The Actor–Partner Interdependence Model for Longitudinal Dyadic Data: An Implementation in the SEM Framework

Gistelinck, Fien; Loeys, Tom

doi:10.1080/10705511.2018.1527223

Cited by 35 publications

(26 citation statements)

References 47 publications

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“…The L-APIMs with autoregressive effects currently do not allow to include the partner's lagged dependent outcome as predictor (Gistelinck & Loeys, 2020). Moreover, Level 1 errors were assumed to be independent over time, however, users might be interested in modeling serial dependency by including autocorrelated within-individual errors (see e.g., Gistelinck and Loeys (2019)). Finally, other non-linear L-APIMs (e.g., including piecewise linear actor and partner effects) have not been included (yet).…”

Section: Discussionmentioning

confidence: 99%

“…Note that other sets of restrictions have been proposed in the literature that allow for auto-dependency of the errors Gistelinck and Loeys (2019), but these can not be imposed with the package nlme.…”

Section: Modelsmentioning

confidence: 99%

“…A popular modeling approach for capturing dyadic processes is the longitudinal actor-partner interdependence model (L-APIM) (see e.g., Gistelinck and Loeys (2019); Kenny, Kashy, and Cook (2020)). The L-APIM is an extension of longitudinal regression approaches, in that it focuses on the effect of a predictor on an outcome across time.…”

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confidence: 99%

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PowerLAPIM: An Application to Conduct Power Analysis for Linear and Quadratic Longitudinal Actor-Partner Interdependence Models in Intensive Longitudinal Dyadic Designs

Lafit¹,

Sels²,

Adolf³

et al. 2021

Preprint

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The longitudinal actor-partner interdependence modeling framework (L-APIM) is often used to study actor and partner effects in dyadic intensive longitudinal data. To capture curvilinear actor and partner patterns, the L-APIM can be extended to include quadratic actor and partner effects. A burning question is how to conduct power analyses for different L-APIM variants. In this paper, we introduce a power analysis application, called PowerLAPIM, and provide a hands-on tutorial for conducting simulation-based power analyses for 32 L-APIM variants, many of which include quadratic effects. With PowerLAPIM, we target the number of dyads needed, but not the number of repeated measurements for both partners, because this is usually fixed in many longitudinal dyadic studies. PowerLAPIM allows studying moderation of the linear and quadratic actor and partner effects by incorporating time-varying covariates or a categorical dyad-level predictor to test group differences. We also provide the functionality to account for serial dependency in the outcome variable by including autoregressive effects. We illustrate how to perform a power analysis for a longitudinal dyadic study using PowerLAPIM based on data from 94 heterosexual couples for which both partners simultaneously reported on their feelings and experiences several times a day for one week.

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Section: Discussionmentioning

confidence: 99%

Section: Modelsmentioning

confidence: 99%

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PowerLAPIM: An Application to Conduct Power Analysis for Linear and Quadratic Longitudinal Actor-Partner Interdependence Models in Intensive Longitudinal Dyadic Designs

Lafit¹,

Sels²,

Adolf³

et al. 2021

Preprint

Self Cite

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“…The importance of partners supporting the patient in the programme is often ignored; however, improving the perceptions of illness on the part of partners of heart attack patients may have important implications not only for patients' recovery [5], but also for improving partners' lifestyle habits [18]. For this reason, it is important to focus on analysing the influence of interpersonal behaviours of the partners [19].…”

Section: Introductionmentioning

confidence: 99%

Psycho-Social Factors in Patients with Cardiovascular Disease Attending a Family-Centred Prevention and Rehabilitation Programme: EUROACTION Model in Spain

Buigues

Queralt

Velasco

et al. 2021

Life

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Background: Coronary heart disease (CHD) persists as the leading cause of death worldwide. Cardiovascular prevention and rehabilitation (CVPR) has an interdisciplinary focus, and includes not only in physiological components, but it also addresses psycho-social factors. Methods: The study analysed the Spanish psycho-social data collected during the EUROACTION study. In Spain, two hospitals were randomised in the Valencia community. Coronary patients were prospectively and consecutively identified in both hospitals. The intervention hospital carried out a 16-week CVPR programme, which aimed to assess illness perceptions and establish healthy behaviours in patients and their partners. Results: Illness perceptions were significantly and inversely associated with anxiety and depression. Low levels of anxiety were associated with better self-management of total cholesterol (p = 0.004) and low-density lipoprotein-cholesterol (p = 0.004). There was concordance at one year among patients and partners who participated in the programme related to anxiety (p < 0.001), fruit consumption (p < 0.001), and vegetable consumption (p < 0.001). Conclusions: The EUROACTION study emphasised the importance of assessing psycho-social factors in a CVPR programme and the inclusion of family as support in patients’ changes in behaviour.

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“…Positive caregiver support can help to facilitate recovery and adjustment following an acute cardiac event [18], and researchers have long advocated the merit of evaluating inter-partner influences over time [19,20], but to date most studies have been conducted in cancer care or with older adults [21][22][23]. Although there have been some cross-sectional dyadic studies in cardiac populations [20][21][22][23][24], there is currently a paucity of longitudinal research examining how caregivers perceive cardiac patients' illness and rehabilitation and how this impacts on both parties at the dyadic level. Thus, simultaneous exploration of patient and caregiver perceptions, informed by the study of patient-caregiver dyads, is both necessary and justified.…”

Section: Introductionmentioning

confidence: 99%

Longitudinal evaluation of the effects of illness perceptions and beliefs about cardiac rehabilitation on quality of life of patients with coronary artery disease and their caregivers

Thomson

Angus

Andreis

et al. 2020

Health Qual Life Outcomes

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Background: Patients' negative illness perceptions and beliefs about cardiac rehabilitation (CR) can influence uptake and adherence to CR. Little is known about the interpartner influence of these antecedent variables on quality of life of patients with coronary artery disease (CAD) and their family caregivers. The aims of the study were: 1) to assess differences in illness perceptions, beliefs about CR and quality of life between patients with CAD and their family caregivers upon entry to a CR programme and at 6 months follow-up; and 2) to examine whether patients' and caregivers' perceptions of the patient's illness and beliefs about CR at baseline predict their own and their partner's quality of life at 6 months. Methods: In this longitudinal study of 40 patient-caregiver dyads from one CR service, patients completed the Brief Illness Perception Questionnaire and Beliefs about Cardiac Rehabilitation Questionnaire at baseline and 6 months; and caregivers completed these questionnaires based on their views about the patient's illness and CR. The Short-Form 12 Health Survey was used to assess patients' and caregivers' perceived health status. Dyadic data were analysed using the Actor-Partner Interdependence Model. Results: Most patients (70%) were men, mean age 62.45 years; and most caregivers (70%) were women, mean age 59.55 years. Caregivers were more concerned about the patient's illness than the patients themselves; although they had similar scores for beliefs about CR. Patients had poorer physical health than caregivers, but their level of mental health was similar. Caregivers' poorer mental health at 6 months was predicted by the patient's perceptions of timeline and illness concern (i.e. partner effects). Patient's and caregiver's illness perceptions and beliefs about CR were associated with their own physical and mental health at 6 months (i.e. actor effects).

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The Actor–Partner Interdependence Model for Longitudinal Dyadic Data: An Implementation in the SEM Framework

Cited by 35 publications

References 47 publications

PowerLAPIM: An Application to Conduct Power Analysis for Linear and Quadratic Longitudinal Actor-Partner Interdependence Models in Intensive Longitudinal Dyadic Designs

PowerLAPIM: An Application to Conduct Power Analysis for Linear and Quadratic Longitudinal Actor-Partner Interdependence Models in Intensive Longitudinal Dyadic Designs

Psycho-Social Factors in Patients with Cardiovascular Disease Attending a Family-Centred Prevention and Rehabilitation Programme: EUROACTION Model in Spain

Longitudinal evaluation of the effects of illness perceptions and beliefs about cardiac rehabilitation on quality of life of patients with coronary artery disease and their caregivers

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