Review of Socioeconomic Status and Psychopathic Traits in a Community Sample of Youth

Cyberspace Interv. 2022 Apr; 28: 100522.

Socioeconomic factors and parents' preferences for cyberspace- and mobile-based parenting interventions to prevent youth mental health bug: A detached choice experiment

Grace Broomfield

^aTurner Institute for Encephalon and Mental Health, Monash University, Clayton, Australia

Scott D. Dark-brown

^bSchool of Psychological Sciences, The University of Newcastle, Callaghan, Australia

Marie B.H. Yap

^aTurner Institute for Brain and Mental Health, Monash Academy, Clayton, Commonwealth of australia

^cMelbourne Schoolhouse of Population and Global Health, University of Melbourne, Melbourne, Commonwealth of australia

Received 2021 Oct 10; Revised 2022 Feb 12; Accepted 2022 Mar five.

Supplementary Materials: Supplementary Fig. ane Screenshot of instructions and definitions provided to participants prior to completing the DCE.

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Supplementary Tables Tables S1 to S5 presenting boosted parameter estimates related to the DCE analyses.

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Abstruse

Background

The positive affect of parenting programs for youth mental wellness is undermined by difficulties engaging parents. Low date disproportionately impacts parents of lower-socioeconomic positions (SEPs). Internet- and mobile-based interventions hold potential for overcoming barriers to enrolment, but additional research is needed to understand how programs can appropriately meet the needs of parents beyond SEPs. Consumer preference methods such as discrete option experiments may be valuable in this endeavour.

Method

A detached choice experiment was used to determine the relative influence of modifiable programme features on parents' intent to enrol. 329 Australian parents of children aged 0–18 repeatedly selected their preferred plan from randomized sets of hypothetical programs in an online survey. Each hypothetical programme was unique, varying beyond 4 programme features: module duration, program platform, user control, and program cost. Cumulative link models were used to predict choices, with education, household income, and community advantage used every bit indicators of SEP.

Results

Overall, parents preferred cheaper programs and briefer modules. Parents' preferences differed based on their socioeconomic challenges. Lower-income parents preferred briefer modules, cheaper programs and application-based programs compared to higher-income parents. Parents with less instruction preferred briefer modules and a predefined module gild. Parents living in areas of less advantage preferred website-based programs, user option of module order, and more expensive programs.

Conclusions

This written report offers program developers evidence-based strategies for tailoring net- and mobile-based parenting interventions to increase lower-SEP parent enrolment. Findings likewise highlight the importance of considering parents' socioeconomic challenges to ensure programs practice not perpetuate existing mental health inequalities, as "one-size-fits-all" approaches are probable insufficient for reaching lower-SEP parents.

Abbreviations: DCE, discrete selection experiments; IMI, internet- or mobile-based intervention; SEP, socioeconomic position

Keywords: Youth mental health, Parenting, Prevention, eHealth, Preferences, Discrete choice experiment

Parenting programs tin be divers as any intervention delivered to a parent to increase parental knowledge, skills, and confidence, with the aim of reducing the prevalence of mental health bug in children and adolescents (Sanders et al., 2008). Despite meta-analyses (Johnson et al., 2018; Furlong et al., 2012; Kaminski et al., 2008; Yap et al., 2016) indicating parenting programs tin significantly reduce child mental health symptoms (d = 0.12–0.59), the positive affect of these programs is undermined by difficulties engaging parents (Finan et al., 2018; Hansen et al., 2019). Studies indicate that simply 10% to 31% of eligible parents enrol to participate in confront-to-confront parenting programs (Garvey et al., 2006; Heinrichs et al., 2005; Thornton and Calam, 2011).

Families experiencing greater socioeconomic challenges are likely to find particular do good in parenting programs aimed at the prevention of youth mental wellness problems, due to the increased risk of mental health issues amongst young people in lower-socioeconomic position (SEP) families (Lawrence et al., 2016; Reiss et al., 2019). SEP is defined equally the relative positions an individual or family concur inside a social structure based on their access to limited and valued resources (Krieger et al., 1997; Lynch and Kaplan, 2000). SEP is understood to be an aggregate concept, which includes both resource-based and prestige-based weather (Krieger et al., 1997). Consequently, a wide assortment of measures have been used in health-related literature to capture this multi-dimensional construct. Common indicators of SEP include measures at an individual level (east.chiliad. education; Richardson et al., 2010) and household level (due east.g. household income; Zimmerman, 2005), or contextual measures at a customs level (due east.g. neighbourhood disadvantage; Farahmand et al., 2011).

Despite the benefit of these programs for lower-SEP families, parents of lower-SEPs are less engaged in confront-to-face parenting programs for youth mental health, compared to higher-SEP parents (Chacko et al., 2016; Lundahl et al., 2006; Reyno and McGrath, 2006). Engagement is ofttimes conceptualised beyond initial date (due east.g. intent to enrol and enrolment) and ongoing appointment (due east.g. retention; Finan et al., 2018), with lower-SEP parents less engaged beyond both stages of engagement. Pregnant associations between SEP and retention have been found in two comprehensive reviews of RCTs of contiguous parenting programs aimed at the prevention of youth mental wellness problems (Chacko et al., 2016; Reyno and McGrath, 2006). These reviews found that parents with less educational activity and less income were significantly more likely to drop out of these face-to-face parenting programs, compared to higher-SEP parents. 1 review (Finan et al., 2018) constitute no consequent clan between SEP and engagement, still it was suggested this finding may have been impacted past the range of predictors used across studies. Of particular interest in the present study, SEP has likewise been found to impact initial engagement. A pregnant moderate issue of SEP on enrolment was institute in a community based parenting intervention (Eisner and Meidert, 2011), with only 30.5% of parents with lower-SEP enrolling in the program, compared to 53.1% of those above-median SEP.

The internet has been identified as an alternative means of intervention delivery that may increment the attain of parenting programs among lower-SEP populations. Meta-analyses indicate parenting internet- and mobile-based interventions (IMIs) can successfully reduce externalizing and internalizing difficulties in young people (Nieuwboer et al., 2013; Spencer et al., 2020), with no pregnant difference in intervention furnishings found betwixt online and face-to-face up parenting programs (Florean et al., 2020). Examples of preventive parenting IMIs targeting youth mental wellness include Cool Lilliputian Kids Online (Morgan et al., 2016; Morgan et al., 2017), ezParent (Breitenstein et al., 2016; Breitenstein et al., 2019), Triple P Online (Baker et al., 2017; Sanders, 1999; Sanders et al., 2003), Parenting Resilient Kids (Fernando et al., 2018; Sim et al., 2020), ParentWorks (Piotrowska et al., 2020), and Partners in Parenting (Cardamone-Breen et al., 2018; Yap et al., 2018; Yap et al., 2019).

Research indicates lower-SEP parents benefit from preventive parenting IMIs (Harris et al., 2020; Nieuwboer et al., 2013), and observe them highly satisfactory (Baggett et al., 2010), withal remained underserved past these programs (Cardamone-Breen et al., 2018; Fossum et al., 2018; Morgan et al., 2017). Preference data suggests parents of lower-SEPs favour media-based parenting information (Metzler et al., 2012), with the affordability, convenience, and self-directed nature of IMIs highly appealing to this population (Baggett et al., 2010; Fleming et al., 2015). However, they also experience unique barriers to initial date, with more than limited access to internet-enabled devices (Willis and Tranter, 2006) and lower digital literacy (Rothbaum et al., 2008). Currently in that location are no meta-analyses bachelor investigating lower-SEP parents' enrolment in IMIs aimed at the prevention of youth mental health difficulties, however trials indicate that lower-SEP parents face greater barriers to engaging in these digital programs, with lower enrolment rates than their higher-SEP peers. For example, an evaluation of the Strongest Families Smart Website intervention institute that nonparticipation was significantly associated with less parental education afterward controlling for other parental factors (Fossum et al., 2018). This is consistent with many evaluations of preventive parenting IMIs noting difficulties enrolling parents with varying socioeconomic challenges (e.g. Fleming et al., 2021; Morgan et al., 2016; Yap et al., 2017). Additionally, a systematic literature review of appointment enhancement strategies for underserved parent populations in engineering science-assisted parenting programs found minimal effective and practical strategies bachelor for addressing the under-engagement of lower-SEP parents in parenting IMIs for youth mental wellness (Hansen et al., 2019).

Ane challenge in ensuring preventive parenting IMIs accomplish parents across the socioeconomic spectrum is a lack of understanding regarding how dissimilar socioeconomic factors touch on parent enrolment. Despite lower-SEP parents often beingness treated as a homogenous group inside the literature (Mendez et al., 2009), research indicates that parents' program preferences probable vary based on the specific social and economic challenges they face (Broomfield et al., 2021). These differences are not well understood as lower-SEP families are underrepresented in nigh samples used to develop and evaluate parenting programs for youth mental health (McGoron and Ondersma, 2015). Therefore, to adequately reach parents across the socioeconomic spectrum, additional enquiry is needed to understand the ways in which lower-SEP and higher-SEP parents' preferences differ and how this may be impacted past parents' sociodemographic characteristics (Hansen et al., 2019).

Detached Choice Experiments (DCEs) have been suggested equally a particularly powerful method for eliciting preferences and exploring the relative importance of program features for different parent populations (Chacko et al., 2016; Hansen et al., 2019). This arroyo has been used to collect stated preference data (i.due east. what someone says they will practice) in the absence of revealed preference data (i.eastward. what someone really does) to model the handling preferences of parents with children experiencing mental health bug (Cunningham et al., 2013; Cunningham et al., 2008; Fegert et al., 2011). DCEs crave participants to make a serial of choices betwixt 2 or more hypothetical scenarios, goods, or services (Lancsar and Louviere, 2008; Louviere et al., 2000). They have been shown to be associated with actual behavior (Caruso et al., 2009), mimic real-earth controlling (Ryan and Gerard, 2003) and reduce social desirability biases (Phillips et al., 2002). DCEs may be peculiarly useful in obtaining preference data from "difficult-to-reach" populations, such as lower-SEP parents, due to their ability to obtain parents' preferences without requiring prior contact with a service or program (Chacko et al., 2016; Hansen et al., 2019). Withal, no study to date has used a DCE design to explore lower-SEP parents' preferences for preventive parenting IMIs for youth mental health.

i. The present study

Due to the lack of evidence-based, practical strategies institute to be constructive in engaging lower-SEP parents in preventive parenting IMIs for youth mental health (Hansen et al., 2019), the nowadays study sought to use a DCE to determine the relative influence of modifiable program features on parents' intent to enrol in preventive parenting IMIs and investigate how preferences vary across the socioeconomic spectrum. The design of the present DCE was informed past a preliminary qualitative investigation of lower-SEP parents' preferences for preventive parenting IMIs (Broomfield et al., 2021). The qualitative study used thematic assay of interview transcripts to identify 23 modifiable program features of import to lower-SEP parents' engagement. Therefore, the nowadays study extends upon Broomfield et al.'south (2021) findings by investigating the relative importance of four of the most salient and plausible program features: 1) module duration; 2) plan platform; 3) user command of module order; and 4) program price. This DCE will offer program developers aiming to increase the uptake of their preventive parenting IMIs with generalisable findings regarding programme features most likely to increase the enrolment of parents across the socioeconomic spectrum.

Inquiry evidence also suggests that parents' preferences for features may vary based on parents' specific socioeconomic experiences (Broomfield et al., 2021; Lakind and Atkins, 2018; Mendez et al., 2009). Therefore, the present study will include participants across the socioeconomic spectrum and utilise several measures of socioeconomic advantage to explore how parents' program preferences differ based on the corporeality and type of advantage or disadvantage they experience. In line with social inequality literature, both resource-based (household income) and prestige-based (education) measures of SEP will exist used, as well every bit a contextual measure (community disadvantage), which is ofttimes used in health literature to investigate how admission to local services and resources can impact service apply (Shavers, 2007). Such an exploration of the style different socioeconomic factors influence parents' program preferences may facilitate the tailoring of programs to optimise enrolment across socioeconomic conditions.

Information technology is hypothesised that all four program attributes will significantly predict parents' pick of program, with parents preferring briefer modules, awarding-based programs, greater user control of module guild, and cheaper programs. Based on findings from Broomfield et al. (2021) equally well as previous literature highlighting barriers nowadays for parents experiencing different types of social and economic challenges (Mendez et al., 2009; Rothbaum et al., 2008; Willis and Tranter, 2006), it is hypothesised that parents' preferences for plan features will differ for higher- and lower-SEP parents, notwithstanding the human relationship between programme features and SEP volition also vary based on SEP indices. In particular, it is predicted that parents' preference for program cost will significantly differ based on household income, with lower-income parents having a stronger preference for cheaper programs. Information technology is besides predicted that parents' preference for module duration will significantly differ based on their level of educational activity, with parents with less education having a stronger preference for briefer modules. Parents' preference for program platform will significantly differ based on community advantage, with parents living in lower-advantage areas having a stronger preference for application-based programs.

2. Methods

two.1. Development of discrete choice experiment

The design of the DCE was informed by a review of the literature (Hansen et al., 2019) and 16 semi-structured interviews with Australian parents of children aged 0 to 18 years (Broomfield et al., 2021). Through thematic analysis of interview transcripts, 23 modifiable program features were identified equally important to programme option for lower-SEP parents. A framework established by Helter and Boehler (2016) through the systematic review of attribute evolution methods used in 86 health-related DCEs was employed to reduce these 23 modifiable program features to an appropriate and viable design. The framework provided seven criteria for attribute selection: saliency, plausibility, adequacy of being traded, completeness, far from latent construct, non-authorisation, and manipulability. Consultations with two experts, a parenting and youth mental health researcher and a preventive parenting IMI developer, guided the appropriate awarding of the selection criteria, with discussions leading to the exclusion of 19 plan features. This resulted in four plan features, also known as attributes, beingness selected to be used in the nowadays DCE. Tabular array 1 indicates the iv attributes used in this study. This table also presents each attribute'southward possible options, referred to equally levels. Each hypothetical program presented in the DCE survey is called a choice selection and includes one level from each of the four attributes. Two choice options are presented next to each other and participants have to select their preferred choice option. An example of a choice prepare of two choice options is shown in Fig. 1. After selecting and drafting the initial version of the survey, farther consultation occurred with experts to simplify the language used throughout the DCE, with this resulting in refinement to the wording of the aspect levels and additional information in the introductory material presented to participants to explain the task (see Supplementary Fig. S1). Four parents were so invited to pilot the survey, providing written feedback on the content and format of the survey.

Table 1

Attributes and Levels Included in the DCE Design.

Attribute name	Attribute description	Attribute levels
Module duration	How long it takes to complete each session or module.	15 min
		25 min
		45 min
Program platform	The platform through which you access the program.	Website
Program platform	The platform through which you access the program.	Downloadable application
User control of module club	The user's power to select the order in which they complete the modules.	Predefined order
User control of module club		User's selection of guild
Program price	The corporeality which has to be paid to admission the program.	AU$20
		AU$thirty
		AU$l

An example choice set.

Notation. Two possible choice options are presented, with each comprising of 4 attributes: one) module duration; 2) program platform; 3) user control of module order; and 4) programme cost. The level for each attribute varies across the choice options. For each option ready the participant must select which program they prefer out of the ii options, with this repeated by each participant 25 times.

The final version of the survey was programmed and administered by Qualtrics (Qualtrics, 2020). The DCE survey required participants to cull between pairs of hypothetical parenting programs for youth mental wellness. An example of one possible choice set up is shown in Fig. 1. The combinations of aspect levels shown across the choice sets were designed experimentally, so statistical methods could exist used to determine parents' relative preferences for changes in attribute levels based on their choices. A binary discrete choice design was chosen, rather than a multinomial blueprint, allowing for clearer application and interpretation (Lancsar and Louviere, 2008). Additionally, a total factorial pattern was utilised in this report, whereby all possible combinations of attributes and their levels are included in the experimental pattern, resulting in 630 choice sets. This allowed for the estimation of both primary effects and interaction furnishings (Lancsar and Louviere, 2008), without the additional assumptions required of efficient experimental designs (Johnson et al., 2013). No "opt-out" pick was provided in this pattern and the left/right presentation of programs was randomized. Due to the time and cognitive load required of participants to consummate DCE surveys, each participant received a random selection of 25 of the possible 630 selection sets, with this number deemed acceptable during piloting.

2.2. Recruitment

Australian parents or guardians of children aged 0 to 18 years were recruited between March 2020 and March 2021 through digital advertisements posted in parenting and community social media pages or alternatively disseminated through one of two survey console platforms, Qualtrics Panels or Prolific Academic (run into Fig. 2). Inclusion criteria were: 1) alive in Australia; 2) aged xviii years or older; 3) parent or guardian of a child anile 0 to 18 years; and four) able to read and understand English. A purposive sampling arroyo was used whereby parents from lower-SEP areas and with lower-household incomes received a greater proportion of digital advertisement materials through targeted Facebook advertizement campaigns and were targeted during Prolific Academic and Qualtrics Panels recruitment to facilitate acceptable representation of these parents. Prolific Academic and Qualtrics Survey Panel were chosen to back up recruitment due to evidence supporting the validity of data obtained from these platforms (Goodman and Paolacci, 2017; Peer et al., 2017). Thorough data cleaning processes were also used to further back up the quality of the data, which included replacing responses that failed quality checks such as non-differentiation in choices, duplications, response times less than one-half the median, and suspicious open up-text responses.

Flowchart of participants recruited through the three recruitment avenues.

The exploratory nature of the present report meant initial parameter values required for minimum sample size requirements (de Bekker-Grob et al., 2015) were uncertain prior to data drove. To plan sampling requirements, expected parameter values were therefore determined by modeling data obtained from the commencement 30 participants. This revealed that with an ⍺ error probability of 0.05, a minimum of 3601 observations, or northward = 144 every bit each participant received 25 choice sets, was required to obtain statistical power at 0.80 level (Cohen, 1992) for main effects analyses.

two.3. Participants

329 participants completed the DCE. The mean age of the sample was 39 years (SD = eight.77), 67.viii% were female and 31.6% were male person. Most participants were married or in a de facto partnership (77.5%) and were employed in either full-time (44.4%) or part-time (22.5%) work. Approximately half the sample (54.four%) were living in a household with an annual taxable income of less than $80,000. Most parents (53.8%) and children (71.4%) had not experienced a mental wellness difficulty, and 16.5% of the sample had previously participated in a parenting program for youth mental health. Additional sociodemographic characteristics are shown in Table 2.

Table 2

Sociodemographic Characteristics of Participants (N = 329).

Variables	Participant characteristics
Parent historic period in years; Mean (SD)	39 (8.77)
Parent gender; n (%)
Female person	223 (67.8)
Male	104 (31.6)
Not-binary	2 (0.6)
Born in Australia; n (%)^a
Yep	253 (76.nine)
No	75 (22.viii)
Human relationship status; n (%)
Married or de facto partnership	255 (77.v)
Separated or divorced	37 (11.2)
Single	33 (10.0)
Widowed	4 (1.2)
Employment status; n (%)
Total-time employment	146 (44.4)
Part-fourth dimension employment	74 (22.five)
Domicile duties	69 (21.0)
Coincidental or freelance work	25 (7.half-dozen)
Unemployed	15 (4.6)
Highest instruction qualification; due north (%)
Senior Secondary Certificate of Pedagogy or below	59 (17.9)
Postsecondary vocational grooming	107 (32.five)
Undergraduate or graduate degree	122 (37.i)
Postgraduate caste	41 (12.5)
Annual taxable household income (AU$); northward (%)
<$xl,000	56 (17.0)
$40,000–$79,999	123 (37.iv)
$lxxx,000–$119,999	67 (20.4)
$120,000–$159,999	40 (12.2)
≥$160,000	43 (thirteen.i)
Postcode rurality; n (%)^a, ^b
Major Cities	252 (77.three)
Inner Regional	49 (15.0)
Outer Regional	24 (seven.4)
Remote	1 (0.iii)
Community disadvantage; n (%)^a, ^c
High	83 (25.5)
Moderate	140 (43.1)
Low	102 (31.iv)
Parent mental health difficulties; n (%)
Yes	152 (46.2)
No	177 (53.8)
Child mental health difficulties; northward (%)
Yes	94 (28.6)
No	235 (71.four)
Prior use of parenting program for youth mental health; n (%)^a
Yes	54 (sixteen.5)
Contiguous	38 (11.5)
Net- or mobile-based intervention	16 (4.9)
No	274 (83.5)
Willingness to engage in a future internet- or mobile-based parenting program; northward (%)^a
Yeah	263 (79.9)
No	64 (nineteen.half dozen)

ii.4. Process

Digital advertisements were posted on social media sites and survey panel platforms, which included key written report information too every bit an URL which took participants to the online survey hosted on Qualtrics. Interested parents were asked to read boosted participant information prior to consenting to participate. Parents were then screened for eligibility using four pre-survey questions to ensure they met the iv inclusion criteria. If eligible, they continued to a series of questions which asked about their sociodemographic features and previous participation in parenting programs. Participants then proceeded to the DCE component of the survey. They were presented with a choice vignette, which explained the task and so a random option of 25 choice sets. For each choice set up participants were asked to cull their preferred programme out of two possible program options. The average completion fourth dimension for participants was 11.85 min. At the conclusion of the survey parents were reimbursed for their time, with reimbursement differing beyond recruitment streams. Participants recruited through Prolific Academic (18.nine%) were reimbursed at the recommended rate of AU$14.42 per hour, Qualtrics participants' (65.3%) reimbursement varied between AU$iii.72 and AU$seven.fifty, and those recruited through community (18.ix%) were offered entry into a raffle for 1 of 4 AU$100 grocery vouchers. Participants did not participate in any farther research activities.

2.4.1. Outcome measures

2.4.one.1. Detached choice experiment

The DCE consists of four attributes, with two or three levels for each attribute as detailed in Tabular array i. The DCE was presented to parents through an online survey. They were first provided a brief description of the task, with key terms explained, and a short vignette. This was followed by 25 choice sets, randomly selected from the 630 available pick sets. Parents were asked to repeatedly select their preferred programme.

2.4.ane.two. Sociodemographic questions

Participants self-reported age, gender, number of children, age of children, postcode, instruction, employment condition, relationship condition, land of birth, and annual household income. They also cocky-reported whether they or their child had ever been diagnosed with a mental health difficulty, whether they had ever used a face-to-confront or internet-based parenting program, and whether they would consider using an internet-based parenting program in the futurity. Three indices of SEP were used in the main analyses. Household income was measured based on parents' self-reported combined annual taxable household income across ten levels. Community reward was measured using the Socio-Economic Indexes for Areas (SEIFA) Index of Relative Socio-Economic Disadvantage (IRSD; Australian Agency of Statistics, 2016), which provided 10 levels of community disadvantage based on parents' postcodes. Parent education was measured using parents' self-reported highest level of education.

ii.iv.ii. Ethics approval

Monash University'southward Human being Research Ethics Committee (Project ID 23122) granted full ideals blessing for this study (03/03/2020).

2.4.iii. Statistical analysis

Data were analysed in R version 3.5.iii (R Core Team, 2020) using packages tidyverse_1.three.0 and ordinal_2019.12–10. Initial analyses included summary statistics of sociodemographic variables and frequency tables for choices. Inferences regarding the influence of different program features on program choice were examined using a type of logistic regression known as cumulative link models (CLM), to predict choices. The dependent variable was binary, with 1 and 2 representing whether the participant chose choice 1 or 2. Independent variables were the attribute levels listed in Table one. Two attributes, module length and programme cost were continuous. 2 attributes, program platform and user control, were dummy coded with the reference levels of 'awarding-based' and 'user selection of module order', respectively. Symmetric utility models were used, whereby the difference between aspect levels for option 1 and pick 2 were used as predictors. Due to the number of tests, a type I mistake rate of blastoff = 0.002, rather than 0.05 was adopted throughout, which resulted in a family unit wise fault charge per unit of 6%. A probit link function was used, respective to Gaussian assumption for a random utility model of preferences. The relative influence of different attributes on choice was quantified by the standard coefficient estimates in these models.

A full model with all two-, iii- and iv-way interactions was reviewed (Supplementary Table S1), however given the complexity of the total model with four main furnishings and eleven interaction furnishings, a restricted model was examined which allowed for higher statistical efficiency (Supplementary Table S2). Supporting our choice, the Akaike information benchmark (AIC) for this restricted model was marginally better than the AIC for the full model. The coefficients from the CLM were reviewed, with the preference weights indicating the effect that each aspect level had on program selection relative to the reference level. To investigate how dissimilar SEP variables influenced participants' preferences, interaction terms were then added to this model using iii indices of SEP. Household income and community advantage were treated as a continuous variables. Parent education was treated equally an ordered gene with four levels. Levels were ordered based on the Australian Qualifications Framework (Australian Qualifications Framework Advisory Lath, 2007) and were: 1) senior secondary document of education or beneath; 2) postsecondary vocational training; iii) undergraduate or graduate caste; and 4) postgraduate degree. The second level was used every bit the reference level to back up clarity in visualisation and estimation. To ensure there were no substantial differences in preferences across the samples drawn from unlike recruitment sources, exploratory analyses were conducted to investigate the human relationship between recruitment source and programme choice. No significant interactions were found and therefore this variable was not included in the primary analyses (Supplementary Tabular array S3).

three. Results

The following results sections will outline: 1) parents' overall preferences for program features; and ii) interactions betwixt program features and indices of SEP, including household income, community advantage and parent education, in predicting parents' preferences for program features.

3.1. The influence of program features on parents' preferences

The CLM model found that two of the four attributes significantly predicted parents' program choice. Choices were about strongly influenced by program cost (z = −11.79, p < .001), followed by module duration (z = −3.44, p < .001). User control (z = −0.67, p = .502) and program platform (z = 0.28, p = .777) did not significantly predict program choice. Every bit shown in Fig. 3, preferences for the two pregnant attributes were in the expected direction. The statistically-meaning negative preference weights for module elapsing and programme cost indicate that parents preferred programs that were cheaper and had briefer modules. The positive preference weight for plan platform, indicates a weak, not-significant preference for a website-based programme, and the negative preference weight for user control indicates a weak, non-pregnant preference for user choice of module order.

Preference weights for the primary effects and the interaction furnishings from the CLM

Note. The lowest level for each SEP variable was used to illustrate the interactions betwixt program features and SEP. Therefore, low-income refers to those with a household income of AU$xx,000 or less, low-advantage refers to those living in a postcode with an IRSD rating of one indicating loftier community disadvantage, and low-education refers to those with no postsecondary pedagogy. Negative scores indicate lower preference for the level listed in the figure, whereas positive scores signal greater preference for the level listed. *p < .002.

iii.two. Lower-SEP parents' preferences for plan features beyond SEP indices

Interaction effects between attributes and SEP indices in predicting parents' preferences for plan features were assessed by inclusion of interactions between the principal furnishings and the SEP indices, with associated tests of the statistical reliability of the covariates' coefficients. Parameter estimates for interaction furnishings between program features and SEP variables are reported below, with additional details provided in Supplementary Table S5.

The CLM model found household income did not have a pregnant chief issue on program pick (z = −one.82, p = .069), however it had a significant interaction with iii of the four main furnishings: plan platform (z = iv.98, p < .001), program toll (z = 4.21, p < .001), and module duration (z = iii.13, p = .002). The interaction between user control and household income was non-significant (z = −2.63, p = .009). Equally income decreased, preference for an application-based program, lower program cost, and briefer modules increased.

Community advantage had a significant main effect on program choice (z = 3.22, p = .001) and likewise had a meaning interaction with three of the programme attributes: user command (z = 5.64, p < .001), program cost (z = −3.72, p < .001), and program platform (z = −iii.27, p = .001). The interaction between module elapsing and community reward was non-significant (z = −1.24, p = .214). As community advantage decreased, preference for user choice of module order, higher program cost, and a website-based program increased.

Parent educational activity levels did not accept a significant main upshot on program pick (p = .243–0.556). Ii of the four attributes had a significant interaction. As parents' education increased from no postsecondary education to vocational training in that location was a significant interaction with both module duration (z = three.67, p < .001) and user control (z = −3.38, p = .001). Parents with no formal postsecondary education preferred briefer modules and predefined module guild. No other interactions between education and programme features were significant.

4. Discussion

This written report is the first to apply a DCE to explore lower-SEP parents' preferences for a preventive parenting IMI aimed at the prevention of youth mental health difficulties. To increase the reach of preventive parenting IMIs for youth mental health, we sought to determine the relative influence of four modifiable program features on parents' intent to enrol in a preventive parenting IMI and investigate how dissimilar socioeconomic factors influence parents' program preferences. Unexpectedly, only ii of the 4 program features significantly predicted parents' choice of program, with parents preferring cheaper programs and briefer modules, with this consistent for college- and lower-SEP parents. Predicted interactions between SEP and program features were meaning, with lower-income parents preferring cheaper programs and parents with no formal postsecondary education preferring briefer programs. Whilst the interaction betwixt community advantage and programme platform was significant, this interaction was non in the anticipated direction. The main findings and their contribution to the literature are discussed farther below.

Of the four available program features, the two associated with affordability and convenience were most strongly preferred across the sample. This is consistent with several studies indicating that two primary barriers to parental engagement in parenting programs are financial concerns and competing demands (Duppong-Hurley et al., 2016; Morawska et al., 2011; Rostad et al., 2018). Qualitative research has suggested that practical factors such equally these are more readily identified past parents equally barriers to their engagement in parenting programs, compared to psychological barriers such as stigma, help-seeking behavior, and subjective norms (Duppong-Hurley et al., 2016).

Equally predicted, the preference for affordable and convenient programs was fifty-fifty stronger amidst lower-income parents. Lower-income parents' prioritisation of program features that optimised affordability and convenience is unsurprising equally the literature has consistently highlighted practical barriers such as limited fourth dimension and financial resources as barriers to lower-income parents' appointment in both in-person parenting interventions (Gross et al., 2001; Keller and McDade, 2000) and IMIs (Brager et al., 2021). The nowadays research extends upon these previous studies by providing quantitative trading between attributes. This written report shows that optimisation of these two features impacts lower-income parents' intent to enrol beyond other programme features such as the type of program platform or the amount of flexibility provided to users in choosing the lodge of module completion, with even small increases in cost undermining parent enrolment. The DCE likewise showed that although the preference was less stiff, higher-income parents also preferred briefer modules and cheaper programs. This preference for cheaper and briefer modules likewise persisted despite the intentional choice of the researchers to apply aspect levels that were realistic but too non excessive to reduce the likelihood that these features would dominate parent preferences. Therefore, program developers can now accept greater conviction that prioritising these two features volition expand the reach of preventive parenting IMIs to parents across the socioeconomic spectrum.

Parents with no postsecondary education also had a stronger preference for brief modules, with this consequent with literature indicating that parents with less pedagogy desire simple, curtailed content (Chavira et al., 2017). Parents with less education prioritised fifteen- and 25-min modules over 45-min modules, with preferences similar across the 2 briefer levels. This supports qualitative evidence (Broomfield et al., 2021) suggesting that although convenience is highly sought after among this population, lower-SEP parents still recognise that adequate time is required to benefit from a parenting intervention. These parents therefore want programs that are both convenient and effective. User command of module order was also important to parents with less education, with parents with no formal postsecondary education preferring a predetermined module order. Mayhap, due to parents with less instruction having less digital literacy (Hale et al., 2010), a more than directive arroyo to programme navigation feels less intimidating for these parents (Van Deursen and Van Dijk, 2014).

The association between customs advantage and programme platform preference was not in the predicted direction. Parents living in disadvantaged areas, particularly regional and rural areas where internet admission is more express (Alam et al., 2019), accept expressed a preference for downloadable content through smartphones and tablet devices (Broomfield et al., 2021), however in the nowadays written report parents living in areas of greater disadvantage appeared to prefer website-based programs. The interactions between community reward and the remaining features were also unexpected and may be better explained by parents' engagement in the DCE. Despite efforts to minimise not-engaged responding, including removing participants with strong left/right bias, long response runs and fast completion times, it is possible that in that location was a greater rate of nondifferentiation among remaining participants from low reward areas. Inclusion of additional attention checks could back up future studies to investigate if such findings are related to appointment. Furthermore, inquiry has shown that expanse-based indicators of socioeconomic disadvantage, such as SEIFA, are poor indicators of individual-level SEP, peculiarly in Australian samples (Lim and Gemici, 2011). As such, these findings should be interpreted with caution every bit further inquiry is required.

Based on findings from the present report, some IMIs for youth mental health might expect to have greater success at reaching lower-SEP parents, due to their inclusion of preferred features. For example, ParentWorks (Piotrowska et al., 2020), Parenting Resilient Kids (Fernando et al., 2018; Sim et al., 2020) and Partners in Parenting (Cardamone-Breen et al., 2018; Yap et al., 2018; Yap et al., 2019) are all gratuitous IMIs, with modules varying between 15 and 30 min. Yet, despite incorporating these desired features, these IMIs still faced difficulties enrolling lower-SEP parents, with greater participation among college-educated and higher-income parents (Cardamone-Breen et al., 2018; Piotrowska et al., 2020; Sim et al., 2020). Depression enrolment of lower-SEP parents in programs with these desired features suggests that further consideration of lower-SEP parents' needs in the design and promotion of IMIs for youth mental health is warranted. Implications from this unexpected design of findings include increasing the customisability of programs and tailoring promotional materials to improve reach lower-SEP parents, with these suggestions expanded upon in the implications department below.

iv.1. Written report strengths and limitations

A major strength of this study is the rigour of the DCE methodology and its novel application in this field. The employ of qualitative data to inform the development of attributes and levels has been shown to better the external validity of DCE choices (Coast et al., 2012). Therefore, the nowadays DCE likely yielded results with strong external validity due to attribute evolution existence informed by qualitative research (Broomfield et al., 2021). Additionally, despite this exploratory study being the first to utilize a DCE to investigate parents' preferences for preventive parenting IMIs, it included a sample with varying levels of socioeconomic reward to explore preferences across SEPs, also every bit multiple measures of SEP to explore heterogeneity among lower-SEP parents. These choices bolster the likelihood that findings can be translated into engaging, appealing programs for parents beyond the socioeconomic spectrum.

Due to the exploratory nature of this study a conservative approach to statistical power was required and therefore only four attributes were included in the DCE design. These attributes were included based on a strict selection process (Helter and Boehler, 2016), however other program features likely too influence parents' intent to enrol. For example, studies accept plant that therapist contact may be peculiarly important to lower-SEP families (Harris et al., 2020; Jones et al., 2013). Therefore, future studies should utilise larger DCE designs with more attributes and levels to gain a more comprehensive view of parents' preferences for preventive parenting IMIs for youth mental health. Furthermore, due to sample size and design considerations, interaction effects between attributes and boosted socio-demographic variables could not be examined, with this also warranting farther attending in future studies.

A farther methodological limitation of this study that may undermine the generalisability of findings, is the exclusion of an opt-out alternative in the DCE design. Providing an opt-out or no-option option in DCEs (Campbell and Erdem, 2019), or alternatively a dual-response design (Veldwijk et al., 2014), can improve the external validity of findings in different research contexts, however the conservative statistical arroyo required of this exploratory report did not back up the inclusion of such options in the nowadays design. Future studies should consider the inclusion of a no-selection or dual-response options in DCEs investigating preferences for prevention programs.

iv.2. Implications for inquiry, policy, and do

Findings from this study offer plan developers several recommendations for increasing the reach of preventive parenting IMIs aimed at the prevention of youth mental health difficulties. Based on parents' preferences, optimising the affordability and convenience of programs will probable atomic number 82 to the greatest increment in uptake. This report highlighted the role plan price and module length can play in optimising such qualities, yet other features could too exist considered, such as payment plans or ongoing access to content. Features such equally application-based programs and predefined module order volition probable also increase the achieve of these programs amid parents with limited household income and education (McCurdy and Daro, 2001).

The heterogeneity in program preferences observed in this written report, and previous literature (e.g. Mendez et al., 2009), may contribute to the ongoing difficulties in reaching lower-SEP parents with universal prevention programs if non addressed (Cardamone-Breen et al., 2018; Piotrowska et al., 2020; Sim et al., 2020). The present report highlights that whilst certain features are desired past most parents (i.e. low price and cursory modules), other features are merely preferred by certain lower-SEP parents (i.eastward. application-based programs for lower-income parents, and predefined module order for parents with less education). As such, a "ane-size-fits-all" program may not appeal to all lower-SEP parents. Instead, IMIs may benefit from incorporating greater customisability into their designs to allow parents to tailor plan features based on their individual preferences. Additionally, the heterogeneity in parent preferences found in this study highlight the importance of adequate representation of parents with varying social and economic experiences when developing and evaluating preventive parenting programs (Chacko et al., 2016).

Comprehensive, multi-staged strategies may be needed to overcome lower-SEP parents' barriers to engagement. A systematic review by Hansen et al. (2019) found that IMIs that utilised multiple appointment enhancement strategies to target underserved populations were more than effective at increasing engagement with these populations. As such, ensuring programs are user-friendly and affordable may non result in increased enrolment by lower-SEP parents unless additional steps are also taken to attain these parents. Strategies could include targeted recruitment campaigns, co-designed features and ensuring promotional materials highlight desired features (Hansen et al., 2019). A recent conceptual framework of initial engagement in preventive parenting programs (Finan and Yap, 2021) highlights that a socio-ecological lens may further support parental enrolment, whereby factors across several levels are targeted. Therefore, broader wellness promotion campaigns to support the awareness and perceived value of preventive parenting IMIs amongst this population may as well support improved reach.

Further empirical bear witness is needed to support the employ of plan features identified as of import in the present written report. Whilst this study provides insight into parents' stated preferences, the feasibility and acceptability of these modifiable program features needs to be farther assessed systematically in efficacy and effectiveness trials. This boosted artery of enquiry will assist determine if altering programs based on the stated preferences obtained in this study will successfully expand the reach of preventive parenting IMIs to parents across the socioeconomic spectrum.

Finally, this study demonstrates the DCE equally a feasible method for eliciting preference data from difficult-to-accomplish populations. Due to lower-SEP parents being consistently under-represented in parenting inquiry (Eisner and Meidert, 2011; Fossum et al., 2018), studies accept reported difficulty in determining their plan preferences and usage patterns (Chacko et al., 2016; Finan et al., 2018). However, this study effectively used a novel DCE blueprint to gather stated preferences from this underserved population. Similar research designs may be used with other under-represented populations to facilitate appropriate and equitable interventions for underserved groups, ultimately reducing existing mental wellness inequalities.

iv.three. Conclusion

The present written report provides valuable insights into the relative influence of plan features on parents' intent to enrol in preventive parenting IMIs for youth mental health. It besides highlights the influence of different socioeconomic factors on parent preferences. Results point that making programs cheaper and modules shorter volition likely take the greatest touch on overall parental enrolment. However, parents' unique preferences associated with their education level, household income, and community advantage also need to be considered when designing programs to ensure interventions take broad appeal, with customisability particularly relevant. This research underscores the importance of including parents with different socioeconomic experiences in the design and evaluation of IMIs for youth mental health, as without adequate representation existing inequalities will probable be exacerbated by the growing prevalence of IMIs for youth mental wellness.

The following are the supplementary data related to this article.

Supplementary Fig. i:

Screenshot of instructions and definitions provided to participants prior to completing the DCE.

Supplementary Tables:

Tables S1 to S5 presenting additional parameter estimates related to the DCE analyses.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Grace Broomfield is supported by the Australian Government Research Preparation Program Scholarship for their candidature in the Doctor of Psychology (Clinical Psychology) at Monash University.

CRediT authorship contribution statement

Grace Broomfield: Conceptualization, Methodology, Investigation, Formal analysis, Visualization, Project administration, Writing – original draft. Scott D. Brown: Methodology, Formal analysis, Supervision, Writing – review & editing. Marie B.H. Yap: Conceptualization, Methodology, Supervision, Writing – review & editing.

Declaration of competing interest

The authors declare that they accept no known competing financial interests or personal relationships that could have appeared to influence the piece of work reported in this paper.

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