For $n\in\mathbb{Z}_{\geq 0}$ and $0\leq i< 2^n$, denote
$$
X_{n,i}=\sup_{t\in[i2^{-n}, (i+1)2^{-n}]}{|W_t-W_{i2^n}|}.
$$
Let $n$ be such that $2^{-{n}}<|\Delta t|\leq 2^{-{n+1}}$. Then,
$$\sup_{s,t\in[0,1],~ |s-t|\le\Delta t}|W_s-W_t|^p\leq 4\sup_{i}|X_{i,n}|^p,$$ because such $s$ and $t$ must belong to a union of three consecutive diadic intervals of length $2^{-n}$. For a fixed $n$, $X_{n,i}$ are i. i. d. random variables; moreover, by Brownian scaling,
$$
X_{n,i}\stackrel{\mathcal{D}}{=}2^{-n/2}X_{0,0}.
$$
If $F(t)$ denotes the cumulative disctribution function of $X_{0,0}$, then we have, with $N=2^n,$
$$\mathbb{P}(\sup_{i}|X_{i,n}|\leq t)=F(N^{1/2} t)^{N}.$$
It is well known that $\mathbb{P}(\sup_{[0,1]} W_t>a)=2\mathbb{P}(W_t>a)\leq 2e^{-a^2/2}$ for $a$ large enough, so that
$F(t)\geq 1-4e^{-t^2/2}$, and
$$
\mathbb{P}(\sup_{i}|X_{i,n}|>t)\leq 1-(1-4e^{-Nt^2/2})^{N}.
$$
Let $T_n:=\sqrt{2\log 2}n^\frac12 N^{-\frac12}$, then, plugging into the above,
$$
\mathbb{P}(\sup_{i}|X_{i,n}|>kT_n)\leq 1-e^{N\log(1-4\cdot 2^{-k^2n})}\leq 10\cdot 2^{(1-k^2)n}.
$$
That is to say, the median of $\sup_{i}|X_{i,n}|$ is of order at most $T_n$ and its tail decays very sharply after that, implying
$$\mathbb{E}\sup_{i}|X_{i,n}|^p=O(T_n^p)$$ for all $p$, or
$$\mathbb{E}\left(\sup_{s,t\in[0,1],~ |s-t|\le\Delta t}|W_s-W_t|^p\right)=O\left((|\Delta t\log (\Delta t)|^\frac{p}{2}\right).$$
These estimates don't lose much and they are of course very similar to Lévy's theorem on the modulus of continuity for Brownian motion.