diff --git a/R/seek_variables.R b/R/seek_variables.R
index 61dddf323..73379d7a7 100644
--- a/R/seek_variables.R
+++ b/R/seek_variables.R
@@ -17,7 +17,7 @@
 #' May also be a character vector of length > 1. `pattern` is searched for in
 #' column names, variable label and value labels attributes, or factor levels of
 #' variables in `data`.
-#' @param source Character vector, indicating where `pattern` is sought. Use one
+#' @param search Character vector, indicating where `pattern` is sought. Use one
 #' of more of the following options:
 #'
 #' - `"name"`: searches in column names.
@@ -45,30 +45,30 @@
 #' # variable names and labels only, so no match
 #' seek_variables(efc, "female")
 #' # when we seek in all sources, we find the variable "e16sex"
-#' seek_variables(efc, "female", source = "all")
+#' seek_variables(efc, "female", search = "all")
 #'
 #' # typo, no match
 #' seek_variables(iris, "Lenght")
 #' # typo, fuzzy match
 #' seek_variables(iris, "Lenght", fuzzy = TRUE)
 #' @export
-seek_variables <- function(data, pattern, source = c("names", "labels"), fuzzy = FALSE) {
+seek_variables <- function(data, pattern, search = c("names", "labels"), fuzzy = FALSE) {
   # check valid args
   if (!is.data.frame(data)) {
     insight::format_error("`data` must be a data frame.")
   }
 
   # check valid args
-  source <- intersect(source, c("names", "labels", "values", "levels", "column_names", "columns", "all"))
-  if (is.null(source) || !length(source)) {
-    insight::format_error("`source` must be one of \"names\", \"labels\", \"values\", a combination of these options, or \"all\".")
+  search <- intersect(search, c("names", "labels", "values", "levels", "column_names", "columns", "all"))
+  if (is.null(search) || !length(search)) {
+    insight::format_error("`search` must be one of \"names\", \"labels\", \"values\", a combination of these options, or \"all\".")
   }
 
   pos1 <- pos2 <- pos3 <- NULL
 
   pos <- unlist(lapply(pattern, function(search_pattern) {
     # search in variable names?
-    if (any(source %in% c("names", "columns", "column_names", "all"))) {
+    if (any(search %in% c("names", "columns", "column_names", "all"))) {
       pos1 <- which(grepl(search_pattern, colnames(data)))
       # find in near distance?
       if (fuzzy) {
@@ -77,7 +77,7 @@ seek_variables <- function(data, pattern, source = c("names", "labels"), fuzzy =
     }
 
     # search in variable labels?
-    if (any(source %in% c("labels", "all"))) {
+    if (any(search %in% c("labels", "all"))) {
       labels <- insight::compact_character(unlist(lapply(data, attr, which = "label", exact = TRUE)))
       if (!is.null(labels) && length(labels)) {
         found <- grepl(search_pattern, labels)
@@ -93,7 +93,7 @@ seek_variables <- function(data, pattern, source = c("names", "labels"), fuzzy =
     }
 
     # search for pattern in value labels or levels?
-    if (any(source %in% c("values", "levels", "all"))) {
+    if (any(search %in% c("values", "levels", "all"))) {
       values <- insight::compact_list(lapply(data, function(i) {
         l <- attr(i, "labels", exact = TRUE)
         if (is.null(l) && is.factor(i)) {
diff --git a/man/describe_distribution.Rd b/man/describe_distribution.Rd
index a23069eea..fd229567d 100644
--- a/man/describe_distribution.Rd
+++ b/man/describe_distribution.Rd
@@ -50,9 +50,14 @@ describe_distribution(x, ...)
 
 \item{...}{Additional arguments to be passed to or from methods.}
 
-\item{centrality}{The point-estimates (centrality indices) to compute.  Character (vector) or list with one or more of these options: \code{"median"}, \code{"mean"}, \code{"MAP"} or \code{"all"}.}
+\item{centrality}{The point-estimates (centrality indices) to compute. Character
+(vector) or list with one or more of these options: \code{"median"}, \code{"mean"}, \code{"MAP"}
+(see \code{\link[bayestestR:map_estimate]{map_estimate()}}), \code{"trimmed"} (which is just \code{mean(x, trim = threshold)}),
+\code{"mode"} or \code{"all"}.}
 
-\item{dispersion}{Logical, if \code{TRUE}, computes indices of dispersion related to the estimate(s) (\code{SD} and \code{MAD} for \code{mean} and \code{median}, respectively).}
+\item{dispersion}{Logical, if \code{TRUE}, computes indices of dispersion related
+to the estimate(s) (\code{SD} and \code{MAD} for \code{mean} and \code{median}, respectively).
+Dispersion is not available for \code{"MAP"} or \code{"mode"} centrality indices.}
 
 \item{iqr}{Logical, if \code{TRUE}, the interquartile range is calculated
 (based on \code{\link[stats:IQR]{stats::IQR()}}, using \code{type = 6}).}
@@ -71,7 +76,9 @@ the first centrality index (which is typically the median).}
 \item{iterations}{The number of bootstrap replicates for computing confidence
 intervals. Only applies when \code{ci} is not \code{NULL}.}
 
-\item{threshold}{For \code{centrality = "trimmed"} (i.e. trimmed mean), indicates the fraction (0 to 0.5) of observations to be trimmed from each end of the vector before the mean is computed.}
+\item{threshold}{For \code{centrality = "trimmed"} (i.e. trimmed mean), indicates
+the fraction (0 to 0.5) of observations to be trimmed from each end of the
+vector before the mean is computed.}
 
 \item{verbose}{Toggle warnings and messages.}
 
diff --git a/man/seek_variables.Rd b/man/seek_variables.Rd
index 928ccc48f..b1493e10a 100644
--- a/man/seek_variables.Rd
+++ b/man/seek_variables.Rd
@@ -4,7 +4,7 @@
 \alias{seek_variables}
 \title{Find variables by its name, variable or value labels}
 \usage{
-seek_variables(data, pattern, source = c("names", "labels"), fuzzy = FALSE)
+seek_variables(data, pattern, search = c("names", "labels"), fuzzy = FALSE)
 }
 \arguments{
 \item{data}{A data frame.}
@@ -14,7 +14,7 @@ May also be a character vector of length > 1. \code{pattern} is searched for in
 column names, variable label and value labels attributes, or factor levels of
 variables in \code{data}.}
 
-\item{source}{Character vector, indicating where \code{pattern} is sought. Use one
+\item{search}{Character vector, indicating where \code{pattern} is sought. Use one
 of more of the following options:
 \itemize{
 \item \code{"name"}: searches in column names.
@@ -57,7 +57,7 @@ seek_variables(efc, "dependency")
 # variable names and labels only, so no match
 seek_variables(efc, "female")
 # when we seek in all sources, we find the variable "e16sex"
-seek_variables(efc, "female", source = "all")
+seek_variables(efc, "female", search = "all")
 
 # typo, no match
 seek_variables(iris, "Lenght")
diff --git a/tests/testthat/test-seek_data.R b/tests/testthat/test-seek_data.R
index 45d7bdc35..5d3183906 100644
--- a/tests/testthat/test-seek_data.R
+++ b/tests/testthat/test-seek_data.R
@@ -16,7 +16,7 @@ test_that("seek_variables - search label attribute", {
   data(efc)
   out <- seek_variables(efc, "female")
   expect_identical(nrow(out), 0L)
-  out <- seek_variables(efc, "female", source = "all")
+  out <- seek_variables(efc, "female", search = "all")
   expect_identical(out$index, which(colnames(efc) == out$column))
   expect_identical(out$labels, "elder's gender")
 })
@@ -32,8 +32,41 @@ test_that("seek_variables - fuzzy match", {
 
 test_that("seek_variables - fuzzy match, value labels", {
   data(efc)
-  out <- seek_variables(efc, "femlae", source = "all", fuzzy = TRUE)
+  out <- seek_variables(efc, "femlae", search = "all", fuzzy = TRUE)
   expect_identical(nrow(out), 1L)
   expect_identical(out$index, which(colnames(efc) %in% out$column))
   expect_identical(out$labels, "elder's gender")
 })
+
+test_that("seek_variables - multiple pattern", {
+  data(efc)
+  out <- seek_variables(efc, c("e16", "e42"))
+  expect_identical(nrow(out), 2L)
+  expect_identical(out$index, which(colnames(efc) %in% out$column))
+  expect_identical(out$labels, c("elder's gender", "elder's dependency"))
+  # only one match, typo
+  out <- seek_variables(efc, c("femlae", "dependency"))
+  expect_identical(nrow(out), 1L)
+  expect_identical(out$index, which(colnames(efc) %in% out$column))
+  expect_identical(out$labels, "elder's dependency")
+  # only one match, not searching in value labels
+  out <- seek_variables(efc, c("female", "dependency"))
+  expect_identical(nrow(out), 1L)
+  expect_identical(out$index, which(colnames(efc) %in% out$column))
+  expect_identical(out$labels, "elder's dependency")
+  # two matches
+  out <- seek_variables(efc, c("female", "dependency"), search = "all")
+  expect_identical(nrow(out), 2L)
+  expect_identical(out$index, which(colnames(efc) %in% out$column))
+  expect_identical(out$labels, c("elder's gender", "elder's dependency"))
+  # only one match, typo
+  out <- seek_variables(efc, c("femlae", "dependency"), search = "all")
+  expect_identical(nrow(out), 1L)
+  expect_identical(out$index, which(colnames(efc) %in% out$column))
+  expect_identical(out$labels, "elder's dependency")
+  # two matches, despite typo
+  out <- seek_variables(efc, c("femlae", "dependency"), search = "all", fuzzy = TRUE)
+  expect_identical(nrow(out), 2L)
+  expect_identical(out$index, which(colnames(efc) %in% out$column))
+  expect_identical(out$labels, c("elder's gender", "elder's dependency"))
+})