Comparison of 3 Different Analytic Approaches for Determining Risk-Related Active and Sedentary Behavioral Patterns in Adolescents

Background:Much of the research conducted to date implies overweight youth exhibit uniform active and sedentary behavioral patterns. This approach negates the possibility that multiple co-occurring, and seemingly contrasting, behaviors may manifest within the same individual. We present a substantive dialogue on alternative analytical approaches to identifying risk-related active/sedentary behavioral patterns associated with overweight in adolescents.Methods:Comparisons were made among latent profile analysis (LPA), cluster analysis (CA), and multinomial logistic regression (MLR). A cross sectional sample of youth (N = 6603; 12−18 yrs) completed a questionnaire assessing: physical activity (PA); competing activities (COMP); and sedentary activities (SED). Demographics associated with PA (age, sex, BMI) were used as covariates/predictors.Results:Comparisons among methods revealed that LPA and CA detected subgroupings of behavioral patterns associated with overweight, each unique in regards to behaviors and demographic characteristics, whereas MLR results followed established associations of low PA and high SED without subgroup separation.Conclusions:Use of LPA and CA provides a rich understanding of behavioral patterns and the related demographic characteristics. Decisions guiding the selection of analytical techniques are discussed.

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Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study

BMJ Open ◽

10.1136/bmjopen-2019-029331 ◽

2019 ◽

Vol 9 (6) ◽

pp. e029331 ◽

Cited By ~ 1

Author(s):

Haining Liao ◽

Minyi Pan ◽

Weinan Li ◽

Changqi Lin ◽

Xuhao Zhu ◽

...

Keyword(s):

Anxiety Disorder ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Multinomial Logistic Regression ◽

School Factors ◽

Cross Sectional ◽

Effective Response ◽

Left Behind ◽

Children’S Anxiety ◽

Latent Profile

ObjectivesPrevious studies have used latent profile analysis (LPA) to examine rural left-behind children’s anxiety. Further study is needed to identify the heterogeneous characteristics of rural left-behind children’s anxiety and explore the related factors.SettingA cross-sectional survey using a school-based sample was conducted in January 2018 in Qingxin district, Qingyuan city, Guangdong province.Participants1026 left-behind children (effective response rate of the questionnaire: 95.39%).Main outcome measuresProfile latent classes (LC) and anxiety disorder.ResultsThe LPA identified three anxiety LC: ‘low anxiety’ (56.6%), ‘medium anxiety’ (34.8%) and ‘severe anxiety’ (8.6%). The multinomial logistic regression model was used to predict the relationship between personal, family, school factors and anxiety. We found that the variables directly related to lower anxiety classes included age (12–14 years), harmonious or fair relationship with classmates, no neglect, harmonious parental relationship and the duration of mother migration <6 months.ConclusionsThese findings suggested the need for careful consideration of differences in anxieties among rural left-behind children. Identifying latent subgroups may provide an empirical basis for teachers and public health practitioners to implement anxiety intervention efforts.

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Identifying Suicide Typologies Among Trauma-Exposed Veterans

Crisis ◽

10.1027/0227-5910/a000637 ◽

2020 ◽

Vol 41 (4) ◽

pp. 288-295 ◽

Cited By ~ 1

Author(s):

Nadia Bounoua ◽

Jasmeet P. Hayes ◽

Naomi Sadeh

Keyword(s):

Latent Profile Analysis ◽

Suicide Attempts ◽

Clinical Symptoms ◽

Profile Analysis ◽

Risky Behaviors ◽

Self Report ◽

Cross Sectional ◽

Research Priority ◽

Self Harm ◽

And Behaviors

Abstract. Background: Suicide among veterans has increased in recent years, making the identification of those at greatest risk for self-injurious behavior a high research priority. Aims: We investigated whether affective impulsivity and risky behaviors distinguished typologies of self-injurious thoughts and behaviors in a sample of trauma-exposed veterans. Method: A total of 95 trauma-exposed veterans (ages 21–55; 87% men) completed self-report measures of self-injurious thoughts and behaviors, impulsivity, and clinical symptoms. Results: A latent profile analysis produced three classes that differed in suicidal ideation, suicide attempts and nonsuicidal self-injury (NSSI): A low class that reported little to no self-injurious thoughts or behaviors; a self-injurious thoughts (ST) class that endorsed high levels of ideation but no self-harm behaviors; and a self-injurious thoughts and behaviors (STaB) class that reported ideation, suicide attempts and NSSI. Membership in the STaB class was associated with greater affective impulsivity, disinhibition, and distress/arousal than the other two classes. Limitations: Limitations include an overrepresentation of males in our sample, the cross-sectional nature of the data, and reliance on self-report measures. Conclusion: Findings point to affective impulsivity and risky behaviors as important characteristics of veterans who engage in self-injurious behaviors.

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Providing instrumental support to older parents of multi-child families in China: are there different within-family patterns?

Ageing and Society ◽

10.1017/s0144686x21000283 ◽

2021 ◽

pp. 1-18

Author(s):

Jia Chen ◽

Xiaochen Zhou ◽

Nan Lu

Keyword(s):

Adult Children ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Multinomial Logistic Regression ◽

Adult Child ◽

Instrumental Support ◽

Older Parents ◽

Older Mothers ◽

Family Patterns ◽

Using Data

Abstract Older parents in China rely heavily on their adult children for instrumental assistance. In different multi-child families, multiple offspring may co-operate in providing instrumental support to older parents in distinct ways in terms of how much support they provide on average and how much differentiation exists between them when they provide such support within a family. We aimed to identify different within-family patterns in relation to multiple offspring's instrumental support to an older parent in Chinese multi-child families, and to investigate potential predictors for different within-family patterns. Using data from the China Family Panel Studies (2016), we had a working sample of 5,790 older adults aged 60+ (mean = 68.54, standard deviation = 6.60). We employed latent profile analysis (LPA) to classify within-family patterns and multinomial logistic regression to investigate predictors. Our findings identified three within-family patterns: dissociated (59.10%), highly differentiated (29.60%) and united-filial (11.30%). Older parents in the highly differentiated families tended to be older, mothers, divorced/widowed and to have poorer physical health compared to their counterparts in the dissociated families. In contrast, the composition characteristics of multiple adult children played more important roles in determining the united-filial within-family pattern. The united-filial families were more likely to have fewer adult children, at least one adult daughter and at least one co-residing adult child.

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Associations between Child and Family Level Correlates and Behavioural Patterns in School-Aged Children

Children ◽

10.3390/children8111023 ◽

2021 ◽

Vol 8 (11) ◽

pp. 1023

Author(s):

Ninoshka J. D’Souza ◽

Miaobing Zheng ◽

Gavin Abbott ◽

Sandrine Lioret ◽

Kylie D. Hesketh

Keyword(s):

Latent Profile Analysis ◽

Profile Analysis ◽

Multinomial Logistic Regression ◽

Working Hours ◽

Target Population ◽

Older Children ◽

Increased Risk ◽

Behavioural Patterns ◽

Family Level ◽

The Individual

Identifying correlates of behavioural patterns are important to target population sub-groups at increased health risk. The aim was to investigate correlates of behavioural patterns comprising four behavioural domains in children. Data were from the HAPPY study when children were 6–8 years (n = 335) and 9–11 years (n = 339). Parents reported correlate and behavioural data (dietary intake, physical activity, sedentary behaviour, and sleep). Behavioural data were additionally captured using accelerometers. Latent profile analysis was used to derive patterns. Patterns were identified as healthy, unhealthy, and mixed at both time points. Multinomial logistic regression tested for associations. Girls were more likely to display healthy patterns at 6–8 years and display unhealthy and mixed patterns at 9–11 years than boys, compared to other patterns at the corresponding ages. Increased risk of displaying the unhealthy pattern with higher age was observed at both timepoints. At 9–11 years, higher parental working hours were associated with lower risk of displaying mixed patterns compared to the healthy pattern. Associations observed revealed girls and older children to be at risk for unhealthy patterns, warranting customisation of health efforts to these groups. The number of behaviours included when deriving patterns and the individual behaviours that dominate each pattern appear to be drivers of the associations for child level, but not for family level, correlates.

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Typologies of Family Functioning and 24-Hour Movement Behaviors

10.21203/rs.3.rs-48988/v1 ◽

2020 ◽

Author(s):

Michelle Guerrero ◽

Joel Barnes ◽

Mark Tremblay ◽

Laura Pulkki-Råback

Keyword(s):

Family Functioning ◽

Family Environment ◽

Parental Monitoring ◽

Latent Profile Analysis ◽

Profile Analysis ◽

The United States ◽

Movement Behavior ◽

Cross Sectional ◽

Family Typologies ◽

Latent Profile

Abstract Objective: The purpose of the current study was to use latent profile analysis to identify family typologies characterized by parental acceptance, parental monitoring, and family conflict, and to examine whether such typologies were associated with the number of movement behavior recommendations (i.e., physical activity, screen time, and sleep) met by children. Methods: Data for this cross-sectional observational study were part of the baseline data from the Adolescent Brain Cognitive Development (ABCD) study. Data were collected from September 1, 2016 to September 15, 2018, across 21 study sites in the United States. Participants included 11,875 children aged 9 and 10 years. Results: Results from latent profile analysis showed that children were meaningfully classified into one of five family typologies, ranging from ideal (high acceptance, high monitoring, and low conflict) to poor (medium acceptance, low monitoring, and high conflict) functioning. Children from good (OR= 0.54; 95% CI, 0.39-0.76), average (OR=0.28; 95% CI, 0.20, 0.40), fair (OR=0.24; 95% CI, 0.16, 0.36), and poor (OR=0.19; 95% CI, 0.12-0.29) functioning families were less likely to meet all three movement behavior recommendations compared to children from ideal functioning families. The odds of meeting all recommendations progressively decreased as family functioning worsened. Similar findings and pattern of results were found for meeting ≥2 recommendations and ≥1 recommendation. Conclusions: These findings highlight the importance of the family environment for promoting healthy movement behaviors among children.

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Children’s Internet Use Profiles in Relation to Behavioral Problems in Lithuania, Latvia, and Taiwan

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17228490 ◽

2020 ◽

Vol 17 (22) ◽

pp. 8490

Author(s):

Vilmantė Pakalniškienė ◽

Roma Jusienė ◽

Sandra B. Sebre ◽

Jennifer Chun-Li Wu ◽

Ilona Laurinaitytė

Keyword(s):

Behavioral Problems ◽

Internet Use ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Cross Sectional Study ◽

Emotional And Behavioral Problems ◽

Behavioral Difficulties ◽

Cross Sectional ◽

Sample Distribution ◽

High Class

This study explored the profiles of elementary-school-aged children’s Internet use in relation to their emotional and behavioral problems. Participating in this cross-sectional study were 877 child–parent dyads from Latvia, Lithuania, and Taiwan. Children (8–10 years old) provided information on three variables: the amount of time they spent online, frequency of online activities, and knowledge of how to do things online. Latent profile analysis including these three variables provided a four-class solution for child Internet use. A comparison between Latvia, Lithuania, and Taiwan on the percentage of the sample distribution in each class showed that there was no difference between sites for the high class (high ratings on all three variables). The largest differences were for the low and average classes (low and average ratings on all three variables, namely, time online, frequency, and knowledge): the Lithuanian and Taiwanese samples were similar in that a higher percentage of each sample was in the low class, whereas the Latvian sample had children equally distributed between the low class and the average class. Analysis of the data from the entire sample for differences in parent-reported child behavioral difficulties suggested that children in the high class had an elevated level of behavioral problems and compulsive Internet use.

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An essay on human and elements, multielement profiles, and depression

Translational Neuroscience ◽

10.2478/v10134-010-0039-2 ◽

2010 ◽

Vol 1 (4) ◽

Cited By ~ 14

Author(s):

Berislav Momčilović ◽

Juraj Prejac ◽

Sanja Brundić ◽

Sandra Morović ◽

Anatoly Skalny ◽

...

Keyword(s):

Analytical Study ◽

Profile Analysis ◽

Essential Element ◽

Analytical Techniques ◽

The Body ◽

Double Blind ◽

Cross Sectional ◽

Health And Disease ◽

Metabolic Impairments ◽

Matrix Sample

AbstractThe recent development of the analytical techniques offers the unprecedented possibility to study simultaneously concentration of dozens of elements in the same biological matrix sample of 0.5–1.0 g (multielement profiles). The first part of this essay entitled “Think globally… An outline of trace elements in health and disease” aims to introduce the reader to the fascinating field of elements, there importance to our nutrition, their essentiality, deficiency, toxicity and bioavailability to the body and their overall role in health and disease, including the genetic metabolic impairments. In the second part of the essay entitled “… and act locally. The multielement profile of depression” we aimed to show the potential of such a hair multielement profile analysis for the study of human depression in a randomized, double blind, prospective, observational, cross-sectional, clinical, epidemiological, and analytical study. The preliminary results of this ongoing study lead us to put forward the hypothesis that the metabolic origin of depression may be due to some “energostat” failure, probably located in the thalamus, and activated by several essential element deficiencies.

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On the nomological net of (non-)workaholic subtypes

Career Development International ◽

10.1108/cdi-12-2018-0327 ◽

2019 ◽

Vol 24 (7) ◽

pp. 672-685

Author(s):

Greta Ontrup ◽

Justine Patrzek

Keyword(s):

Latent Profile Analysis ◽

Profile Analysis ◽

Statistical Technique ◽

Online Questionnaire ◽

Cross Sectional ◽

Content Type ◽

Future Studies ◽

Model Based Clustering ◽

Starting Point ◽

Cross Sectional Design

Purpose Research on workaholism distinguishes between enthusiastic and non-enthusiastic workaholics, a typology used in many studies. Yet, the methodical foundation on which the derivation of the types is based lacks robust statistical evidence. The purpose of this paper is twofold: first, to replicate the often-cited typology of enthusiastic and non-enthusiastic workaholics (and non-workaholic subtypes), based on model-based clustering as a robust statistical technique; and second, to validate the class solution based on affective, cognitive and behavioral measures. Design/methodology/approach The study followed a cross-sectional design, targeting a sample of people from various fields of industries. An online questionnaire was distributed; workaholism was assessed with McMillan et al.’s (2002) Work-BAT-R scales. A total of 537 respondents’ data were analyzed. Findings Latent profile analysis extracted four classes, namely, enthusiastic and non-enthusiastic workaholics and relaxed and uninvolved non-workaholics. As expected, workers characterized by high enjoyment (enthusiasts and relaxed) showed higher job satisfaction and occupational self-efficacy than workers with low enjoyment (non-enthusiasts and uninvolved). Relaxed workers reported higher life satisfaction than all other classes. Originality/value The robust methodology applied establishes a good starting point for future studies investigating workers subtypes: the replication suggests that the workaholic subtypes might be core profiles that occur in different populations with regularity. As a next step, the replication of the typology based on alternative operationalizations of workaholism is proposed for future studies.

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Discovering unique profiles of adolescent information and communication technology (ICT) use: Are ICT use preferences associated with identity and behaviour development?

Cyberpsychology Journal of Psychosocial Research on Cyberspace ◽

10.5817/cp2017-4-3 ◽

2017 ◽

Vol 11 (4) ◽

Cited By ~ 3

Author(s):

Anna Kurek ◽

Paul E. Jose ◽

Jaimee Stuart

Keyword(s):

Information And Communication Technology ◽

Communication Technology ◽

Technology Use ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Cross Sectional ◽

Ict Use ◽

Information And Communication ◽

Types Of Information ◽

The Impact

Over the course of the last seven years, the average weekly screen-time of youth has dramatically increased. The present study was designed to better understand how young people utilise multiple types of information and communication technology (ICT) in their everyday lives and how these preferences may be associated with key aspects of their development. To this end, the present study was designed to explore whether specific profiles of technology usage would be associated with key characteristics of identity and behaviour. To identify groups of adolescents who share similar technology use habits, a sample of 933 adolescents reported on their time spent interacting with various digital communication devices and associated platforms. Utilizing a latent profile analysis, four distinct profiles of technology use preferences emerged. Then, a series of linear regressions were calculated to investigate the degree to which class membership predicted indicators of identity and problem behaviours. The findings suggest that important concepts of both identity and behaviour are associated with individual ICT usage preferences. Acknowledging the cross-sectional nature of the data, it is suggested that the impact of clusters of communication technology use on adolescent development should be investigated with longitudinal data.

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Existence of Differential Belief Profiles of COVID-19 Narratives: The Role of Trust in Science

10.21203/rs.3.rs-35919/v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Jon Agley ◽

Yunyu Xiao

Keyword(s):

Online Survey ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Religious Commitment ◽

Open Science ◽

Political Orientation ◽

Cross Sectional ◽

Full Sample ◽

Scientific Consensus

Abstract BackgroundThe global spread of coronavirus disease 2019 (COVID-19) has been mirrored by diffusion of misinformation and conspiracy theories about its origins (such as 5G cellular networks) and the motivations of preventive measures like vaccination, social distancing, and face masks (for example, as a political ploy). These beliefs have resulted in substantive, negative real-world outcomes but remain largely unstudied.MethodsThis was a cross-sectional, online survey (n=660). Participants were asked about the believability of five selected COVID-19 narratives, their political orientation, their religious commitment, and their trust in science (a 21-item scale), along with sociodemographic items. Data were assessed descriptively, then latent profile analysis was used to identify subgroups with similar believability profiles. Bivariate (ANOVA) analyses were run, then multivariable, multivariate logistic regression was used to identify factors associated with membership in specific COVID-19 narrative believability profiles.ResultsFor the full sample, believability of the narratives varied, from a low of 1.94 (SD=1.72) for the 5G narrative to a high of 4.56 (SD=1.64) for the zoonotic (scientific consensus) narrative. Four distinct belief profiles emerged, with the preponderance (70%) of the sample falling into Profile 1, which believed the scientifically accepted narrative (zoonotic origin) but not the misinformed or conspiratorial narratives. Other profiles did not disbelieve the zoonotic explanation, but rather believed additional misinformation to varying degrees. Controlling for sociodemographics, political orientation and religious commitment were marginally, and typically non-significantly, associated with COVID-19 belief profile membership. However, trust in science was a strong, significant predictor of profile membership, with lower trust being substantively associated with belonging to Profiles 2 through 4.ConclusionsBelief in misinformation or conspiratorial narratives may not be mutually exclusive from belief in the narrative reflecting scientific consensus; that is, profiles were distinguished not by belief in the zoonotic narrative, but rather by concomitant belief or disbelief in additional narratives. Additional, renewed dissemination of scientifically accepted narratives may not attenuate belief in misinformation. However, prophylaxis of COVID-19 misinformation might be achieved by taking concrete steps to improve trust in science and scientists, such as building understanding of the scientific process and supporting open science initiatives.

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