We present two openly accessible databases related to the assessment of implicit motives using Picture Story Exercises (PSEs): (a) A database of 183,415 German sentences, nested in 26,389 stories provided by 4,570 participants, which have been coded by experts using Winter's (1994) coding system for the implicit affiliation/intimacy, achievement, and power motives, and (b) a database of 54 classic and new pictures which have been used as PSE stimuli. Updated picture norms are provided which can be used to select appropriate pictures for PSE applications.Based on an analysis of the relations between raw motive scores, word count, and sentence count, we give recommendations on how to control motive scores for story length, and validate the recommendation with a meta-analysis on gender differences in the implicit affiliation motive that replicates existing findings. We discuss to what extent the guiding principles of the story length correction can be generalized to other content coding systems for narrative material. Several potential applications of the databases are discussed, including (un)supervised machine learning of text content, psychometrics, and better reproducibility of PSE research.

Although rooted in reality, partner perceptions often reflect wishful thinking due to perceivers' needs. Dispositional needs, or motives, can differ between persons; however, little is known about their differential associations with everyday partner perception. The present study used data from a 4-week experience sampling study (N = up to 60942 surveys from 510 individuals nested in 259 couples) to examine the effects of perceivers' partner-related implicit and explicit communal motives on the perception of (i) global communal partner behaviour and (ii) specific communal and uncommunal partner behaviours. The results of truth and bias models of judgement and quasi-signal detection analyses indicate that strong implicit communal approach motives and strong explicit communal motives are associated with the tendency to overestimate the partner's communal behaviour. Additionally, strong implicit communal approach motives were associated with the tendency to avoid perceptions of uncommunal partner behaviour. Neither implicit nor explicit communal motives had an effect on accuracy in the perception of particularly communal partner behaviour. The results highlight the relevance of both implicit and explicit communal motives for momentary partner perceptions and emphasise the benefits of dyadic microlongitudinal designs for a better understanding of the mechanisms through which individual differences manifest in couples' everyday lives.

The investigation of within-person process models, often done in experience sampling designs, requires a reliable assessment of within-person change. In this paper, we focus on dyadic intensive longitudinal designs where both partners of a couple are assessed multiple times each day across several days. We introduce a statistical model for variance decomposition based on generalizability theory (extending P. E. Shrout & S. P. Lane, 2012), which can estimate the relative proportion of variability on four hierarchical levels: moments within a day, days, persons, and couples. Based on these variance estimates, four reliability coefficients are derived: between-couples, between-persons, within-persons/between-days, and within-persons/between-moments. We apply the model to two dyadic intensive experience sampling studies (n1 = 130 persons, 5 surveys each day for 14 days, ≥ 7508 unique surveys; n2 = 508 persons, 5 surveys each day for 28 days, ≥ 47764 unique surveys). Five different scales in the domain of motivational processes and relationship quality were assessed with 2 to 5 items: State relationship satisfaction, communal motivation, and agentic motivation; the latter consists of two subscales, namely power and independence motivation. Largest variance components were on the level of persons, moments, couples, and days, where within-day variance was generally larger than between-day variance. Reliabilities ranged from .32 to .76 (couple level), .93 to .98 (person level), .61 to .88 (day level), and .28 to .72 (moment level). Scale intercorrelations reveal differential structures between and within persons, which has consequences for theory building and statistical modeling.

Relationship satisfaction can be assessed in retrospection, as a global evaluation, or as a momentary state. In two experience sampling studies (N = 130, N = 510) the specificities of these assessment modalities are examined. We show that 1) compared to other summary statistics like the median, the mean of relationship satisfaction states describes retrospective and global evaluations best (but the difference to some other summary statistics was negligible); 2) retrospection introduces an overestimation of the average annoyance in the relationship reported on a momentary basis, which results in an overall negative mean-level bias for retrospective relationship satisfaction; 3) this bias is most strongly moderated by global relationship satisfaction at the time of retrospection; 4) snapshots of momentary relationship satisfaction get representative of global evaluations after approximately two weeks of sampling. The findings extend the recall bias reported in the literature for retrospection of negative affect to the domain of relationship evaluations and assist researchers in designing efficient experience sampling studies.

The investigation of within-person process models, often done in experience sampling designs, requires a reliable assessment of within-person change. In this paper, we focus on dyadic intensive longitudinal designs where both partners of a couple are assessed multiple times each day across several days. We introduce a statistical model for variance decomposition based on generalizability theory (extending P. E. Shrout & S. P. Lane, 2012), which can estimate the relative proportion of variability on four hierarchical levels: moments within a day, days, persons, and couples. Based on these variance estimates, three reliability coefficients are derived: between-persons, within-persons/between-days, and within-persons/between-moments. We apply the model to two dyadic intensive experience sampling studies (n_1 = 130 persons, 5 surveys each day for 14 days, >= 7.508 unique surveys; n_2 = 510 persons, 5 surveys each day for 28 days, >= 47.871 unique surveys). Five different scales in the domain of motivational processes and relationship quality were assessed with 2 to 5 items: State relationship satisfaction, communal motivation, and agentic motivation, which consist of two subscales, namely power and independence motivation. Largest variance components were on the level of persons, moments, couples, and days, where within-day variance was generally larger than between-day variance. Reliabilities ranged from .95 to .98 (person level), .52 to .86 (day level), and .28 to .70 (moment level). Scale intercorrelations reveal differential structures between and within persons, which has consequences for theory building and statistical modeling.