an effective application of earlyintervention programs. Second, measurement of self-reportedoutcomes as well as process variables of implementationshould be complemented by observational methods as moreobjective indicators of program effects. Third, interventioneffects were tested while the home visiting program was im-plemented, so possible sleeper effects of the interventioncould not be detected. Follow-up analyses could reveal long-term benefits of the home visiting program (e.g., in terms ofchild development).

Conclusion

In summary, we found only a few intervention effects of BProKind,^ in part with marginal significance. This underlinesdoubts of recent reviews in investing home visitation as astand-alone early intervention strategy. As Johnson (2009)points out, programs that provide a dense network of adequatesupply of resources in communities are likely to achieve betteroutcomes than similar programs in communities with scarceresources or networks of poor quality. Although German com-munities supply those high resources, the networking initiatedby the Pro Kind home visitors was partly low (e.g., only 18 %of children in the TG who needed early developmental sup-port received it in comparison to 12 % of children in the CG).

Furthermore, outcomes of early intervention programs arealso shaped by public policy environment (Gomby 2007). Instates offering liberal and high-quality public health insurancecoverage for families, such as Germany, early interventionsmay not be able to produce large or various effects on mothersand children. Thus, home visitation should be linked with andadapted to existing social and health care services. Our resultson subgroup effects and implementation variables underlinethat future home visitation programs should consider theneeds of different risk groups and focus more strongly onimplementation process variables such as the characteristicsof the helping relationship. Moreover, there are indicationsthat continuing research on this unique sample of sociallydisadvantaged families in Germany could be worthwhile,since effects on children may be easier to measure if they areolder. Therefore, the rationale of outcomes for disadvantagedchildren should follow developmental trajectories in the un-derstanding of services that would be most beneficial to thesechildren.

Acknowledgments The authors thank Dr. Annette M. Klein for herhelpful comments. Tilman Brand declared a possible conflict of interest,

as he has worked for the Pro Kind foundation from October 2011 toFebruary 2012.

This work was supported by the German Federal Ministry of FamilyAffairs, Senior Citizens, Women and Youth (grant number IIA6-25080820V6). The State Ministry for Social Affairs and Consumer Pro-tection Saxony, the TUI Foundation, the Dürr Foundation, and theReimann-Dubbers Foundation gave grants to complete this project.

Conflict of Interest The authors declare that they have no competinginterests.

References

Achenbach, T. M., & Rescorla, L. A. (2000). Manual for the ASEBAPreschool Forms & Profiles: An Integrated System of Multi-informant Assessment; Child Behavior Checklist for Ages 1 1/2-5;Language Development Survey; Caregiver-Teacher Report Form.University of Vermont.

Arnold, D. S., O’Leary, S. G., Wolff, L. S., & Acker, M. M. (1993). Theparenting scale: A measure of dysfunctional parenting in disciplinesituations. Psychological Assessment, 5(2), 137–144.

Bakermans-Kranenburg, M. J., Van Ijzendoorn, M. H., & Juffer, F.(2003). Less is more: Meta-analyses of sensitivity and attachmentinterventions in early childhood. Psychological Bulletin, 129(2),195.

Bandura, A. (1977). Social learning theory. Englewood Cliffs: PrenticeHall.

Bodenmann, G. (2000). Stress und Coping bei Paaren. Göttingen:Hogrefe.

Bowlby, J. (1969/1982). Attachment and loss. Vol. 1 attachment. NewYork: Basic Books.

Brand, T., & Jungmann, T. (2012). Implementation differences betweenof two staffing models in the German home visiting program BProKind^. Journal of Community Psychology, 40(8), 891–905.

Brand, T., & Jungmann, T. (2014). Participant characteristics and processvariables predict attrition from a home-based early intervention pro-gram. Early Childhood Research Quarterly, 29(2), 155–167.

Bronfenbrenner, U. (1979). Contexts of child rearing: Problems and pros-pects. American Psychologist, 34(10), 844–850.

Cohen, S., & Williamson, G. (1988). Perceived stress in a probabilitysample of the United States. In S. Spacapan & S. Oskamp (Eds.),The social psychology of health (pp. 31–68). Newbury Park: Sage.

Condon, J. T., & Corkindale, C. J. (1998). The assessment of parent-to-infant attachment: Development of a self-report questionnaire in-strument. Journal of Reproductive and Infant Psychology, 16(1),57–76.

Davis, M. H. (1980). A multidimensional approach to individual differ-ences in empathy. JSAS Catalog of Selected Documents inPsychology, 10, 85.

Eckenrode, J., Campa, M., Luckey, D.W., Henderson, C. R., Jr., Cole, R.,Kitzman, H., Anson, E., Sidora-Arcoleo, K., Powers, J., & Olds, D.L. (2010). Long-term effects of prenatal and infancy nurse homevisitation on the life course of youths: 19-year follow-up of a ran-domized trial. Archives of Pediatrics & Adolescent Medicine,164(1), 9–15.

Efron, B. (1971). Forcing a sequential experiment to be balanced.Biometrika, 58, 403–417.

Fahrenberg, J., Myrtek, M., Schumacher, J., & Brähler, E. (2000).Fragebogen zur Lebenszufriedenheit [Life SatisfactionQuestionnaire]. Göttingen: Hogrefe.

Gaylor, E., & Spiker, D. (2012). Home visiting programs and their impacton young children’s school readiness. In R. E. Tremblay, M. Boivin,& R. Dev Peters (Eds.), Encyclopedia on early childhood

Prev Sci


development (pp. 1–9). Montreal: Centre of Excellence for EarlyChildhood Development and Strategic Knowledge Cluster onEarly Child Development.

Gomby, D. S. (2007). The promise and limitations of home visiting:Implementing effective programs. Child Abuse & Neglect, 31(8),793–799.

Gomby, D. S., Culross, P. L., & Behrman, R. E. (1999). Home-visiting:Recent program evaluations-analysis and recommendations. TheFuture of Children, 9(1), 4–26.

Grimm, H., & Doil, H. (2006). ELFRA. Elternfragebögen für dieFrüherkennung von Risikokindern. Göttingen: Hogrefe.

Gr imm, H. , Aktas , M. , & Frever t , S . (2000) . SETK-2:Sprachentwicklungstest für zweijährige Kinder. Diagnose rezeptiverund produktiver Sprachverarbeitungsfähigkeiten. Göttingen:Hogrefe.

Hosser, D. (2000). Soziale Unterstüzung im Jugendstrafvollzug. DerEinfluss sozialer Beziehungen auf das Befinden und sozialeEinstellung von Inhaftierten. (Unpublished doctoral dissertation).Braunschweig: Technische Universität Braunschweig.

Horvath, A. O., & Greenberg, L. S. (1989). Development and validationof the Working Alliance Inventory. Journal of CounselingPsychology, 36(2), 223–233.

Howard, K. S., & Brooks-Gunn, J. (2009). The role of home-visitingprograms in preventing child abuse and neglect. The Future ofChildren, 19(2), 119–146.

Johnson, K. (2009). State-based home visiting strengthening programsthrough state leadership. NewYork: National Center for Children inPoverty.

Jungmann, T., Ziert, Y., Kurtz, V., & Brand, T. (2009). Preventing adversedevelopmental outcomes and early onset conduct problems throughprenatal and infancy home visitation: The German pilot project BProKind^. International Journal of Developmental Science, 3(3), 292–298.

Kahn, J., & Moore, K. A. (2010). What works for home visiting pro-grams: Lessons from experimental evaluations of programs andinterventions. Washington, DC: Child Trends.

Kitzman, H., Olds, D. L., Henderson, C. R., Jr., Hanks, C. A., Cole, R.,Tatelbaum, R., et al. (1997). Randomized trial of prenatal and infan-cy home visitation by nurses on pregnancy outcomes, childhoodinjuries, and repeated childbearing: A randomized control trial.Journal of American Medical Association, 278(8), 644–652.

Kitzman, H. J., Olds, D. L., Cole, R. E., Hanks, C. A., Anson, E. A.,Arcoleo, K. J., et al. (2010). Enduring effects of prenatal and infancyhome visiting by nurses on children: Follow-up of a randomized trialamong children at age 12 years. Archives of Pediatrics & AdolescentMedicine, 164(5), 412–418.

Korfmacher, J., Kitzman, H., & Olds, D. L. (1998). Intervention process-es as predictors of outcomes in a preventive home-visitation pro-gram. Journal of Community Psychology, 26(1), 49–64.

Korfmacher, J., Green, B., Spellmann, M., & Thornburg, K. R.(2007). The helping relationship and program participation inearly childhood home visiting. Infant Mental Health Journal,28(5), 459–480.

Korfmacher, J., Green, B., Staerkel, F., Peterson, C., Cook, G., Roggman,L., Faldowski, R., & Schiffman, R. (2008). Parent involvement inearly childhood home visiting. Child & Youth Care Forum, 37(1),171–196.

Mahoney, G. (1999). The maternal behavior rating scale. Tallmadge:Family Child Learning Center.

Nievar, M. A., van Egeren, L. A., & Pollard, S. (2010). A meta-analysisof home visiting programs: Moderators of improvements in mater-nal behavior. Infant Mental Health Journal, 31(5), 499–520.

O’Brien, R. A.,Moritz, P., Luckey, D.W.,McClatchey,M.W., Ingoldsby,E. M., & Olds, D. L. (2012). Mixed methods analysis of participantattrition in the nurse-family partnership. Prevention Science, 13(3),219–228.

O’hara, M. W., & Swain, A. M. (1996). Rates and risk of postpartumdepression—A meta-analysis. International Review of Psychiatry,8(1), 37–54.

Olds, D. L. (2006). The nurse–family partnership: An evidence-basedpreventive intervention. Infant Mental Health Journal, 27(1), 5–25.

Olds, D. L., Robinson, J., O’Brien, R., Luckey, D. W., Pettitt, L. M.,Henderson, C. R., Jr., et al. (2002). Home visiting by paraprofes-sionals and by nurses: A randomized, controlled trial. Pediatrics,110(3), 486–496.

Olds, D. L., Kitzman, H., Hanks, C., Cole, R., Anson, E., Sidora-Arcoleo,K., et al. (2007). Effects of nurse home visiting on maternal andchild functioning: Age-9 follow-up of a randomized trial.Pediatrics, 120(4), 832–845.

Olds, D. L., Kitzman, H. J., Cole, R. E., Hanks, C. A., Arcoleo, K. J.,Anson, E. A., et al. (2010). Enduring effects of prenatal and infancyhome visiting by nurses on maternal life course and governmentspending: Follow-up of a randomized trial among children at age12 years. Archives of Pediatrics & Adolescent Medicine, 164(5),419–424.

Peacock, S., Konrad, S., Watson, E., Nickel, D., & Muhajarine, N.(2013). Effectiveness of home visiting programs on child outcomes:A systematic review. BMC Public Health, 13(1).

Perkins, J., Butterfield, P., & Ottem, N. (2002). Listen, love and play.Educator’s guide. The partners in parenting education curriculum.Brighton, CO: How To Read Your Baby.

Porter, C. L., & Hsu, H.-C. (2003). First-time mothers’ perceptions ofefficacy during the transition to motherhood: Links to infant tem-perament. Journal of Family Psychology, 17(1), 54–64.

Reece, S. M., & Harkless, G. (1998). Self-efficacy stress, and parentaladaptation: Applications to the care of childbearing families.Journal of Family Nursing, 4(2), 198–215.

Reuner, G., Rosenkranz, J., Pietz, J., & Horn, R. (2007). Bayley scales ofinfant development-II. Harcourt Test Services: Frankfurt a. M.

Sandner M. (2012). The effects of early childhood intervention on childdevelopment and early skill formation. Evidence from a randomizedexperiment. mimeo.

Twisk, J. W. R. (2003). Applied longitudinal data analysis forepidemiology. Cambridge: Cambridge University Press.

Prev Sci
