An Exploration of Prospective Longitudinal Associations between Adverse Childhood Experiences and Adult Mental Health Outcomes: A Protocol for a Systematic Review and Meta-Analysis

DOI: https://doi.org/10.21203/rs.3.rs-1323710/v1

Abstract

Background: Research cites a strong, dose-response relationship between adverse childhood experiences (ACEs) and poor adult mental health outcomes including anxiety, depression, post-traumatic stress disorder (PTSD), self-harm, suicidality, and psychotic-like experiences.

Aim: To systematically investigate the existence and strength of association between ACEs and adult mental health outcomes in prospective longitudinal studies. The review will focus on the outcomes: anxiety, depression, PTSD, self-harm, suicidal ideation, and psychotic-like experiences.

Methods: Twelve electronic databases will be searched: Embase, PsycINFO, MEDLINE, and Global Health through the OVID interface. ProQuest will be used to search Public Affairs Information Service (PAIS), Dissertations and Theses, Sociology Database (including Sociological Abstracts and Social Services Abstracts), PTSDpubs (formerly The Published International Literature on Traumatic Stress (PILOTS) Database) and Applied Social Sciences Index and Abstracts (ASSIA). CINAHL, World Health Organisation (WHO) Global Index Medicus, and WHO Violence Info will also be searched. Eligible studies will be double screened, assessed, and their data will be extracted. Any disagreement throughout these processes will be settled by a third reviewer. If enough studies meet the criteria and the methodological quality of each study is sufficient, a meta-analysis will be conducted.

Analysis: A narrative synthesis of included studies and the associations between ACEs and adult mental health will be completed. If the number of studies included per mental health outcome is two or more, a random effects meta-analysis will be completed using odds ratio effect sizes as outcomes.

Discussion: This review will contribute to the existing body of literature supporting the long-term effects of ACEs on adult mental health. This review adds to previous reviews that have either synthesised cross-sectional associations between ACEs and mental health outcomes, synthesised longitudinal studies exploring the effect of ACEs on different physical and mental health outcomes or synthesised longitudinal studies exploring the effect of ACEs on the same mental health outcomes using different methods. This review aims to identify methodological weaknesses and knowledge gaps in current literature that can be addressed in future primary studies.

Protocol Registration and Reporting: This protocol has been registered in PROSPERO (CRD42021297882) and followed the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) 2015 statement: recommended items to address in a systematic review protocol (1) (see checklist in Additional file 1).

Background

The term “Adverse Childhood Experiences” or “ACEs” was first coined in Felitti et al.’s (2) seminal “Adverse Childhood Experiences Study” and was used to describe a group of specific childhood experiences. Adverse childhood experiences (ACEs) can broadly be defined as potentially traumatic life events occurring in the first 18 years of life (3). Experiences that are defined as ACEs vary within the literature; however, they can broadly be categorised into three overarching classifications: abuse (emotional, sexual, and physical), neglect (emotional and physical), and household dysfunction (alcohol and/or drug abuse in the house, imprisoned family member, mother treated violently, and parental loss, separation, or divorce) (4). While these ACEs are the most heavily researched, this list is not exhaustive. There are further experiences recognised as ACEs in research that this review will also consider, such as being bullied (5), community and collective violence (6), parental mortality and morbidity (7), child marriage, (8) and child trafficking (9).

Over the last three decades, extensive research has explored the relationship between ACEs and the later onset of poorer cognitive, emotional, and behavioural outcomes (2, 10). Strong cross-sectional and longitudinal relationships have been established between ACEs and an increased risk of developing various psychiatric problems including depression (11), anxiety disorders (12), suicidal ideation (13) and psychosis (14). The increasing body of extant literature has concluded that ACEs are a dangerous public health problem (15), and emerging research has recognised adult mental illness as one of the largest public financial burdens associated with ACEs (16).

Adverse Childhood Experiences and Poor Life Outcomes

In 1998, Felitti et al. conducted the aforementioned “Adverse Childhood Experiences Study” in Southern California in the United States of America. The retrospective cohort study collected data over two waves from 1995-1997 and was responded to by 17,337 participants. Participants were selected for the study from their attendance of the Kaiser Permanente’s Health Appraisal Centre (HAC) due to being adult members of the Kaiser Health Plan in San Diego County. The study was designed to explore whether there was a relationship between early life adversity and adult physical and mental ill-health. In both waves, adults who had completed a standard medical evaluation at HAC one-to-two weeks’ prior were asked about adverse childhood experiences (ACEs) and health behaviours through questionnaires sent by mail. The HAC evaluations provided standardised medical histories and formed part of the ACE study database. There were ten adverse childhood experiences included that were separated into two broader categories of childhood maltreatment and household dysfunction (17): emotional and physical neglect; emotional, sexual, or physical abuse; living in a household where members abused substances, where there was violence against the mother, where members were mentally ill/ suicidal or where members were ever incarcerated; and parental separation or divorce.

Felitti et al. (2) found that around two-thirds of the sample experienced at least 1 ACE and around 12.5% experienced at least 4 ACEs. When exploring later negative life events, the researchers found a variety of health outcomes that were strongly associated with having 4 or more ACEs. For example, compared to having no ACEs, those with 4 or more were around 4.6 times more likely to have had depressed mood in the past year, 12.2 times more likely to have ever attempted suicide, 7.4 times more likely to consider themselves and alcoholic and 10 times more likely to have ever injected drugs. A strong dose-response relationship was established between one’s number of ACEs and poor outcomes, including the emergence of later life mental difficulties and physical diseases.

After the pioneering work of Felitti et al. (2), ACEs studies have been conducted globally that confirm ACEs are associated with a variety of poor outcomes (18). For example, studies have evidenced the association between ACEs and suicidal behaviour in sub-Saharan African (19), heavy drinking amongst other health-harming behaviours in the United Kingdom (20), depressed affect in California, North America (21), illicit drug use in Brazil, South America (22) and anxiety, depression and PTSD symptoms in South-East Asia (23). In recent years, ACE studies have also been synthesised in systematic reviews and meta-analyses such as the one completed by Hughes et al. (24) that explored the effect of multiple ACEs on health.

Rationale

Despite the seminal ACE study (2) following the original participants to measure the emergence of poor health outcomes over time, the study still measured ACEs retrospectively. In current literature, retrospective reporting of ACEs by adults remains the most common method of obtaining comprehensive self-reports of adversity (25). Studies using test-retest reliability to explore the consistency of reports of ACEs over time generally find stability in retrospective measures (26). However, due to the reporting of adversity being many years after the event occurred (27), one must consider the possible biases that may result in inaccurate data. Scepticism of the validity of childhood information collected in adulthood has existed for over five decades now, as Yarrow, Campbell and Burton (28) suggested recollection of childhood information may be largely contingent on the information and narration of events told by one’s parents. Retrospective reporting of ACEs is thought to be at a far higher risk of inaccuracy than prospective reporting (the reporting of ACEs as they emerge) due to further issues such as recall bias (29), memory decay (30) and mood-congruent bias (31), where the reporting of historical events is determined by one’s current mental state. For example, researchers have posited that adults diagnosed with mental disorders such as depression exhibit specific “retrieval biases” that subsequently result in superior recall of more negative historical events and fewer positive events (32, 33).

Henry, Moffitt, Caspi, Langley and Silva (34) explored the agreement between retrospective and prospective reporting of ACEs across a prospectively studied large sample of adolescents. Several categories of information were compared and whilst more objective content such as moving house and height were consistently reported between prospective and retrospective measures, the poorest agreement was found in the more subjective information such as one’s psychological state and childhood adversities such as maternal mental illness and family conflict. The lack of agreement between retrospective and prospective reports of childhood adversities has also been substantiated in more recent research. For example, Baldwin et al.’s (35) systematic review and meta-analysis found that around 52% of participants who prospectively reported adversity in childhood did not go forward to report it retrospectively. Furthermore, 56% of participants who retrospectively disclosed ACEs had not reported this adversity prospectively. Whilst it has been argued the poor agreement between retrospective and prospective approaches to reporting is due to poor validity of the retrospective measures, there may be other reasons for such disagreement. For example, prospective measures may record ACEs before childhood ends and subsequently may not capture adverse events that happened after data collection in the way that retrospective accounts of adversity across the whole of childhood do (35). This current systematic review has subsequently chosen to only include studies using prospective measures of ACEs in line with Baldwin et al.’s (35) recommendation not to compare studies across prospective and retrospective approaches to data collection. This is primarily due to the large discrepancy in populations they identify.

The current review will include prospective, longitudinal research designs that study ACEs instead of retrospective, cross-sectional designs due to their ability to explore temporal sequencing of events (36). Prospective studies offer valuable information about developmental changes, incidence rates of ACEs, and a better understanding of the timing and chronicity of ACEs (37, 38). Furthermore, without the temporal patterning of events, the direction of the relationships cannot not be established (39). This is one of the main reasons why retrospective adult studies of ACEs are not sufficient to understand causal pathways between ACEs and adult outcomes (40). In prospective longitudinal studies, the collection of data through time allows opportunity for confounding variables to be measured and adjusted for at each time point (41). However, it should be acknowledged that causal mechanisms between adverse childhood experiences and later-life poor outcomes such as mental ill-health are difficult to infer- even in longitudinal research (42). This is due to many factors including under-reporting biases (37) and a lack of consideration of unobservable genetic components and family characteristics that contribute to any causal relationships (42). Despite the limitations of prospective longitudinal ACEs studies, prospective measures of ACEs still provide a valuable tool for identifying risk markers for later poor outcomes in adults (43).

Methods/ Design

Aim and Review Questions

The main aim of this systematic review and meta-analysis is to address the gap in the literature by exploring the associations between ACEs and the specific adult mental ill-health outcomes of depression, anxiety, PTSD, psychotic-like experiences, suicidality, and self-harm in prospective longitudinal research globally. The authors are aware of a similar systematic review and meta-analysis that recently explored longitudinal associations between childhood trauma and adult mental disorder (44). However, the current review provides the novel inclusion of grey literature, differing mental health outcomes (unlike McKay et al. (44) who included the outcomes of depression, anxiety, psychotic disorder and bipolar disorder, this study seeks to include anxiety, depression, psychotic-like experiences, PTSD, suicidality, and self-harm) and a lower threshold for the measurement of mental health outcomes. Unlike McKay et al. (44), the current study stipulates the mental health outcomes need not be formal psychiatric diagnoses using established diagnostic criteria for mental disorders in adulthood as such use of these measures is rare in low-and middle-income countries. Furthermore, this review completes an updated and more comprehensive database search (including ProQuest Dissertations and Theses comprising of grey literature), which, in turn, may reduce potential effects of algorithm or publication bias (45). 

Certain questions may not be answered as they remain contingent on enough studies fitting the criteria. We will address the following questions: 

  1. What are the associations between ACEs and depression, anxiety, PTSD, suicidal ideation, self-harm, and psychotic-like experiences in adulthood with a specific interest in the prevalence of research conducted in HICs versus LMICs?
  2. Which geographical locations does the evidence on ACEs stem from?  
  3. Which ACEs have the largest negative associations withadult mental health?  
  4. Is there a cumulative effect of ACEs on mental health outcomes?  
  5. Is the association between ACEs and adult mental ill-health moderated by geographical location of study? 
  6. Is the association between ACEs and adult mental ill-health moderated by peer-reviewed status?  
  7. Is the association between ACEs and adult mental ill-health moderated by study design or analysis? 
  8. Is the association between ACEs and adult mental ill-health dependent on age of onset at the first adversity? 
  9. What is the quality of studies looking at longitudinal associations between ACEs and mental health outcomes?

Inclusion Criteria

Studies must meet the following criteria to be included in the review:

  1. Studies included must be prospective panel or cohort studies and have at least 2 time points.
  2. There must be at least one prospective ACE measured during childhood (< 18 years old) and one mental health outcome measured in adulthood (when subjects are 18 years old or over). The cohort study can include prospective measures of ACEs obtained through official reports of child maltreatment (such as police, court, or child welfare records) that were recorded when the adult participant was a child and are then incorporated into the study through data linkage. 
  3. The sample should be from the general human population but need not be nationally representative. 
  4. The sample does not need to be selected based on mental ill-health or exposure to ACEs. However, the sample can be “clinical” or “special” in the sense that they may be recruited through an outpatient clinic or attend an outpatient clinic (for example, an outpatient clinic for depression or an outpatient HIV clinic). They may also have a diagnosed mental illness or be at a higher risk of experiencing ACEs or poor mental health through, for example, coming from a disadvantaged background. 
  5. The ACE(s) was/were reported by anyone who knew the child (I.e., teacher, parent, caregiver, child themselves) or child welfare records or court records.
  6. The studies do not need to use clinical diagnostic tools for ascertaining mental health conditions but included measurement(s) of mental health outcomes will be validated measures of PTSD, depression, anxiety, suicidal ideation, self-harm, or psychotic-like-experiences. The validation of the tool need not be in the context the study is set in. 
  7. Adult mental health is measured using a continuous or cut-off score approach. Clinical records of adult mental health such as patient records will also be included.
  8. Studies can be peer-reviewed or non-peer-reviewed. 
  9. The study can be conducted in any geographical location.
  10. Findings can be from books, research articles, government documents, conference abstracts, annual reports, dissertations, and theses.
  11. The studies were published from 1990- 2021, but the data may have been collected before 1990. This specific period has been chosen as it aligns with the drafting of the United Nations Convention on the Rights of the Child by the United Nations (46). 
  12. The studies are readily available in English due to limited research resources prohibiting translation.

Exclusion Criteria 

The following criteria will exclude studies from the review:

  1. Cross-sectional studies.
  2. Any study that only includes retrospective measures of ACEs (I.e., the study only includes the reporting of ACEs when the subjects are 18 and over) will be excluded.
  3. Studies in which the only adversity is a physical trauma without a maltreatment/ abuse/household dysfunction or chronic component (e.g., a car crash).
  4. Studies that only use crude measurements of adversity or mental health such as “were you abused as a child” or “have you ever been depressed” without asking about specific symptoms (such as hopelessness for depressed mood) or events (such as being hit for physical abuse). 
  5. Analyses of interventions will be excluded.
  6. Whilst certain “clinical” samples may be included (see inclusion criteria), specific groups that live outside of the general community such as inpatients in psychiatric hospitals or those currently imprisoned will be excluded. 
  7. Research containing non-empirical work as well as qualitative research and non-original data such as commentaries. 
  8. Studies published before 1990.

Information Sources 

For this review, twelve electronic databases will be searched: Embase, PsycINFO, MEDLINE (Ovid version), and Global Health through the Ovid interface. ProQuest will be used to search Public Affairs Information Service (PAIS), Dissertations and Theses, Sociology Database (including Sociological Abstracts and Social Services Abstracts), PTSDpubs (formerly PILOTS) and ASSIA. CINAHL, WHO Global Index Medicus, and WHO Violence Info will also be searched. The search was conducted throughout the month of June, 2021. The search will limited to publication date from 1990 onwards and to human subjects in databases that include this limiter. This specific period has been chosen as it aligns with the drafting of the United Nations Convention on the Rights of the Child (UNCRC) by the United Nations (46). It should be noted that studies published after 1990 that used data from cohorts prior to 1990 will still be eligible if all inclusion criteria are satisfied. This has been decided as the study rationale, research design, research questions, analyses and findings will be interpreted with knowledge from the UNCRC, including a universal definition of when childhood ends and detailed conceptualisations of child protection and maltreatment (56). The English language specification will be manually screened.

To ensure literature saturation, the authors of this review will email authors of known large cohort studies in the relevant field of research to query whether they have any research that is unfinished/ in the process of being published. Search terms can be found in Appendix A and a table of definitions of kay concepts can be found in Appendix B. 

Search Strategy 

Examples of the search strategies can be found in the Appendices C-H. The search strategy will be altered to account for varying syntax, limiters, and expanders in different databases. 

Data Management 

Studies identified by the database searches will be extracted and be uploaded to Covidence (a systematic review management software). Before importing search results into Covidence, database citations and abstracts will be exported into Zotero where they will be de-duplicated. Then, references will be transformed into a RIS file format. Once imported to Covidence, duplicates will be checked for and removed again. 

Selection and Collection Process: Screening and Extraction 

Abstracts and titles will be independently double screened to determine whether the studies meet the inclusion criteria. Next, the remaining papers will be subject to a full-text screen for assessment of inclusion by two reviewers. If necessary, additional information will be sought from the authors of included studies. Any discrepancies in the decision to include a study in the final review will be resolved by team discussion or a third independent reviewer. The final review will include a PRISMA flow diagram documenting the flow of studies throughout the systematic review process. 

The final data extracted from the remaining studies will be stored in a spreadsheet on Covidence. The data extracted by reviewers will include:

Risk of Bias (quality) Assessment 

Study quality (evaluated in review question 9) will be assessed using the Newcastle-Ottawa Scale for cohort studies and case-control studies (NOS) (57). This assessment of quality implements a star system based on three overarching domains of study characteristics: Selection of Study Groups, Comparability of Groups and Ascertainment of Exposure/ Outcome. Typically, a maximum of 8 stars can be awarded (A maximum award of 1 star per item within the domains Selection and Exposure and a maximum award of 2 stars for the domain of Comparability) (58). Two reviewers will independently assess the methodological quality of the included studies and any discrepancies in agreement will be resolved by a third reviewer. However, we will not give each included study an overall quality score or “total star rating”. This is in line with limitations of overall quality scores highlighted in the Cochrane Handbook for Systematic Review of Interventions (59), including a lack of uniformity of quality appraisals across different quality scales being largely attributable to differing conceptualisations of “quality”.

Data synthesis 

A narrative synthesis of included studies will be completed with study information presented in tables and in text. The qualitative discussion will include tabular summaries of the included studies and a discussion of the relationships within and between the studies and will answer review questions 1-4. If enough studies are identified by the database searches and they have enough similarity in design, meta-analyses will be conducted using the “metafor” (60) package in R to answer review questions 5-8. The meta-analysis will implement a random-effects model as it is predicted reported effect sizes will vary as a function of exposure, the measurement tools used, and differences in the populations from which the samples are drawn. Specifically, odds ratios (ORs) will be computed in the meta-analysis and when the study outcome is a continuous measure, Hasselblad and Hedges’ (61) method will be used to convert standardised mean differences to log odds ratios. ORs have been cited as a preferred computation for effect size over risk ratio (RR) when computing meta-analyses with binary data (see 62-64). This is given odds ratios’ symmetry regarding outcome definition and their homogenous, constant nature (65). The minimum number of studies to permit meta-analyses is two studies per mental health outcome. Again, if enough studies permit, meta-regressions will be conducted in which the moderating effects of the age of adversity onset, country, types of adversity, publication status, and duration of follow-up period will be explored.

Iwill be used to assess statistical heterogeneity. It was originally intended to be independent of the number of studies (unlike Cochran’s Q) and has been regularly used in Cochrane reviews (66). However, it should be noted some research suggests Ican still be biased in small meta-analyses (67) 

Meta Bias(es)

The possibility of publication/ dissemination bias in the identified studies will be explored. Publication bias will be examined by first using the “trim and fill” method (68) which will be conducted for each outcome in the meta-analysis. This procedure will help detect and correct any asymmetry in the funnel plots. The Egger bias test will be computed for further examination of funnel plot asymmetry (69).

Discussion

The purpose of this review is to systematically investigate the existence and strength of association between ACEs and adult mental health outcomes in prospective longitudinal studies with a focus on the mental health outcomes anxiety, depression, PTSD, self-harm, suicidal ideation, and psychotic-like experiences.

First, by exploring associations between ACEs and key mental health outcomes, we aim to evaluate the importance of identifying prospectively measured individual ACEs and cumulative ACE scores as risk markers for later poor mental health outcomes in adults (46). Second, by exploring how ACEs relate to different mental health outcomes, we may assist in the future prioritisation of specific preventative mental health interventions in ACE-exposed populations. Third, we will also evaluate whether studies in the field of childhood adversity are affected by publication bias. This will provide further insight as to whether the included published studies are a representative sample of available evidence of the longitudinal associations between ACEs and adult mental health. Lastly, this review may have further implications for ACEs research such as identifying methodological weaknesses and knowledge gaps in literature that can be addressed in future primary studies. For example, we may be able to tell what ACEs and mental health outcomes are under-researched and whether there are regions of the world that are under-represented or missing from the literature.

The authors acknowledge the risk of bias that results from being unable to include studies not readily available in English. Whilst this decision was made due to resource constraints, authors may miss high-quality studies and key data (70). We must also consider limitations associated with the use of official records (e.g., child protective service records or court cases) to obtain information about ACE exposure in prospective ACE studies. Official records are more likely to include only the most severe cases of childhood adversity and are more likely to document ACEs that happened chronically or earlier in life (71). They subsequently miss childhood experiences that may not require official child protective services record such as childhood bullying or parental divorce, but that may still be significantly associated with poor outcomes (72, 73). Furthermore, prospectively measured ACEs may also be vulnerable to under-reporting due to substantiation bias, report bias, investigation bias, and issues relating to stigma and secrecy (7476). Despite the limitations outlined, prospective measures of ACEs provide valuable information about temporal patterning of ACEs and later-life mental ill-health.

In conclusion, studies exploring longitudinal associations between ACEs and adult mental health outcomes have already been synthesised, but this review aims to expand the existing systematic review methodological and analytical approaches. We aim to offer valuable insights about the associations between ACEs and mental health outcomes, their moderators, the quality of longitudinal ACEs studies, specific methodological weaknesses and knowledge gaps that may influence future research directions such as targeting under-researched locations, ACEs, and mental health outcomes.

List Of Abbreviations

ACEs

Adverse Childhood Experiences

ASSIA

Applied Social Sciences Index and Abstracts

CDC

Centre for Disease Control and Prevention

HAC

Health Appraisal Centre

NOS

Newcastle–Ottawa Scale

NSPCC

National Society for the Prevention of Cruelty to Children

OR

Odds Ratio

PAIS

Public Affairs Information Service

PILOTS

Published International Literature on Traumatic Stress

PRISMA-P

Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols

PRISMA

Preferred Reporting Items for Systematic Review and Meta-Analysis

PTSD

Post-traumatic Stress Disorder

RR

Risk Ratio

UNCRC

United Nations Convention on the Rights of the Child

WHO

World Health Organisation

Declarations

Contact

Corresponding author: Christina Thurston ([email protected], Chrystal Macmillan Building, The University of Edinburgh, 15a George Square, Edinburgh, EH8 9LD) 

Ethics approval and consent to participate 

Not applicable 

Consent for Publication 

Not applicable 

Competing Interests 

Not applicable 

Acknowledgements 

Not applicable 

Availability of Data and Materials 

Not applicable 

Author’s contributions 

The main researcher for this review is CT, who produced this protocol with advice from all reviewers. CT, FM, HFO, and AM contributed to the development of the selection criteria and all authors contributed to the decision for the assessment of methodological quality and data extraction criteria. CT developed the search strategy with input from FM and AM. Database searches were conducted by CT who extracted the identified studies to Zotero to de-duplicate papers. The de-duplicated sources were then uploaded to Covidence- a systematic review management software. CT and two additional reviewers will screen, extract, and assess the methodological quality of the selected studies. Data will be synthesised and analysed by CT with support from FM, HFO, and AM. All authors will review the manuscript to suggest changes before approving the final draft for publication. CT is the guarantor of the review. 

Support 

This protocol was completed with support from an ESRC Advanced Quantitative Methods Studentship to Christina Thurston (ES/P000681/1). FM and HFO were supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme [Grant Agreement Number 852787]. 

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