Key Points
Question
What is the agreement between prospective and retrospective measures of childhood maltreatment?
Findings
This systematic review and meta-analysis of 16 unique studies and 25 471 unique participants found poor agreement between prospective and retrospective measures of childhood maltreatment, with Cohen κ = 0.19. On average, 52% of individuals with prospective observations of childhood maltreatment did not retrospectively report it, and likewise, 56% of individuals retrospectively reporting childhood maltreatment did not have concordant prospective observations.
Meaning
Because findings from this meta-analysis demonstrated that prospective and retrospective measures of childhood maltreatment identify largely different groups of individuals, the 2 measures cannot be used interchangeably to study the associated health outcomes and risk mechanisms.
This systematic review and meta-analysis assesses the agreement between prospective and retrospective measures of childhood maltreatment.
Abstract
Importance
Childhood maltreatment is associated with mental illness. Researchers, clinicians, and public health professionals use prospective or retrospective measures interchangeably to assess childhood maltreatment, assuming that the 2 measures identify the same individuals. However, this assumption has not been comprehensively tested.
Objective
To meta-analyze the agreement between prospective and retrospective measures of childhood maltreatment.
Data Sources
MEDLINE, PsycINFO, Embase, and Sociological Abstracts were searched for peer-reviewed, English-language articles from inception through January 1, 2018. Search terms included child* maltreatment, child* abuse, child* neglect, child bull*, child* trauma, child* advers*, and early life stress combined with prospective* and cohort.
Study Selection
Studies with prospective measures of childhood maltreatment were first selected. Among the selected studies, those with corresponding retrospective measures of maltreatment were identified. Of 450 studies with prospective measures of childhood maltreatment, 16 had paired retrospective data to compute the Cohen κ coefficient.
Data Extraction and Synthesis
Multiple investigators independently extracted data according to PRISMA and MOOSE guidelines. Random-effects meta-analyses were used to pool the results and test predictors of heterogeneity.
Main Outcomes and Measures
The primary outcome was the agreement between prospective and retrospective measures of childhood maltreatment, expressed as a κ coefficient. Moderators of agreement were selected a priori and included the measure used for prospective or retrospective assessment of childhood maltreatment, age at retrospective report, sample size, sex distribution, and study quality.
Results
Sixteen unique studies including 25 471 unique participants (52.4% female [SD, 10.6%]; mean [SD] age, 30.6 [11.6] years) contained data on the agreement between prospective and retrospective measures of childhood maltreatment. The agreement between prospective and retrospective measures of childhood maltreatment was poor, with κ = 0.19 (95% CI, 0.14-0.24; P < .001). Agreement was higher when retrospective measures of childhood maltreatment were based on interviews rather than questionnaires (Q = 4.1521; df = 1; P = .04) and in studies with smaller samples (Q = 4.2251; df = 1; P = .04). Agreement was not affected by the type of prospective measure used, age at retrospective report, sex distribution of the sample, or study quality.
Conclusions and Relevance
Prospective and retrospective measures of childhood maltreatment identify different groups of individuals. Therefore, children identified prospectively as having experienced maltreatment may have different risk pathways to mental illness than adults retrospectively reporting childhood maltreatment. Researchers, clinicians, and public health care professionals should recognize these critical measurement differences when conducting research into childhood maltreatment and developing interventions.
Introduction
Do prospective and retrospective measures of childhood maltreatment identify the same individuals? This question has captivated psychiatrists and psychologists since the inception of our discipline1 and still permeates many aspects of our professions. Researchers use retrospective reports as a shortcut to better understand the consequences of childhood maltreatment without the significant time or financial investment needed to undertake cohort studies.2 Clinicians use retrospective reports to swiftly identify individuals who are at heightened risk of mental illness by virtue of their exposure to childhood maltreatment.3 Public health professionals use retrospective reports to pragmatically estimate the health burden associated with exposure to childhood maltreatment.4 All these practices rely on the assumption that retrospective reports and prospective measures identify the same, or at least similar, groups of individuals. However, qualitative reviews5,6 have raised concerns about the validity of this assumption. Herein we present, to our knowledge, the first quantitative assessment of the agreement between retrospective reports and prospective measures of childhood maltreatment.
Methods
Data Sources
We performed a systematic review and meta-analysis in line with the PRISMA and MOOSE guidelines, following an a priori–defined protocol (eMethods and eTables 1 and 2 in the Supplement). We searched MEDLINE, PsycINFO, Embase, and Sociological Abstracts for peer-reviewed articles written in English and published from database inception to January 1, 2018, that included prospective assessments of childhood maltreatment. We used the following search terms: child* maltreatment, child* abuse, child* neglect, child bull*, child* trauma, child* advers*, and early life stress combined with prospective* and cohort.
Study Selection
Two authors (J.R.B. and A.R.) independently screened titles and abstracts of all articles retrieved from the search before reviewing the full text of potentially eligible studies. We included original, peer-reviewed articles with prospectively collected information on childhood maltreatment (age <18 years). Measures of maltreatment (sexual abuse, physical abuse, emotional abuse, and neglect), domestic violence, bullying, institutionalization, and broader measures of adverse childhood experiences that included maltreatment were used to define overall childhood maltreatment. From the articles with prospective assessment of childhood maltreatment, we selected studies with data on corresponding retrospective measures (defined as subsequent assessment of the same individuals’ exposure undertaken at any age).
Data Extraction
Three authors (J.R.B., A.R., and J.B.N.) independently extracted data from all studies with prospective assessment of childhood maltreatment on sample characteristics (cohort name, sample size, location, age at latest assessment, and sex distribution), childhood maltreatment type(s) assessed, prospective measure type(s) (official records, interview, and questionnaire), source (child protection services, hospital records, parent, child, teacher, or multiple informants), and availability of retrospective measures. If retrospective measures of childhood maltreatment were available, 2 authors (J.R.B. and A.D.) subsequently extracted data on the retrospective measurement type (interview or questionnaire) and source, agreement between prospective and retrospective measures, and study quality. Inconsistencies were resolved in consensus meetings and confirmed with the authors of the primary studies when necessary. Relevant missing information was requested from authors.
Statistical Analysis
The extracted data were converted to contingency tables comparing prospectively identified childhood maltreatment (yes or no) with retrospectively reported childhood maltreatment (yes or no). From the contingency tables, we derived estimates of prevalence, raw percentage of agreement between measures, and Cohen κ coefficient. Some studies only reported a κ. Prevalence and raw percentage of agreement estimates were used for descriptive purposes, and our primary outcome was the κ. The other extracted variables were used to explain the heterogeneity in the κs across studies.
We first described the prevalence of childhood maltreatment based on prospective and retrospective measures of childhood maltreatment. We then examined the (1) prevalence of retrospective reports of childhood maltreatment among those with prospective observations, (2) prevalence of prospective observations among those with retrospective reports, and (3) raw percentage of agreement between the 2 measures through meta-analyses of proportions for different childhood maltreatment types with the metafor R package.7 Data from contingency tables were first converted using the Freeman-Tukey double arcsine transformation8 to normalize and stabilize the variance of the sampling distribution, then aggregated using random-effects model meta-analyses, and finally back-transformed using the inverse of the Freeman-Tukey double arcsine transformation.8 To display the overlap between prospective and retrospective measures of child maltreatment based on these meta-analyses, we built Venn diagrams using the VennDiagram R package.9 To build Venn diagrams, we let the relative complements (the prevalence of retrospective reports without prospective observations [R − P] and the prevalence of prospective observations without retrospective reports [P − R]) vary while holding the intersection (RΩP or the prevalence of concordant retrospective reports and prospective observations) constant.
Because the raw percentage of agreement can be inflated by chance, we derived a measure of agreement based on the κ, which accounts for chance findings and provides an estimate of variation in agreement in the population.10 The κs for each study were derived from contingency tables using the cohen.kappa() command from the psych R package,11 which computes CIs based on the variance estimates discussed by Fleiss et al.12 The meta-analyses of κs were undertaken with the metafor R package using a random-effects model. When a study reported multiple effect sizes for different types of maltreatment, we calculated the mean of multiple κs to generate a single overall effect size for each study. We also undertook a sensitivity analysis selecting the largest κ from each study to assess the upper limit of agreement.
We next explored the effects of various possible sources of artifact or bias on κ estimates using the metafor R package.7 First, we assessed heterogeneity between studies using the I2 statistic. Second, we assessed the presence of publication bias visually by funnel plot and formally by funnel plot–based tests, such as the Begg and Egger tests. Because these tests might be underpowered if only a few studies are available, we used a nonparametric trim-and-fill procedure to identify and correct for funnel plot asymmetry and reestimated the aggregate results. Third, we assessed the undue effect of individual studies on the meta-analysis results through jackknife sensitivity analyses, by testing changes in the estimate across permutations in which each study was omitted in turn.
Finally, we tested predictors of heterogeneity in κs. We used subgroup analyses to test the contribution of measurement characteristics (ie, measure used for prospective or retrospective assessment of maltreatment, type of childhood maltreatment). We also used metaregression analyses to test the contribution of sample characteristics (ie, sex distribution, age at retrospective report, sample size, and study quality) (eTable 4 in the Supplement for coding). A 2-tailed P < .05 was considered statistically significant.
Results
Search Results
The study selection procedure is summarized in Figure 1, and further details are provided in the eResults in the Supplement. We identified 450 independent studies with prospective measures of childhood maltreatment (eTable 5 in the Supplement). Of these studies, we identified 20 studies (26 365 participants) with at least partial data on the agreement between prospective and retrospective measures of childhood maltreatment and 16 unique studies13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28 with 25 471 unique participants (52.4% female [SD, 10.6%]; mean [SD] age, 30.6 [11.6] years) with direct measures or paired data sufficient to compute measures of κs. Details of these studies are reported in the Table.
Table. Description of Studies With Prospective and Retrospective Measures of Childhood Maltreatment.
Source (Study Name) | No. of Participants | Female, % | Sample Description | Type of Maltreatment Assessed | Prospective Measurea | Retrospective Measure | Agreement Data | ||||
---|---|---|---|---|---|---|---|---|---|---|---|
Type | Source | Type | Source | Age at Report, y | κ | Paired Measures | |||||
Robins,29 1966 (Deviant Children Grown Up) | 411 | NA | Children with antisocial behavior problems and matched controls from St Louis, Missouri | Maltreatment | Mixed | CPS, self | Interview | Self | 45 | No | No |
Williams,30 1994 | 129 | 100 | Sexually abused females from a Northeastern US city examined at a hospital, 1973-1975 | Sexual abuse | Mixed | Medical records, self, parent | Interview | Self | 24.5 | No | No |
Widom and Shepard,31 1996; Widom and Morris,13 1997; Raphael et al,32 2001 |
1181-1196 | 48.7 | Maltreated children and matched controls from a metropolitan area in the Midwestern United States | Maltreatment, physical abuse, and sexual abuse |
Records | CPS | Interview | Self | 28.7-29.2 | Yes | Yes |
Johnson et al,14 1999 (Children in the Community Study) |
639 | 47.7 | Children from 2 counties in northern New York State | Maltreatment | Records | CPS | Interview | Self | 22.3 | Yes | Yes |
Goodman et al,33 2003 | 175 | 80.6 | Sexually abused children referred from DAs’ offices in Denver, Colorado, 1985-1987 | Sexual abuse | Records | CPS | Interview | Self | 23 | No | No |
Tajima et al,15 2004 (Lehigh Longitudinal Study) | 409 | 45.7 | Children from 2 counties in eastern Pennsylvania with overrepresentation from low-income families | Physical abuse | Interview | Parent | Interview | Self | 18 | Yes | Yes |
White et al,26 2007 (Rutgers Health and Human Development Project) | 359 | 50.7 | Adolescents from New Jersey recruited through random telephone sampling | Physical abuse | Questionnaire | Self | Questionnaire | Self | 30.5 | Yes | Yes |
Everson et al,16 2008 (Longitudinal Studies of Child Abuse and Neglect) | 348-350 | 51 | Children from Eastern and Southeastern United States identified to be high risk for poor medical or developmental outcomes | Physical, sexual, and emotional abuse |
Records | CPS | Interview | Self | 12 | Yes | Yes |
Shaffer et al,17 2008 (Minnesota Longitudinal Study of Parents and Children) | 125-170 | 47.1 | Children born to pregnant women with low socioeconomic status who attended prenatal care in Minnesota | Maltreatment, physical and sexual abuse, and neglect |
Mixed | CPS, self, parent, teacher | Interview | Self | 19 | Yes | Yes |
Barnes et al,34 2009 | 179 | 100 | Sexually abused females and matched controls in Washington, DC | Sexual abuse | Records | CPS | Interview | Self | 24 | No | No |
Scott et al,18 2010 (The New Zealand Mental Health Survey) | 2144 | 55.1 | New Zealand, Maori, and Pacific adults in New Zealand | Maltreatment | Records | CPS | Interview | Self | 21.9 | Yes | Yes |
Denholm et al,19 2013 (National Child Development Study)b | 8461 | NA | Children from Great Britain born in a single week in 1958 | Neglect | Multiple | Parent, teacher | Questionnaire | Self | 45 | Yes | Yes |
Elwyn and Smith,20 2013 (Rochester Youth Development Study) | 846 | 27.1 | Children from Rochester, New York, with overrepresentation of boys and students from high-crime census tracts | Maltreatment | Records | CPS | Interview | Self | 22.7 | Yes | Yes |
Patten et al,21 2015 (National Longitudinal Study Survey of Children and Youth/National Population Health Survey) | 1977 | 48.3 | Children from Canada assessed as part of 2 linked surveys in childhood and adulthood | ACEs | Interview | Parent | Interview | Self | NA | Yes | No |
Plant et al,27 2015 (South London Child Development Study)b | 97 | 52.4 | Children born to pregnant women who attended antenatal clinics in South London, UK | Physical and sexual abuse | Interview | Parent, self | Questionnaire | Self | 25 | Yes | Yes |
Mills et al,22 2016 (Mater-University of Queensland Study of Pregnancy) | 3739 | 57.3 | Children born to pregnant women who attended maternity services at a hospital in Brisbane, Australia | Sexual abuse | Records | CPS | Questionnaire | Self | 21 | Yes | Yes |
Reuben et al,23 2016 (Dunedin Multidisciplinary Health and Development Study) | 950 | 49.9 | Children born in Dunedin, New Zealand, in 1972-1973 | Physical, sexual, and emotional abuse, neglect, and ACEs |
Mixed | CPS, parent, research workers, teacher | Interview | Self | 38 | Yes | Yes |
Shenk et al,24 2016 (Female Adolescent Development Study)b | 514 | 100 | Maltreated females and matched controls from an area in the US Midwest | Maltreatment | Records | CPS | Interview | Self | 15.7 | Yes | Yes |
Newbury et al,25 2018 (E-Risk Longitudinal Twin Study) | 2055 | 51 | Twin children from England and Wales born in 1994-1995 | Physical, sexual, and emotional abuse, neglect, and maltreatment |
Interview | Parent, research worker | Interview | Self | 18 | Yes | Yes |
Naicker et al,28 2017 (Birth to Twenty Plus Cohort) | 1506-1565 | 51.8 | Children born in Soweto- Johannesburg, South Africa, during 7 weeks in 1990 | Sexual, physical, and emotional abuse | Questionnaire | Self | Questionnaire | Self | 23 | Yes | Yes |
Abbreviations: ACEs, adverse childhood experiences; CPS, child protection services; DA, district attorney; NA, not available.
“Mixed” refers to studies assessing childhood maltreatment using a combination of records and interviews or questionnaires; “multiple” refers to studies assessing childhood maltreatment using interviews and questionnaires (excluding records).
Data on agreement between prospective and retrospective measures were obtained from study authors rather than from the published article.
Overlap Between Individuals Identified by Prospective or Retrospective Measures of Childhood Maltreatment
eFigure 1 in the Supplement displays the range of prevalence estimates for childhood maltreatment based on 32 paired prospective and retrospective measures extracted from 15 studies.14,15,16,17,18,19,20,22,23,24,25,26,27,28,31 Capitalizing on the paired nature of the data, we next analyzed (1) the prevalence of retrospective reports of childhood maltreatment among those with prospective observations, (2) the prevalence of prospective observations among those with retrospective reports, and (3) the raw percentage of agreement between prospective and retrospective measures. A random-effects meta-analysis of 7 studies14,17,18,20,24,25,32 focusing on a broad measure of child maltreatment revealed that the prevalence of retrospective reports among those with prospective observations was 48% (95% CI, 34%-62%; I2 = 96%); the prevalence of prospective observations among those who retrospectively reported childhood maltreatment was 44% (95% CI, 24%-65%; I2 = 99%); and the percentage of agreement between prospective and retrospective measures of childhood maltreatment was 76% (95% CI, 67%-84%; I2 = 99%). Therefore, on average, 52% of individuals with prospective observations of maltreatment did not retrospectively report it, and 56% of individuals retrospectively reporting maltreatment did not have concordant prospective observations (Figure 2A).
We next undertook sensitivity analyses to test whether the overlap between individuals identified as maltreated through prospective or retrospective measures varied as a function of the type of maltreatment (Figure 2B-E and eTable 3 in the Supplement). First, the prevalence of retrospective reports among those with prospective observations in 8 studies13,16,17,22,23,25,27,28 that included childhood sexual abuse was 45% (95% CI, 18%-75%; I2 = 97%); the prevalence of prospective observations among those who retrospectively reported childhood sexual abuse was 25% (95% CI, 12%-41%; I2 = 96%); and the percentage of agreement between prospective and retrospective measures of childhood sexual abuse was 86% (95% CI, 75%-94%; I2 = 99%). Second, the prevalence of retrospective reports among those with prospective observations in the 9 studies15,16,17,23,25,26,27,28,31 that included childhood physical abuse was 38% (95% CI, 18%-60%; I2 = 98%); the prevalence of prospective observations among those who retrospectively reported childhood physical abuse was 42% (95% CI, 19%-66%; I2 = 98%); and the percentage of agreement between prospective and retrospective measures of childhood physical abuse was 75% (95% CI, 62%-86%; I2 = 99%). Third, the prevalence of retrospective reports among those with prospective observations in the 4 studies16,23,25,28 that included childhood emotional abuse was 37% (95% CI, 23%-52%; I2 = 84%); the prevalence of prospective observations among those who retrospectively reported childhood emotional abuse was 15% (95% CI, 4%-33%; I2 = 97%); and the percentage of agreement between prospective and retrospective measures of childhood emotional abuse was 76% (95% CI, 57%-91%; I2 = 99%). Finally, the prevalence of retrospective reports among those with prospective observations in the 4 studies17,19,23,25 that included childhood neglect was 23% (95% CI, 14%-34%; I2 = 81%); the prevalence of prospective observations among those who recalled childhood neglect was 18% (95% CI, 13%-25%; I2 = 61%); and the percentage of agreement between prospective and retrospective measures of childhood neglect was 84% (95% CI, 70%-94%; I2 = 99%).
Agreement Between Prospective and Retrospective Measures of Childhood Maltreatment
Because the raw percentage of agreement can be inflated by chance, we next examined the agreement between prospective and retrospective measures based on the κ, which accounts for chance findings and provides an estimate of variation in agreement in the population. A random-effects model meta-analysis of the 16 studies that included any measure of maltreatment revealed that the agreement between prospective and retrospective measures of childhood maltreatment was poor, with κ = 0.19 (95% CI, 0.14-0.24; P < .001; I2 = 93%). A forest plot displaying the meta-analytic findings is reported in Figure 3.
We found some evidence of publication bias, as suggested by slight asymmetry of the funnel plot (eFigure 2A in the Supplement) (Egger test, z = 4.4273; P < .001) and association between effect sizes and corresponding sampling variances (Begg test, τ = 0.37; P = .052). To correct for funnel-plot asymmetry arising from publication bias, we used a trim-and-fill procedure. The trim-and-fill results with 17 studies (κ = 0.19; 95% CI, 0.14-0.24; P < .001; I2 = 92%) (eFigure 2B in the Supplement) were similar to the results of our original meta-analysis, suggesting no substantial role of publication bias on the meta-analysis results.
Jackknife sensitivity analyses showed overall little evidence of undue effects of individual studies in the meta-analyses. The κ estimates in 16 automated permutations where each study was omitted in turn were similar and had overlapping CIs (eFigure 3 in the Supplement).
Predictors of Heterogeneity in Agreement Between Prospective and Retrospective Measures of Childhood Maltreatment
Finally, we tested predictors of heterogeneity across studies with subgroup and metaregression analyses. First, we considered whether the measure used for prospective assessment of maltreatment could explain heterogeneity in effect sizes. Agreement with retrospective reports was similar regardless of whether prospective assessment was based on records (eg, child protection records or medical records; κ = 0.16; 95% CI, 0.09-0.24), reports (eg, questionnaires or interviews by parents or young people; κ = 0.22; 95% CI, 0.14-0.31), or mixed measures (records and reports; κ = 0.23; 95% CI, −0.01 to 0.48). An overall test of moderation showed that prospective measure type did not explain the heterogeneity in agreement (Q = 1.1755; df = 2; P = .56). Second, we considered whether the measure used for retrospective assessment of maltreatment could explain heterogeneity in effect sizes. As shown in Figure 4, retrospective recall during interviews (eg, verbal assessment, including reading a questionnaire aloud) showed higher agreement with prospective measures (κ = 0.22; 95% CI, 0.16-0.27) compared with retrospective recall using questionnaires (eg, written assessment; κ = 0.11; 95% CI, 0.06-0.16; difference, −0.11; P = .04). An overall test of moderation showed that retrospective measure type explained the heterogeneity in agreement (Q = 4.1521; df = 1; P = .04). Third, we tested whether the type of childhood maltreatment could explain heterogeneity in effect sizes. As shown in eFigure 4 in the Supplement, broad measures of childhood adversity (κ = 0.36; 95% CI, 0.25-0.48) or maltreatment (κ = 0.23; 95% CI, 0.17-0.30) showed the strongest agreement, whereas measures of emotional abuse (κ = 0.09; 95% CI, 0.04-0.13) or neglect (κ = 0.09; 95% CI, 0.05-0.13) showed the weakest agreement. A formal test of moderation across type of childhood maltreatment was not possible because the subgroups were not independent (ie, different types of childhood maltreatment were measured in the same individuals). Fourth, we tested in meta-regression analyses whether characteristics of the samples could explain heterogeneity in effect sizes. As shown in eFigure 5 in the Supplement, sample size was negatively associated with the κ coefficient (Q = 4.2251; df = 1; P = .04), indicating that smaller samples had higher agreement between prospective and retrospective measures. However, we did not find that heterogeneity in agreement was explained by other characteristics of the samples, such as sex (Q = 1.1653; df = 1; P = .28) or age at retrospective report (Q = 1.0561; df = 1; P = .30). Variation in study quality also did not explain heterogeneity in effect sizes (Q = 0.1632; df = 1; P = .69) (eTable 4 in the Supplement). Finally, in sensitivity analyses where we selected the highest effect size for the 7 studies reporting multiple effect sizes for different abuse types (instead of calculating the mean as above), we found similar results (eResults in the Supplement).
Discussion
This meta-analysis is the first, to our knowledge, to examine the agreement between prospective and retrospective measures of childhood maltreatment. Across 16 studies that included 25 471 individuals, we found that prospective and retrospective measures of childhood maltreatment showed poor agreement. Notably, more than half of individuals with prospective observations of childhood maltreatment did not report it retrospectively, and likewise more than half of individuals retrospectively reporting childhood maltreatment did not have concordant prospective observations (Figure 2). This finding suggests that prospective and retrospective measures of childhood maltreatment identify largely different groups of individuals and, thus, cannot be used interchangeably.
Low agreement between prospective and retrospective measures of childhood maltreatment could be explained by multiple factors, such as motivation of reporters, measurement features, and memory biases. Motivation can reduce agreement if prospective or retrospective reporters may gain something by intentionally withholding information about childhood maltreatment (ie, nondisclosure, for example owing to embarrassment, feeling uncomfortable with the interviewer, not wanting to discuss upsetting events, or fear of referral to the authorities) or by fabricating information (ie, false disclosure, for example in the context of harassment, revenge, or family disputes).
Measurement features can also reduce agreement in several ways. First, all childhood maltreatment measures have imperfect test-retest reliability,35 and constraints on reliability add error variance, ultimately reducing agreement between prospective and retrospective measures.36 Second, low agreement may be due to systematic differences in the sensitivity of the measures (as reflected by the lower prevalence of childhood maltreatment identified by prospective vs retrospective measures) (eFigure 1 in the Supplement); for example, prospective measures through official records might capture only the most severe cases of maltreatment, whereas retrospective reports might detect more true cases. Third, low agreement may be owing to other systematic differences between prospective and retrospective measures, such as the reporter13,14,15,16,17,18,19,20,21,22,23,24,25,31,32 (eg, official records vs later self-reports), the reporting period15,19,20,21,23 (eg, prospective observation until 12 years of age vs retrospective recall of experiences from 0-18 years of age, or official records capturing maltreatment limited to early childhood owing to the focus of child protection services), or the definition of the maltreatment experience between prospective and retrospective measures19 (eg, neglect measured prospectively as lack of parental affection and retrospectively as lack of input or stimulation).
Finally, memory biases can reduce agreement by promoting underreporting and overreporting of actual experiences. On the one hand, underreporting may occur because of (1) deficits in encoding the maltreatment experience in early life owing to immature, delayed, or impaired brain development37; (2) deficits in consolidating the maltreatment memory owing to low emotional valence (ie, not experiencing the event as distressing)38 or disrupted sleep patterns39; (3) deficits in reconsolidating the maltreatment memory owing to memory updating during subsequent reactivation if false feedback is given40 (eg, being told that the experience was not abusive), if the memory is no longer associated with distressing emotions (eg, after successful psychotherapy),41 or if reappraisal is positively biased by personality features (eg, high agreeableness)23; (4) deficits in memory storage owing to brain injury or aging42; or (5) deficits in retrieving the maltreatment memory owing to infantile amnesia,43 forgetting (eg, because of low contextual reinforcement or interference by competing memories),44 or cognitive avoidance strategies to regulate affect.45,46,47 On the other hand, overreporting may occur because of (6) bias in memory encoding or reconsolidation owing to individual suggestibility (as shown in experimental paradigms of imagination inflation, false feedback, or memory implantation) or a source-monitoring error (eg, misinterpretation of internal images or dreams as lived experiences)40,48,49 or (7) inaccurate retrieval linked to negative bias in autobiographical memory (eg, in depression).50
Our findings support some of these factors. First, we found that the agreement between prospective and retrospective measures of childhood maltreatment was higher in studies that used interviews rather than questionnaires to elicit retrospective recall (Figure 4). This finding is consistent with broader observations regarding the assessment of life stress and may occur because interviews enable provision of a more detailed definition of maltreatment, contextual or anchoring methods, and greater engagement of participants.51 Second, agreement was also higher in studies with smaller samples (eFigure 5 in the Supplement), which might reflect the presence of more detailed retrospective assessments. Finally, the agreement for any of the childhood maltreatment measures included was substantially lower than the agreement for more clear-cut forms of adversity, such as parental loss (κ = 0.83 in the study by Reuben et al23; Figure 2F), suggesting that subjective interpretation of the childhood maltreatment measures may contribute to the observed heterogeneity. More research is clearly needed to disentangle factors contributing to the low agreement between prospective and retrospective measures of childhood maltreatment.
Limitations
Our findings should be interpreted in the context of some limitations. First, because of the high levels of heterogeneity, the average meta-analytical effect sizes for agreement should be interpreted with caution. However, we used random-effects models to minimize bias linked to high heterogeneity and note that the meta-analytical CIs are narrow and consistent with the interpretation given.
Second, the results describe the agreement between prospective and retrospective measures of childhood maltreatment commonly used in the context of research studies. Therefore, the results cannot be extrapolated to infer agreement or validity of measures of childhood maltreatment used in other contexts (eg, retrospective allegations brought to the attention of the criminal justice system).
Third, although prospective measures are generally considered to be more valid (specific) indicators of the occurrence of maltreatment,52 the low agreement between prospective and retrospective measures cannot be interpreted to directly indicate poor validity of retrospective measures. For example, prospective measures may have lower sensitivity (ie, may identify a lower proportion of individuals who were maltreated), and the higher prevalence of retrospective measures could, thus, indicate greater ability to identify true cases of childhood maltreatment. If that was the case, predictions from retrospective measures should converge on the same outcomes as those of more specific prospective measures (convergent validity), and retrospective measures should not only be associated with outcomes assessed with the same method (ie, self-reports) but should also be associated with outcomes assessed with other methods, such as objective measures (eg, medical examinations or biomarkers [discriminant validity]).53 A few studies13,15,23,25 have tested these questions and have observed that prospective and retrospective measures assessed in the same individuals are associated with similar outcomes. However, retrospective measures showed stronger associations with self-reported outcomes than objectively assessed outcomes,23,31 raising concerns about potential common method bias.54 Therefore, further research in other samples is needed to comprehensively evaluate the construct validity of retrospective measures. Regardless of any concerns regarding their validity, retrospective reports may still be pragmatically used in the clinic as risk indicators associated with incidence of psychopathology, its course of illness, or treatment response.3,55
Conclusions
Our findings have implications for researchers and health care professionals. Although retrospective reports and prospective measures identify at-risk individuals, the groups of individuals identified with either measure are not the same (Figure 2). Therefore, assuming that the underlying risk mechanisms are the same in both groups may be inaccurate. That is, the mechanisms underlying disease risk in children identified as being maltreated through prospective assessments may be different from the mechanisms underlying disease risk in adults retrospectively reporting childhood maltreatment. If risk mechanisms are different, then the 2 groups will need different interventions to effectively prevent and treat disease. As such, our findings provide a new framework for etiologic research on childhood maltreatment and intervention development.
References
- 1.Masson JM. Freud and the seduction theory. Atlantic. https://www.theatlantic.com/magazine/archive/1984/02/freud-and-the-seduction-theory/376313/. February 1984. Accessed February 11, 2019. [Google Scholar]
- 2.Teicher MH, Samson JA, Anderson CM, Ohashi K. The effects of childhood maltreatment on brain structure, function and connectivity. Nat Rev Neurosci. 2016;17(10):652-666. doi: 10.1038/nrn.2016.111 [DOI] [PubMed] [Google Scholar]
- 3.Nanni V, Uher R, Danese A. Childhood maltreatment predicts unfavorable course of illness and treatment outcome in depression: a meta-analysis. Am J Psychiatry. 2012;169(2):141-151. doi: 10.1176/appi.ajp.2011.11020335 [DOI] [PubMed] [Google Scholar]
- 4.Felitti VJ, Anda RF, Nordenberg D, et al. . Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14(4):245-258. doi: 10.1016/S0749-3797(98)00017-8 [DOI] [PubMed] [Google Scholar]
- 5.Brewin CR, Andrews B, Gotlib IH. Psychopathology and early experience: a reappraisal of retrospective reports. Psychol Bull. 1993;113(1):82-98. doi: 10.1037/0033-2909.113.1.82 [DOI] [PubMed] [Google Scholar]
- 6.Hardt J, Rutter M. Validity of adult retrospective reports of adverse childhood experiences: review of the evidence. J Child Psychol Psychiatry. 2004;45(2):260-273. doi: 10.1111/j.1469-7610.2004.00218.x [DOI] [PubMed] [Google Scholar]
- 7.Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36(3). doi: 10.18637/jss.v036.i03 [DOI] [Google Scholar]
- 8.Freeman MF, Tukey JW. Transformations related to the angular and the square root. Ann Math Stat. 1950;21(4):607-611. doi: 10.1214/aoms/1177729756 [DOI] [Google Scholar]
- 9.Chen H, Boutros PC. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinformatics. 2011;12(1):35. doi: 10.1186/1471-2105-12-35 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Cohen J. A coefficient of agreement for nominal scales. Educ Psychol Meas. 1960;20(1):37-46. doi: 10.1177/001316446002000104 [DOI] [Google Scholar]
- 11.Revelle WR. psych: Procedures for psychological, psychometric, and personality research, R package 1.8.4. https://cran.r-project.org/web/packages/psych/index.html. Accessed February 11, 2019.
- 12.Fleiss JL, Cohen J, Everitt B. Large sample standard errors of kappa and weighted kappa. Psychol Bull. 1969;72(5):323-327. doi: 10.1037/h0028106 [DOI] [Google Scholar]
- 13.Widom CS, Morris S. Accuracy of adult recollections of childhood victimization, II: childhood sexual abuse. Psychol Assess. 1997;9(1):34-46. doi: 10.1037/1040-3590.9.1.34 [DOI] [Google Scholar]
- 14.Johnson JG, Cohen P, Brown J, Smailes EM, Bernstein DP. Childhood maltreatment increases risk for personality disorders during early adulthood. Arch Gen Psychiatry. 1999;56(7):600-606. doi: 10.1001/archpsyc.56.7.600 [DOI] [PubMed] [Google Scholar]
- 15.Tajima EA, Herrenkohl TI, Huang B, Whitney SD. Measuring child maltreatment: a comparison of prospective parent reports and retrospective adolescent reports. Am J Orthopsychiatry. 2004;74(4):424-435. doi: 10.1037/0002-9432.74.4.424 [DOI] [PubMed] [Google Scholar]
- 16.Everson MD, Smith JB, Hussey JM, et al. . Concordance between adolescent reports of childhood abuse and Child Protective Service determinations in an at-risk sample of young adolescents. Child Maltreat. 2008;13(1):14-26. doi: 10.1177/1077559507307837 [DOI] [PubMed] [Google Scholar]
- 17.Shaffer A, Huston L, Egeland B. Identification of child maltreatment using prospective and self-report methodologies: a comparison of maltreatment incidence and relation to later psychopathology. Child Abuse Negl. 2008;32(7):682-692. doi: 10.1016/j.chiabu.2007.09.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Scott KM, Smith DR, Ellis PM. Prospectively ascertained child maltreatment and its association with DSM-IV mental disorders in young adults. Arch Gen Psychiatry. 2010;67(7):712-719. doi: 10.1001/archgenpsychiatry.2010.71 [DOI] [PubMed] [Google Scholar]
- 19.Denholm R, Power C, Li L. Adverse childhood experiences and child-to-adult height trajectories in the 1958 British Birth Cohort. Int J Epidemiol. 2013;42(5):1399-1409. doi: 10.1093/ije/dyt169 [DOI] [PubMed] [Google Scholar]
- 20.Elwyn L, Smith C. Child maltreatment and adult substance abuse: the role of memory. J Soc Work Pract Addict. 2013;13(3):269-294. doi: 10.1080/1533256X.2013.814483 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Patten SB, Wilkes TC, Williams JV, et al. . Retrospective and prospectively assessed childhood adversity in association with major depression, alcohol consumption and painful conditions. Epidemiol Psychiatr Sci. 2015;24(2):158-165. doi: 10.1017/S2045796014000018 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Mills R, Kisely S, Alati R, Strathearn L, Najman J. Self-reported and agency-notified child sexual abuse in a population-based birth cohort. J Psychiatr Res. 2016;74:87-93. doi: 10.1016/j.jpsychires.2015.12.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Reuben A, Moffitt TE, Caspi A, et al. . Lest we forget: comparing retrospective and prospective assessments of adverse childhood experiences in the prediction of adult health. J Child Psychol Psychiatry. 2016;57(10):1103-1112. doi: 10.1111/jcpp.12621 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Shenk CE, Noll JG, Peugh JL, Griffin AM, Bensman HE. Contamination in the prospective study of child maltreatment and female adolescent health. J Pediatr Psychol. 2016;41(1):37-45. doi: 10.1093/jpepsy/jsv017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Newbury JB, Arseneault L, Moffitt TE, et al. . Measuring childhood maltreatment to predict early-adult psychopathology: comparison of prospective informant-reports and retrospective self-reports. J Psychiatr Res. 2018;96:57-64. doi: 10.1016/j.jpsychires.2017.09.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.White HR, Widom CS, Chen PH. Congruence between adolescents’ self-reports and their adult retrospective reports regarding parental discipline practices during their adolescence. Psychol Rep. 2007;101(3, pt 2):1079-1094. [DOI] [PubMed] [Google Scholar]
- 27.Plant DT, Pariante CM, Sharp D, Pawlby S. Maternal depression during pregnancy and offspring depression in adulthood: role of child maltreatment. Br J Psychiatry. 2015;207(3):213-220. doi: 10.1192/bjp.bp.114.156620 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Naicker SN, Norris SA, Mabaso M, Richter LM. An analysis of retrospective and repeat prospective reports of adverse childhood experiences from the South African Birth to Twenty Plus cohort. PLoS One. 2017;12(7):e0181522. doi: 10.1371/journal.pone.0181522 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Robins LN. Deviant Children Grown Up. Baltimore, MD: Williams & Wilkins; 1966. [Google Scholar]
- 30.Williams LM. Recall of childhood trauma: a prospective study of women’s memories of child sexual abuse. J Consult Clin Psychol. 1994;62(6):1167-1176. doi: 10.1037/0022-006X.62.6.1167 [DOI] [PubMed] [Google Scholar]
- 31.Widom CS, Shepard RL. Accuracy of adult recollections of childhood victimization, I: childhood physical abuse. Psychol Assess. 1996;8(4):412-421. doi: 10.1037/1040-3590.8.4.412 [DOI] [Google Scholar]
- 32.Raphael KG, Widom CS, Lange G. Childhood victimization and pain in adulthood: a prospective investigation. Pain. 2001;92(1-2):283-293. doi: 10.1016/S0304-3959(01)00270-6 [DOI] [PubMed] [Google Scholar]
- 33.Goodman GS, Ghetti S, Quas JA, et al. . A prospective study of memory for child sexual abuse: new findings relevant to the repressed-memory controversy. Psychol Sci. 2003;14(2):113-118. doi: 10.1111/1467-9280.01428 [DOI] [PubMed] [Google Scholar]
- 34.Barnes JE, Noll JG, Putnam FW, Trickett PK. Sexual and physical revictimization among victims of severe childhood sexual abuse. Child Abuse Negl. 2009;33(7):412-420. doi: 10.1016/j.chiabu.2008.09.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Colman I, Kingsbury M, Garad Y, et al. . Consistency in adult reporting of adverse childhood experiences. Psychol Med. 2016;46(3):543-549. doi: 10.1017/S0033291715002032 [DOI] [PubMed] [Google Scholar]
- 36.Anastasi A, Urbina S. Psychology Testing. New Jersey: Prentice Hall; 1997. [Google Scholar]
- 37.Eichenbaum H. Memory: organization and control. Annu Rev Psychol. 2017;68:19-45. doi: 10.1146/annurev-psych-010416-044131 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Roozendaal B, McEwen BS, Chattarji S. Stress, memory and the amygdala. Nat Rev Neurosci. 2009;10(6):423-433. doi: 10.1038/nrn2651 [DOI] [PubMed] [Google Scholar]
- 39.Rasch B, Born J. About sleep’s role in memory. Physiol Rev. 2013;93(2):681-766. doi: 10.1152/physrev.00032.2012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Brewin CR, Andrews B. Creating memories for false autobiographical events in childhood: a systematic review. Appl Cogn Psychol. 2017;31(1):2-23. doi: 10.1002/acp.3220 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Lane RD, Ryan L, Nadel L, Greenberg L. Memory reconsolidation, emotional arousal, and the process of change in psychotherapy: new insights from brain science. Behav Brain Sci. 2015;38:e1. doi: 10.1017/S0140525X14000041 [DOI] [PubMed] [Google Scholar]
- 42.Frankland PW, Bontempi B. The organization of recent and remote memories. Nat Rev Neurosci. 2005;6(2):119-130. doi: 10.1038/nrn1607 [DOI] [PubMed] [Google Scholar]
- 43.Travaglia A, Bisaz R, Sweet ES, Blitzer RD, Alberini CM. Infantile amnesia reflects a developmental critical period for hippocampal learning. Nat Neurosci. 2016;19(9):1225-1233. doi: 10.1038/nn.4348 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Wimber M, Alink A, Charest I, Kriegeskorte N, Anderson MC. Retrieval induces adaptive forgetting of competing memories via cortical pattern suppression. Nat Neurosci. 2015;18(4):582-589. doi: 10.1038/nn.3973 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Dalgleish T, Rolfe J, Golden A-M, Dunn BD, Barnard PJ. Reduced autobiographical memory specificity and posttraumatic stress: exploring the contributions of impaired executive control and affect regulation. J Abnorm Psychol. 2008;117(1):236-241. doi: 10.1037/0021-843X.117.1.236 [DOI] [PubMed] [Google Scholar]
- 46.Goodman GS, Quas JA, Ogle CM. Child maltreatment and memory. Annu Rev Psychol. 2010;61:325-351. doi: 10.1146/annurev.psych.093008.100403 [DOI] [PubMed] [Google Scholar]
- 47.Shields GS, Sazma MA, McCullough AM, Yonelinas AP. The effects of acute stress on episodic memory: a meta-analysis and integrative review. Psychol Bull. 2017;143(6):636-675. doi: 10.1037/bul0000100 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Loftus EF. Planting misinformation in the human mind: a 30-year investigation of the malleability of memory. Learn Mem. 2005;12(4):361-366. doi: 10.1101/lm.94705 [DOI] [PubMed] [Google Scholar]
- 49.Schacter DL. The seven sins of memory: insights from psychology and cognitive neuroscience. Am Psychol. 1999;54(3):182-203. doi: 10.1037/0003-066X.54.3.182 [DOI] [PubMed] [Google Scholar]
- 50.Dalgleish T, Werner-Seidler A. Disruptions in autobiographical memory processing in depression and the emergence of memory therapeutics. Trends Cogn Sci. 2014;18(11):596-604. doi: 10.1016/j.tics.2014.06.010 [DOI] [PubMed] [Google Scholar]
- 51.Monroe SM. Modern approaches to conceptualizing and measuring human life stress. Annu Rev Clin Psychol. 2008;4:33-52. doi: 10.1146/annurev.clinpsy.4.022007.141207 [DOI] [PubMed] [Google Scholar]
- 52.Gilbert R, Kemp A, Thoburn J, et al. . Recognising and responding to child maltreatment. Lancet. 2009;373(9658):167-180. doi: 10.1016/S0140-6736(08)61707-9 [DOI] [PubMed] [Google Scholar]
- 53.Campbell DT, Fiske DW. Convergent and discriminant validation by the multitrait-multimethod matrix. Psychol Bull. 1959;56(2):81-105. doi: 10.1037/h0046016 [DOI] [PubMed] [Google Scholar]
- 54.Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol. 2003;88(5):879-903. doi: 10.1037/0021-9010.88.5.879 [DOI] [PubMed] [Google Scholar]
- 55.Agnew-Blais J, Danese A. Childhood maltreatment and unfavourable clinical outcomes in bipolar disorder: a systematic review and meta-analysis. Lancet Psychiatry. 2016;3(4):342-349. doi: 10.1016/S2215-0366(15)00544-1 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.