diff --git a/DESCRIPTION b/DESCRIPTION
index d3cadf72..45c7a283 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: effectsize
 Title: Indices of Effect Size
-Version: 0.8.6.4
+Version: 0.8.6.5
 Authors@R: 
     c(person(given = "Mattan S.",
              family = "Ben-Shachar",
diff --git a/NEWS.md b/NEWS.md
index bfd8f3f0..4fa67482 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -4,6 +4,8 @@
 
 ## New features
 
+- `cohens_d()` and `glass_delta()` gain an `adjust` argument for applying Hedges' small-sample bias correction (`hedges_g()` is now an alias for `cohens_d(adjust = TRUE)`).
+
 - `repeated_measures_d()` to compute standardized mean differences (SMD) for repeated measures data.
   - Also supported in `effectsize(<t.test(paired = TRUE)>)`
   
diff --git a/R/cohens_d.R b/R/cohens_d.R
index f778e624..0bf528ba 100644
--- a/R/cohens_d.R
+++ b/R/cohens_d.R
@@ -26,6 +26,9 @@
 #' @param paired If `TRUE`, the values of `x` and `y` are considered as paired.
 #'   This produces an effect size that is equivalent to the one-sample effect
 #'   size on `x - y`. See also [repeated_measures_d()] for more options.
+#' @param adjust Should the effect size be adjusted for small-sample bias using
+#'   Hedges' method? Note that `hedges_g()` is an alias for
+#'   `cohens_d(adjust = TRUE)`.
 #' @param ... Arguments passed to or from other methods. When `x` is a formula,
 #'   these can be `subset` and `na.action`.
 #' @inheritParams chisq_to_phi
@@ -133,6 +136,7 @@
 #' @export
 cohens_d <- function(x, y = NULL, data = NULL,
                      pooled_sd = TRUE, mu = 0, paired = FALSE,
+                     adjust = FALSE,
                      ci = 0.95, alternative = "two.sided",
                      verbose = TRUE, ...) {
   var.equal <- eval.parent(match.call()[["var.equal"]])
@@ -141,7 +145,7 @@ cohens_d <- function(x, y = NULL, data = NULL,
   .effect_size_difference(
     x,
     y = y, data = data,
-    type = "d",
+    type = "d", adjust = adjust,
     pooled_sd = pooled_sd, mu = mu, paired = paired,
     ci = ci, alternative = alternative,
     verbose = verbose,
@@ -155,31 +159,23 @@ hedges_g <- function(x, y = NULL, data = NULL,
                      pooled_sd = TRUE, mu = 0, paired = FALSE,
                      ci = 0.95, alternative = "two.sided",
                      verbose = TRUE, ...) {
-  var.equal <- eval.parent(match.call()[["var.equal"]])
-  if (!is.null(var.equal)) pooled_sd <- var.equal
-
-  .effect_size_difference(
-    x,
-    y = y, data = data,
-    type = "g",
-    pooled_sd = pooled_sd, mu = mu, paired = paired,
-    ci = ci, alternative = alternative,
-    verbose = verbose,
-    ...
-  )
+  cl <- match.call()
+  cl[[1]] <- quote(cohens_d)
+  cl$adjust <- TRUE
+  eval.parent(cl)
 }
 
 #' @rdname cohens_d
 #' @export
 glass_delta <- function(x, y = NULL, data = NULL,
-                        mu = 0,
+                        mu = 0, adjust = FALSE,
                         ci = 0.95, alternative = "two.sided",
                         verbose = TRUE, ...) {
   .effect_size_difference(
     x,
     y = y, data = data,
     type = "delta",
-    mu = mu,
+    mu = mu, adjust = adjust,
     ci = ci, alternative = alternative,
     verbose = verbose,
     pooled_sd = NULL, paired = FALSE,
@@ -191,10 +187,12 @@ glass_delta <- function(x, y = NULL, data = NULL,
 
 #' @keywords internal
 .effect_size_difference <- function(x, y = NULL, data = NULL,
-                                    type = "d",
+                                    type = "d", adjust = FALSE,
                                     mu = 0, pooled_sd = TRUE, paired = FALSE,
                                     ci = 0.95, alternative = "two.sided",
                                     verbose = TRUE, ...) {
+  if (type == "d" && adjust) type <- "g"
+
   if (type != "delta") {
     if (.is_htest_of_type(x, "t-test")) {
       return(effectsize(x, type = type, verbose = verbose, ...))
@@ -294,16 +292,19 @@ glass_delta <- function(x, y = NULL, data = NULL,
   }
 
 
-  if (type == "g") {
+  if (adjust) {
     J <- .J(df)
+    col_to_adjust <- intersect(colnames(out), c(types[type], "CI_low", "CI_high"))
+    out[, col_to_adjust] <- out[, col_to_adjust] * J
 
-    out[, colnames(out) %in% c("Hedges_g", "CI_low", "CI_high")] <-
-      out[, colnames(out) %in% c("Hedges_g", "CI_low", "CI_high")] * J
+    if (type == "delta") {
+      colnames(out)[1] <- "Glass_delta_adjusted"
+    }
   }
 
   class(out) <- c("effectsize_difference", "effectsize_table", "see_effectsize_table", class(out))
   .someattributes(out) <- .nlist(
-    paired, pooled_sd, mu, ci, ci_method, alternative,
+    paired, pooled_sd, mu, ci, ci_method, alternative, adjust,
     approximate = FALSE
   )
   return(out)
diff --git a/R/sysdata.rda b/R/sysdata.rda
index 50806d57..24b21355 100644
Binary files a/R/sysdata.rda and b/R/sysdata.rda differ
diff --git a/data-raw/es_info.R b/data-raw/es_info.R
index 88044de6..401a991d 100644
--- a/data-raw/es_info.R
+++ b/data-raw/es_info.R
@@ -4,6 +4,7 @@ es_info <- tibble::tribble(
   "Cohens_d", "Cohen's d", NA, "twotail", -Inf, Inf, 0,
   "Hedges_g", "Hedges' g", NA, "twotail", -Inf, Inf, 0,
   "Glass_delta", "Glass' delta", "Glass' \u0394", "twotail", -Inf, Inf, 0,
+  "Glass_delta_adjusted", "Glass' delta (adj.)", "Glass' \u0394 (adj.)", "twotail", -Inf, Inf, 0,
   "d_rm", "d (rm)", "d\u1D63\u2098", "twotail", -Inf, Inf, 0,
   "d_av", "d (av)", "d\u2090\u1D65", "twotail", -Inf, Inf, 0,
   "d_z", "d (z)", NA, "twotail", -Inf, Inf, 0,
diff --git a/man/cohens_d.Rd b/man/cohens_d.Rd
index 90d7b1c8..60236654 100644
--- a/man/cohens_d.Rd
+++ b/man/cohens_d.Rd
@@ -13,6 +13,7 @@ cohens_d(
   pooled_sd = TRUE,
   mu = 0,
   paired = FALSE,
+  adjust = FALSE,
   ci = 0.95,
   alternative = "two.sided",
   verbose = TRUE,
@@ -37,6 +38,7 @@ glass_delta(
   y = NULL,
   data = NULL,
   mu = 0,
+  adjust = FALSE,
   ci = 0.95,
   alternative = "two.sided",
   verbose = TRUE,
@@ -61,6 +63,10 @@ variance). Else the mean SD from both groups is used instead.}
 This produces an effect size that is equivalent to the one-sample effect
 size on \code{x - y}. See also \code{\link[=repeated_measures_d]{repeated_measures_d()}} for more options.}
 
+\item{adjust}{Should the effect size be adjusted for small-sample bias using
+Hedges' method? Note that \code{hedges_g()} is an alias for
+\code{cohens_d(adjust = TRUE)}.}
+
 \item{ci}{Confidence Interval (CI) level}
 
 \item{alternative}{a character string specifying the alternative hypothesis;
diff --git a/tests/testthat/test-cohens_d.R b/tests/testthat/test-cohens_d.R
index a412a20a..f79031d6 100644
--- a/tests/testthat/test-cohens_d.R
+++ b/tests/testthat/test-cohens_d.R
@@ -54,6 +54,9 @@ test_that("hedges_g (and other bias correction things", {
   expect_equal(x[[1]], 1.844, tolerance = 0.001)
   expect_equal(x$CI_low, 1.004, tolerance = 0.001)
   expect_equal(x$CI_high, 2.664, tolerance = 0.001)
+
+  x2 <- cohens_d(wt ~ am, data = mtcars, adjust = TRUE)
+  expect_equal(x2, x)
 })
 
 test_that("glass_delta", {
@@ -66,6 +69,12 @@ test_that("glass_delta", {
   expect_equal(x[[1]], 2.200, tolerance = 0.001)
   expect_equal(x$CI_low, 1.008664, tolerance = 0.001)
   expect_equal(x$CI_high, 3.352597, tolerance = 0.001)
+
+  x2 <- glass_delta(wt ~ am, data = mtcars, adjust = TRUE)
+  expect_equal(colnames(x2)[1], "Glass_delta_adjusted")
+  expect_lt(x2[[1]], x[[1]])
+  expect_lt(x2$CI_low, x$CI_low)
+  expect_lt(x2$CI_high, x$CI_high)
 })